CICTP 2016: Green and Multimodal Transportation and Logistics

This study aims to investigate the green vehicle routing problem (GVRP), which considers stochastic traffic speeds, so that fuel consumption and emissions can be reduced. Considering a heterogeneous fleet, the fuel consumption rate differs due to several factors, such as vehicle types and conditions, travel speeds, roadway gradients, and payloads. A mathematical model was proposed to deal with the GVRP, and its objective is to minimize the sum of the fixed costs and the expected fuel consumption costs. A customized genetic algorithm was proposed for solving the model. The computational experiments confirm the efficiency of the algorithm and show that the solution of GVRP is quite different from that of the traditional vehicle routing problem. The proposed model and algorithm are capable of suggesting a guidance for green logistics service providers to adopt a beneficial vehicle routing plan so as to eventually achieve a low economic and environmental cost.

With the development of the global economy, the living circumstances of human subjects to resources, and environmental issues, all aspects of the social life and economy are filled with “green” boom. The green supply chain is not only a product of sustainable development, but also a significant trend to logistics development. In this paper, in order to judge the warning status and put forward the improvement suggestions, the theories of mathematical statistics and early-warning were adopted, factor analysis method (FAM) was used to distill the main indicators of green supply chain impact; then, the grey correlation degree and relative degree of the positive-negative ideal point of indexes were determined by using grey prediction ideal point approximation method TOPSIS. The research conclusions have great value on enriching the theoretical system of logistics research and improving the quality of enterprise economy.

For a destination, there are many guide signs guiding to it. These guide signs form some guiding paths to the destination. But not all of the guiding paths can guide people to their destinations successfully. This paper presents an efficient model to solve the guiding accessibility optimization problem of guide signs. The goal of this optimization model is a plan for an optimal guiding path for each existing problematic guiding path which can not guide people to a certain destination successfully. In this model, the artificial bee colony (ABC) algorithm is employed as the main optimizer. In this paper, the cost of each planned guiding path includes two parts, the path length, and the number of deployed new guide signs. The optimal planned guiding path is obtained by minimizing the cost. Finally, the proposed model is applied in a typical area and the genetic algorithm is employed as the contrast for comparison. The experimental results show that the ABC algorithm performs better for solving the guiding accessibility optimization problem of guide sign system than the GA algorithm does.

In this paper, the authors proposed a local ramp metering model based on the hybrid Petri net, which consists of a traffic distribution observer, ramp metering surface model, and an on-ramp traffic controller. The model produces real-time decisions according to the real-time traffic state, and a set of pre-specified constraints. On-ramp signals use decisions given by the model to adjust the on-ramp traffic flow. In a simulation case study, there is around 9% decrease of vehicle total travel time in the local ramp metering area. The results have shown that the model can adjust on-ramp traffic flow according to mainline real-time traffic state effectively, and alleviate bottleneck congestion.

With the development of adaptive cruise control (ACC) vehicles, the traffic on freeways will be a mixture of ACC vehicles and traditional manual vehicles. It is a new challenge for freeway traffic state estimation. This paper proposes a neural network-based method to estimate the traffic speed under the mixed traffic. Three different neural network models are investigated using the simulation data, which is programmed by MATLAB. The results indicate that the neural network model with three input neurons (average speed of ACC vehicles, speeds from the microwave detector, and percentage of ACC vehicles) has a significant performance. Besides the fusion of measurements from the microwave detectors and ACC vehicles could improve the overall estimation accuracy, especially, the penetrate rate of ACC vehicles which is below 35%.

Recent studies reveal that traffic conditions might not be improved, or the network might still lead to gridlock, if the control strategies are applied in an unstable system, which is heavily congested with high demand. In this paper, we introduce a three-layer hierarchical control strategy for a heterogeneously congested two-region urban city. In the first layer, the synthesis of stability analysis and perimeter flow control for a two-region MFD system is considered. Surface boundaries of the stable regions are conducted to find the range of the control input. In the second layer, we adapt the model predictive control approach to solve the optimal control problem such that the network total delay is minimized and the network capacity is maximized. The third layer minimizes the subregional accumulation heterogeneity by coordinating the flows between the subregions.

A reliable shortest path problem is focused on finding a reliable a priori shortest path to maximize the probability of travelers arriving at their destination within a given travel time budget in a stochastic network. The mathematical model based on nonlinear mixed integer programming is established to analyze the problem of finding the reliable shortest path in a stochastic traffic network. A penalty method is developed to solve the nonlinear mixed integer programming problem by transforming the proposed problem to an unconstrained nonlinear programming problem through penalty function. Numerical results are provided using a small network and show the validity and feasibility of the proposed method.

A merging event involves three vehicles: the merging vehicle and the putative leading and following vehicles on the mainline. Understanding the interactions of the subject vehicle with the surrounding vehicles is fundamental to the study of the safety and modeling of merging behavior. This research studies the statistical properties of 8 lane changing parameters. These parameters describe the gaps, times to collision between vehicles and the merging vehicle’s speed. Visual angle parameters are first analyzed during the merging situation. The parameter values were extracted from the vehicle trajectory data in the NGSIM data sets. The results show that: (i) some of the parameters are highly correlated; (ii) visual angles are highly correlated with other parameters except the time-to-collisions; (iii) the visual angles are best described by the gamma distribution; (iv) the gaps are best described by the log-logistic distribution; (v) the times to collisions and speed are best described by the logistic distribution. The results can help promote temporal and spatial accuracy of merging behavior models.

With the development of mobile network technology, many kinds of taxi systems based on application (APP) are appearing, which provides convenience for travelers and makes taxi-pooling possible. But the taxi systems are working almost based on independent choices of parties, drivers and passengers, and some systems are not efficient enough. This easily leads to defaults. Particularly, order-competing always influences driving safety. In this paper, we divide one day into several periods, the dynamic taxi scheduling problem is converted into a static one. A taxi-pooling scheduling model is built based on many-to-many pickup-and-delivery problems (MPDPs), in which the information such as taxi positions and passengers’ demands are known, travel time, and passengers cost are considered. An intelligent heuristic algorithm is designed, and we get the optimization results of two instances which included passenger distribution program, taxi-pooling plan, and taxi routes scheme. Our method is efficient, especially in a large-scale road network.

The shortest path under a given on-time arrival probability is valuable to travelers wishing to save time and avoid traffic uncertainty. Conventional reliable shortest path methods often assume that travel time follows normal distribution, but substantial evidence shows that travel time in peak periods follows lognormal distribution. This paper proposes a reliable shortest path method under the assumption that travel time in peak periods follows lognormal distribution. Due to the character of bi-objective optimization, first-order stochastic dominance was conducted to compare the priority of a set of paths. Then, an improved RSPP-LC algorithm that simplifies the path-correcting procedure was constructed and applied to a small network in Shenzhen. The computational result indicates that RSPP-LC algorithm performs well in a small-scale network.

Automobile service enterprise location determination is an interesting and important issue in the logistic research field. To deal with this uncertainty, some researchers addressed the fuzzy time and cost issues for locating an automobile service enterprise. However, a decision maker hopes to minimize the travel time of customers meanwhile minimizing their costs when locating a facility. They prefer arriving at the destination within the specific time period and cost. To handle this issue in a more practical manner, by taking the vehicle inspection station as a typical automobile service enterprise example, we proposed a fuzzy change-constrained multi-objective optimization approach to handle it. Moreover, some region-wide constraints can greatly influence FLA and travel time is also has indeterminate due to the influence of some unpredictable factors. To handle them, we developed a fuzzy chance-constrained multi-objective programming model to determine its location with regional constraints, fuzzy inspection demands and varying velocities. A hybrid algorithm integrating fuzzy simulation, neural networks (NN), and genetic algorithms (GA), namely a random weight based multi-objective NN-GA, is proposed to solve the proposed models. A numerical example is provided to illustrate the effectiveness of the proposed model and the proposed algorithm.

In order to enhance the safe performance of comprehensive passenger transport terminal, the paper presents a pre-warning system of pedestrian flow abnormity state identification based on the model of space pedestrian flow parameters. The system includes five subsystems: the data acquisition and management subsystem, the safety risk identification subsystem, the safety risk prediction subsystem, the safety risk assessment subsystem, and the forecasting subsystem. A prediction model of pedestrian flow density is proposed and a clear line of pedestrian flow security warning standard is developed. Taking Liaoyang City comprehensive passenger transport terminal as an example, we applied the simulation software AnyLogic to simulate the operation process of pedestrian flow, and demonstrate the establishment and application of pedestrian flow security pre-warning system. The results show that the system can effectively detect the pedestrian flow operation abnormal state and determine the warning level.

The highway network toll data are used for extracting the travel time distribution. Three indexes are put forward to compare the fitting results, including error sum squares (SSE), the determination coefficient (R²), and cumulative distribution of the error sum squares (SSE of CDF). The results show that it is the most appropriate to model the travel time with the extreme value distribution, compared with log-normal, normal, and Weibull distribution models. On the basis of annual average daily traffic data, the level of service (LOS) is quantified by the evaluation index of the service reliability. The evaluation method of highway LOS is established. Finally, an example of verification is carried out on the highway sections in the Shaan’xi province. Evaluation results show that reliability can reflect the quality of highway sections and the fluctuation objectively. It is more suitable than the traditional LOS on describing the actual conditions in highway networks. The proposed method is effective as the calculated result is consistent with the actual observation.

Collecting and distributing traffic information is vital to intelligent transportation systems (ITS). Origin destination (OD) data and road geographical information systems (GIS) data were combined to locate potential providers of traffic information for drivers in the city of San Francisco. There were very few major providers of traffic information for most traffic zones, suggesting that locating the sources of traffic information can considerably reduce the volume of information transmitted for a future internet of vehicles. The Gini coefficient was used to quantify the contribution of heterogeneous information providers in different traffic zones. This work could offer useful support for a future internet of vehicles, in which a huge amount of traffic information would need to be transmitted through V2V and V2I communications.

Driver distraction induced by drivers concurrently executing multiple tasks has become a central issue for traffic safety. It is crucial to understand how different demands of secondary tasks affect driver visual behavior. This study employed a simulator-based experiment to assess the discrepances of manual and non-manual secondary tasks on drivers’ eye movements. Twenty five subjects performed oral calculation quizzes in different types and levels under dual-task conditions. Results suggested that drives had the smallest visual search area, the largest pupil area, and the most dispersed gaze points in manual-task conditions with regard to others. Subjective ratings and reaction time showed the similar variation. The more difficult the task was, the more degradation of main tasks and secondary tasks showed. These results revealed secondary tasks cause mental workload and the impact appeared to be greater when the driver performed manual tasks. The interface design would follow a rule to reduce manual tasks.

In a typical traffic time series, a within-day seasonal cycle is evident from the similarity of traffic data from one day to the next; a within-week seasonal cycle can be observed when comparing traffic data on corresponding days of adjacent weeks. Recently a new method called the double seasonal (DS) Holt-Winters method has been proposed to deal with double seasonality in time series. The primary objective of this study is to investigate the possibility of using the DS method to account for both within-day and within-week seasonal cycles in traffic time series. Based on speed data from Freeway I-5, California, the DS method, the standard Holt-Winters method and the ARIMA method are employed to perform short-term traffic forecasting. The result shows that the proposed DS model outperforms the other two methods, indicating that the double seasonal Holt-Winters approach is a promising and effective method for short-term traffic forecasting.

A lane changing strategy for vehicles facing the dilemma zone problem is proposed to increase the possibility that vehicles in multi-lane traffic can cross an intersection without being caught in the dilemma zone. With the impacts of vehicle-vehicle interaction, especially for car-following safety on lane changing behavior, conditions needed for vehicles performing lane changing are indicated. The decision algorithm for lane changing is presented as is a method of calculating the minimum longitudinal acceleration rate for vehicles that would have been caught in the dilemma zone at the onset of a yellow light clearing the intersection. Simulation results show that the proposed lane changing strategy satisfies driver comfort and vehicle safety. It was found that, according to the decision algorithm, vehicles can perform lane changing behavior at the right time and cross the intersection without dilemma risk and time delay.

A traffic state prediction of congestion areas in traffic networks is an important basis of traffic control and guidance. By knowing the congestion state of traffic networks, typical types of bottlenecks can be determined through statistical analysis of the inflow-outflow rate according to traffic flow directions at each intersection in a congested area. Based on the auto regressive analysis method, a traffic demand prediction model of traffic congestion bottlenecks was developing by using historical and real-time traffic volume as the reference. Furthermore, comparing forecasting traffic volume with outflow ability of each congestion node in a traffic network, a self-correcting discriminate model of real-time state and occurrence time for traffic congestion is proposed. A comparative analysis of predicted results and actual traffic networks was conducted to confirm the validity of the discriminate model, which showed that accumulated volume during traffic congestion can be used to predict the real-time operation state of traffic networks.

This paper aims to combine the use of both TRANSYT and VISSIM software in an attempt to reduce roadway traffic saturation while also combatting stop delay and queue lengths to improve the efficiency of traffic through an intersection. Investigation into and analysis of current conditions on Huang-Shan Road and Xiang-Zhang Avenue in Hefei city allows the TRANSYT and VISSIM models to be created and the two models to be compared. After using the TRANSYT model for signal optimization under two conditions, pedestrians are introduced. The model is combined with the VISSIM simulation software to verify the optimized results. The research shows that combining the software can reduce the road saturation effectively and reduce the both stop delay and queue length to improve the efficiency of the intersection.

This study brings forward an improved travel time estimation method without signal timing data for an individual probe car. The method consisted of three modules, the first module used a fuzzy logic algorithm to determine during which signal interval the target probe car arrives at downstream intersection. The second module estimated travel time for target probe cars that arrived at downstream intersections during the green light interval. The third module estimated travel time for target probe cars that arrived at the downstream intersection during a red light interval. The latter two modules didn’t use real-time signal timing data and mostly relied on probe car data to estimate travel time. VISSIM was used with a 30 second sampling interval and performance was compared to that of traditional, direct methods. After analysis, it was discovered that the improved method out-performs the traditional methods at near-saturated traffic conditions.

Based on probe car data, two fundamental average travel time estimation methods that are commonly used in engineering applications were compared. The first method is named ‘average instantaneous speed method’, it calculates the arithmetic mean value of instantaneous speeds of all probe points during the estimation interval (usually 5 minutes) on the target link. The second method is named ‘average travel time method’, it estimates individual probe car travel time based on two probe car points that are respectively nearest to the two link sections of target link. VISSIM was used to compare the performance of these two methods using 25 and 30 second sampling intervals. With an 8% penetration rate of probe cars, analysis of the results showed that the average travel time method performs better than average instantaneous speed method under a borderline traffic state. In the end, research conclusions and the possible further related research were brought forward.

Science and technology in the comprehensive transportation service mainly includes three aspects: government transportation website construction and management, the improvement of the online travel information service, and traffic data services. This paper evaluates the application of science and technology in the comprehensive transportation service area.

Vehicle trajectory records the vehicle location and time sequence, which is significant for the travel state analysis and road accidents forecast. In order to repair the fault data of vehicle location and time updates resulted from global position system (GPS) data transmission interruption and resolve problems of vehicle trajectory information lack. This paper studies vehicle trajectory restoration, designing a distributed model for vehicle restoration trajectory, using Vondrak filtering to smooth the travel trajectory and then repairing latitude and longitude information by using cubic spline interpolation. The vehicle trajectory can be got by the merger of latitude and longitude information. Restoration methods are verified by MATLAB under simulation. The results show that the algorithm error is 6.01×10^-5, which is able to guarantee the accuracy of vehicle trajectory information and provide relatively accurate data to support researches based on travel trajectory.

Trajectory information recognition is an efficient and convenient approach for trip information obtaining. The trajectory segmentation is a pivotal step to group data into travel parts and activity parts. This paper presents a study on a novel fast search clustering method generalized into the trajectory segmentation. The clustering algorithm was extended and the selection of the cut-off distance was discussed. A comparison among four segmentation methods including two empirical and two clustering methods were conducted to examine the effect of them. The result shows that the two clustering methods achieve lower segment error rate, point error rate, and miss rate than the empirical methods. The fast search algorithm works with the three error rates below 0.03, which can provide reliable samples for information recognition.

Now it is the trend of government home and abroad more transparency and providing open data for public access and properly tapping. Traffic data are an important part of these data. This paper presents the big traffic data visualizing procedures and illustrates an integrated open source platform with R Shiny. This paper also presents some tapping data tools and illustrates with corresponding traffic feature examples. Properly mining the big traffic data by the interested members will contribute to solve the traffic congestion problem to some degree.

Accurate and real-time traffic flow prediction nowadays shows more and more dependence on big transportation data. Deep learning, a powerful method for feature learning, has turned out to be an effective tool to cope with these explosive data. Recently, deep models, especially unsupervised models like deep belief networks (DBN) and stacked autoencoder (SAE), are being employed into the field of traffic research and have shown great prospect. However, there is still a vacancy in the exploration on comparing the performances of different kinds of deep architectures to find an optimal solution. In this paper, we set up two deep-learning-based traffic flow prediction models for feature extraction and performances comparison: One is a deep belief networks (DBN) based on restricted Boltzmann machines (RBMs) that have Gaussian visible units and binary hidden units, and the other is a DBN based on RBMs with all units being binary. A conclusion is drawn where the former one performs better in traffic flow prediction after a series of experiments.

Traffic data is often missing or incomplete. Recently, it has been constructed into a tensor model and its missing data can be completed from a subset of its observed entries to fully express the multi-modal properties of traffic data. However, with the dimension of the data becoming higher, the completing speed, and accuracy usually decreases rapidly. To solve this problem, in this paper, we introduce a square-norm model for tensor completion, which uses the matrix completion method to accelerate the procedure of iterations, which makes it more adapted for higher-dimension tensor completion. The experimental results show that our algorithm is more suitable for those tensors with dimensions greater than three, and the accuracy can be ensured even when the missing ratio is as high as 80%.

Travel time reliability (TTR) is an indicator of the level of service, especially the level of congestion experienced on it. Measures of TTR attempt to quantify the variability of the travel time of travelers’ experiences along the same route at different times. Traffic guidance is an alternative method to improve the TTR of road networks. However, the traditional traffic guidance based on variable message signs (VMS) encounters the delay effect of guidance information, which degrades the effectiveness of route guidance. The traffic guidance based on the connected vehicle (CV) is an effective method to enhance the TTR. Impact of real-time guidance information on TTR measures in a CV environment is analyzed. A traffic guidance algorithm based on CV technologies is proposed, and is validated by an integrated simulator for connected vehicle technologies. The simulation results show that traffic guidance has a significant influence on TTR in a CV environment. The increase of incident duration will produce the more serious traffic congestion, which results in the decline of TTR. A high penetration rate will improve the TTR of road networks. The proportion of non-CVs guided indirectly has also an influence on TTR, namely, a high following rate can help alleviate the impact of the incident on TTR.

In order to improve the accuracy of lateral and vertical target recognition in a car-following situation, the box plot is used to analyze and filter discrete points to overcome the LIDAR point data error; application of the modified adaptive K-means clustering algorithm which is based on the clustering evaluation index is applied to process the LIDAR point from LUX4; the candidate targets are output by clustering results. The test results show that the obstacle detection algorithm is more robust and reliable in the car-following situation.

Up until now, a lot of driving safety assistant systems have been developed. As to the low stability and precision, android system is confined in reality use. This paper aims at the real-time warning system based on android APP. In order to decrease the traffic accident rate, a warning system based on video detection and android system is developed. The real-time visual detection and tracking approach benefit from Camshift and Kalman filter with frame differential in region of interest (ROI) can detect the vehicles successfully. With the direct linear transformation (DLT) calibration method, motion parameters are easily extracted. Besides, current images are collected and shown to the drivers involved in danger by APP. With another APP the real latitude and longitude could be easily obtained in one mobile phone. Comparing with the actual road surveying data, the calibration accuracy could easily be obtained. When hazardous vehicle behavior is detected by PC, warning signals would be released to attract the related drivers’ attention. The experimental results indicate that the proposed system is of high precision and real time.

Real time and accurate predictions of intersections help set scientific traffic signal programs, expand road capacity and improve traffic conditions. The paper establishes a short-term forecasting model of intersection channel imports according to the Levenberg-Marquardt (LM) neural network algorithm, which is based on the analysis of intersection traffic volume time and spatial correlation, combining LM neural network distributed processing, self-organizing, adaptive, self-learning, and other good characteristics. Using MATLAB to forecast short-term traffic volume of intersection imports with the prediction model and some specific examples, the empirical results show that the prediction model has preferable prediction accuracy.

In order to uncover the key influencing factors of logistics demand, this study explored the relationship between logistics demand and socio-economic development. This paper selected the total freight traffic to characterize the logistics demand from the point of view of macro economy, explored the impact of social and economic development indicators on logistics demand, and grey correlation analysis method was used to calculate the correlation degree between each influencing factor and logistics demand. Finally, taking Ji’nan City as an example, the empirical analysis of the influencing factors of logistics demand was carried out. The results show that the first industry production, the tertiary industry production, and per capita consumption expenditure have a significant relationship with logistics demand.

Cruise service supply chain (CSSC) refers to the cruise tourism service-oriented integrated supply chain. It takes “cruise services provider-cruise tourism service integrators-tourists” as the basic structure, tourism services as the core, customer-centric as the idea, and finally forms an interconnected, interactional and “vertically integrated” supply chain. This article attempts to use social network theory to analyze the network attributes of CSSC from the two dimensions of structural attributes and relationship attributes. It also illustrates the network activities of CSSC and mechanism of the growth of member enterprises. This paper argues that the model is new thinking based on the study of CSSC’s social network and of great theoretical significance and academic value. This paper only presents the theoretical framework. The mathematical model establishment and empirical analysis will be done in the next step.

In this paper we study a logistics hub location problem in which the network could not be formed as a full interconnected hub-level network because of the investment restrictions. Nevertheless, the hubs to be located must form a set of interconnecting lines. Logistics hubs can be connected with highly efficient pathways, enabling economies of scale to be achieved on the transportation cost (or transport time) between hubs. The objective is to minimize the total weighted transport time between all pairs of nodes while considering the logistics operation time taken on each key connected component of the network. Besides, a budget constraint on the total set-up cost of the hub network is also taken into account. A mathematical model is presented to solve the hub line location problem (HLLP) through pure integer nonlinear programming (PINLP). Numerical results on a test case confirms the validity of the proposed PINLP model and indicates the impact of the budget constraint on the topology of the network.

As China’s economic development continues, people’s living standard improves, and the development pace of the logistic industry in China has gradually accelerated, but the development level of the logistics industry in various regions still needs a detailed analysis. This paper collected in 2014 13 indicators from China’s 31 provinces which reflected the development level of the logistics industry; it then conducts a thorough analysis, using the factor and cluster analysis method to understand more about the development level of China’s logistics industry. Finally, a comprehensive evaluation is offered.

In order to reduce logistics distribution system costs, this paper proposed a two-layer distribution network model for the multi-objective multi-depot location routing problem (MOMDLRP) in an urban area. This problem considered the shortest-path between factory to distribution center (lower layer) and the location routing from distribution center to customer (upper layer). In this study, the geo-information system (GIS) was also employed for the necessary concern of urban road network topology structure and road passage capacity in the real world. By the principle of urban road connection and road grading as well as with the consideration of balanced workload, the proposed model aimed at minimizing the total cost to determine the distribution center’s location, quantity, customer allocation and vehicle routing. To this end, the proposed model in this paper is much better in practical application.

With the development of traffic motorization, urban traffic problems persist. In order to overcome traffic problems, it is imperative to develop a comprehensive bike-sharing system. However, the current bike-sharing system faces the challenges of site selection and determining the number of slots needed for rental stations. Therefore, this paper will take the bike-sharing system as its starting point and focuses on the layout of the stations. Based on the hierarchical model, an optimal model with capacity constraints for the system’s location is studied to minimize the walk cost for users, setup cost and penalties. With the model successfully solved by LINGO, this paper will also demonstrate the whole process of the planning with an instance that verifies the efficiency and feasibility of the model. The study’s results show the significance of optimizing the public bike rental station layout on solving the “last mile” problem.

In the process of transporting hazardous materials, the difference in a decision makers’ preference will have an impact on the choice of the transportation route. On the basis of analyzing the preferences of decision makers, the models are divided into risk-taking, risk-neutral, and risk-averse. The attribute set of hazardous materials transportation route includes transportation time, transportation cost, and transportation risk, which were chosen in order to build the truck transportation routing’s multiple attribute decision-making model based on the risk preference. Additionally, the attribute weights were attained using the least square combination method and solving the model with the ELECTRE- II method. Finally, the numerical example is given to show the reliability of this model.

This paper introduces a flexible supply contract with put options model into a single-period two-stage supply chain with long manufacturing lead-times, short selling seasons and high demand uncertainties, which can make the supplier and the buyer cooperate with each other. We will derive the optimal initial order and number of purchased options, and in a numerical study, the supplier’s optimal decision is also obtained. Meanwhile, it is also proved that the profits of decentralized supply chain with this flexible contract is higher than that of the NV model, but lower than that of centralized decision model.

To improve the performance of the traditional decentralized supply chain with one buyer and one supplier, this paper studies the supply contracts with bidirectional options which allow the buyer to adjust the initial order both upward and downward. We analyzed the contracts from both parties’ perspective and derived a closed-form formula of the buyer’s optimal decision. To obtain the supplier’s optimal decision, a numerical study is provided. In the numerical study, we also calculated the profit of the buyer, supplier and supply chain, respectively. By the numerical results, we derived that using options can improve all of their profit compared the traditional supply chain.

This article selected six parameters—logistics performance index, proportion of third-party logistics services, relationship between intensity ratio of freight per unit of GDP, total logistics costs to GDP ratio, proportion of intermodal freight traffic, GDP per unit of energy use, and other indicators—to evaluate the service level of freight and logistics of Shandong Province and to analyze influencing factors. Typical cases were selected to expand the comparative studies both at home and abroad to fully draw on the experiences of advanced countries to determine the direction of freight and logistics future development in Shandong Province.

Distribution center location and route are of equal importance to cold chain logistics. It is necessary to consider the location and route optimization comprehensively for the benefit of the overall cold-chain logistics system. Constraints of time window are adopted to determine the location of a distribution center and the arrangement of transportation route for cold chain product on the basis of a bilevel programming model. The two levels of the model are checked but mutually promoted to minimize total cost. One case will be analyzed and solved by means of network optimization algorithm. Then the model and solution are proved to be feasible and reasonable for the optimization of distribution center location and route.

In developing countries, the ordinary pedal bicycles have been gradually replaced by the electric bicycles, which have different operational characteristics compared to the former. In order to allocate road resource reasonably and analyze operational characteristics of electric bicycles efficiently, the primary objective of this study was to develop a quantitative approach to calculate the conversion factors of electric bicycles, and investigate the relationships of flow-density-speed with mixed traffic flow. According to the traffic characteristics of motor vehicles and electric bicycles, the conversion factor models were introduced to convert the number of bicycles to passenger car unit (pcu). The conversion factor for electric bicycles in the road section was 0.64, which was the average of 0.71 (traditional methods), 0.64 (dynamic methods), and 0.58 (static methods). A case study was conducted to show the applicability of the proposed model with data collected from the city of Xi’an in China. The results of R-square values indicated the method was well validated and could be practically used for the analysis of electric bicycles’ operational characteristics with mixed traffic flow in China.

In order to analyze the capacity of the opening high-speed rail (HSR) to compete against the existing alternatives in the Guangzhou-Zhaoqing transport corridor, a mixed stated preference (SP) and revealed preference (RP) is adopted to calculate tourists’ preference pattern for alternatives. Twelve potential variables, preliminary selecting from personal attributes, travel characteristics, and transport characteristics, are conducted to the binary logit model (BL) and the multinomial logit model (MNL) to forecast the market share of alternatives before and after the opening the HSR respectively. The result shows that before the opening of HSR, the market share of coach and conventional railway (CR) are 68.43% and 31.57%, respectively. However, after the opening of HSR, HSR attracts 62.99% market share, which is composed of 36.21% from the coach and 26.78% from the CR. The conclusion provides a foundation for predicting the share rate of passenger flow for establishing intercity railway.

Considering the association between the airport and the urban transportation system, the airport ground access plays a significant role in fully achieving the function of the airport, and exerts an important influence on airport capacity and efficiency. Based on the field investigation and questionnaire of Pudong International Airport, the analysis of the service characteristics of various ground access modes was conducted with the full consideration of several factors including travel time, travel time composition and cost. In addition, total travel costs of different transport modes were quantitatively calculated. The result shows that the higher the total travel cost, the lower the sharing ratio, in terms of public transport. Finally, the current ground access structure and its forming reasons were summarized by analyzing comprehensive influence caused by various factors. The result might provide theoretical guidance and engineering reference for the landside traffic improvement of the current airports and the design of new airports.

The proposal of building the Silk Road Economic Belt aiming to strengthen cooperation among Asian and European nations will benefit all the people along this Economic Belt. To establish the Silk Road Economic Belt, implementation of comprehensive transport corridors, including multiple transport modes, is foremost. Accordingly, the evaluation of coordination of multi-modes is a valuable foundation issue. This study constructs the coordination degree evaluation model of multiple transportation modes on the basis of the DEA principle. The model can calculate the coordination degree among multiple subsystems. The key idea of the evaluation model is that the output parts of the one subsystem could be regarded as the input parts of another subsystem. Then, the correlation level of the input and the output can be used to measure the coordination degree of the two subsystems. Furthermore, an application instance, based on some classical western regions that mostly involved in railroads and motorways, in the Silk Road Economic Belt, has been discussed in detail. Results of the application instance illustrate the coordination situation, trend, and improvement measures.

In order to accelerate the development of the integrated transport system and realize the coordination of five transport modes, using systems theory and coordination theory, analyzed systematically multi-perspective meanings of measuring integrated transport efficiency in three aspects: integrated transport effect, transport structure, and the advanced degree of infrastructure development. From a technical efficiency point of view, the concept of tonnage kilometers was introduced, calculated integrated transport system capacity, which is mainly composed by road and railway transport; then a specific method for measuring integrated transport efficiency was put forward, based on transport capacity utilization. Moreover, using this method analyzed integrated transport efficiency empirically from 1979 to 2013 in China. Results show that the overall efficiency of China’s integrated transport is relatively low, only about two thirds of the United States and Japan, which shows that modes of transport have not yet been a realized the coordinated development. This is consistent with the reality, indicating that this method is feasible and credible.

In the view of increasing environmental pollution, emissions of CO₂ and other harmful gases, the main aim of this article is changing the modal shift of the continental cargo by railway to inland water transport. This article focusses on different modes of transport for main cities in the Netherlands and Germany. For inter-modal transport, the port of Duisburg is the transshipment station for goods, which handles the inter-modal transport. In this article we would like to stress an important module that is required for developing inter-modal transport models. The simulation will check the transport and emissions and show the best alternative.

This paper presents a new maritime container assignment model to seek the most proper method to assign two different types of containers with different priorities to minimize its objective function. This model enforces the flow conversation of each node, examines whether each link is attractive, and takes the throughput constraints and shipping sizes into consideration based on a linear programming model. We mainly consider two types of containers to illustrate the properties of this model. The containers with a higher priority in the allocation problem cannot be placed on the less priority containers’ slots. Numerical examples are presented to illustrate the application of the model.

Berths and quay cranes are the most critical resources in determining the capacity of container terminals. In order to utilize berths and quay cranes efficiently, this paper studies the integrated dynamic discrete berth allocation and quay crane assignment problem considering the cost balance. The objective of the proposed model is to reduce the total service cost, including the handling cost, the waiting cost, and the quay crane operation cost. Due to the inherent computation complexity, a genetic algorithm is designed to attain a near optimal solution. Computational experiments show that the proposed genetic algorithm is effective in solving the studied problem. The total service cost is influenced by the value of the cost balance.

The interface is the weakest part in the asphalt plug expansion joint pavement. ANSYS finite element software was adopted to analyze the interfacial stresses. The results show that the interfacial controlling indexes are the tensile stress and the shear stress. The cornering ratio and tire contact pressure have greater influence on the tensile stress and the shear stress of the interface. Some useful measures that are good for the interface include: choosing larger modulus of the expansion joint mixture, interface roughness processing, making the interfacial elevation difference smaller, preventing the vehicle starting or braking urgently on the expansion pavement, and preventing overloaded vehicles.

Three kinds of cement and two kinds of single-graded stone were selected to prepare the mixture of the asphalt plug expansion joint, respectively. A direct tensile test and an oblique shear test were used to analyze the cement type, mixture gradation, temperature, interfacial treatment mode, and loading rate on the influence of the tensile and shear performance of the asphalt plug expansion joint’s interface. The results show that fine aggregate gradation is necessary, the interface should be kept dry and free of pollution, and the interface should be kept rough. Increasing temperature and decreasing vehicle loading speed induce a decrease of the tensile and shear strength of the interface more easily.

An advanced repeated load permanent deformation (ARLPD) test that can simulate the lateral confinement and temperature gradient in actual pavements was employed in this study. The test was conducted based on field cores and laboratory-made specimens of several newly constructed hot mix asphalt (HMA) pavements, reclaimed asphalt pavements (RAP), and asphalt overlay pavements. The rutting resistance and distribution were evaluated using various rutting indicators. It is found that newly constructed HMA layers using the SBS modified binder show a great improvement in the rutting resistance. Overlay and hot in-place recycling (HIR) pavements exhibit similar anti-rutting performance. The cold in-place recycling (CIR) mixture could be used in the bottom asphalt layer for highway maintenance. For overlay and HIR pavements, the new top asphalt layer contributes approximately half of the total rut depth. The rutting distribution is relatively uniform when SBS modified binder is used in the middle asphalt layer.

Surface characteristics of asphalt pavement have significant impacts on road noise. However, the quantitative relationship between them is not completely clarified. The objective of this paper is to quantify the effect of asphalt pavement surface characteristics on road noise. Firstly, based on acoustics theory, we determined the pavement roughness (IRI) and texture depth (TD) as the factors affecting road noise. Secondly, we conducted a series of field tests, collecting the road noise inside and outside the automobile and measuring the IRI and TD. Finally, we statistically obtained the relationships among interior vehicle noise and exterior vehicle noise, the IRI and ID of the pavement. The result shows that road noise, neither inside nor outside the vehicle, is significant to the TD. Interior vehicle noise is linearly related to the IRI, which rises with the increase of IRI. In addition, exterior vehicle noise can be considered to have a quadric relationship with ln(IRI · TD).

Three-dimensional structure model on a Winkler foundation considering inter-layer contact status was established. The effect that base modulus, thickness, and interface contact status between a slab and base on maximum stress of the slab bottom and base bottom, shear stress between a slab and base, and warping of the slab was calculated. The results showed that interface contact status had a great influence on slab stress and warping. Maximum stress of the slab bottom dropped while bonding status decreased and slab warping increased, while bonding status weakened. Base modulus was the primary factor for base stress. Maximum stress of the base bottom increased while modulus increased, and decreased while bonding status weakened. Interface shear stress occurred mainly at the slab’s edge, and decreased while the bonding status weakened, and had almost no correlation to base modulus and thickness.

By using compounded technology of flame retardant and synergistic agent, three groups of compounding flame retardant asphalt systems and relevant SMA asphalt mixtures were designed. On the basis of the oxygen index test and burning test, properties of flame retardancy and smoke suppression were evaluated, as well as the influence of a synergistic agent. Pavement performance of a compounding flame retardant asphalt mixture was evaluated through rutting test, tensile splitting strength test and bending beam test. The results show that the proper synergistic agent can increase the oxygen index of the compounding flame retardant asphalt and the smoke suppression of the asphalt mixture will be significantly improved at the appropriate compound proportion. Smoke suppression of [MH+ZB] is the best and no obvious adverse influences are revealed on high temperature stability, water stability and low temperature crack resistance of asphalt mixture.

In this paper, we focused on different types of highways and vehicles, and established a speed prediction model for different sections of highway based on the running speed. The operating speed method is designed according to the driver’s demand and rules, and the road traffic environment. After analyzing the running speed and road alignment at home and abroad, this study presented a prediction method for running speed based on road alignment. It demonstrated the changing rules on different sections of highway, established a prediction model using a linear regression model, and put forward a speed controlling method. Finally, we performed instance analysis on Yibao Highway using the prediction model, and obtained certain results.

A mechanical calculation model of tunnel composite pavement was established using finite element software ABAQUS. The shear stress and horizontal tensile strain in the asphalt layer, the horizontal tensile stress in the concrete layer as well as the interlaminar shear stress were selected to be the key indexes. The mechanical calculation results show that with the increase of the thickness of the asphalt layer, its maximum shear stress increases and its tensile strain increases first and then decreases, while the interlaminar shear stress decreases. The maximum horizontal tensile stress in the concrete layer decreases with the increase of the thickness of concrete layer and the modulus of bedrock. Besides, the maximum horizontal tensile strain in the asphalt layer decreases when increasing its thickness. The thickness design methods of the asphalt layer are put forward based on the shear stress index and horizontal tensile strain index as well as interlaminar shear stress index. The thickness of an asphalt layer between 8cm and 10cm is verified to be reasonable. The thickness of the concrete layer is mainly to meet the functional requirements. In order to improve the service life, a minimum thickness of 40cm is recommended.

Similar to other metropolitan cities in China, urban rail transportation has been highly emphasized in Beijing in the past decades. However, the growing subway system is seriously challenged by several critical issues, one of which is that the ridership must be restricted at certain stations during peak hours due to crowded conditions. This suppresses the transport demand and pushes passengers to other modes of transport. Therefore, the characteristics of subway ridership should be carefully studied to increase the appeal of subways and maximize their potential. This paper categorizes Beijing subway ridership characteristics into seven different groups based on their temporal distributions and corresponding land use types by analyzing Beijing’s subway smart card data. In addition, the heterogeneity among stop-level, line-level, and network-level ridership temporal distributions is analyzed. Temporal distribution characteristics should be incorporated into ridership prediction and subway network optimization, and can thereby improve subway demand forecasting, planning, and design.

Based on regional integration, the concept of a “one-hour traffic circle” is widely mentioned. Due to such increasing traffic demand in the region, intercity rail transport has been proposed widely. However, unlike urban rail transit, intercity rail cannot travel deep into the core area of the city, which makes the transfer with conventional public transit an important aspect to consider. Taking intercity rail and conventional public transit as the objects, this paper mainly focused on the transfer efficiency evaluation between the two. First, the characteristics of intercity rail are introduced. Second, six indexes were selected to evaluate the transfer efficiency, including coordination capacity, average transfer time, average transfer distance, per capita transfer facilities area, completeness, and rationality of transfer guide facilities. Thirdly, the AHP method was adopted to establish the transfer evaluation model. Finally, based on the project of Ning-He intercity rail, Jingmingjiayuan station was chosen to evaluate the transfer efficiency.

This paper investigates and compares several transit fare structures including flat fare, station-based, and mileage-based fare. For each fare structure, there exists an optimal fare pattern inducing to the highest total social benefit and total net profit. A bi-level model is then proposed to determine the optimal fare pattern. The upper-level problem intends to address the maximization of total social benefit from the perspective of transportation authority and the maximization of profit of transit authority, whereas the lower-level problem is a path-based stochastic transit assignment problem with elastic demand. A modified genetic algorithm is adopted to solve the bi-level model. A numerical example of a 9-node transit network is provided to illustrate that differentiated fare structures and have a better financial performance than flat fare.

In developing countries like China, economic benefit and efficiency have been considered primary factors in the design of feeder bus routes. This paper intends to present a method that balances the socioeconomic benefits during the optimal routing design procedure, considering the fact that some feeder bus routes provide social benefit. This study addresses the development of an optimal routing design for feeder buses in suburbs. A research model focusing on optimal route design was developed, and a genetic algorithm was used to solve the problem and test the results within reasonable running time; factors including passenger travel cost and coverage of existing nodes were studied as constraints. Results show, in general, that the method can optimize the route design in a suburb area where the equalization of public traffic service is emphasized, and the results of feeder route design were reasonable.

Real-time control of buses can prevent bus vehicles from chaotic operation due to stochastic features of traffic flow. This paper proposed a hybrid real-time station control strategy combining holding and skipping control. The proposed model can determine when, where and how the strategy implements based on the threshold ratio of headways and dispatch intervals. A simulation experiment is conducted to verify the effectiveness of the proposed strategy compared with no control situation. Five evaluation indexes are aggregated to obtain the optimal key parameters for holding and skipping. The two scenarios whose weights tend to passengers or bus operation agencies respectively shows the same consequence: the optimal key parameter for holding is 0.7, and that for skipping is 2.0 or 3.0. The improvement percentages of the multi-criterion evaluation index are 11.43 and 8.46% which indicates satisfied results.

In order to solve the “last mile” problem, bicycle sharing systems are rapidly developing in many cities. Meanwhile during the practical operation phase, the quantities of bikes and vacant lockers can’t meet the fluctuating demand. The reason is complex; besides the disequilibrium of spatial and temporal distribution in demanding of bicycles and lockers, the scales of lockers and the quantities of bicycles at the initial time are two crucial factors affecting the operational condition of the sharing systems. This paper presents the modeling aiming to achieve the latest repositioning time during the morning peak time, combining the practical operational condition to optimize the scales of lockers and the quantities of cycles at the initial time. Improved genetic algorithm is used to achieve the model and obtain a high quality solution to this frequent everyday instance.

Bicycle sharing systems are a kind of green transportation, which plays an important role into reduce carbon emissions. But the problem of “difficult to rent or return a bike” in actual operation has restricted the development of bicycle sharing systems. In order to solve this problem, this paper carried out research on single depot multi-vehicle static bicycle rebalancing problem with time windows (SDMVSBRPTW), and established a mathematical model, which the objectives are minimize the redistribution costs, and maximize the customer satisfaction. Then LINGO was used to verify the accuracy of the model. The computational results show that the model is suitable for the rebalancing optimization of bicycle sharing systems. This study has a certain pragmatic value for bicycle sharing system to improve the operation efficiency, and to reduce operating costs.

Growing congestion is a problem faced by cities around the world. Ridesharing is a recent alternative in which people with similar travel plans travel together. Many studies have focused on ridesharing, including taxi-sharing. In present research on the taxi-sharing, a few models are adopted to optimize the fare sharing and the route choice simultaneously. No research has focused on taxi-sharing to consider the difference between off-peak hours and rush hours. In this paper, we take into account the benefit of both drivers and passengers on the principle of equity, and we establish a route choice and fare optimization model for taxi-sharing during off-peak hours and rush hours, respectively. Finally, LINGO is used to solve the model, and the validity of the model is verified by an example. The result shows that the rate and the route choice can satisfy both sides.

In the process of public transit operation there are two aspects, supply and demand, both of which are interactive. How to reasonably determine the frequency to coordinate the interest of two aspects is a key problem for transit operation management. Aimed at the frequency allocation problem, this paper uses dispatch frequency as decision variables and develops the minimum waiting time and the maximum net profit models, respectively, under the constrains of operating cost, service frequency, bus capacity, ridership, and the number of buses. Then the two models are combined with time value into one. In the model, the ridership is elastic to the number of bus trips at a given stop and a bus route can have more than one service pattern. The model is applied into a test network and the results show the model can maintain ridership, reduce waiting time, operational cost, and bus load.

Bus lane with intermittent priority (BLIP) is a new method to alleviate traffic jams. It improves reliability of bus services and better utilized road resources. There are limited research studies on BLIP and additional study on this area is needed. More importantly, influences to the adjacent lane, impacts on the capacity of BLIP by different bus departure intervals, setting conditions for deployment of BLIP such as reasonable clear distance and traffic density are not clear until now. This paper is focused on the capacity of connected vehicles (CV) based BLIP lane with cellular automaton (CA) simulation. The recommended traffic density range and clear distance of BLIP, and how BLIP affects the adjacent lane are also studied in this paper.

In order to improve the efficiency of bus systems in rail transit hubs, an optimal method is proposed to adjust the existing bus lines passing through the hub. Firstly, an optimal model minimizing the trip number of single bus lines and maximizing passenger volumes was presented. Then the enumeration method was applied to solve the optimal model. A case study based on the North Street rail hub in Xi’an was conducted to optimize the bus routes, including the direction, site, and scheduling scheme. The results indicated that the proposed method could optimize the bus lines in rail transit hubs to meet the travel requirements of passengers and improve the traffic conditions.

Having reviewed the types of outburst mass passenger flow and their impacts on the operation of the urban rail transit, this paper expounds the main factors influencing passenger evacuation. Taking for example the Dongsishitiao Station in Beijing Subway Line 2, we have focused on the causes and the characteristics of the stream and volume of the outburst mass passenger flow, and pointed out the structural defects of the station as well. Based on the information of the facility and the structure of the station, together with the characteristics of the outburst mass passenger flow, we introduce some multi-layer measures to limit the passenger flow and the corresponding auxiliary measures to evacuate the crowd to provide the gauge in the event of large-scale activities to ensure safety.

To analyze the impacts of linear bus stops in separation zones on road capacities, we investigated 6 bus stops in Hohhot. We collected relevant data and comprehensively considered the vehicle arrival distribution characteristics at bus stops, vehicle parked time distribution characteristics, and vehicle deceleration time characteristics. By using the SPSS software for statistical data regression analysis, we calibrated relevant parameters and obtained the regression model.

This paper examins the impact of different exit designs on the collective movement patterns of the crowd. A series of controlled experiments with 50 participants were performed in a designed chamber. Considering different exit locations (exit at the middle/corner) and obstacle placements (without/with obstacle) under two desired speed categories (normal walking/slow running), eight sets of experiments were conducted with three repetitions. From the trajectory data derived from the recorded video footage, crowd egress features such as escape headway frequency distribution, escape time duration, and relative effectiveness were obtained. Results showed that for corner exits, without obstacle was the most effective scenario. In addition, presence of obstacle increases the egress time, compared to middle exits. Findings of this study are useful resources for crowd researchers to validate their proposed crowd simulation models and for architects to improve exit designs.

The analysis of the multi-mode public transportation evaluation framework aims to provide theoretical support to the assessment of public transportation service levels. However, many studies extend service level with respect to a single trip mode. The multi-mode public transportation includes the metro, ordinary bus and bus rapid transit. Based on smart card data, the trip chain was extracted for further study on the job-housing relationship and network service level. Afterwards, the public transportation network coverage and the transfer convenience degree were considered for research on public transportation accessibility. Besides, load factor was determined for framework evaluation, as well. The service level evaluation provides the real-time travel information for ridership to plan more suitable trip chains, in the meantime, offer guidance for commuters to select workplace and residence scientifically. Moreover, the comprehensive evaluation framework not only contributes to the adjustment of intelligent schedules but also optimizes the public transportation service level.

Transit signal priority strategy has a positive effect on improving traffic efficiency and level of service in the urban area. This paper focuses on transit signal priority (TSP) optimization regarding the effect of capacity drop in lane-changing areas. A passenger-based TSP optimization method for minimizing the total passenger delay at the basic unit (defined as intersection and upstream bus stop) is developed, and capacity drop is calculated based on the VISSIM-based simulation platform. Then, the performance of proposed optimization model for decreasing passenger delay of an experimental segment along Longpan Boulevard in Nanjing, China is simulated by the VISSIM software platform. Compared with the traditional TSP scenario, the proposed optimization model considering the effect of capacity drop in lane-changing areas presents promising outcomes in the design of transit priority signal control regarding decreasing passenger delay for the urban transit system.

Taking the advantage of convenience and high efficiency, the subway system has been a favorite of passengers. Providing better services to minimize the travel time for the passengers is of particular importance. Metro train’s headway and running time have determined that the most important factor affecting the travel time is the passengers’ walking time. In order to study the relationship between those factors, a field study was conducted on Line 1 of Beijing subway system. The investigated facilities include the passageway, platform, escalators, and stairs. For each walking facility, a function of travel time and distance was calculated and the factors that affected the walking time were analyzed.

After years of urban and rural road passenger transportation development, researchers recognize the importance of integrated development and gain plenty from construction experiences. Taking into account the development laws and environment requests, this study proposes a development stage division method which considers county regions as planning units. The method divides development stages about the integration of urban and rural road passenger transportation reasonably, and helps different regions select development modes suitable to their development environment and levels. Through stage division, the integration of urban and rural road passenger transportation is further promoted and service equalization is further improved.

This paper investigated the impacts of various factors on travelers’ intentions to use public transportation (PT) routes with transfers based on the theory of planned behavior (TPB). Data were collected from a questionnaire survey of 503 participants in Nanjing, China. Then, structural equation model (SEM) and multiple linear regression (MLR) analysis were conducted to estimate the influences of different factor variables, e.g., habit, anticipated affect, and perceived risk on transit riders’ intentions to use route with transfer. Also, relationships among socio-demographic, conventional TPB, and extended TPB variables were explored. The results show that psychological factors—e.g., attitude, subjective norms, perceived behavioral control, and habit—have more significant influences on mode choice behaviors than socio-economic factors such as age, gender, and income. Habitual factors explain travelers’ intentions better than the three key traditional TPB variables. The findings of this study are useful for public transit agencies to develop constructive solutions from a user perspective to increase the attraction of transfer routes, which can contribute to the increase of PT ridership.

The impact of a public transport fare adjustment on the travel mode choice for residents is studied in this thesis. Analyzing the macro temporal and spatial variation of public transport passenger flow characteristics before and after the fare adjustment, it was found that there was a great impact of fare adjustment on the travel of residents. Through a questionnaire survey, the influence level of the fare adjustment, and the characteristics of travel mode transfer for commuters and non-commuters were different. Based on the temporal and spatial feature vectors of smart card data for public transport travelers, the commuters’ classification based on machine learning was proposed. Using massive public transit smart card data of about 13 million every day in Beijing, including rail, bus and public bicycles, the accurate classification of commuters and non-commuters was achieved, which proved that the classification accuracy reached 94.24%. Based on the accurate classification and significance analysis on the temporal and spatial trip characteristics of different types of public transport travelers, the effect difference of the public transport fare adjustment for the travel frequency, public transport travel mode choice of commuters or non-commuters was quantitatively analyzed. The results showed that, for public transport commuters, the proportion of travelers whose travel frequency using rail and bus obviously decreased was 14.90% and 25.47%, respectively, while 3.73% of commuters transferred from rail to bus. On the other hand, for non-commuters, the proportion of travelers whose travel frequency using rail and bus obviously decreased was 21.32% and 26.96%, respectively. The decreasing rate of rail travel frequency for non-commuters was greater than that for commuters, while the decreasing rate of bus travel frequency for two types of travelers was basically equal. The research conclusion provides scientific support and useful reference to the public transit network planning, operation management and policy implementation impact assessment.

In this study, a non-linear optimization model involving two objectives, i.e. the efficiency of the total travel time and the rate of return on an investment of public transportation companies, was proposed to dispatch buses on the town-village bus route from the perspective of the passengers and the operators. In addition, the law of gravitation was used to analyze the differences of passenger volumes owing to the different bus service frequency. Genetic algorithms were also introduced to solve the optimization model. Finally, the proposed methodology was applied to a town-village bus route in the city of Changzhou, China. The results showed that the model was well validated in terms of reliability and robustness, and could be practically used for the analysis and design of the town-village bus service frequency. Sensitivity analyses were also conducted to investigate the effects of weighting values on the performance of the proposed method.

The rapid development of economics in China has lead to a substantial increase in vehicle population and serious urban traffic problems. It has great significance to develop public transport and the implementation of a bus priority strategy in China. Bus scheduling is at the core of bus operations management and intelligent scheduling; and the optimization of the bus scheduling program is the key to improve the operational level and enhance the attractiveness. IC card data has a very large value both in the public transportation network planning and operational planning. Aiming at this problem, the technique of multi-objective optimization is used as the core tool. Based on IC card data, this paper develops a mathematical model to research the bus scheduling from the overall perspective. The method converted this complex system decision problem into mathematical models based on the following three objectives: minimizing passengers waiting time, maximizing of passenger’s comfort, and maximizing the bus company’s operating revenue.

In this study, a multi-objective optimization model was developed to minimize the total time of bus system including passenger travel time and bus operating time. In addition, bus emission was introduced to assess the bus operation based on the pollutant emissions CO, HC, and NO_x. Finally, the proposed methodology was applied to a bus route in Nanjing, China. The results showed that the total time decreased by 520197s by adding a new station between the Gulou station and the Zhujiang Road station, and the corresponding emissions of CO, HC, and NO_x merely increased by 0.87%, 1.07%, and 0.79%, respectively. It indicated that the model was well validated in terms of reliability, and could be used for the analysis and design of bus stop location. Sensitivity analyses were also conducted to investigate the effects of service frequency on the performance of the proposed method.

The management and organization of a transfer station is a key characteristic and plays a decisive role in urban mass transit. This paper focuses on minimizing the transfer waiting time, so as to optimize the issue of synchronized and coordinated train connecting in a transfer station. In addition, three different influencing factors are summarized, including transfer forms, walking distance in the station and congestion degree of passenger flow. The relationships between these factors and transfer time are also revealed. Finally, this paper develops a model to obtain the minimum waiting time of transfer passengers in all of the transfer directions, laying a foundation of coordinating arrival time and departure time.

In order to study the generality and specific characteristics of the topological structure of three-scale urban public transit networks, this paper empirically studies transit networks of 253 China cities based on space P concept. Statistical results show that the degree distribution of a small transit network can best be described by an exponential function and the power-law distribution is more suitable to larger-scaled transit networks. Three-scale networks show typical small-world behaviors which is characterized by a smaller average shortest path and a larger clustering coefficient. A transition between the larger network (N > 9000) and small network (N < 900) is observed. Urban public transit networks are well characterized by hierarchical modularity; small transit networks are tighter than larger networks. A public transfer network is sensitive to degree attack; two average shortest path mutation points seemingly exist for the small scale urban public transit network. The research conclusions have important value and provide guidance for researching urban public transit systems and public transit network evolution modeling.

The construction of a transit village is one of the effective ways to achieve the concept of transit-oriented development (TOD) planning around major rail transit stations. The mismatch between land use intensity and carrying capacity of public transit, however, may lead to the deviation from expected planning vision, which makes it significant to put forward rational land use and intensity model for transit villages. This study summarized land use pattern and layout for transit villages around different types of subway stations, and the allowable intensity model has been presented to consider the carrying capacity of the metro line. The aim is to maximum the subway system ridership, and the decision variables are floor area ratios for all types of land use. The constraints include restrictions on land use density, land use combinations, and level of service facilities. An example has been conducted to illustrate the application and result of this model.

Understanding passengers’ trip activity, especially the distribution along the metro line, is important to rail transit operation and management. Using large volumes of mobile phone user data, we derive the trip information of rail passengers. In this study, according to the generation principle and structure of the phone data, the feature of passengers’ phone data is analyzed and summarized. Based on the feature analysis, a phone-based identification method is proposed to obtain the passenger’s trip information on one metro line. By using the trip data, we analyze the distribution of a line’s passengers from the temporary and spatial dimension. The paper demonstrates the utilization of phone data in the metro system and the method we proposed contributes to the further study of passengers’ trips outside the metro.

Manual data processing and frequent transmission are main factors that affect production inefficiency in urban rail transit depots. Therefore, it is important to establish a comprehensive information management system to address such concerns. This paper attempts to analyze both the demands of sharing information amongst departments and the requirements of an ideal system designed for doing this. Based on that, the overall architecture of the system is proposed, including five aspects: information acquisition layer, data layer, processing layer, application layer and presentation, respectively. Furthermore, seven functional modules of the system in accordance with the method to share and transfer information among departments are developed in detail. With compendious design, this proposed system meets most department requirements and contributes to information transferring and sharing in real time.

Port State control (PSC) is an important method which the Port State adopts to manage ship safety and marine pollution in its territory. During the process of promoting the construction of the 21st Century Maritime Silk Road (MSR), subject to economic development and shipping, there is a lack of unified standards and requirements among different states along MSR, which causes many problems. Firstly, the level of economic development among countries around MSR is different leading to some countries cannot afford to develop their PSC. There is a lack of cooperation among these countries. Secondly, the PSC levels of most countries along MSR are weak. Moreover, the standards of PSC and the capacity of the officers of the Port State are different. Lastly, there is a deviation in the direction of the same State’s PSC. They are even not clear on the major functions of PSC, so they may be confused by the pre-supervision and the latter examination. Therefore, taking advantage of the experience from the successful PSC organizations, the states may learn from the examples of the new mechanism under Paris MOU and Tokyo MOU, then formulate the cooperative mechanism fitting better to them. In order to fulfill this goal, we shall try to unify the standards of PSC, quantify the PSC content index, and rectify the direction of PSC among different states along MSR. In the meantime, the states shall strengthen information exchanges and further develop extensive cooperation, and improve the modes of cooperation about shipyard and ship classification society among countries. Then it will create a favorable environment for the development of shipping and the MSR construction.

The subway corridor curve is a common component in the subway station. The safety and walking capacity of pedestrians along the subway corridor curve have attracted more and more research attention. The objective of this paper is to analyze the influence of the angle and radius of subway corridor curves on pedestrian flow characteristics. The Legion Studio simulation software was introduced to perform a simulation experiment, and the capacity of curves is defined and calculated, aiming to reflect pedestrian walking capacities. It is found that (1) the middle point is a critical position in a subway corridor curve; (2) pedestrian walking capacity will improve with the angle increasing when the volumes are 120 per/3m/min and 180 per/3m/min; (3) pedestrian walking capacity is seemed to stay at a better level when the radius is bigger than 10m; and (4) pedestrian volume might also influence pedestrian walking characteristics, which is worthy of further investigations in the future study.

Crew rostering for urban rail transit (URT), whose quality has a significant influence on the operation of URT, plays an important part of URT operational management. This paper takes the balance of working intensity as the objective to obtain a crew roster in a given period, and proposes a mathematical model for crew rostering. The crew rostering model is developed in two stages, which are namely rostering and assignment. The rostering model at the first stage simplifies the problem without any distinction among the type of shifts. Due to the result of the rostering model, the assignment model at the second stage assigns different shifts to specific duties. Finally, this two-stage model is applied to the management of urban rail transportation system in Beijing. The overall crew rostering in the case studies is solved by CPLEX. The result shows that the proposed model and solution method are able to efficiently find a fairer crew rostering plan for URT comparing to the existing plan.

Turning vehicles often play an important part at signalized intersections owing to the conflicting movement of different traffic. In the real-world, the through movement of shared lanes is probably blocked by the right-turn movement because of the lag time. In this situation, the green time of shared lanes cannot be fully used. Meanwhile, the signal control of right-turn lag time is utilized in large quantities. In this paper, a mathematical model is presented according to the probability and combinatory theory. The capacity model was proposed to exactly calculate the blockage probability of right-turn movement caused by the lag time and the capacity of single-shared lanes at signalized intersections. The proposed model was verified by using microscopic traffic simulation software VISSIM. The results show that the simulated results were consistent with the theoretical model.

The emergencies caused by some factors that would interfere with freight locomotives to accomplish train services on time and result in the delay of subsequent train services as well as failures of locomotive scheduling and routing. It is actually necessary to formulate a high-reliable daily working diagrams for locomotives, which can adapt to uncertain environment changes. Through the assumption that the delay time of the trains follows the negative exponential distribution, this paper analyzes the connection reliability of the adjacent train services once a train is delayed. The problem is then transformed into a multiple traveling salesman problem (MTSP) considering some complicated constraints including multi-type locomotives, train services and maintenance tasks, etc. The proposed model aims to minimize the total operational costs of locomotives. The ant colony algorithm is developed to solve the proposed model. A case study is finally given to verify the validity and effectiveness of the proposed model and algorithm.

In normal circumstances, the safety of metro train operations is guaranteed by the automatic train protection system (ATP). When the ATP system becomes ineffective, train operations are in degradation mode. In order to ensure the safety of the metro trains, the auxiliary anti-collision scheme, which is based on broadband wireless ranging technology CSS (chirp spread spectrum), can provide the real-time distance detection between the successive running trains and the alarm information of dangerous distances between trains. The paper firstly elaborates the structure, key technology and working principles of the scheme. Furthermore, the design of the ranging unit is presented. Finally, a distance measurement experiment has been completed in a subway tunnel. The test results show that this scheme can provide real-time, accurate distance information between successive running trains. The scheme can achieve safety warning requirements.

In the high-speed maglev transportation system, the vehicle control system (VCS) is an on-board part of the operation control system (OCS). It connects with the electrical facilities of a maglev train and is responsible for monitoring, safety protection and control. First, this paper analyzes the interface relationship of VCS with the train’s electrical facilities, and summaries the communication mode, key function and interactive information for each interface. In order to graphically represent the information flow of VCS, this paper refers to the data flow diagram (DFD) of software engineering and defines six graphic elements. Also, this paper uses six diagrams to systematically analyze the flow of information diagram for VCS to simplify the information flow diagram of VCS. These diagrams are drawn from the perspective of the originator of an information flow. According to the analysis of information flow diagram of VCS, the software function modules are identified and divided into four layers according to their characteristics. Based on that this paper proposes a hierarchical software architecture for VCS.

High-speed maglev transportation can provide high security as well as high speed. It not only can ensure the safe operation of the train within the prescribed scope of speed, but also can ensure that the train run to an assigned stop area and stop in safety in case of failure or emergency situations. This requires the operation control system with double speed limit protection functions for both the upper and lower speed limit. This function is realized by speed curve monitoring function module of the operation control system. In this paper, the speed limits factors of high speed maglev train operation are analyzed. The theoretical model of maximum speed curve and minimum speed curve is presented and simulated. Based on the theoretical analysis, the key function and realization mechanism of speed curve monitoring module are analyzed.

The comprehensive transportation system has developed into a new situation. To solve the problem of comprehensive transportation system, this article analyses the problems existing in the comprehensive transportation system in Shandong Province, China and conceives the comprehensive transportation system dominated by railway.

This paper presents a data acquisition scheme based on fault recording for the problems existing in the TJWX-2000 railway signal microcomputer monitoring system. Research on the secondary development of microcomputer monitoring system was conducted. This paper designed the fault recording function, and the algorithm of the fault recording. Finally, the simulation of fault recording model was carried out by Matlab. The result indicated that the algorithm could record the information of the fault in an efficient way.

With the railway signaling infrastructure to ensure trains’ safe operation, large numbers of track circuits are widely distributed along railway lines. Track circuits’ high failure rate and the limitation of monitoring track circuits indoor parameters lead to its lower maintenance efficiency. According to this situation, health management system with ZPW2000A track circuits monitors the electrical characteristics of outdoor trackside equipment by outdoor trackside acquisition units, and applies the thought of fault recorder to achieve storage of mass data, which sends effective data to upper centralized management computer by CAN bus. To realize the valid health management of track circuits, a mathematical model of maintenance priority is constructed by analyzing factors affecting the maintenance and combining track circuits real-time fault diagnosis and fault warning results, which formulates intelligent maintenance plan to improve equipment maintenance efficiency and reduce security risks and maintenance costs.

The prime objective of this paper was to develop the models of evaluating the passenger transfer time during the urban rail transit transfer with point transfer and channel transfer. The prevailing statistical model of multiple linear regression was applied to construct the relationships between the transfer time and the variables of transfer distance, marking sensitivity, passenger flow, and channel width. The models were calibrated with the field data collected from the cities of Nanjing and Shanghai. It revealed that the transfer distance, marking sensitivity, ratio of passenger flow and width had linear relationship with the transfer time.

This paper puts forward a convenient model called the cell-based intersection flow transition model (CIFTM), to extend the traditional cell transmission model (CTM) to deal with intersection situations on two-way road networks. Taking the VISSIM software as the reference standard, the performance of the proposed CIFTM is compared with the widely used general node model. The results of the comparison show that the CIFTM can model more realistic traffic flows occurring at intersections than the general node model. Also, the CIFTM’s simulation results are identical to those of VISSIM, and demonstrate CIFTM’s potential to assist with other traffic engineering research topics such as dynamic traffic assignment.

Intersection is an important part of an urban road network. Vehicle delay at signalized intersections is a significant index of traffic running efficiency and service level. Considering that the principle of the VISSIM simulation method and spot sample method are only used to calculate the traffic delay at the signalized intersection, these two methods have not been used to optimize the signal timing. In order to obtain the signal timing of intersections that create a minimum traffic delay, signalized intersections are researched on in this paper, and an optimization scheme of intersections that is based on a graphical method, and the HCM2000 algorithm is designed. Firstly, we use the graphical method to analyze and calculate the delay of one approach at intersections that are unsaturated. Secondly, we get the optimization scheme of intersections through the HCM2000 algorithm. Thirdly, this scheme is verified with the practical measured GPS data in a city. The results show that the scheme has a perfect feasibility, and the intersection delay of this scheme is improved separately by 5% and 8%.

Ramp metering has been widely used for managing motorway traffic congestion. The majority of the research in the area of ramp metering strategies is concentrated on local traffic responsive algorithms. This paper presents a dynamic optimization framework for maximizing the efficiency and stability of motorway operations with consideration of uncertainties in traffic demand and flow characteristics. The optimization model based upon the macroscopic cell transmission model (CTM) which captures traffic dynamics by a piecewise linear fundamental diagram. The global optimal solution is solved by using CPLEX solver. The optimal solution provides useful insights and guidance on how we should manage our transport infrastructure to maximize its efficiency with uncertain demand and supply.

To improve the study of the system of separating trucks from passenger vehicles in China, this paper proposes a new vehicle classification. The results of simulation experiments tested the advantages of this new classification compared with the traditional classification on freeways. The new classification provides a scientific based vehicle classification for reforming the system of separating trucks from passenger vehicles. In this paper, through scientific argumentation, it presents a method for evaluating the system of separating trucks from passenger vehicles by comparing the indicators of average speed, delay, speed dispersion coefficient, and lane changing times, which provides the research idea for the evaluation of the system of separating trucks from passenger vehicles.

Speed bumps are extensively used to regulate speed and improve traffic safety. Speed bumps can also affect traffic characteristics significantly. Aiming to explore the impact of speed bumps on traffic flow, we propose a simulating method with improved cellular automata model based on the NaSch model. The developed model incorporates the aspects of three diverse driving behaviors: (1) type of drivers (cautious or rash), (2) decelerating range, and (3) passing speed. Numerical results show that traffic flow state experience phase transitions from free flow to stable flow to traffic jams due to the installation of speed bumps. During the stable flow, a speed bump can cause small-scale traffic jams in the upstream. The influence of speed bumps enlarges significantly as cautious drivers increase and the passing speed declines, but the expansion of decelerating range has a less significant effect. The results hope to enlighten sensible applications of speed bumps.

Anticipatory traffic control determines signal timings to optimize network performance, taking into account travelers’ route choice responses and the resulting flow patterns. In general, the route choice response is predicted through traffic assignment models. However, model-reality mismatch usually brings suboptimal conditions characterized by unexpected congestion to the real-life system. The objective of this paper is first to propose an iterative optimizing control algorithm to elevate traffic system to its real optimal performance, by learning from errors between modeled and measured flows. A key algorithmic implementation issue regarding calculation of the network flow sensitivity is then addressed. We present a method to estimate the derivative of real flows with respect to control variables. The proposed algorithm is tested on a simple network as well as a midsize network. Numerical examples confirm the effectiveness of the new reality-tracking control strategy and its ability to identify (local) optimal solutions on real traffic networks.

Bus stops are divided into midblock stops and nearside stops near the intersection in this paper. A total of 7-day data during peak hours were collected at the Daliushu North Stop and Erligou West Stop. To analyze the distributions of passenger arrival rates, the passengers at stops near the intersection are divided into two groups depend on whether the passengers’ arrival behavior are influenced by signal or not. The distributions of passenger arrival rates at different stops are determined. The results show that the passenger arrival rates for midblock stops and nearside stops near the intersection where the passengers’ arrival behavior are not influenced by signal follows a gamma distribution. The passenger arrival rates for nearside stops near the intersection where the passengers’ arrival behavior are influenced by signal follows a lognormal distribution. Waiting time models are derived and proven to be reliable based on the determined distributions of passenger arrival rates.

Assuming that the travelers are heterogeneous in terms of their reference points, we divide the whole travelers into several classes and develop a multi-class cumulative prospect theory-based equilibrium model by incorporating such heterogeneity. The numerical results show that the travelers with lower reference points prefer to choose the routes with higher free-flow time but lower risks, while travelers with lower reference points are likely to choose the routes with lower free-flow time but higher risks. The results show that the risk parameters indeed significantly influence the resultant flow distribution. Furthermore, it is found that the higher the OD travel demand, the more serious the travelers’ risk-aversion behavior.

In order to accurately and rapidly estimate vehicle queue length at signalized intersections, the basic assumption is made that traffic flow in transition is divided into two parts on the basis of traffic queue process analysis and the survey data. Then, the real-time queue length estimation model is formulated and the parameter calibration is proposed. The equivalent queue length model is developed. The models are validated by the field data from the cities of Dalian and Changchun in China. The results indicate that the average relative errors between the estimated and observed queue lengths are 6.22% and 7.95%, respectively. Moreover, the equivalent queue lengths are all longer than the observed ones for congested traffic. The new method can be easily implemented and is applicable to address the vehicle queue length estimation under the other situations.

Traditional signalized intersections use fixed-time control. The duration of a signal is invariant in a period of time. However, traffic volume changes drastically and is nonlinear. With the development of vehicle-to-infrastructure (V2I) communication technology and sensors, original signal control is antiquated. In this paper, how infrastructure obtains vehicle data is introduced. Applications on-board or mobile phone applications (apps) will transmit information such as position, speed, and heading to servers on the roadside. The signal optimization algorithm uses this information to calculate delay and queue length and then allocates phase duration on the basis of these data. A simulation using NETLOGO5 was set up to verify the algorithm. The results indicate that for common crossroads, it works well in unsaturated traffic conditions or with no more than two branches in a saturated condition. As for a T-intersection, this algorithm can reduce delay significantly.

In this paper, the feasibility of evaluating traffic operation status at freeway networks by utilizing dedicated short range communications (DSRC) data is discussed. The method of data processing as well as the data analysis algorithm are proposed. The data analysis and processing method is done based on the DSRC data and the toll dataset of an operational freeway network from 1st to 15th of July 2015. This includes some fundamental pieces of information, such as the penetration rate of electronic toll collection (ETC) vehicle, the ETC vehicle flow analysis, the proportion of missing data, the speed calculation, and the freeway corridor traffic operation index. The analysis shows that it is feasible to evaluate the traffic operation status of freeway networks by DSRC data when the ETC penetration is big enough, and that the outputs of DSRC data can be used for real-time traffic information service.

In order to improve the level of operational monitoring and management on freeways, this paper develops an optimal model for AVI (automatic vehicle identification) sensor locations on freeways, where the maximized monitored total weight vehicle-kilometers is considered as the optimal object. First, according to the characteristics of a freeway corridor, a new method is proposed to replace the direct graph topological structure extraction method. After that, the incidence matrix, adjacency matrix of the topological graph and the relationship matrix between link and origin-destination paths are chosen as input parameters; the calculation method of the monitored total vehicle-kilometers is then established by matrix operations. Then, the optimal model about maximum vehicle-kilometers is developed. Finally, the effectiveness of the proposed optimal model is evaluated through a simple example. The results show that the proposed model is feasible for freeways, and the principles of maximum sensor coverage and maximum traffic flow are considered.

The behavior of lane-changing for buses has an effect on the traffic flow around the bus stations. Despite the growing literature on this subject, very few empirical studies exist on the mathematical models of the influence of buses on the traffic. The purpose of this research is to build a mathematical model of the delay of traffic flow induced by buses entering and exiting the bus bay. A bus bay in Beijing, China is taken as an object. First, the headway distribution is analyzed. Second, the process of buses entering and exiting the bus bay is discussed and a delay model is formulated combining the relevant theories of probability theory and calculus knowledge. Finally, the model is verified by conducting an error analysis. The study provides a theoretical basis for estimating the delay of the traffic flow.

Arterial signal coordinated control system and transit signal priority strategy are widely used for decreasing delay and improving the level of service in the urban areas, therefore, transit signal priority (TSP) optimization under arterial coordinated control condition needs to be focused on for improving urban traffic efficiency. This paper develops an arterial signal coordinated control method regarding TSP scenarios considering passenger delay and transit schedule adherence simultaneously, and a passenger-based MAXBAND graphic method is proposed to a generate coordinated control plan. Consequently, a test arterial segment of Nanjing (in China) is simulated by the VISSIM software platform to evaluate and analyze the performance of the proposed optimization method in decreasing delay and improving system reliability. The results illustrate that the proposed optimization model presents promising outcomes in transit signal priority under signal coordinated control conditions compared with traditional coordinated optimization methods.

Mixed-traffic streams that contain motorized vehicles (m-vehicles) and non-motorized vehicles (nm-vehicles) are very common in urban areas, especially in the branch without physical isolation of m-vehicles and nm-vehicles. To study the impact of m-vehicles on nm-vehicles, a comparison study between driving m-vehicles with and without nm-vehicles on their right sides was conducted. Data was collected by video recorder at one cross section of a road. Mixed-traffic analysis has focused mainly on the flow rate, variation of speed, acceleration, and headway as indicators to reveal driving behavior. In particular, this paper discusses the nm-vehicles’ impact on the m-vehicles’ trajectory when the m-vehicles and nm-vehicles are on the same cross section of road. Statistical results show that the lateral position of m-vehicle is related to the lateral position of nm-vehicle on its right side, especially, when the nm-vehicles is close to the m-lane. The potential hazard of nm-vehicle’s behavior was also determined.

Considering there are thousands of signalized intersections in Shanghai, it is necessary to find a rapid calculation indicator to evaluate the intersections’ operational condition and select intersections with large improvement space for traffic management departments. Based on the large number of floating car data, stop rates were calculated for 144 signalized intersections in Shanghai according to the travel speed. Meanwhile, signalized intersections’ traffic, geometric, traffic control, as well as location characteristics were also collected. A generalized linear model has been developed to analyze the relationship between these characteristics and the intersections’ stop rates. The results indicate that: larger traffic volume, less main road lanes, more secondary road lanes, the set of left turn lanes, separating motor from non-motor in the main road, and a once crossing facility for pedestrians would contribute to a larger intersection stop rate.

In order to optimize the coordinated control of the urban expressway exit ramp and the adjacent intersection, this research analyzes the causes for congestion at the adjacent area between the expressway exit ramp and conventional road. Combining with a relatively common form of elevated road with parallel roads, a coordinated control optimization scheme of expressway exit ramp and adjacent intersection have been put forward. This paper simultaneously analyzes the theory of single point control of intersections, which is based on regular traffic management and control, and an optimization method is offered, The integrated control of expressway and the ground connection area is realized. Finally, a contrast test scheme is designed through VISSIM, and the results show that signal conditioning based on the conventional control can promote expressway exit ramp traffic entering the intersection and travelling more smoothly, which proves the feasibility of the method.

This paper aims to compare the rear-end crash risk in work zone activity areas by using work zone traffic trajectory data collected from Singapore and Beijing, as well as analyze the differences of the traffic flow characteristics between the two cities. A surrogate safety measure, time-to-collision (TTC), is adapted to measure vehicle rear-end crash risk. Potential reasons for the differences in the work zone traffic safety in Beijing and Singapore are discussed based on the comparison. Some practical improvement plans, based on guidance from Singapore are then recommended for implementation in order to improve traffic safety in work zones in Beijing.

Vehicle license plate recognition technology is an important component of an intelligent traffic surveillance and control system. This paper details a study of travel characteristics of vehicles on urban arterials by using license plate data. Example verification was conducted in Shenzhen by applying data mining technologies. According to the research, vehicles seem to follow certain temporal and spatial distributions in an urban road network. A key focus of this study was the method for gathering spatial distribution characteristics of vehicles from the analysis of license plate data. First, it is proposed that there are obvious spatial patterns regarding travel behaviors of vehicles during periods of travel with high recurring demands. Second, the existing methods for deducing origin-destination (OD) information are summarized, and a new method for utilizing vehicle license plate recognition data is presented. Then, the proposed OD deduction method was applied in the actual data analysis in the city of Shenzhen. Finally, application of vehicle license plate recognition data in analysis of traffic structure along key sections of roadways was also proposed and then verified with real data in Shenzhen.

The traffic bearing capacity of a road network can be defined as the maximum number of vehicles that a road network can efficiently handle, which is an important basis for dynamic network management. This paper first presents a newly defined macroscopic fundamental diagram (MFD), that is, the relationship between the numbers of vehicles in the network to the number of vehicles that leave the network. Second, data requirements and detector distributions will be discussed. Third, the newly defined MFD is modeled using piecewise fitting and the least squares method; additionally the method for determining traffic bearing capacity is proposed. Finally, the developed method will be tested on two networks, including a computer-generated network and a real-world road network. The results show that the proposed methods are effective for modeling the MFD and determining the traffic bearing capacity of a network.

Public transport service systems provide travelers with comprehensive, accurate, timely, and perfect traffic information service. The system mainly depends on various traffic information of the city’s traffic database or processing center to collect all kinds of information. Then the system releases the information to the travelers by the Internet, mobile phones, traffic TV broadcasts, and so on. The basis of theories in this paper will be through the analysis of the urban public transport‘s influence factors of the traffic information system service level. According to the scientific, practical, systematic, comprehensive, and comparable indicators, this paper will build the urban park-and-ride system service level evaluation index system.

Owing to the uncertainty of the traffic system and incomplete travel information, travelers usually make route-choice decisions relying on their own experience. In this paper, we assume that commuters make their route-choice decisions based on the perceived cost in a logit-based manner, and different memory-based learning strategies on previous travel time, such as smoothed adaptive pattern and peak-end adaptive pattern (anchoring on highest travel time or lowest travel time), are proposed to obtain the perceived cost. A numerical example is also given for comparing the impact of different learning strategies on flow evolution and further illustrating the model. The results show that the peak-end adaptive pattern could capture the commuters’ risk attitude in the route choice process and thus provide a more actual traffic flow, which is obviously helpful to traffic control.

The urban development of Beijing, China has increased rapidly in recent years. Meanwhile, there is a larger increase in the possession of private cars. This paper is mainly based on the real time traffic data of urban roads and districts published by the Beijing Municipal Commission of Transport. Based on these data, we explored their distribution characteristics. Utilizing R programming, we determined the time sequence regularity in different seasons. By rattle analyzing of R, we distinguished the difference and relations of six districts as well as in four zones between different ring roads. In reference to the regional distribution, we took the conventional traffic control and other factors into consideration. Eventually, we draw the conclusion and provided some recommendations for delivery arrangements of freight companies and road users. Moreover, it can be adopted by policymakers to adjust the traffic rules for more efficient and real time adaptability.

The vehicle-waiting area makes contribution to improve the spatial utilization in the intersection, decrease the queue length and improve the capacity of the approach. However, the vehicle-waiting area may cause some detrimental impacts, such as increasing stopping frequency and fuel consumption. In order to investigate the advantages and disadvantages of the vehicle-waiting area, this study selects the waiting-area for through and right-turn vehicles (hereafter abbreviated as TR waiting-area) as the research target. This study analyzes vehicles’ behaviors in the TR waiting-area. Based on the analyses, this study proposes a model for calculating the capacity of the TR waiting-area. Then we validates this model with the data collected in the Jiangsu Road–Changning Road intersection, Shanghai. The data is also used to compare the capacity of the lane with and without TR waiting-area. This study analyzes the beneficial impacts and detrimental impacts from the emission of waste gas, average stop frequency and average delay.

In China, accesses are always randomly set and can even be at the bottleneck of an urban road. To analyze the impacting mechanism of upstream access to the adjacent signalized intersection, a new intersection capacity model is established, which considers green time loss occupied by access traffic. Then, the occupation time of different types of access traffic are respectively regressed by measured data. Another case study shows that the new model is more close to the measured data than HCM method for the signalized intersection with an upstream access. Combined the new model with the capacity reliability theory, explore the access design method for the distance and organization mode design. The curve reflecting the relation between traffic volume, distance, organization mode and capacity reliability can be used as access design reference. Paper results supplement access management theory to a certain degree. However, more work should be done to reduce or demonstrate assumptions before application.

Real-time traffic signal countdowns display the time remaining on the traffic signals that can alert drivers and pedestrians under a phase start time, so that drivers and pedestrians can make the appropriate response with the upcoming phase change, with reasonable and efficient use of time waiting for the green light to display the startup phase. To study the impact of the countdown lights on signalized crossing capacity to Beijing’s West Fourth Ring Road crossing for a typical object, both the countdown and the no-countdown crossing signals were observed. The T-test method using statistical analysis found similar environmental signals traffic crossing. There is a countdown display compared to the saturation time headway and lost time has been reduced crossing traffic crossing with no-countdown display capacity and traffic safety increased.

Large scale activity is an important source of urban road network traffic congestion. In this paper, a cellular automaton model is proposed to simulate large scale activity traffic flow in urban two-way-four-lane network systems without signal control at intersections. In the proposed model, a two-lane traffic rule is adopted to represent vehicle movements on road sections, turn lane changing and overtaking lane changing are allowed, and vehicle movements in intersection areas are determined by priority which relies on vehicle position. Simulation results show that the severity of traffic congestion increases with the increase of activity scale and background traffic.

In order to study the suitable conditions of different reform plans of separating trucks from the passenger vehicles and provide evidence and guidance for reforming the system of separating trucks from the passenger vehicles, this paper provides an index system, including delay, times of changing lanes, coefficient of speed variance and so on. What’s more, this paper carries out the analysis to this index system by applying the method of principle component analysis (PCA) and gets the selection and evaluation methods of reforming the system of trucks from the passenger vehicles. It confirms the effectiveness of the method by comparing it with the other methods, which are the mainstream in current through sequence-number summation theory. The results show that the method of PCA is more effective than other comprehensive evaluation methods when they are used to evaluate the efficiency of reforming the system of separating trucks from the passenger vehicles.

In order to estimate the traffic delay of the Jinan Yanshan interchange west export intersection during evening peak hours, the field measurement was taken to get the simulation parameters of the west export intersection. Several signal timing optimization schemes for the intersection were designed according to Highway Capacity Manual 2010 (HCM2010). After the analysis with VISSIM, the results show that: compared with no signal condition, current signal timing can relieve the road traffic congestion in some sections of the west export intersection, but further optimization is still needed. Also, among the six different signal timing optimization schemes, scheme D performs better than the others, which can dramatically improve the traffic passage efficiency and relieve delay. Therefore, traffic efficiency in the interchange export intersection can be further improved by optimizing the signal timing.

Car-following is the most frequent driving scenario, and is characterized by headway. Headway is a measure of the temporal space between two vehicles. It relates to the time available for a driver to react, and is a safety measure of car-following behavior. The characteristics of car-following headways remain poorly understood in China and this has a secondary effect on road alignment design, road capacity, traffic flow stability, traffic safety, and the design of many in-vehicle systems. With high validity naturalistic driving data, this study investigated the distribution of drivers’ car-following headways and how drivers would adjust their headways due to level of operating speed, visibility, roadway type, and traffic density. From 60,689 km of naturalistic driving data, 1,489 car-following events were identified. Headways were then extracted and statistically compared across different driving situations to quantify changes in car-following headways as a result of driving situations. The results of this study show that (1) the distribution of car-following headway was similar to a lognormal distribution; (2) drivers tended to maintain longer headways in slow-speed driving, nighttime, surface roads, and dense traffic conditions. The results of this study may be valuable for understanding car-following behavior and traffic simulation.

When residents are choosing a path, some residents mainly combine their own driving experience to select the optimal path of familiarity network. The situation of accidental factors is too big that it may cause road congestion. Therefore, it is not the best means to choose a route. This paper builds a new information releasing model. Firstly, we determine the network in any node, and the surrounding road network consisting of region as a study unit by processing the multi ways probability distribution model to determine the origin destination traffic information. Secondly, we get the road load degree and clear out the walker road expected load degree, road construction negative load dynamic change interval, to determine the corresponding sections of the degree of load variation. Lastly, we imply our study.

Correct, immediate and effective decision of emergency preparedness will powerfully mitigate and reduce the damage of ship oil-spill accidents. However, emergency decision-making is a complicated cognitive process influenced by many factors, which makes a significant impact on the effectiveness and efficiency of emergency plan implementation. An understanding of the reasons why people choose to implement a contingency plan in a certain manner is critical to the development of appropriate policies. In order to identify these influencing factors, this paper introduces a stated preference model to design a questionnaire for dealing with the determinants of spilled oil clean-up decision making. In this context, a survey of 240 emergency response officers from six major sea ports in China has been obtained. Moreover, a multi-logit model is utilized to generate an explanatory model, which shows how emergency response officers with different personalities make decisions when faced with different situations. The methodology can be used in other similar cases to provide valuable suggestions to improve the reliability and reasonability of emergency decision making.

This study proposes a statistical model to estimate link traffic flows in a congested network. In this study, it is assumed that traffic flows conform to the stochastic user equilibrium (SUE) principle. In the case of SUE, as we know, the network traffic flow pattern is obviously affected by the dispersion parameter adopted in the logit formula. Hence, we make some efforts to estimate this dispersion parameter in this paper. In this study, the Bayesian theorem is applied to derive the probability density function of the conditional distribution. While the calculation of Bayesian posterior will typically be intractable, a Markov chain Monte Carlo (MCMC) algorithm is used to estimate the traffic flow. The performance of the proposed method is tested on the Nguyen-Dupuis network through a numerical example.

Real-time traffic incident detection is essential for traffic management and control. This paper proposes a traffic incident detection method based on a data mining technique named bagging support vector machine (bagging-SVMs). The performance of the proposed method was evaluated using the data collected on I-880. The performance measurements include detection rate (DR), false alarm rate (FAR), correct rate (CR), and F-measure. Several key issues were investigated to find the kernel function that better fits the new model and to calculate the important parameter bagging times. The results indicated that the standard SVM model with linear kernel function has advantages in traffic incident detection and is better than the other three models, comparatively. However, the bagging-SVMs model with a radial kernel function has a better comprehensive performance than the standard SVM model when bagging time is greater than 70. Models that use the polynomial kernel function also perform well even when the bagging time is less than 70. Preliminary results show superior performance of bagging-SVMs compared with legacy algorithms.

In China’s urban road traffic, aggressive lane change driving behavior is very prevalent. Statistics from traffic accident data show that aggressive lane changing is one of the biggest potential dangerous behaviors for urban road traffic safety. This study aimed to analyze the impact on vehicle operation by aggressive lane change compared to normal lane change. Based on the actual road traffic environment, we built a real vehicle driving data acquisition system to collect driver operating data, including velocity, acceleration, and lateral acceleration. Based on the experimental data from vehicle test, we determined “time headway” as a quantitative parameter value to define “aggressive lane change.” Changes in vehicle movement are more obvious under the impacts of aggressive lane change and show that aggressive lane change makes drivers produce an oppressive sense of space and has a great influence on driver operation.

Fire protection and response is most costly as an important public service in urban areas. It is essential to optimize fire station locations because the loss can be unbearably high due to a fire disaster if no timely and reliable fire response service is available. This paper reviews (1) key factors considered in fire station location formulation, (2) development of the covering and maximum covering approaches to this problem, and (3) heuristic algorithms to solve the problem. Remarks have been provided on new factors that may affect the choice of fire station locations, including traffic congestion, uncertainties, and the latest technologies.

With the rapid development of expressway systems, traffic safety issues caused by speeding have been concerned by the public. Speed limit, as one of the most common safety measurements, plays an irreplaceable role in the protection of traveler safety. Therefore, a comparative study on speed control effect of speed limit facilities on the expressways is of practical significance for ensuring traveler safety and operation efficiency. In this paper, the Beijing-Hong Kong-Macao Expressway was selected as a sample site for on-site speed surveys. Four types of the speed limit control modes of expressway, including color pavement, vibration marking, deceleration marking, and portal frame, were chosen. The speed of cars and large size vehicles were collected. On the base of speed surveys, the evaluation system was developed and a comparative study on the evaluation of speed control effects was accomplished. The positive effect of the proposed improvements of speed limits was verified.

Pedestrian walking speed is an important reflection of pedestrian characteristics. From the perspective of statistics analysis, this paper aims to investigate the statistical distribution models of pedestrian walking speed and the impacts of pedestrian gender and age on their walking speed. Based on the data of the pedestrian walking speed in port shopping centers, the relationship between pedestrian walking speed and pedestrian density is analyzed using the VISSIM simulation platform. Also, the relationship model of pedestrian walking speed and pedestrian density is provided in this paper. The results show that pedestrian walking speed is affected and shown as a log-normal distribution model when the pedestrian density is high. Moreover, pedestrian gender and age are also major contributing factors. Finally, a linear negative correlation coefficient is calculated between pedestrian density and walking speed under certain pedestrian flows.

Tibetan Plateau along the highway terrain is with better conditions, and road alignment indicators were generally great. There is a little horizontal interference factor of the road that is not at urban area. The driver often desired for higher speeds. In the high altitude environment, the driver is difficult to guarantee attention, increasing the severity of the accident. Accident data covers the State Road of 214 with 1,205 km in Qinghai. Two indicators that the rate of accident and deaths caused by speeding measure the number of road accidents caused by speeding and accident severity. The study gathered basic data by field investigation. The field was accident-prone sections that were identified by analyzing accident date. To understand the status of the vehicle’s operation status in Tibetan Plateau, the author analysis the accident-prone sections’ traffic flow conditions through the proportion of speeding vehicles and speeding vehicles’ speeding amplitude. For special plateau environment, this text proposed illegal speeding preventive measures, based on setting a reasonable speed limit.

The management of dangerous goods transportation is essential for reducing accidents and ensuring transportation safety. Few integration studies have specified management both in normal and emergent situations, therefore, an emergency management system for dangerous goods transportation was constructed based on ArcGIS. Visual Studio 2010 and SQL Server were adopted as the development platform and database, respectively. An information map of dangerous goods transportation enterprises was portrayed by ArcGIS. ArcGIS Engine combined with the C# language was utilized for secondary development and emergency management system resulting in both geographical coordinates and enterprise location. This system could present key information of enterprises from multiple perspectives. The shortest paths and best rescue strategies under emergency were further investigated via data mining. Finally, data of Guizhou province were applied. This research would directly manage dangerous goods transportation in an intuitive way, so as to provide decision making strategies for an enterprise manager.

Many incidents and crashes can be attributed to driver distraction, due to increasing use of in-vehicle information systems (IVISs). Although visual and cognitive distraction has been studied extensively, relatively little research has compared the differences of effects between them on driving performance in the field. To fill this gap, twelve participants drove on roads under three distraction conditions: without distraction, with visual distraction, with cognitive distraction. Results revealed that visual distraction leads to higher speed variance and resulted in higher workload. Cognitive distraction made steering less smooth, but improved lane maintenance. Visual distraction was associated with more off-road glances, while increased blink frequency was observed during cognitive distraction. Both distractions caused gaze concentration and slow saccades when drivers looked at the roadway. Overall, visual distraction interferes with driving performance more than cognitive distraction, but they influence vehicle control and gaze behavior in different ways. These results suggest that minimizing visual demand is particularly important in the design of in-vehicle systems and also will be beneficial for the development of distraction countermeasures.

Road crashes are still a big problem for traffic safety. Rear end crashes are one important crash type researchers are trying to mitigate. China’s in-depth crash study collects and analyzes road crashes in order to provide data support for new technologies research. This paper uses data collected by the China in-depth crash study to analyze rear end road crash characteristics in China using three parts: passenger car-to-passenger car rear end crashes, passenger car-to-truck rear end crashes, and truck-to-truck rear end crashes. Results found that driving at night and fatigued driving are main factors for truck rear end crashes. Use of safety belts was found to decrease an occupant’s injury severity. Underrun protection devices and small overlap collision testing are necessary in China.

Vehicle stability is important for ensuring road safety. Shown in previous studies, crash risks on freeways were closely associated with vehicle stability, especially when passing a horizontal curve. Claimed dangerous, combined horizontal and vertical alignments are used frequently in mountainous freeways. Some studies have provided the relationship between road alignment and vehicle stability, but they involved the 85th percentile value or average value of all the drivers, which ignores the difference between individuals. In this study, combined alignments implemented in a driving simulator were classified into four types. Lateral offset and lateral acceleration were investigated on individual levels. The influence of combined alignment on vehicle stability was analyzed using random effects logistic regression models. The models showed that the slope, curvature, length, and turn direction had significant influence on vehicle stability. For different types of combined alignments, the significant influence characteristics were different.

In order to further study traffic capacity and service level of freeways, this paper establishes a multiple linear regression model to analyze traffic capacity of an A-type weaving area of a freeway based on data in HCM2000. After analyzing, relationships between capacity, length, lanes, the velocity of cars, and weaving ratios of weaving area were obtained and the model parameters were determined by fitting of the data. Validation was proven by verifying the road and traffic data from a weaving area of one expressway. The results show that the degrees of fittness of the parameters and other influence factors for the reciprocal of capacity and length in the weaving area are not less than 0.963 and 0.929, respectively. The traffic capacity of weaving area is inversely related to the length and the lanes but has positive correlation with weaving ratios. The relative errors of the model are within 0.1.

A human factors laboratory study was conducted to evaluate the effect the number of road names on an expressway exit guide sign. Research has shown the influence of the guide sign information on motorists, however questions regarding the number of road names that can be presented on expressway exit guide signs is not known with certainty. The results of the study indicate that more information on an expressway exit guide sign leads to an increase in confirmation time and subjective assessments grow. From the results, an evaluative index of expressway exit guide sign information overload threshold can be determined. The results show that when the number of road names on an exit sign is six or less, motorists can perceive and understand the information on the sign faster.

Information on hazardous actions of parties involved in a crash could support determination of crash responsibilities. However, information on hazardous actions that is explicitly recorded in a crash report may often be inconsistent with the narrative given in a crash report. Identification of such inconsistencies requires a large amount of manual effort. To address this issue, a new method is proposed in this paper to automatically classify hazardous actions described in a crash report based on the narrative. The proposed method leverages natural language processing (NLP) techniques to extract features from the narratives, as well as machine learning (ML) techniques to classify the hazardous action described in a narrative based on its values corresponding to selected features. The proposed method was preliminarily tested on a randomly selected set of crash reports from the state of Michigan. An accuracy of 92.77% and a kappa statistic of 83.54% were achieved on the testing data, which shows that the proposed method is promising.

Transport of dangerous goods via railway is quite complicated as there are many uncertain factors that can threaten the security of such operations. A limited supply of emergency vehicles must be dispatched effectively in the event of a railway dangerous goods accident in order to minimize losses. Therefore, a multi-objective model of emergency vehicle dispatching for railway dangerous goods accidents is established. The model considers the minimum time for rescue, the minimum losses due to the accident, and the lowest cost as the objectives. Meanwhile, cooperative game theory is used by regarding each goal as a player and all possible emergency vehicle dispatching schemes as the strategy set. The optimal emergency vehicle dispatching scheme is proposed by solving the cooperative game model, which considers the players’ profit equilibrium and an overall high return. Finally, an example is given to test the model feasibility and effectiveness of the algorithm.

This study focused on vulnerable road user crashes induced by mixed traffic at signalized intersections in China. Data on various possible risk factors including road design, signal control, and weather conditions were collected and analyzed accordingly. A count data model was adopted for crash frequency analysis with random matched resampling database to remove the effects of excess zeros on prediction performance. The results indicate that more accurate and reliable parameter estimates and reduced standard errors can be obtained with the random matched resampling method. As results, cycle time of signal, separated right-turn lane (SRL), left-turn waiting area (LWA), and awnings are all significantly related to the risk of vehicle-to-vulnerable road user crashes. This helps to shed light on the development of remedial engineering and traffic management and control measures.

Speeding is quite common on freeways, and speed cameras often have limited coverage. Thus, the effect of them on speeding behavior is unclear. This lack of knowledge on the effect of the cameras may lead to irrational decision making in terms of investment in and configuration of enforcement facilities. In this study, sample speed data were collected at five locations near a speed camera on the G45 Freeway (i.e., the Daguang Freeway) in China. Statistics showed that the distance effect model of the speed camera can be represented by a concave parabolic function. Speeding drivers begin to slow down to speed limits when they approach advance warning signs, and then they immediately speed up after passing the enforcement site. The deterrent effect of fixed-site speed enforcement is limited to a 300-meter range. Deterrence theory was used to conclude that there is an obvious distance halo effect for fixed-site speed enforcement locations. The findings of this study imply that the deterrent effect of fixed-site speed enforcement is weak due to its short effective distance and overt form of control. Ultimately, reasonable configuration of enforcement facilities and use of fixed-site facilities in combination with mobile speed enforcement are appropriate methods that can be used to reduce speeding.

Various research on heart rate variability (HRV) have focused on the characteristics of the peaks and the valleys of a heart rate graph and most have been analyzed using medical devices. This paper developed a driving physiological indicator extraction method. The method is based on a pulse signal detection with a feature point identification model and an abnormal signal detection combined with a revamp model. According to physiological theory and the relationship between pulse and ECG readings, the pulse feature points can be detected. This method is easier and more accurate than the existing wavelet pulse signal detection method, which can be used in the wearable devices, such as the smart band and the smart watch. The method was also validated efficiently and accurately in the experiments.

Left-turns are one of the most critical maneuvers at signalized intersections. There are several types of left turn signal phasing in use: protected-only, permitted/protected, permitted-only, and prohibited. If the protected part of a left turn phase is assigned before the through phase starts, a left-turn sequence is called lead. If the opposite is true, it is called lag. Currently there are no uniform guidelines on left-turn installations. Furthermore, the practice on left-turns is not consistent. This paper summarizes a literature on left turn phasing, sequencing and left-turn signal displays (e.g., flashing yellow arrows) and points out the key findings and shortcomings. The authors propose computational and simulation tools—driving simulators, microsimulation, surrogate safety models and augmented reality for future research which could lead toward the unification of left-turn set of guidelines.

The objective of this research is to develop a safety management model that uses event chains and complex networks to evaluate the risk levels of airport emergency events that are caused by flight delays. Safety management is generally divided into risk identification and safety risk management. Risk identification is used to determine whether the events are actually hazardous under the existing security measures. Safety risk management is used to acquire the probability and severity of the risk event. A subset of data gathered from the hub airports was applied to accomplish this study. The results show that conflicts between passengers and service staff, failure to check in on time, and too many gathering passengers have the highest risk levels. These events are unacceptable and should be eliminated over time.

The roundabout’s capacity is usually analyzed by the gap acceptance theory model. There are obvious differences between the value calculated by the model and the observed values. This study modifies the model with a parameter reflecting the change of the critical headway analyzed by multiple linear regressions, and validates the model with the data from VISSIM simulation. Compared with the classical model, the relative error of the modified model reduced by 50 percent.

Road traffic accidents remain a major concern in China due to an astonished number of casualties. To better investigate the cumulative regularity of accidents at different severity levels, a novel method considering cumulative probability of severity distribution is introduced. By using Heinrich’s theory, a 7-year accident dataset collected in China is applied to analyze the relationship between accidents and number of fatalities. Given the positive-skewed characteristic of accident data, the inverse functions of the cumulative distribution function of the chi-square distribution, F distribution and Weibull distribution are used to establish the statistical model to describe the distribution regularity of road traffic accidents. The results reveal that when road traffic accidents in China are classified by fatalities, the accident data conforms to the characteristics of positive-skewed distribution. The best degrees of freedom of the chi-square distribution and F distribution are 0.16, 19, and 12, respectively, and the scale parameter and shape parameter of Weibull distribution are 0.7 and 1.1, which are obtained by fitting the accident data. The test results of goodness-of-fit by minimum mean square error, F(19,12) is more reasonable to explain the distribution of accident severity on Chinese roads from 2005 to 2011, and the fitting error within an acceptable range.

Accidents can be seen as the result of an unsuccessful interplay between drivers, vehicles, traffic environments, and organizations. Human actions are an important source of vulnerability for road transportation. Current research about lane changing focuses on driving intentions. Few studies are focused on human failures during lane changing processes. In this paper, based on cepstral analysis, the characteristics of steering operation are studied to research driving failure characteristics during the lane changing processes. Then, a BP neural network model of lane changing is established to identify driving failures in lane changing processes. The identification rate of this model is 70%, which can be used to improve driving safety.

This article studies the awareness and comprehension of traffic signs of vulnerable road users, for example passengers and cyclists; and it also studies how personal factors influence the surmise of traffic signs. From the way of conducting a questionnaire investigation, the research collected the personal data of users’ factors, and then tested their degree of comprehension of traffic signs. We found that gender, their own experience with traffic accidents, and their relatives experience with traffic accidents had no effect on their degree of comprehension. Riding experience, family car ownership situation, the attention to traffic signs, and the experience of learning driving license had a significant impact. However, the willingness to get a driver’s license doesn’t impact the comprehension of subjects significantly.

To improve the evacuation efficiency of low-mobility populations, a transit staged evacuation strategy is proposed in this paper. The proposed strategy divides the evacuation process into two stages, the internal evacuation stage from the aggregation points to the transit hubs, and the external evacuation stage from the transit hubs to final shelters. Also, a transit network optimization model is established to locate the transit hubs and to search the transit routes with the target of a minimum total distance of transit-based evacuations. To solve the optimization model, A GA-based solution method is also presented. The numerical results from optimizing an evacuation network for a super typhoon justify the validity and usefulness of the transit staged evacuation strategy, and the transit network optimization model.

Method based on fuzzy mathematics in combination with principal component analysis (FUZZY-PCA) can be used on evaluation of unmanned ground vehicles in U-turn environment. Relative membership degree is applied to make all indicators normalized and standardized after establishing index system of U-turn behavior, and using PCA method to compare all the teams with their evaluation index, which can obtain the final value matrix, and easily collate the results. The ranking of applying the method to the evaluation of “Future Challenge 2012” of the four unmanned ground vehicles is in agreement with the ranking of referee group. This kind of method is valuable for evaluation of unmanned ground vehicles’ behavior both in U-turn and other environment.

Logistic regression and statistics are combined to analyze accident-related data collected from the “Traffic Accident Database System” (TADS) in order to find the relationship between expressway characteristic parameters and accident rate in a mountainous area. A total of 2,004 observations are used to illustrate the proposed model. A new concept average corner (AC) is also introduced to evaluate the effect of horizontal alignment. Accident rate (the dependent variable) in this study is a dichotomous variable so a binary logistic regression is found suitable. In total, sixteen variables are put forward and fourteen are used in the model. Eight variables are found to be significantly associated with the accident rate at the 0.05 significance. Each of variables is interpreted with the results of Spss 19.0. The findings show that the logistic regression and the statistical method used in this paper are a powerful forecasting tool and can be applied to the further studies. After the analysis, some valid measures are taken to reduce the accident rate of expressway in mountainous area.

This study aims at analyzing the effects of phase transition signals on critical behavioral characteristics of e-bike riders from a safety point of view which includes their start-up behavior at the green onset following a red-green phase transition signal such as a red/yellow light (RY) or a red countdown (RC) and pass/stop decision behavior at a yellow onset following a green-red phase transition signal such as flashing green (FG) or green countdown (GC). Based on e-bike traveling data collected at five typical intersections in Shanghai, a significance comparative analysis during FG and GC was made using red/yellow-running violation rates as the evaluation index. Further research was developed on comparative analysis of the start-up time of e-bikes caused by RY and RC, respectively. The results concluded that e-bikes enjoy more safety to a certain extent in FG than in GC. RY and RC usually make e-bikes arrive at conflicting points ahead of time at the onset of a green light, which can weaken the protective effects of inter-green intervals on vehicles in adjacent phases and has a serious potential safety hazard.

The effects of winds are not considered when traditionally determining the minimum highway horizontal radius. Some literature has discussed the direct forces of crosswinds, but the indirect lateral aerodynamic force induced by the Bernoulli effect has been overlooked so far. In this paper, the Bernoulli effect on running vehicles was investigated using the CFD (computational fluid dynamics) method. The velocity of front wind wasn’t uniformly distributed in the lateral direction, a series of simulations of a bus were conducted in FLUENT, and the lateral aerodynamic forces induced by the Bernoulli effect were calculated. The numerical study shows that when the gradient of wind speed variation goes over 5 m/s per meter, the ratio of the lateral force to the gravity of the bus will exceed 2%. Finally it is suggested that all the limiting values of the highway horizontal radii should be increased for safety reasons. This optimization study may provide a useful reference to the forgiving road design in special areas exposed to asymmetric wind conditions, such as high-class roads along deep gorges.

The pedestrian flow rate is the key factor for evaluating the level of service in compound corridors. Different pedestrian arrival rates, corridor width and time of pedestrians who accept service is closely related with the flow rate. In this paper, the mathematical model has been established on the basis of queuing theory to quickly calculate the unit width pedestrian flow rates and rapidly evaluate the service level of compound corridors.

The objective of this research was to investigate road crossing behaviors of pedestrians and non-motor vehicles at signalized pedestrian crossings. Video recordings at three pedestrian crossings enabled the collection of required data, which included different factors (gender, age, educational level, group number), collected in different conditions. The results of three case studies showed that inappropriate road crossing behaviors were frequent during red light intervals and last countdowns of the green light, and the compliance rate of students was not satisfying as expected. The results also indicated that fluke mind and herd mentality was common in both pedestrian and non-motor vehicle offenders. The outcomes suggest that characteristics of signalized crossing users is a critical factor affecting traffic offense behavior and contributes to create a safer crossing environment for pedestrians and non-motor vehicles.

With a high frequency of traffic incidents on the highways and urban freeways, it is urgent to make a response and dispatch the emergency vehicles as quickly as possible. The solution about how to isolate and protect the incident scenario becomes an issue. It means fast layout and recovery of road cones in a traffic incident scenario becomes an urgent problem. A research and design for a road cones vehicle is conducted then, it is used to handle the traffic incidents on site. The entire console was based on the pickup-car, the character of mobility for vehicle device is qualified and the console is installed into the carriage of the rear, and an electro-magnet mechanism is used to deliver road cones. At last, it is simulated by SolidWorks, and the console has received good recognition. The design of a road cones vehicle is targeted to be simple, efficient and reliable. It is able to be isolated quickly from the incident scenes to avoid harsh traffic jams, decrease traffic injuries, and it has played a key role that prevents the traffic situation from getting worse.

This paper focuses on releasing traffic safety early warning information based on short-term expressway traffic flow forecasting in order to enhance the drivers’ and administrators’ vigilance and reduce the incidence of traffic accidents. The chaotic forecasting method was used to predict short-term traffic flow, and the stability and accuracy of the forecasting was increased with the improved C-C algorithm. Based on such traffic flow forecasting, the traffic safety early warning was classified.

To develop effective speed-limit strategies and improve driving safety for work zones, the variance analysis for vehicle speeds in work zones was explored. A method on variance analysis for vehicle speeds in work zones was proposed based on the K-S test and validated the method in carriageway lane closure work zones on a dual-way-four-lane freeway. The method of P-P probability plots was utilized to verify normal distribution for the speed samples of trucks and cars in different traffic control divisions of carriageway lane closure work zones and the method of two samples K-S test was adopted to verify the variance significance of vehicle speeds between test sections, respectively. The research results show that the speed samples of trucks and cars are normal distribution and there is significant variance in vehicle speeds in different traffic control divisions of carriageway lane closure work zones.

One of the most valuable objectives of traffic accident analysis is to identify key factors of severe traffic accidents. Tracking causes or influential factors of accidents becomes possible through the analysis of large quantities of data of traffic accidents, which provides reference for lowering the number of accidents and the severity of accidents. In this paper, latent class clustering (LCC), a classification method, is applied to first classify 1,043 highway accidents, the data of which is from China’s State Administration of Work Safety, into four categories, and then to explore their respective accident attributes through analysis of seven accident variables (weather, season, time, accident category, the number of involved vehicles, etc.). This clustering of decreases its state of irregularity and homogeneity. Binary logistic regression is then employed in the whole data and the four categories to infer main causes of severe traffic accidents.

The objective of this study is the analysis of pedestrian safety at signalized crosswalks by using traffic conflict techniques. Video data was collected at a busy T-leg signalized intersection in Shanghai, China. Pedestrian-vehicle conflicts as well as pedestrian violations were automatically detected by analyzing the road users’ trajectories. It was found that the major cause of pedestrian-vehicle conflicts was right-turning vehicles that have a permitted right-turn phase. The right-turning vehicles involved in pedestrian-vehicle conflicts account for 64.81% of the total conflicts. The most serious pedestrian-vehicle conflicts occurred between pedestrians in crosswalks and vehicles from the crossing road traveling at high speed. It was found that more than half of the pedestrians were violation of signal timing or the crosswalk boundary: 37.81% were spatial violations and 18.46% were temporal violations. The results showed that conflicts associated with temporal violation behavior are much more numerous than spatial violation (48.41% and 17.06%).

The objective of this paper is to evaluate the influence of large vehicles on safety at highway climbing sections. As a distinctive traffic feature in China, traffic mixture means different types of vehicles running in the same flow and having interactions. Vehicles are categorized into small vehicles, medium vehicles, and large vehicles in this paper. As a result of great difference in vehicle structure, geometry, dynamic performance and applications, large vehicles often block the highway traffic flow, especially at the climbing sections of highway, and thus reduce capacity; increases delay and even impact the safety performance of the facility. This paper selected seven representative traffic flow characteristics to analyze the travel mechanism of large vehicles. Then, a safety assessment index at climbing sections was proposed. The results of a case study showed that among the entire climbing sections under the influence of large vehicles, the safest area is the upstream influenced sections, and the most dangerous part is the starting area of the vertical curve.

Red-light-running (RLR) is one of the important causes of intersection crashes, and is always a research hotspot of the traffic safety community. The goal of this study is to review the state-of-the-art of countermeasures to reduce RLR. Together with the start and termination of the red light, the concept of the dilemma zone is introduced to classify RLR into three types: intentional RLR at red start, unintentional RLR at red start, and RLR at red termination. After that, the causes for different types of RLR are discussed from the standpoints of driver attributes and road traffic environment. The corresponding “3E” countermeasures for different types of RLR are summarized, including enforcement, engineering, and education countermeasures. Moreover, the advantages and disadvantages of these countermeasures are investigated to form appropriate measures for preventing RLR. In the end, some areas for future research are proposed, such as the joint implementation of multiple countermeasures, a gradually increasing punishment mechanism, and upgrade of red light capture systems.

Buildings with atriums or annexes are common in urban areas. However, the traditional beam tracing method can’t deal with these kinds of situations directly. In order to simulate traffic noise around buildings with atriums or annexes, this paper presents a traffic noise simulation model which is based on beam tracing method and triangular-prism space subdivision. Firstly, the paper presents the data structure for buildings with atriums or annexes, so these two kinds of buildings could be recognized by the simulation model. Then, the model divides the whole area into triangular-prism subspaces, according to the building shapes. Finally, the traffic noise propagation around buildings with atriums or annexes is simulated by using beam tracing method. Examples are given at the end of the article and prove the method to be effective.

The reasonable development of non-motorized traffic will improve people’s quality of life, promote the city’s economic development and increase the comprehensive strength of the city. To solve the problem of what kinds of people choose non-motorized traffic based on a residents travel survey in 2014 in Tongchuan, this paper analyzes the basic and non-motorized travel characteristics of residents and establishes a binary logistic regression model of non-motorized (walk/bike) influencing factors. As shown, the family and personal property, and convenience travel attributes have significant effect on non-motorized traffic. Students, housewives, and retired people prefer to choose between walking and bicycling. Shopping and entertainment also promote the non-motorized traffic. The results can assist decision-makers on all levels to wisely allocate resources to slow traffic improvement and plan a non-motorized traffic system.

Since the scale of China’s port enterprises continues to expand. The gantry crane has problems of a serious waste of energy consumption, highlighted security risks. And the current performance evaluation and management is relatively backward during the production operation process. With the “Internet +” as the background and we are supported by the IoT technology. To establish the whole space time evaluation system cover the team personnel and equipment safety supervision. Based on the network statistics alarm system and take unit loading and unloading energy consumption as the key assessment index. Through the vertical beacon scale, continuous improvement and comparison, optimize personnel management operation mode of the equipment. In combination with the practical running situation of port enterprises, it is verified that this system can not only provide a feasible path for the safety supervision of the port gantry crane, but also provide a useful exploration for the construction of a resource-saving and environment-friendly “eco por0074”.

The number of vehicles in China will be more than 250 million by 2015, and it is increasing at the rate of 20% per year. A lot of research shows that vehicles emission is one of the causes of the haze weather. Thus, the environmental benefits of low-carbon travel have become a hot topic in the current research. Aiming at urban public transportation system, the paper analyzes carbon emissions in its construction process. It calculates carbon emissions from the human activity, materials production, mechanical fuel consumption, and vehicles production in the construction process, as well as the carbon emissions of the fossil fuel consumption and power production in the vehicles operation. This research can provide the reference for the urban travel structure choice under the background of low carbon to support the sustainable development of urban transportation.

The shipping industry is investigating alternative fuels for ships in order to comply with stricter emission requirements implemented by the International Maritime Organization (IMO). Liquefied natural gas (LNG) is a promising alternative since it could reduce emissions substantially and offer potential fuel cost savings. But the investment in LNG fuelled vessels is currently facing a high degree of uncertainty, such as the differential between the prices of LNG and conventional maritime fuels, the availability of LNG, and the reliability of its supply chain. This paper makes an attempt to study the possibility of investing in LNG powered vessels under uncertainty. A deferral option model is proposed to quantify the value of flexibility for a deferral based on multi-variables following specified stochastic processes. By exploiting the stochastic processes, it is possible to determine the value of deferral by solving a dynamic program using a least squares Monte Carlo simulation. The model is tested on an investment of a new chemical vessel with 19,000 deadweight tonnage (dwt) powered by LNG. Empirical analysis may suggest different investment strategies based on the probabilities of exercising an option, and related option values each year, and it indicates further that the attractiveness of LNG as a ship fuel is dominated by three parameters: difference of ship prices between a LNG powered vessel and a reference one, price difference between LNG and conventional fuel prices, and the share of operation time inside emission control areas (ECAs).

In order to reduce the vehicle energy consumption of urban road intersections, from the viewpoint of reducing energy consumption of the signalized intersection, combining with the drivers’ behavior changes at intersections under different traffic conditions, the decision points are optimized and analyzed. First, a scale is develop for drivers’ path decisions under different intersection traffic conditions, and combined with the results, the current signals are divided into six scenarios. Then the driving trajectory of a vehicle passing through the intersection under different situations is expressed quantitatively by using mathematical modeling. Second, combined with the existing fuel consumption rate of different driving conditions, the vehicle fuel consumption model relative to the driving behavior is established, and the behavior decision point of the driver is optimized. Finally, the scene and the parameters are assumed, and the C# program is used to simulate the different decision points of driving behavior. The simulation results show that the model can optimize the behavior decision point of the driver at the intersection, and the validity of the model is verified.

To explore the characteristics of vehicle VOCs emission, 4 arterials, 6 minor arterials, and 4 branches located in Zhujiang New Town were selected as the representative road network of an urban area. Three traffic states (namely free, congested, and seriously congested) on different road types (namely major arterials, minor arterials, and branches) throughout the network were chosen by floating car data. Localized emission factors were obtained from MOVES and modified according to local parameters. Traffic volumes of different roads were detected by the SCATS system of Guangzhou and high resolution emission inventories under the predefined traffic states were developed. The results showed that the traffic states of each road type fluctuated throughout the day while congestion frequently occurred on network branches. Though the branches were shown as having higher emission factors, the overall emissions on branches were less than major arterials and minor arterials.

A logit model is established based on three indexes: economy, timeliness, and natural factors to broaden the express transportation mode and products of high-speed rail. The model can be used to predict the respective market sharing rates of high-speed rail and air transportation after the entry of express industry of HSR, calculate respective profits, and analyze the strategy and benefit while the concept of dynamic game was imported. The express transportation between Xi’an and Lanzhou is analyzed in accordance with the theory. The game equilibrium shows that the established high-speed rail would benefit the express industry between the two places.

The purpose of this research is to analyze the connotation of the urban rail transit sustainable development from the following three aspects: social sustainability, environment sustainability, and economic sustainability. Based on the “pressure-state-response” (PSR) theory, this study builds the urban rail transit sustainable development evaluation index system which includes the following three sub-systems: pressure system, state system and response system. The PSR evaluation model of urban rail transit sustainable development is established, the calculation methods and solution approaches are proposed. Besides, in order to verify the feasibility of the model, a case study is conducted.

The time series of particulate matter at urban intersection consists of complex linear and non-linear patterns and are difficult to predict. Wavelet neural network (WNN) model has been applied to air quality prediction in urban areas, but it has limited accuracy owing to the co-linearity between the input variables. To overcome it, a novel hybrid model combining WNN model and factor analysis (FA) is proposed to improve the prediction accuracy. The FC was applied before the WNN model was implemented to generate principal components as input variables, rather than using the original data, to reduce the complexity and eliminate data co-linearity.

Bar-Gera proposed a new algorithm for the traffic assignment problem that promises to produce highly precise solutions by identifying a list of paired alternative segments (PAS) on origin-based sub-networks and shifting flow with PAS. This paper systematically studies the theory of traffic assignment by PAS algorithm proposed by Bar-Gera, especially introducing key steps of the algorithm, such as establishing PAS structure, shifting flow, and equalizing proportions between origins. Then the paper tests the PAS algorithm with different sizes of road networks to demonstrate the efficiency and convergence precision of the algorithm. In addition, this paper also compares the PAS algorithm with the gradient projection (GP) algorithm to analyze these two algorithms’ efficiency and convergence precision. The comparison result indicates that when the required accuracy is not high, their efficiency is the same, but when the required accuracy is high, the PAS algorithm is better.

Travelers always hope to arrive on time, but many uncertainties exist in traffic systems. Based on traffic characteristics, the uncertainties in supply are grouped into three categories: predictable uncertainty, expected uncertainty, and unexpected uncertainty. The stochastic chance-constraint model is used to deal with expected uncertainties, and robust optimization is used to build the model with unexpected uncertainties. The conception of robust chance-constraint travel time is proposed, and the equilibrium conditions are given. Then the multi-class variational inequality (VI) model based on robust optimization under stochastic supply is built. The existence of a solution to this VI problem and its equivalence to the robust chance-constraint traffic equilibrium condition are illustrated using numerical examples. The quasi method of successive average is proposed to solve the VI problem. A medium network is used to test the algorithm performance, and it shows that the algorithm can quickly converge to high accuracy.

In this research, we study the multi-commodity flow problem (MCFP) in the context of air transportation systems. MCFP deals with assigning a variety of goods to flow from sources to their destinations in a network. While many optimization problems in transportation networks can be formulated as a classic MCFP, previous research has mostly considered the edge capacity as a network flow constraint. Based on a traditional path-flow model and edge-flow model, this research proposes new modifications with the consideration of node capacity in the network. In addition, we implement new optimization heuristics improving the path-finding stage of the algorithm. These optimizations allow us to solve the MCFP for networks with around one hundred nodes. Based on these results, we define and compute the node-dependency relationship in MCFP networks. For preliminary evaluation, our novel techniques are evaluated on an air transportation network consisting of 164 nodes. The experiment showed that dependencies on a node are the results of joint influence of the network structure factors and flows. Moreover, the dependencies in our network come in geographical clusters.

This paper explores the impact of expressway investment on the economic development of the various regions of Guangdong province in the following three aspects: the degree of contribution of investment to economic growth, the lagging effect of investment, and the efficiency of investment. Study shows that in Guangdong province a close correlation exists between expressway investment and economic growth. Among the economic factors in the various regions, there is a considerable difference in their contribution to the economic development of the regions. Expressway capital stock contributes markedly more to the economic growth of the eastern, western and northern regions than to that of the Pearl River Delta Region. Moreover, the lagging effect of expressway investment has a longer duration in the eastern, western and northern regions than in the Pearl River Delta Region. Among the various regions of the province, the expressway investment in the western region is the most efficient. Expressway investment is excessive in the Pearl River Delta Region, whereas that in the eastern and northern regions is chronically underfunded. And finally, as a further point of observation, the use and management of expressway funds in the eastern and northern regions need to be optimized.

Recently, some modified alternating direction methods have been proposed to solve a class of nonlinear variational inequality problem with separable structure. These methods are more efficient than the classical one, but cannot avoid solving a variational inequality subproblem. In this paper, we convert the nonlinear variational inequality problems with separable structure and special constraints to an equivalent cobweb model, and then we propose a self-adaptive bisection method to solve the original problems. Specifically, the proposed method only needs to compute some iterative values which are not needed to solve a variational inequality subproblem. The proposed algorithm is applied to the traffic assignment problem, and the results show that the proposed algorithm is quite robust with respect to different starting points as well as different inner loop accuracy.

In this paper we investigate the relationships between multimodal transportation demand and macroscopic socio-economic variables in Beijing using a time-series cointegration and error correction approach. The results indicate that gross domestic product (GDP), and the ratio of urban to total population, have co-integrating relationships with the highway and civil aviation passenger turnover rate, respectively, while urban public transport ridership exhibits long-term equilibrium with GDP and registered private cars. As expected, long run demand elasticities are higher than their short run counterparts except for the case of bus ridership. In addition, demand elasticity varies greatly among different modes of transport, demonstrating the necessity to consider the performances in various modes separately. Lastly, the error correction model (ECM) shows that the coefficients of the residuals representing the speed of adjustment towards the long run equilibrium are negative and statistically significant, confirming the co-integrating relationships mentioned above. The findings of this study can help better understand the determinants of transport demand and are also helpful to policy makers adopting efficient planning and operation strategies.

With the development of China’s cruise industry since 2006, many homeports being built. This paper compares the structure of the cruise industry domestically and abroad. After that, authors found imperfections in industries that are upstream and downstream from cruises in China. Based on the theory of benefits distribution in industry chain, this study proposes the mechanism of benefits distribution for the cruise industry chain. When analyzing the Shanghai cruise industry chain, which is the most mature cruise industry in China, the problem of imbalance was found in the industry chain. Using game theory, the result was calculated that the profits distribution ratio of cruise companies, port companies and service supporting enterprises is 13/48:47/96:23/96. By using the Nash Model, the authors consider the benefits distribution among those member enterprises with equal status as the evaluation criterion of the maximum benefit. Modeling results show that the Shapley model corresponds with the requirements of benefit maximization. Finally, using the Shanghai “Twelfth Five-Year” Plan target of 100 million people as a validation analysis, the total profits of the industry chain will increase by 128.57%. Therefore, in order to develop the local economy of our country, it’s necessary to draw on the experience of foreign cruise industry development. For now, the dominant right of the industrial chain should be gradually transferred to the port enterprises, in order to maximize the cruise economic benefits.

Previous research on urban road network capacity involves only motor vehicles and does not consider non-motor vehicles on the road network. Since there still are large numbers of non-motor vehicles in most cities in China, this study proposes a model to calculate road network capacity under mixed traffic conditions using the time and space resources consumption (TSRC) model. Differences between motor vehicles and non-motorized vehicles are taken into account, and total road network resources under mixed traffic conditions are obtained accordingly. Taking Nanning City as a case study, the capacity of the urban road network and the corresponding maximum ownership numbers of motor vehicles and non-motor vehicles in Nanning city are given. Results show that the mixed road network capacity in consideration of non-motor vehicles can be used to compare with vehicle ownership and to evaluate the operating situation of the urban road network more effectively.

Mixed traffic is one of the typical features of road traffic in China. Especially at intersections, pedestrians, and non-motorized vehicles usually have a substantial effect on the driving environment of motorized vehicles, even causing bottlenecks. A conventional HCM delay model is applicable to the motorized intersections which mainly consist of vehicles. Non-motorized vehicles are not considered in this model. This paper takes Nanning City as a case to improve the intersection delay model by introducing a non-motorized vehicle interference factor γ in the HCM2010 delay model. The main influence factors of γ include the proportion of non-motorized vehicles and the degree of saturation within the intersection. The functional relationship between γ and the two factors are fitted by using SPSS software. Consequently the improved delay model of intersections under the condition of mixed traffic in Nanning City is built. Comparison of numerical calculation results and simulation results show that the average relative error is small enough to verify the usability of the model.

Modal shift is considered a promising way to mitigate port congestion and related issues in port-hinterland transport. A prerequisite for the realization of modal shift is to understand the shifting mechanism. Given that whether the modal shift will be achieved depends on the shipper’s choice behavior; this paper aims to explore the modal shift mechanism from the shipper’s choice behavior. For this purpose, a discrete choice model based on random coefficients logit model is developed to analyze the shipper’s behavior and modal shift mechanism. The data to calibrate the model was collected from a questionnaire survey by using stated preference technique. The result shows that total transport time is the most important factor influencing the modal shift, followed by the total transport time and its fluctuation. It also reveals that lowering the cost of the road-rail combined transport chain may be the most practical and acceptable way to realize the modal shift.

In order to reform old downtown and improve living conditions, poor houses in Shanghai are demolished and the government relocates the residents. Usually they are relocated in large scale residential areas in the periphery of the city. Jinhexincheng is one of them. Previous studies usually focused on travel behaviors in the developed countries. Few studies looked into mode choices and preferences in large scale residential areas in the suburbs in the developing countries. In order to fill the gap, this study analyzes three groups’ (overall samples, city-center-old-house-demolition movers, and non-movers) mode choices, preferences, and predicts mode shares in different policy scenarios. It can provide a deeper understanding of this issue and support transportation planning in large Chinese cities. 320 valid samples are collected. Three groups are different in age, Hukou, apartment ownership, and years living in Shanghai. Mode-choice-multinomial-logit models are generated separately for three groups. All models show that males tend to travel by car. For overall and mover samples, for longtime residents, the less likely a person will uses a bike, motorcycle/moped, or transit. For non-mover samples it is not significant. The movers have a higher value of time (1.61 RMB/minute) compared to other groups. For travel time and cost, only the overall model has an acceptably significant travel time coefficient, this model is used to predict mode shares in 4 sets of travel-time-related-policy scenarios. Results suggest that “make bikes available to movers/all residents”, “make shopping shuttle bus more efficient” and “improve transit service” are good policies and can be accepted in transportation planning.

The rapid growth of cars has brought a lot of parking and road traffic problems around large airports. Parking facilities around the airport can be used to reduce the problem of excessive concentration of parking demand. Based on a survey conducted at the T3 terminal of Beijing Capital International Airport, this paper established a nested logit model for parking location and connection mode choice for long-term parking travelers. The research results indicate that the best location of off-site parking facility layout is within 5 km from the airport. When the distance between the parking facility to the airport is more than 10 km, the recommended connection mode is free airport rapid rail transit. Long-term parking travelers who are within eight districts, with no companions, long driving time and self-paid for parking fee are more willing to choose off-site airport parking.

The assumption of route choice behavior plays an essential role in various traffic assignment models. Regret theory (RT) that assumes travelers being regret averse, might be more reasonable and realistic than the traditional utility maximization theory. Using RT, we develop a new combined trip distribution and traffic assignment model in this paper. The model is formulated as a variational inequality and solved by a path-based algorithm with the use of the method of successive averages. A numerical study is conducted for illustrating the difference between results given by the proposed model and the traditional model. It is shown that regret aversion indeed influences the travelers’ route choice behavior.

This paper proposes a method of pricing calculation for public bicycle rental systems. By combining the value of time and the public bicycle users’ fatigue, a more accurate calculation of price for the rental system is achieved. Taking Hohhot as an example, this paper conducted a survey and analysis about the public bicycle sharing system users. By determining the value of time and estimating the users’ fatigue of the cost function, the paper offers a reference on price for public bicycle rental systems in Hohhot.

This paper proposes an integrated residential location and transportation model to calculate the housing price. First, according to the population distribution, we determine the operation parameters of a newly planned rail transit line in a profit-maximization model (i.e., site location, headway and fare, etc.). Then, the generalized transportation cost is calculated for each site. An integrated residential location and transportation model is subsequently defined in logit form with the variability of the average housing price and the generalized transport cost. Finally, the equilibrium average housing prices at each site are calculated based on the condition of housing supply and demand being in balance.

In order to improve the level of control and management of traffic flow, especially something about the bus rapid transit (BRT). Traffic surveys were conducted in the Guangzhou, China, and the time headway characteristics of BRT vehicles on the BRT roads were analyzed. We knew that the time headway of BRT vehicles is different from transportation modes. Moreover, with the situation of the space occupancy of BRT roads is lower, but the roads on both sides are congested, this research proposed a innovate traffic control and management strategy which allows some private cars run on the BRT roads at peaking hours, and it will help relieve traffic congestion on both sides of the BRT lanes. Researchers established the influence factor (IF) model based on mathematical statistics and modeling to figure out the policy which private cars can travel on the BRT roads at peaking hours. Then, the writers used VISSIM software to simulate and analyze the influence of private cars on BRT applying this traffic control strategy, and gave the threshold which determines the implementation of traffic control strategy. This paper proposed the transportation control strategy that could help the conducted policy and achieve higher efficiency.

To study the relation between urban elderly leisure motivation and travel behavior has great practical significance for urban transport policy adjustments and public transport service mode innovation under an aging society in China. In order to explore the special influence of urban elderly travel restriction to its leisure motivation, the elderly leisure motivation and design survey scheme based on the “Push-Pull” theory were analyzed. Six hundred thirty three valid sample and 74 in-depth interviews of the elderly over 60 years old who are retired in Kunming were studied. The relation among leisure activity and travel behavior characteristic variables was calculated through structural equation model method. Some research results were obtained. First, the elderly leisure motivation indirectly affects the travel behavior mainly through leisure site features. This has a significant positive effect. Performance is defined as the leisure purpose and the leisure environment cognition that indirectly affects the travel distance, travel mode and travel frequency through the level of leisure place, scale, and environmental characteristics. Second, unlike the impact of commuters attribute parameters, the elderly’s age and living state have relatively significant direct impact on leisure travel behavior. Performance is defined as: age has relatively significant restriction on travel mode, travel distance, and travel frequency; living state has relatively significant restriction on departure time.

This study aimed to optimize network structure under the condition of regional transportation integration to compare and analyze the transportation costs, transportation time, and rate of traffic accidents before regional transportation integration. A network optimization model with the maximum economic benefit as the objective function of the network was set up, which could achieve optimization of the whole highway network under the regional traffic integration condition. Finally, the evaluation of costs-benefit ratio of optimized traffic network was made, and examples are given to demonstrate the regional transportation integration can bring economic benefits.

This study constructed the topological structure of the grid road network and the round-radiation road network by Space-L and analyzed the degree of the vertex and characteristic path length a in the networks. Based on the MATLAB software platform, this study simulated the effects of random attack and intentional attack of the road networks, and analyzed the reliability of the grid road network and the circular radial road network under the two types of attack behavior. By comparing the reliability of the two networks, we obtained a more reliable theory for future urban road network planning.

Taking densely populated Guangzhou, the 3rd biggest city in China, as an example, the demand and operation data was collected by a questionnaire survey and field observations, respectively. Next, the characteristics of non-motorized transport were analyzed from both the macroscopic and microscopic views. At the macroscopic level, the fundamental demand characteristics, such as travel purpose, frequency and distance, and the mode choice features, such as travel mode, duration, and intention, were investigated, while at the microscopic level, traffic flow and speed were observed and analyzed. Finally, the relationships among non-motorized transport characteristics, land use and facilities are studied. Finally, several problems related to the development of non-motorized transport in metropolitan areas were discussed and some key points that should be considered are presented.

Flexible work hours (flextime) allow employees to choose their work start and end time, thus providing them with an opportunity to avoid traveling during morning and afternoon peak traffic periods. In order to test the effect of flextime in reducing morning peak-hour traffic, this study has built a multinomial logit model which divided morning departure times as pre-peak (0:00 a.m. to 6:30 a.m.), peak (6:30 a.m. to 8:30 a.m.) and post peak (8:30 a.m. to 12:00 a.m.). The results demonstrate a correlation between having flextime and traveling in post-peak hours, and also proved that commuters with different characteristics may react diversely to flextime. The result of the what-if analysis provides suggestions for future implementation of flextime in metropolitan Miami, that manufacturing, construction, maintenance, or farming workers and those working in high-density locations, such as central business districts (CBDs), should be seriously considered, as they are more sensitive to the program.

There are many uncertain factors in the demand and supply of urban traffic network. Transportation network flexibility can describe the road network’s ability to process or absorb changes caused by uncertainty, and can be used for transportation network performance evaluation. Based on the concept of reserve capacity, two assessment methods of transportation network capacity flexibility were analyzed. The first method only considers the link capacity constraints; the second method, on the basis of the first method, considers the influence of level of service, this method has more application value because it cannot only get the network biggest reserve capacity flexibility like the first method, but also get the network capacity flexibility of each level of service. Finally, a specific example of the two methods for validation and analysis was given.

To acknowledge running status and development trend of regional freeway, statistical data are necessary. This paper first elaborates three transportation indicators of regional highway and explains the mode to compare with that of railway or waterway. Second, taking Fujian province as research object which with a developed freeway network, we discuss the regional transport volume, vehicle velocity, traffic composition, overloaded problems, and for-hire transportation for passenger travel based on networked toll collection data and field survey, and the concept and statistical method of provincial vehicles’ freeway transport volume. Finally, goods varieties are analyzed for determining goods composition and goods varieties suitable for transporting on regional freeway compared with railway.

As the development of transportation in China continues, transit is a growing need. Cities in China are experiencing a critical period of developmental pattern transition, especially large cities. Shanghai and Beijing, as the most developed cities in China, have carried out useful explorations in the transition path. However, compared with those developed cities which have completed the course of transition, these Chinese cities are still at the initial stage. Thus, experience can be learned from these cities, both positive and negative. In this paper, research will be conducted in a comparative perspective. System operating indexes will be the most important. After analyzing the changes of several important indexes in the past fifty to hundred years, the transition process of each city can be concluded. All the cities mentioned have different features from each other. Finally, the advantages and disadvantages of each developmental pattern are offered.

The process of land use and travel behavior interactions can help to solve transportation congestion problems and optimize the city infrastructure. This paper addresses the relations between travel behavior and land use patterns using a structural equations modeling (SEM) framework. Base on the Shenzhen household travel survey, this paper considers travel behavior data as the endogenous latent variable; travel distance, travel time, and trip times as the endogenous variables; land-use, social economic attributes and household attributes as the exogenous latent variables; land-use entropy, age, income, number of bus stops in the living area, and other factors as the exogenous variables. Taking trips of one person as the analysis object, this paper quantitatively qualified the relationship among these variables. The results showed that social economic characteristics have a greatest influence on the travel behavior, and land-use factors of developed area and developing area have opposite effects on travel behavior.

The land use pattern of the areas along urban rail transit is crucial for the efficiency of transportation system and city sustainable development. This paper analyzes the characteristics of land use along urban rail transit in Shanghai, China from three levels: rail network, lines, and stations by taking advantage of the POI data collected from open source map. The indicators we propose to measure are the land use characteristics including the land use density, degree of concentration, and the entropy of land use structure. The results show that the land use density declines as the distance from rail line increases and the rail transit attracts commercial facilities significantly, keeping away from residential facilities. The result also reveals that the intensity of land use along the rail transit is related to the relative location of the line in the city.

Along with the development of computation techniques, the storage memory is no longer a critical bottleneck to the solution algorithms for transportation network models. The researches of the traffic assignment problem (TAP) have focused on the large-scale problems with higher precise solutions. The route-based algorithms were reported to have a fast convergence speed to high precision. Thus, a new method is proposed to improve the route-based algorithms by eliminating the dependent routes in the set of active routes. The modification is carried out on the well-known projected gradient (PG) algorithm. According to the numerical experiments, the improved algorithm is demonstrated to be nearly two times faster than the original version, and is more space-saving. Other features are also analyzed from the results.

With the development of society, communities cannot adapt to the new age. Therefore, more and more problems have shown up. This article discusses how to improve old community governance in traffic to solve the problems of old communities. First, this paper points out some problems of old communities. Second, the paper provides some principles of old community governance, focusing on the humanity and equality of communities. Finally, the paper discusses some measures to improve old communities, with much attention on parking difficulties and uses an example to show old community governance in detail.

The problem of pedestrian crossings is one of the topics that traditionally have played an important role in pedestrian dynamics research. A pedestrian flow dynamics simulation will lead to a system that serves as a rational tool for the urban pedestrian crossing design process to better understand how facilities designs will influence pedestrian behavior. The article describes a multi-agent system (MAS) method with a social force model in pedestrian dynamics modeling at a crossing, whose primary objective is to develop a microscopic dynamics model for a bi-directional pedestrian flow at a crossing. In this paper, we newly develop a pre-avoid forces model, which can describe either a collision avoidance or the lane formation phenomenon between adjacent pedestrians. The MAS method with the pre-avoid forces model shows good predictions of the characteristics to bi-directional pedestrian flow at a crossing.

The determination of capacity and delay significantly affects the transit system’s performance from the perspectives of operators, passengers, and vehicles. Buses will form the spillback queue, in the entrance of the bus bay, when the demand of buses stopping is high. Therefore, bus bay blockage will reduce the capacity and service level of the bus bay and increase the dwell time. The upper partial moment is used to estimate the maximum threshold of blockage probability. The capacity of the bus bay is modeled as a function of arrival buses, blockage probability and critical headway, taking into account spillback and blockage in bus bay entrance and exit. According to bus bay operating time and dwell time, the research aims at estimating a delay based on blockage probability, traffic flow of the adjacent lane and the number of berths. Congestion can be effectively alleviated by increasing the number of berth when demand of buses stopping is low due to the probability threshold has significant change. However, the probability has little significant change when traffic flow of the adjacent lane is more than 450veh/h. It is significant to have congestion delay when multiple bus routes converge into a bus bay.

At the long distance bus station and in the surrounding areas where population and vehicles gather, traffic is in disorder, traffic congestion is severe, and traffic safety problems are highlighted. Based on an analysis and research on the road traffic situation and traffic problems inside and outside the station, this paper aims to offer governance programs and measures, including improving functional layout, adjusting entrances and exits, optimizing traffic organization, strengthening parking management, improving the level of intelligent traffic, and so on.

The phenomenon that the aging population is increasing continuously will have profound effects on the traffic system. This study took the urban elderly as the study object and built a structural equation to recreate travel decisions of the elderly, according to the theory of planned behavior. Then it tried to find the influences of all kinds of planning behavior factors on the urban elderly’s leisure travel. The results show that self-satisfaction of the elderly is the most important factor in inducing the leisure activities because the leisure activity itself can help the elderly to improve their quality of life. Meanwhile, the old people’s leisure travel intention in the planning process is a connection factor between the perceived behavior control and the actual travel behavior. When the limitation showed on physiological function or the external traffic environment, the elderly were more likely to reduce the frequency and range of leisure activities due to the decrease of their willingness to travel.

The car-following behaviors at on-ramp bottlenecks are complex, especially those at the acceleration lane, where the vehicles are not only affected by the preceding vehicles but also the vehicles at the mainline. In this paper, the empirical trajectory data set of the Hongxu on-ramp bottleneck at the Yan’an Expressway in Shanghai, China is collected. Firstly, both time gap and space gap standards are proposed to identify the car-following state. Then the random forest method is used to select the key variables from 17 possible factors that affect the car-following behaviors at the acceleration lane. Finally, a parameterized model, Gazis-Herman-Rothery (GHR) model, and a non-parameterized one, a Bayesian network (BN) model, with the consideration of lateral stimuli are developed. As a result, 4 key variables are selected, and a half of them are related to vehicles at the shoulder lane. Comparing with the conventional GHR and BN model without lateral stimuli, both R-square and Ossen index are reduced, which implies the significant influence from the mainline.

With the rapid development of China’s economic construction, an increasing variety of hazardous articles is being used, and the frequent accidents caused by the transportation of hazardous articles have led to a series of problems including those related to the society and the environment. The emergence of the Internet of Things (IOT) has provided new technological support to the assessment and the surveillance of hazardous articles’ transportation. In this paper a multi-targeting path optimization model is to be built based on the dijkstra algorithm and fuzzy neural network, which means a lot to the transportation safety, the improved management of hazardous articles and accidents’ forewarning and rescue.

The main objective of this study is to examine travel characteristics and travel chain characteristics of urban low-income residents in different locations. Using the travel data collected in the city of Huzhou, a two-step clustering analysis was conducted to identify low-income residents. A method of K-means clustering based on principal component analysis was utilized to divide the central district into a transportation advantaged area and a common area. It was found people in the common area generally have lower mobility than those in the advantaged area. They make fewer trips with longer distance and duration. Travelers in the common area make more trips by bus. The number of the travel chain of residents in the common area is less than that in the advantaged area. With respect to trip purpose, people in the advantaged area are simple, while purposes in the common area are complex. Some policy implications were recommended in the context of providing travel equity services to improve the mobility of urban low-income people, including mixed land development, slow traffic design, public transport service, and a travel subsidies strategy.

In this paper, the driver stress response is analyzed in order to determine its effects on safe driving. The thresholds of driver stress response indexes are obtained by using fuzzy mathematics. In addition, the driver stress response measurement system is designed with the application of three-dimensional visualization software to determine whether the driver stress response ability is qualified. It is significant to reduce road traffic accidents.

In this paper, through the analysis of a freeway security prevention and control system, using the specific circumstances of Jingshi freeway safety prevention and control as an example, the security prevention and control system is evaluated according to the method of analytic hierarchy process and fuzzy comprehensive evaluation, and suggestions for improvement are put forward. It has certain reference value for the prevention of traffic accident black spots.

Plug-in electric vehicles (PEVs) has received a great deal of attention recently due to its environmentally friendly characteristics. The ability of fast charging the batteries of vehicles has become one of the most important factors that could limit the widespread use of the PEVs. Effective planning and installation of charging stations is also important to meet the needs of potential PEV drivers. Another concern for utility companies is to understand the necessary infrastructure requirements to minimize their impacts on the electric grid. This study presents a method of PEV demand estimation and site selection of fast charging stations to maximize the demand under cost and power grid constraints. A case study was performed and results show the feasibility and effectiveness of the method.