Journal of Transportation Engineering, Part A: Systems

Queue spillback onto the freeway mainlines and the interactions with the adjacent intersections can have adverse impacts on traffic operation and safety, whereby the freeway becomes an expensive substitute for storing vehicles when spillback is prevalent. Thus, queue spillback onto the freeway mainlines and adjacent intersections should be analyzed as an integral part of the preliminary design selection of the service interchange. Past studies produced valuable ideas for preventing queues from reaching freeway segments, and to a smaller extent, reaching the neighboring intersections on the crossing roads. The majority of the past research focused on nonstructural remedies that are useful for improving traffic operations on existing roads, but only a few of them provided results useful in the planning and design stages. The objective of the study was to investigate the operational footprints of alternative diamond interchanges by estimating the longest queues on off-ramps and crossing roads under various geometric and traffic conditions. Ten thousand simulations of six alternative diamond designs were conducted under various geometric and traffic conditions, providing results that can assist practitioners in informed decision making. The methodology can be implemented to other interchange and intersection forms to define the operational footprint and identify potential problems in the early stages of planning and design.

As the amount of traffic congestion continues to grow, pinpointing freeway bottleneck locations and quantifying their impacts are crucial activities for traffic management and control. Among the previous bottleneck identification methods, limitations still exist. The first key limitation is that they cannot determine precise breakdown durations at a bottleneck in an objective manner. Second, the input data often needs to be aggregated in an effort to ensure better robustness to noise, which will significantly reduce the time resolution. Wavelet transform, as a powerful and efficient data-processing tool, has already been implemented in some transportation application scenarios to much benefit. However, there is still a wide gap between existing preliminary explorations of wavelet analysis in transportation research and a completely automatic bottleneck identification framework. This paper addresses several key issues in existing bottleneck identification approaches and also fills a gap in transportation-related wavelet applications. The experimental results demonstrate that the proposed method is able to locate the most severe bottlenecks and comprehensively quantify their impacts.

The maintenance and renewal of ballasted track can be optimized in terms of time and cost if a proper statistical model of track deterioration is derived from previous maintenance history and measurement data. In this regard, quite a few models with simplified assumptions on the parameters have been suggested for the deterioration of ballasted track. Meanwhile, data driven models such as the artificial neural network (ANN) and support vector regression (SVR), which are basic ingredients of machine learning (ML) technology, were introduced in this study to better represent the deterioration phenomena of track segments so that the results can be directly plugged into the optimization schemes. For this purpose, the influential parameters of track deterioration have been selected based on the maintenance history, and two ML models have been studied to find the best combination of input parameters. Through numerical experiments, it was found that at least 2 years of maintenance data were needed in our case to obtain a stable prediction of track deterioration.

Macroscopic traffic flow models are often applied as prediction models in proactive traffic control strategies. For model calibration and validation, existing tests have been conducted on simple freeway corridors, meaning that model performance is still unknown for complicated corridors with multiple potential bottlenecks. To address this research gap, this study firstly proposes extensions for a common model from the literature. The fundamental diagram of this model is extended to adapt it to variations in discharge flow that occur when multiple bottlenecks are activated on complex corridors. Subsequently, the extended model is calibrated with traffic data from an actual freeway corridor, called Whitemud Drive, in Edmonton, Canada. The calibration is conducted using segment-specific and global parameters, respectively. Then the extended model is validated to confirm its applicability in real-life conditions. It is concluded that the extended model can predict traffic-state evolutions under complex traffic conditions.

The existence of traffic bottlenecks limits the network capacity and leads to massive recurring and nonrecurring congestions during daily traffic peaks and in the critical event of an emergency evacuation. It is important to identify possible network bottlenecks to improve evacuation efficiency. Based on Newell’s simplified kinematic wave model, this paper presents a methodology to identify the network bottleneck links under hurricane evacuation. The methodology mainly includes three parts: (1) achieve traffic flow state updating and propagation based on the kinematic wave model; (2) estimate the evacuation demand using a hurricane evacuation response curve; and (3) identify the bottleneck links according to the mean and variance of the measurement of the degree of congestion. Hence, the proposed methodology is elaborated with a sample network, and the travel time distribution of identified bottleneck is analyzed. Furthermore, the method is applied to the bottleneck identification of a realistic network and results are obtained based on simulations using the methodology.

In China, the overtaking disturbance caused by mopeds on a shared bicycle path is one of the most important factors that could significantly affect a cyclist’s riding safety. However, bicycle paths are currently designed for the pure bicycle flow condition and not the new moped-bicycle-mixed flow condition. This paper investigates how a bicycle is affected when it is overtaken by a moped and determines the critical condition of the occurrence of this overtaking disturbance. The research analyzes the overtaken bicycle maneuvers in 257 moped-passing-bicycle events. Results show that when an overtaking disturbance occurs, the bicycle’s lateral acceleration volatility decreases. Based on probability theory, this research demonstrates that both widening the bicycle lane and posting a speed limit could mitigate the overtaking disturbance. However, the positive effect of posting a speed limit is more efficient than that of widening the bicycle lane, and only a speed limit of $25\mathrm{km}/\mathrm{h}$ for mopeds without any change to the current bicycle lane width could mitigate over 90% unacceptable overtaking disturbances.

Median openings are provided in multilane divided roads to enable U-turns. The atypical conditions prevailing in India motivated this study for the development of a methodology for the proper computation of the capacity for U-turns at these locations. Harders’ formula has been widely used by various researchers to evaluate capacity for U-turns and this formula needs three elementary factors—namely, conflicting traffic volume, critical gap, and follow-up time. We collected the required data for capacity estimation from different uncontrolled median openings in India. We estimated the first input parameter required for Harders’ formula, conflicting traffic volume, by analyzing the lateral placement of vehicles at the median opening area. We estimated the second parameter, critical gap, by using four different critical gap estimation procedures—namely; modified Raff, maximum likelihood, macroscopic probability equilibrium, and merging behavior. The third parameter, follow-up time, was measured directly in the field. Consequently, we calculated U-turn capacity for the given traffic streams and the findings were tested against the field capacity estimated in the field using Kyte’s method. We then determined a suitable method for critical gap estimation in the Indian context by using two statistical parameters.

Federal rules mandate state departments of transportation and metropolitan planning organizations to measure and report on the performance of highways within their jurisdictions. Those rules support an initiative for performance-based planning and programming. However, the federal mandates do not provide guidance on how to measure performance during performance-deteriorating events like the presence of work zones. To bridge this gap, this study proposed three performance measures representative of level of service (LOS), travel delays, and environmental impacts and demonstrated their applicability through a case study that simulated work zones under various configurations. The results of the analysis provided clear evidence that work zone length is insignificant with respect to facility performance. Additionally, the study concluded that late merge control holds great promise for implementation as an alternative to early merge control, which is currently the standard practice. The study is significant for presenting pioneer work on performance measurement and management at work zones. The study results are expected to assist agencies in developing improved performance-based measures for work zone planning and scheduling purposes.

Proper estimation of external trips is vital because it may affect the model validation results when compared with traffic counts. In practice, external trips are divided into three categories: external–external (EE), external–internal (EI), and internal–external (IE) trips. EE and EI trips are carried out by nonresidents, whereas IE trips are carried out by residents of the study area. This paper discusses modeling attempts for EE and EI trips and the application of existing models for generation and distribution of EE and EI trips. These models are applied in the Leuven region of Belgium to study their transferability, which was found to be poor. Given these shortcomings, new extensions and variables are proposed that have improved the model performance. Then, the current practices to incorporate residents’ external trips (IE) in activity-based models are also described along with their consequences in the demand modeling framework. An approach by defining a catchment area (CA) outside the study area is then proposed to improve the modeling framework. Results validate the proposed methodology. The paper, therefore, shall be beneficial for both researchers and practitioners.

This study formulates three fundamental extensions of the standard optimal road use analysis: (1) considering fuel and emissions as variable costs, (2) maximizing the social welfare inside and outside the congestion zone simultaneously, and (3) accounting for time-of-day travel demand variations. Using Fresno, California, as case study, I found several interesting results. (1) Although emissions costs are small relative to other variable travel costs, their impacts on the analysis are significant, especially during off-peak periods; for example, in the case study doubling emissions costs triples the optimal (although relatively small) welfare gain from a congestion charge. (2) Without spillover effects consideration, the analysis overestimates the optimal toll rate significantly and can even lead to a total social welfare loss, relative to no-charge conditions. (3) Policymakers should avoid applying a flat daily charge, which can even reduce system performance in off-peak hours.

Road crash fatalities and debilitating injuries are preventable, both before and after the crash occurrence. The provision of medical care in cases of road crashes is among the most defining elements in trauma handling, with the care provided within the first hour (a period frequently termed as the golden hour) significantly decreasing mortality. As a result, the reduction in response times often represents one of the top priorities, especially for large-scale urban conglomerations. In this research, response times in cases of road crash emergencies in urban networks were investigated, particularly correlating important features that affect them, such as location accessibility, type of emergency or crash, and environmental conditions (in this case weather). Besides the response times, all other data came from opportunistic data sources, available for any region in the world. The methodological framework leverages advances from the field of spatial econometric modeling, which explicitly take spatial relationships into consideration. Incorporating the spatial dimension, in turn, may capture location-specific relationships, weather effects, or other significant elements and provide detailed results on response times for alternative cases of emergency. The application was performed over a suitable metropolis case, namely, the urban area of Riyadh, Saudi Arabia, while the results offer valuable insight that can be exploited for a meta-analysis aiming at improving the system’s performance. Results suggest that besides accident severity and distance from the central business district (CBD) and points of interest, visibility and wind play a role in modeling emergency crew response times for the case of Riyadh.

One of the easiest and most efficient ways to control vehicle speeds is to create undulations perpendicular to the axis of the road. The types of undulations especially used for speed management on urban road networks are called speed control bumps (SCBs) and speed control humps (SCHs) according to their width. In general, the undulation geometry is a very important factor in changing the shock levels to which passing vehicles are exposed, and accordingly, in reducing the vehicle speeds. This study compares SCBs and SCHs with regard to human health risks using the whole-body vibration (WBV) components (VDV, ${\mathrm{S}}_{\mathrm{e}}$, and $R$) to which vehicle drivers are exposed while passing over the undulations. Because SCBs and SCHs are usually preferred for use in urban road networks, experimental vibration measurements are conducted at 20, 30, 40, and $50\mathrm{km}/\mathrm{h}$ vehicle speeds. In order to demonstrate the effects of different vehicle types, vibration measurements are repeated in the same driver and undulation geometries with sedan, hatchback, and station wagon vehicles for each measurement speed. The evaluations use standard evaluation methods which are frequently preferred in the world in WBV analysis. Using these methods, vehicle type and vehicle speed effects are reciprocally evaluated considering SCB and SCH geometries with equal heights. Use of the SCHs appears to be more suitable for human health in traffic speed management.

Traffic on urban roads in developing countries is characterized by wide mix of vehicles with loose lane discipline, which results in parallel movement of vehicles in the same lane. Hence, vehicles not only interact longitudinally with the vehicles ahead but also laterally with vehicles to the sides. Lateral movements have a significant impact on the characteristics of traffic flow and therefore are of great importance in microscopic traffic simulation models. Existing simulation models for mixed traffic conditions model lateral shifts (lateral movements) as an instantaneous process but neglects detailed modeling. However, the duration for lateral shifts is generally in the range of 0.5–15 s. The omission of lateral shift duration from simulation models may have a significant impact on simulation outputs. Also, different vehicle types may have different lateral shift durations due to variations in their physical and operational characteristics. This paper attempts to develop a vehicle-specific lateral shift duration model by considering different explanatory variables such as direction of lateral shift, available space gaps, speeds of subject vehicle and surrounding vehicles, vehicle types, and clearance. The models were estimated using trajectory data collected during medium-flow conditions from an urban arterial in Chennai city, India. The findings from this study have direct implications on modeling lateral shifts in microscopic traffic simulations to be developed specifically for mixed traffic conditions.

The level of service on two-lane rural highways can be estimated using the percent time spent following (PTSF) and average travel speed (ATS). Because PTSF cannot be directly observed in the field, the literature suggests alternative measures of service (MOS) that can be obtained from traffic stream parameters. The objective of this paper was to analyze measures of service that could adequately describe the quality of service on two-lane rural highways. Traffic data collected on 16 road segments in the state of São Paulo were used to calibrate and validate the traffic simulation software CORSIM by means of a genetic algorithm. The recalibrated CORSIM was used to create a synthetic set of traffic data that comprise an extensive range of traffic flow and road geometry patterns. Nine alternative measures of service were analyzed, and models that relate these measures of service to directional traffic flow were fitted using a synthetic traffic data set. Comparisons between the values obtained from these models and the values obtained from the field indicated that two measures of service, density and follower density, could be used to create level of service criteria for two-lane rural highways in Brazil.

This paper presents a shockwave-based method for estimating queue length associated with presignals for bus priority. Both queue length at presignals and main signals are estimated by the proposed method. In this study, we first analyze traffic operations with the implementation of presignals for bus priority using shockwave theory. On this basis, queue length at presignals and main signals are estimated for eight cases in which a bus arrives at different times during a traffic signal cycle. Detailed comparisons of queue length estimated by shockwave theory and that obtained by a cellular-automaton-based simulation are made from the shape of the fundamental diagram (triangular and concave), areas (upstream of the presignal and between the presignal and the main signal), bus arrival scenarios (bus is not present and bus is present), and bus arrival times (during the red presignal and during the green presignal). Simulation experiments show that the proposed shockwave-based method is effective in estimating queue length associated with presignals for bus priority in all cases. The efforts are made to provide the basis for evaluating the performance of intersections with presignals for bus priority implemented and designing sorting area for presignals for bus priority.

This work addresses the problem of bus timetabling under multiple operational constraints with the objective of minimizing the waiting time variations of passengers at stops. It places specific emphasis on practical operational constraints such as the required meal and resting time breaks, the required headway ranges between successive bus trips, and many others that are largely ignored in the literature but impose significant problems on timetable planners. Given the computational intractability of the multiconstrained timetabling problem, the authors introduce an exterior point penalty scheme for approximating the constrained optimization problem by an unconstrained one. In this way, it becomes easier to explore the effect of multiple timetabling options with the use of evolutionary optimization. The proposed approach is tested at a major Asia Pacific (APAC) bus operator, demonstrating that a favorable trade-off between improving the service reliability and satisfying most of the operational constraints can be achieved. Finally, additional extensive simulation tests demonstrate that optimized timetables perform well for travel time noise levels of less than 30%.