This paper proposes a method to maximize the throughput of a single-lane approach with a branched configuration (one-lane arterial with multiple turn bays at the intersection approach). Field observations determined that, for such an intersection approach, turn bays can be efficiently used only for a limited amount of time after the start of green, and setting the maximum green too high will result in loss of efficiency. The proposed method provides equations for estimating the maximum green that would maximize throughput and suggests repeating the phase twice in the cycle, such that the multilane section can be filled up each time before the green is given. After the new approach is presented and discussed, it is applied to modify the signalization pattern of an existing signalized intersection. This study site is along a single-lane arterial with three lanes at the stop bar: left turn, through and right turn. The new signalization pattern is applied at the study site, and the field evaluation of the before and after conditions are reported. It was concluded that the new scheme increased the throughput of the subject approach by 12.6%.

This paper analyzes driver behavior when alerted to the impending end of green while they travel on high-speed signalized intersection approaches that are equipped with actuated advance warning (AAW) systems. These systems are widely deployed in Nebraska and provide a more than 90% likelihood of improving safety. They consist of one detector placed in advance of the intersection and active warning signs with the legend, “prepare to stop when flashing.” The overall goal is to reduce, if not eliminate, the number of drivers who are caught in the dilemma zone. A nonintrusive mobile data collection system was used to monitor traffic and collect a continuous stream of traffic data up to 304.8 m (1,000 ft) upstream of the stop line on two high-speed signalized intersection approaches that were equipped with AAW systems. The results indicate that the system is effective at alerting drivers to the impending end of the green light; approximately 78% of the drivers observed in this study either maintained their speeds or slowed down when the active warning signs began to flash. The number of vehicles in their dilemma zones was statistically significantly lower than would be expected if the AAW system was not used.

Lane utilization represents how the rate of traffic flow is distributed among the available number of lanes in a given section. This utilization or split is affected by several factors, including traffic flow rates and the presence and amount of heavy-goods vehicles (HGVs) within the traffic. It is important to study lane utilization because it is one of the input parameters for any traffic microsimulation models, which are increasingly being used to assess and suggest solutions for traffic problems. This paper uses two sources of data to model lane utilization—motorway incident detection and automatic signaling (MIDAS) data and individual-vehicles raw data. The latter source of data is specifically used to model how HGVs are distributed between motorway lanes as flow increases because MIDAS data do not specify the proportions of HGVs by lanes. Because the data used to develop the models in this paper are based on a relatively large set of data (compared with those represented by older models), one could argue that these models are more representative of current lane utilization on United Kingdom motorways. The development of lane-utilization models for HGV traffic will help in providing more realistic predictions of traffic behavior when represented by microsimulation models and in assessing such commercial vehicles using the lanes when it comes to pavement design.

Two-wheelers (TW) constitute a major proportion of urban traffic in developing countries and therefore their effect on the saturation flow at signalized intersections could be substantial. This paper attempts to study and analyze the effect of two-wheelers on the saturation flow of signalized intersections by collecting data at a few signalized intersections in Bangalore, India. A strong correlation is observed between the measured saturation flow and the proportion of two-wheeler traffic, which suggest that two-wheelers have significant impact and should be considered in the capacity analysis of signalized intersections. In this paper, the effect of two-wheelers on saturation flow rate is incorporated in a previous model by calibrating and introducing a new adjustment factor for two-wheelers. Results show that saturation flow measured using the modified HCM equation is closer to observed saturation flow values.

Freeway interchanges accommodate large traffic volumes within a constrained area. When their design is complex and includes unexpected features, it may increase drivers’ workloads and lead to driving errors, thus increasing the likelihood of a crash. The study’s goal is to provide a tool for assessing the safety impacts of interchange complexity, promoting a simpler and safer design. This paper presents an interchange complexity model (ICM) that is based on estimations of aggregated drivers’ workload in interchanges. A database of 25 interchanges from the New Jersey interstate road system was used to examine the ICM and construct a resulting crash prediction model by comparing their interchange complexity index (ICI) with three years of crash data. Further on, nine additional interchanges were analyzed similarly in order to validate both the use of the ICM and the resulting crash prediction models. Actual observations of the validation data were relatively close to average model predictions. It is proposed that highway planners could use the ICM for estimating the complexity of interchange design alternatives and the implications for road safety to minimize driver errors and thus reduce crash occurrences.

The present study demonstrates the relationships between pavement roughness and distress parameters like potholes, raveling, rut depth, cracked areas, and patch work. The pavement distress data collected on four national highways in India using a network survey vehicle (NSV) are used to develop linear and nonlinear regression models between roughness and distress parameters. Analysis of variance of these models indicated that nonlinear relation is better than a linear model. $R^2$ value, root mean square error (RMSE), and mean absolute relative error (MARE) also supported nonlinear models. An artificial neural network (ANN), which is an advanced technique of modeling, is also used in the present study to model pavement roughness with distress parameters. A network with five input nodes, 15 hidden nodes, and one output node is considered. The network was trained with 90% of the data and tested with remaining 10% data. Results of $R^2$ and MSE showed that the neural network performed highly significantly in both training and testing phases. Finally, the performance of the ANN model is compared with that of linear and nonlinear regression models. The mean absolute error (MAE) for the ANN model is around 18% less than that for the linear model and 11% less than that for the nonlinear model. MARE values are also 12.5% lower in the case of ANN modeling, indicating that the ANN model yields a better forecast of road roughness for a given set of distress parameters.

This study evaluated the field performance of asphalt pavements with two sequential slurry seal applications, developed performance models for asphalt pavements without slurry seals and asphalt pavements receiving slurry seals at various times following construction, and identified the optimum time for the application of two slurry seals on asphalt pavements within the Washoe County, Nevada, region. This is a continuation of a previous study in which a single application of slurry seal was investigated. The MicroPAVER system was used to evaluate the long-term pavement performance data collected for the last 15 years and the cost-effectiveness of slurry seals applied to new and existing flexible pavements at 0, 1, 3, 5, 7, and 9 years after construction. The data generated in this study clearly reveal an optimum time window for slurry seal application. The optimum times and highest relative benefit of application of slurry seals for both overlaid and newly constructed pavements were when the first slurry seal was applied at 3 years after construction, followed by a second slurry seal at year 7 or 9. Accordingly, it was recommended to apply the first slurry seal for newly constructed and overlaid pavements, respectively, when the pavement condition index (PCI) is 90 and 87, followed by a second slurry seal when the PCI reaches a value of 86 and 77.

The evaluation of the pavement preservation interventions is the most important component of a pavement management system. There is a need for a rational methodology to evaluate pavement preservation alternatives to maximize both project- and network-level benefits. Lack of adequate guidance on the timing of preventive maintenance treatments was the main motivation for this study. On the basis of different effectiveness criteria, mathematical models to estimate optimum timing (OT) of maintenance treatments are developed to alleviate surface rutting. The developed model based on the long-term benefits was found to be a rational and a practical tool to estimate OT for various maintenance treatments by adjusting its parameters. The sensitivity and practical usage of the models are demonstrated by using the SPS-3 pavement sections in the paper. Although the modeling approach uses the existing understanding, the model can estimate OT of a fix on the basis of the pretreatment pavement rutting performance, jump, and slope adjustment factors for various treatment types. The required data for various treatments can be obtained from historical performance data collected for pavement management purposes. The results show that slurry and chip seals can be applied on younger pavements when rutting is minimal. However, thin overlay applications on older pavements with higher rutting levels will maximize the long-term benefits.

Travel behavior plays an important role in transportation planning. Mode choice analysis is the process of arriving at a decision about which mode to use under a set of circumstances. Choice of a particular mode by a commuter affects the general efficiency of travel within the city. Various techniques are available in the literature for mode choice modeling. Among these, multinomial logit models are found to be efficient in estimating the different mode shares in a scenario where more than two choices of modes of travel are available for a commuter. The present study used multinomial logistic regression to analyze the mode choice behavior of commuters in Thiruvananthapuram, a typical Indian city. The findings from the study revealed that as age increases preference to car increases and preference to two-wheelers decreases in comparison with public transport. Increase in time per distance and increase in cost per distance cause the commuters to switch to car and two-wheelers from public transport. Identification of such factors and its variations will help city planners to formulate effective transport policies to improve the transport within the city.

Bus-only shoulders (BOS), which allow transit buses to bypass congested freeways and arterials during rush hours, are a key cog in the ground transportation machine in the Twin Cities metropolitan area. In the Twin Cities, the Minnesota Department of Transportation has invested in 476 km of certified BOS. Traditional BOS benefit-cost analyses fail to justify the investment in Twin Cities BOS, yet the network in the Twin Cities continues to expand. This paper will explain the local investment in BOS, the real benefits associated with BOS, how to design BOS service, and how the incremental investment in technology to support BOS operations produces even greater return on the BOS investment.

This paper applies a binary logistic analysis method for assessing impacts of modal shifts from automobiles, normal buses, and nonmotorized vehicles caused by bus rapid transit (BRT) deployments using survey data collected on six representative BRT corridors in China. The traveler’s demographic and socioeconomic attributes (gender, age) and trip-related attributes (trip purpose, travel time savings, trip costs, trip distances, and weekly travel frequencies) are found to be statistically significant in influencing modal shifts to BRT. Ridership characteristics and preferences are found to vary significantly by BRT corridor based on travel mode, demographics, socioeconomic status, and the perceived benefits in travel time and trip costs, suggesting that BRT deployment strategies must recognize the heterogeneous nature of ridership and travel preferences. The probability of modal shifts to BRT could reach up to 15% for travel time savings of 10 min and then increase steadily for a greater extent of travel time savings. For relatively long trip distances greater than 5 km and high weekly trip frequencies greater than 10 trips, all other things being equal, the probability of modal shifts to BRT could reach 13–57% and 9–55%, respectively. The findings are consistent with some notable studies conducted in other countries.

Americans with Disabilities Act (ADA) paratransit systems are dial-a-ride services that provide public transportation to disabled customers. In large metropolitan areas, these services might use zoning strategies to simplify their management. The objective of this paper is to provide a more in-depth evaluation and comparison between centralized and decentralized zoning strategies. This is achieved by developing a simulation model to evaluate the effects of zoning strategies on the productivity and quality of service for the particular ADA paratransit service, using actual demand data from the city of Houston. Four decentralized zoning strategies are compared with a centralized no-zoning strategy. Higher degrees of decentralization degrade the operational efficiency in terms of larger fleet size because the causative empty trip kilometers are greater. The intrazonal trip percentages of demand and productivity are positively correlated.

In operating conditions, railroads are subject to abrasive and fatigue wear. Their durability period depends on the properties of the materials from which rail sections are made, the characteristics and value of the load, and the distribution of contact stresses and strain in the places at which wheels contact track and turnout components. Forecasting of the real load and the resultant contact stress and strain makes it possible to rationally design railway turnouts and correctly select the material to be used for their components. For these reasons, characteristics of load and, subsequently, distributions of contact stresses and deformations in places of wheel/turnout-component contact were determined in numerical calculations using Universal Mechanism and MSC.MARC computer applications. It was determined that the distributions of contact and reduced stresses depend on the load value. The highest reduced stresses occur in the contact zone and right under the rolling surface of the section.

Allocating tracks with operation restrictions for trains in a conflict-free way is known as the basic scheduling problem, and it has attracted much attention, especially at the station bottlenecks. First, this paper presents a mean-variance optimization model for solving the track allocation problem that minimizes the occupation time costs in groups of turnouts at station bottlenecks. Then the simulated annealing algorithm is provided to solve this programming. In addition, a case of a China railway station focused on track allocation is performed that illustrates the application of the proposed model. Also, considering the quality of track allocation program, an evaluation function that tests the results in a balanced allocation is built to further strengthen the allocating results. Finally, to verify the efficiency of the simulated annealing algorithm, the effects of algorithm parameters on an optimizing function have been tested. It illustrates that the algorithm parameters have great effect on the global optimal results. The more cycles the program runs, the better optimization results will be obtained.