Traditional pedestrian level of service measures at signalized intersections are based on pedestrian space and pedestrian delay. However, these measures may not adequately reflect the negative impact of right-turning traffic on pedestrians. This paper presents a statistical analysis using a binary logit model that provides new insights into the factors that affect the likelihood that a pedestrian is compromised (delayed, altered their travel path, or altered their travel speed) in response to traffic turning right (on green) during concurrent vehicle/pedestrian signal timing. The statistical analysis indicates that a number of factors affect the likelihood of a pedestrian being compromised including pedestrian direction of travel, right-turn traffic volume, number of pedestrians crossing, whether the pedestrian arrived late and began crossing after the end of the walk interval, and the crosswalk characteristics including location (downtown versus suburban) and one-way/two-way streets.

Recent advances in the optimization of fixed time traffic signals have demonstrated a move toward the use of genetic algorithm optimization with traffic network performance evaluated via stochastic microscopic simulation models. This paper examines methods for improved optimization. Factors examined included the number of replications of the stochastic traffic simulation performed, the use of common random numbers to reduce variability, modified versions of the genetic algorithm, and alternative genetic operators. Computing resources are found to be best utilized by using a single replication of the traffic simulation model with common random numbers for fitness evaluations. Application of the cross-generational elitist selection, heterogeneous recombination, and cataclysmic mutation search algorithm with real crossover and mutation operators is found to offer improved optimization efficiency over the standard genetic algorithm with binary genetic operators. Combining the improvements, delay reductions between 13 and 30% were obtained on the test networks relative to the standard genetic algorithm approach. A coding scheme allowing for complete optimization of signal phasing is proposed as well as an alternative delay measurement.

Traffic data collection under mixed traffic conditions is one of the major problems faced by researchers as well as traffic regulatory authorities. Study and analysis of traffic behavior is critically dependent on the availability of observed traffic data. For mixed traffic observed in developing countries, no suitable tool is available for this purpose. Keeping in view these necessities and problems in data collection, a novel offline image processing-based data collection system, suitable for mixed traffic conditions, is developed. Its underlying ability to detect, track, and classify vehicles makes it useful in collecting traffic data under varying traffic conditions. This system can automatically analyze traffic videos and provide macroscopic traffic characteristics such as classified vehicle flows, average vehicle speeds and average occupancies, and microscopic characteristics such as individual vehicle trajectories, lateral, and longitudinal spacing. It is observed that this new system is working well even under congested mixed traffic conditions.

This study addresses the development of a sampling protocol for condition assessment of selected assets in the state of Maryland. The proposed sampling protocol targets a desired precision and level of confidence in the estimates of levels of service (LOS) for individual assets at each maintenance shop. This work includes the evaluation of the effect of sample size [i.e., number of $0.8\mathrm{km}$ $\left(\frac{1}{2}\mathrm{mi.}\right)$ roadway sections] on the accuracy of estimates of LOS. The distribution of sample sizes among the various maintenance shops accounts for factors such as roadway functional classification, average annual daily traffic, geographical location, the approximate distribution of assets, and the variability in estimates of LOS for each individual asset. The implementation of the proposed sampling protocol will allow maintenance personnel to make reasonable inferences regarding the condition level of the entire asset population. This information will be useful to prioritize areas of need and determine levels of funding, personnel, and equipment. Three different variations of the proposed sampling protocol are evaluated. These variations are a function of how sample sizes are calculated: Option 1—sample size based on the asset with the largest number of required samples; Option 2—sample size based on the asset with the largest number of required samples from a selected group of assets; and Option 3—sample size based on the average number of required samples for all assets. It was concluded that, for a given confidence level, if a minimum precision is to be met for all assets, Option 1 should be used. However, if the sample size is to be limited and a minimum precision is to be met only for a selected group of assets, then Option 2 would be the best alternative. The framework proposed in this study can be modified so that it can be applied to other geographical regions.

Transportation professionals have indicated that a facility-based evaluation methodology for two-lane highways would be much more useful and practical to them than just the individual segment and point analysis methodologies. A facility level analysis will allow the various features (e.g., isolated intersections, continuous grades, passing lanes) that are typical to an extended length of two-lane highway to be addressed in a combined analysis with a single performance measure and level of service value resulting. Currently, no operational analysis methodology exists to address two-lane highways with different segment types at the facility level. The scope of analysis provided in the HCM 2000 for two-lane highways is limited to a single segment within the facility. This paper describes an effort to develop a methodology for the operational analysis of a two-lane highway that includes occasional isolated signalized intersections. The developed methodology provides a model for the basic structure of a facility level analysis that will be amenable to the incorporation of a variety of segment types.

This paper deals with modeling the operations of an airport affected by a large-scale disruptive event, which in this case is considered to be the persistent heavy snowfall. Under such circumstances, the processes taking place at the affected airport are analyzed as two interrelated queuing systems. The first system represents the snowfall and its accumulation in the airport airside area (runway(s), taxiway(s), and apron/gate(s) complex), which affect the airport service rate, i.e., capacity. The other system represents handling of the aircraft/flights at such affected capacity. The deterministic queuing model is used for modeling both systems. The model of the snowfall uses input such as the intensity of snowfall, the snow-melting rate, the “critical” depth of snow when its removal should start, and the capacity and tactics of the snow removal. The output from the model embraces the accumulation of snow in the airport airside area, depending on time. The model of handling the aircraft/flights uses inputs such as the snow accumulation, the characteristics of the scheduled arrival and departure demand, and the corresponding service rates, i.e., capacities, affected by the snowfall. The output from the model embraces the queues, delays, and cancellations of the affected aircraft/flights, and the related costs imposed on the airport, airlines, users-air passengers, and society. The model could be used for more efficient and effective planning of dealing with the snowfall and/or ice rain at airports, estimation of costs of the affected airports, airlines, and air passengers for different scenarios of a given snowfall disruptive event, and sensitivity analysis of these costs regarding changes of the main influencing factors.

This research presents an optimization heuristic to solve the horizontal alignment of a highway segment. The iterative heuristic works in two stages. The first stage uses a neighborhood search approach to find a good piecewise linear line that approximates the highway alignment. The second stage further adjusts the alignment so that the external and code requirements are accurately satisfied. Both stages manipulate the piecewise linear line with a neighborhood search heuristic, and use a mixed integer program (MIP) to ensure that the piecewise linear line crosses the control areas and avoids the restricted ones. The optimal objective function value returned by the MIP is used to compare the quality between different piecewise linear lines. The lengths of each line segment are properly constrained in the MIP to ensure that curves can be correctly deployed. Starting from an initial feasible solution the process gradually improves the alignment through iterations. Computational examples are provided.

To protect motorists and avoid tort liability, highway agencies expend considerable resources to repair damaged longitudinal barriers, such as w-beam guardrails. With limited funding available, though, highway agencies are unable to maintain all field-installed systems in the ideal as-built condition. Instead, these agencies focus on repairing only damage that has a detrimental effect on the safety performance of the barrier. The distinction between minor damage and more severe performance-altering damage, however, is not always clear. This paper presents a critical review of current U.S. and Canadian criteria on whether to repair damaged longitudinal barrier. Barrier repair policies were obtained via comprehensive literature review and a survey of U.S. and Canadian transportation agencies. In an analysis of the maintenance procedures of 40 states in the United States and 8 Canadian transportation agencies, fewer than one-third of highway agencies were found to have quantitative measures to determine when barrier repair is warranted. In addition, no engineering basis for the current U.S. barrier repair guidelines could be found. These findings underscore the importance of the development of quantitative barrier repair guidelines based on a strong technical foundation.

This paper concerns analysis of rutting of urban pavements using finite-element modeling, which takes into account the nonlinear behavior of the pavement materials and the complex traffic condition. A viscoplastic constitutive relation is used for the description of the behavior of the asphalt concrete layer, while an elastoplastic constitutive relation, based on the Mohr–Coulomb criterion, is used for the other layers. The performances of the numerical model are checked over full-scale pavement tests. The model is used for analysis of rutting in urban pavements and for the analysis of rehabilitation methods. Analyses show that urban traffic conditions are detrimental for urban pavements and the use of high resistance asphalt concrete constitutes an efficient alternative for urban pavement rehabilitation.

In recent years, research has been devoted to the control of permanent deformations in flexible pavements. In order to prevent rutting, fatigue, and low-temperature cracking, different types of polymer modifiers have been utilized. The use of polypropylene (PP) fibers as a modifier in pavement mix that can be found locally and at low cost compared to other modifiers is an attractive option. This paper reports on the Marshall design and the optimum bitumen content for asphalt concrete with the addition of polypropylene fibers. Different types of PP fibers were used in order to determine the optimum bitumen content and the optimal PP fiber dosage. Marshall specimens were tested using the universal testing machine to determine the creep behavior of dense bituminous mixtures under repeated loading. The results from the analysis of the tested specimens show that the addition of polypropylene fibers improves the behavior of the specimens by increasing the life of samples under repeated creep testing.