Journal of Transportation Engineering, Part A: Systems

Work zones have become the second largest contributor to the nonrecurring delay disruptions of traffic on US highways. The development of a sound model to minimize the total cost (i.e., road user cost and agency cost) by implementing effective traffic management strategies (i.e., traffic diversion or shoulder use) is desirable. The objective of this study was to optimize work-zone schedules and associated characteristics (e.g., maintenance crew, work-zone lengths, and diversion rates) that yield the minimum total cost. Floating car data enable traffic engineers and planners to obtain accurate and reliable traffic measures, such as speed, travel time, and delay. By considering prevailing road and time-varying traffic conditions, the proposed model evaluated the efficiency and effectiveness of traffic management strategies for freeway work zones. A case study was conducted in which the developed model was applied to optimize the work schedule for a road maintenance project on Interstate 80 (I-80) in New Jersey, in which the relationships among the decision variables and model parameters were explored. The findings of this study can assist traffic management decision making to mitigate congestion caused by freeway work zones.

This paper focuses on shaping the variable curvature in the diverging track of a railway turnout. Based on some earlier studies, solutions provided with a circular arc in the midzone and extreme regions with segments of nonlinear curvature of equal length and zero curvature at the start and end of the turnout have been assumed as models. The most advantageous type of curvature has been chosen, taking into account the kinematic conditions. The presentation includes an analytical record of the curvature, tangent inclination angle in the diverging track length, and Cartesian coordinates of the track. The paper also discusses the determination of a set of basic values relating to geometric parameters appropriate for a given speed of trains adequate for ensuring the minimization of the length of the entire turnout at a given final ordinate.

Urban bus services are subject to high levels of uncertainty and disturbances. Methods to determine the timetable are designed to absorb variations in riding times between stops by allocating additional travel time. The propagation of service unreliability along the route could be restrained by drivers’ adjustment at stops and between stops. This paper analyzes the main determinants of bus riding times deviations based on automatic vehicle location (AVL) data from four trunk lines in Stockholm, Sweden. The analysis indicates that drivers can and do adjust their speeds in response to instantaneous real-time schedule adherence information, although these adjustments depend on the underlying control scheme: locations where the performance is measured. A model for bus riding time deviations was estimated with autoregressive effects, performance indicators, link characteristics, and trip attributes as the explanatory factors. The results can support the development of travel time prediction and real-time control strategies that take drivers’ response to operations into account. This highlights the importance of the human factor in designing control schemes and the corresponding transit performance evaluation.

Automobile trip lengths are increasingly used in the calculation of development impact fees or bulk services contributions, affecting the revenue collected by local authorities. It is, however, difficult to obtain accurate estimates of current or predicted trip distances, and the empirical evidence base is relatively thin. Global positioning system (GPS) technology might provide a more accurate way of filling this data gap at a lower cost. The paper describes the use of mobile GPS loggers to collect and analyze trip-length data for car-based trips to and from shopping centers based on data collected from drivers in the Pretoria–Johannesburg area of South Africa. We verify the minimum stopped-time criterion used to identify trip ends under local conditions. Significant variation in trip lengths is observed, but average trip lengths vary systematically by shopping center type and size. Average GPS-derived trip lengths were found to be significantly longer than those estimated using conventional surveys in Florida, especially for smaller centers, raising the possibility that conventional methods lead to underestimation of the traffic impacts of individual centers. Although the study confirms the feasibility of using mobile GPS loggers for measuring trip lengths, several methodological questions remain to be solved to improve the robustness of the findings.

This paper addresses a critical operational issue of optimally converting some signalized intersections in an evacuation network into crosselimination control points to improve system performance. A mathematical model with equilibrium constraints incorporating a parametric variational inequality was formulated to optimize the distribution and locations of signalized and crosselimination intersections as well as their turning restriction, channelization, and signal timings with the objective of minimizing the total evacuation time. An efficient heuristic approach embedded with a diagonalization algorithm was developed to solve the proposed model in an acceptable amount of time. Extensive numerical analyses were performed to demonstrate the applicability and effectiveness of the proposed model in a subnetwork in Washington, DC.

Bicycling and walking can provide public health and quality of life benefits to a community, but safety concerns and crash rates for those who choose to bicycle or walk remain high. To better understand how agencies decide which bicycle and pedestrian treatments to install in their regions and where to install them, the team surveyed state, regional, and local agencies regarding current practices in bicycle and pedestrian design policy. Results show that agencies believe a data-driven approach is important for improving safety, but very few collect the data necessary to assess safety implications. Safety was reported as the most important variable in all stages of bicycle and pedestrian infrastructure implementation, with 78% of respondents listing safety as a variable in site identification and 97% saying safety was very or somewhat important in site prioritization. However, one third of the responding agencies stated that they did not collect any type of permanent or temporary bicycle or pedestrian counts, which means that it is impossible to know the risk exposure rates in their regions and at specific sites.