This research documents the operational benefits of a 16-phase, phase-insertion, "call-based" transit priority signal phasing over and above a more traditional 8-phase, preemption-based transit signal phasing. These two scenarios were field tested in Portland, Oregon at the signalized intersection at the west, bridgehead of the Tillikum Crossing (SW Harbor Drive) and SW Moody Avenue, which has private automobiles, streetcar, light-rail trains, buses, pedestrians and bicycle modes. Many of the modes and movements experienced up to a 50% reduction delay in the test weekday PM peak hour through the use of a more flexible number of phases and phase insertion for a lighter transit prioritization for light-rail operations versus the previous less flexible phasing and use of signal preemption for light-rail train operation. These field operations are captured and tested using hardware and software in-the-loop simulation (VISSIM) to attempt to isolate the expected change in operations in terms of modal delay.

Recent studies have proposed using person-based traffic signal timing optimization frameworks to minimize total passenger delay experienced by passenger cars and transit vehicles at signalized intersections. However, the efficiency and the practical application of existing efforts is limited by the assumption of fixed cycle lengths and deterministic bus arrival times. This paper extends the algorithms developed in previous work for isolated intersections to accommodate flexible cycle lengths and uncertain bus arrivals. Flexible cycle lengths are accommodated by minimizing total passenger delay within some fixed planning horizon that allows cycle lengths to vary within a feasible range. Two methods are proposed to accommodate uncertain bus arrival times: 1) a robust optimization approach that seeks to achieve a “best” worst-case scenario; and, 2) a rule-based strategy that applies green extension to signal timings obtained from deterministic optimization. The proposed strategies are tested using numerical simulations of an intersection in State College, PA. The results reveal that the flexible cycle length algorithm can significantly reduce bus passenger and total passenger delay with negligible increases in car passenger delay. These results are robust to both the bus and car flow expected at the intersection. The robust optimization strategy appears to reduce the additional passenger delay generated by bus arrival uncertainty for low uncertainty levels, while the rule-based strategy performs better for larger uncertainty levels when intersection flow ratios are low. The anticipated benefits decrease with the intersection flow ratio due to the inflexibility of signal timings at the intersection.

Queue length and delay are the primary performance measures of signalized intersections and their accurate estimation is essential for proper management of traffic. However, measurement of queue and delay is difficult due to their spatial nature. Their measurement becomes more challenging in case of mixed traffic conditions, where vehicles of varying static and dynamic characteristics occupy the entire road space without any lane discipline. In this study, model based estimation schemes were developed for queue and delay at signalized intersection using occupied area as measurement, for two different scenarios, namely queue within detector (QWD) and queue beyond detector (QBD). Sensor errors were explicitly incorporated while using automated detectors. The evaluation showed very good performance of the proposed method, indicating the efficacy of the scheme in cases with detector errors. The developed estimation schemes can be used as part of travel time information applications in real time Intelligent Transportation System (ITS) implementations.

This paper develops a Multi-modal HierArchically Responsive Signal control model called MARS for trajectory-based signal control, by assuming that high penetration of floating sensors (e.g. Connected Vehicles, Smartphones, etc.) is available. First, this study conducts a comprehensive survey with traffic signal professionals, who bring up existing state-of-practice, open issues and future challenges in multi-modal traffic signal control. This survey also identifies the issues of current weight-based modeling for multi-modal control. It is found that assigning weights cannot be tied with delay of each mode in a straight forward manner. Second, by using multi-modal trajectory data, this paper develops a hierarchically multi-modal signal control model, in which each travel mode is solved by a dynamic programming hierarchically with the consideration of the delay and budget from upper-level modes. Further, the proposed control model is evaluated by microscopic simulation tool VISSIM at an isolated intersection, including three competing travel modes: light rail, buses and passenger cars (with trucks).

Transit Signal Priority (TSP) systems are implemented with the goal of reducing travel times for bus passengers and ensuring that buses adhere to schedules. TSP systems encounter trouble when there are multiple bus requests, heavy traffic conditions on cross streets, or uncertain bus arrival times. In this study, we modified the existing logic concepts for TSP strategies by assuming access to video detection technologies to accurately provide bus and vehicle locations. We examined the effect of these modifications by testing five different scenarios in CORSIM on a network reflecting the Guadalupe southbound corridor in Austin, TX during the 5-6 PM peak hour. The simulations use 11 bus routes, with approximately 20 buses, at nine intersections. Along with the “Base” scenario, four other scenarios tested variations of (1) whether cross streets are compensated for lost green time or not and (2) what sort of red truncation logic is used – traditional logic or logic that relies on searching for a critical gap to gauge traffic conditions on the cross street. Simulations were repeated for four bus occupancy levels to show the effect of switching between commute modes. The scenario that preformed best in terms of bus delay was the traditional red truncation in which green time was paid back to the cross street. However, overall corridor delay improved most in the scenario that combined the gap-based logic and the traditional - compensation logic.

ABSTRACT

This paper addresses signal transitions due to "outsized" or "oversized" pedestrian timing. This form of transition happens at coordinated intersections when the side-street required green time is less than the required pedestrian time (RPT) to cross the main street if there is a pedestrian call. To have a quantitative tool to analyze different transition options, mathematical models of transition methods were developed. Three new transition methods were also suggested. With this model, practitioners simply input the common timing parameters such as cycle length, vehicle and pedestrian volume, and RPT. The model will then give a recommendation based on the overall system delay or arterial delay and is expected to provide much improved recommendations when dealing with pedestrian crossings at coordinated signal systems.

Keywords: Pedestrian timing accommodation; Signal coordination; Transition methods

Continuous flow intersection (CFI) is a potential treatment to relieve traffic congestion at intersections. Conventional geometry design, signal timing and performance evaluation for CFI are usually performed in vehicle-only operating environment which may not yield truly operating conditions in China, where lots of pedestrians and bicycles gather and distribute at urban road intersections. In this paper, three integrated optimization models including design for pedestrian crossing facilities, signal phases and coordinated signal timings are proposed over the full CFI. Facilities and signal phases are designed within primary intersection to enhance pedestrian safety with space-time resources fully utilized at the same time. Optimization model of coordinated signal timing is formulated as a mixed-integer linear programming problem and solved by programming on the MATLAB 7.0 software platform. Then length of cycle, phase durations and offsets between successive signals can be finally optimized for each proposed model.

Evaluations are conducted by numerical experiment under different traffic volumes combined with through movements, left turns and pedestrians. Sensitivity and comparison results show that the optimization models proposed in this paper have clear advantages over safety and efficiency for pedestrians, furthermore, average delay of vehicles in two of them doesn’t have a significant decline compared with current CFI design, which further validate the applicability of CFIs in mixed traffic environment.

Most signalized intersections in locations with some level of pedestrian activity include pedestrian crossing signals, but the engineer must still decide whether to activate those signals concurrently with adjacent vehicle phases or exclusively with no vehicular movements.  Exclusive pedestrian movements, also known as a “Barnes Dance”, are assumed to increase the safety for the pedestrians, but this increased safety also increases vehicular (and sometimes pedestrian) delay.  Few research studies have been conducted to investigate the impact of exclusive pedestrian phasing compared to concurrent pedestrian phasing and strategies to minimize the impact of exclusive pedestrian phasing on vehicular delay.  While the safety of pedestrians should not be ignored, vehicle delay and intersection efficiency should also be considered as factors in the decision making process.  This study examines the impact of five pedestrian phasing alternatives across a range of volume scenarios.  An intersection in Morgantown, WV was modeled and simulations were run to determine the average vehicle delay and the total vehicle delay during the AM Peak hour.  The optimal alternative for a given intersection will depend heavily on the traffic volumes and pedestrian volumes, therefore the purpose of this study is not to provide a blanket recommendation for the best alternative, but identify possible alternatives for a traffic engineer to consider. 

One of the measures to reduce the conflicts between pedestrians and left-turning vehicles at crosswalks of signalized intersections is to provide separate phases for pedestrians and curbside turning vehicles, such as exclusive pedestrian phase (EPP) or Leading Pedestrian Interval (LPI). LPI, which displays a few seconds of dedicated pedestrian green phase ahead of vehicle green phase provides better visibility of pedestrians to the drivers of turning vehicles, and a portion of pedestrians can be protected from the conflicting turning vehicles. From the viewpoint of safety and operational performance, LPI can be positioned between the concurrent pedestrian phase (CPP) which shares the same signal phase with adjacent vehicles, and the EPP which has a dedicated phase for pedestrians only. However, the application range of LPI depending on intersection layout and traffic conditions is still unclear. Thus, this study proposes a methodology for quantitatively evaluating the change level of pedestrian-vehicle conflict risk as pedestrian green time proceeds, and in conjunction with the evaluation of operational performance, the effective application range of LPI is investigated through a case study on typical situations at signalized intersections in Japan.

  Real-time signal control systems to provide transit signal priority are critical for improving the efficiency and reliability of transit systems towards more sustainable transportation systems. However, the uncertainty associated with transit arrivals is often a barrier in the performance of real-time signal control. This paper extends previous research that optimized signal timings by minimizing total person delay of both autos and transit vehicles at isolated intersections. In particular, it presents a real-time signal control system that minimizes total person delay at a single intersection that is part of a larger signalized arterial corridor. This system provides conditional priority to transit vehicles based on their passenger occupancy while ensuring a priority window of two standard  deviations of the transit arrival times to address the issue of wasted priority due to the stochasticity in transit vehicle arrivals. The proposed real-time signal control system has been tested through simulation on the intersection of San Pablo and University Avenues in Berkeley, CA. The results of this person-based have been compared with fixed-time signal timings obtained from SYNCHRO as well as  against vehicle-based optimization with and without the provision of priority window. The results show that the proposed real-time signal control system can outperform the SYNCHRO signal timings as well as the vehicle-based ones with and without priority window provision in reducing transit vehicle delay without significantly increasing delays for autos.

Schedule reliability is one of the critical measurements to evaluate the service quality of transit systems. Responsible agencies often take various strategies to ensure bus headway reliability with mostly real-time controls which, however, may cause negative impacts on general traffic. To increase bus headway reliability without interfering with other traffic modes, this study develops a passive control method to reduce the variance of bus headways by adjusting signal offsets while ensuring the progression of passenger cars. The proposed model is to take advantage the linear nature of the most existing signal progression programs for passengers cars which often yield multiple sets of offsets that can result in the same maximized progression band. A search algorithm embedded in the model is developed to identify the set of signal offsets that can achieve the minimal signal delay variance for buses from those non-inferior offsets for passenger cars. The results of the numerical analysis with nine cases under different bus headways and different arterial demand levels confirm that the proposed algorithm is able to reduce the headway variance without incurring excessive delays to other traffic.

Transit vehicles create special challenges for urban traffic signal control. The presence of bus  tops often restricts or blocks traffic flows, resulting in disruption to signal coordination plans, and signal increased overall wait times and delays throughout the system. Transit Signal Priority (TSP) systems have been introduced to mitigate these issues. However, predominant existing TSP strategies give unconditional priority to transit vehicles thereby exacerbating quality of service for other modes. One way to address these shortcomings is to consider bus prioritization in the broader context of real-time traffic signal control, and attempt to factor in other traffic flows when optimizing bus movements. Such a capability necessarily requires the ability to predict when buses will arrive at the intersection, which, in turn, requires an accurate model of bus stop dwell times. As a first step toward developing a dwell time model for purposes of predicting bus arrival times, this paper analyzes trends in AVL/APC data provided by the Port

Authority of Allegheny County (PAAC) collected over the two year period from September 2012 - August 2014 for the two major bus routes: 71A and 71C. Our analysis enables several inferences to be drawn. First, the statistical properties of dwell times are similar (for most stops)

across years for a given season and hence it is fine to join the data for the same season (or month) across years. Second, the probability of a non-zero dwell time varies from stop to stop in a given route suggesting that buses need not be given same priority at all signalized intersections. Third, cumulative density functions (CDFs) of dwell time distributions do provide insights into reliability of dwell times for a given stop; this information is especially useful in real-time control decisions; Fourth, fifteen minute interval dwell time CDFs of peak hour demonstrate the highly stochastic nature of dwell times. Based on this trend analysis, we argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.

This paper presents a Location-Based System (LBS) for pedestrians utilizing low-cost position capabilities on a smartphone together with high fidelity map data. This system operates in a connected vehicle environment, which includes pedestrian-to-infrastructure (p2i) and pedestrian-to-vehicle (p2v) wireless communications, generally called p2x. The location-based system may be especially beneficial to differently abled pedestrians, including blind or visual impaired pedestrians, which would benefit from active support to safely cross the street at a signalized intersection. This can be achieved by means of effective and timely indications about roadway geometry and traffic signal status provided to the pedestrians through an application on a smartphone. A method to estimate a pedestrian’s position is presented in this paper. The algorithm is based on integrating Map Matching and an Extended Kalman Filter (EKF) in a connected vehicle environment to provide precise location information. The algorithm is based on an assumption that pedestrians generally approach an intersection by first walking on the sidewalk and then enter the crosswalk at signalized intersections. The results show that the location algorithm can accurately estimate a pedestrian’s position for use in p2x applications.