Effectiveness Of Transit Signal Priority Research Articles

Use of High-Resolution Signal Controller Data to Measure Transit Signal Priority Performance: A Case Study in the Boston Region

Automated traffic signal performance measures (ATSPMs) have been developed to organize data within a traffic signal, which will then be used to evaluate and monitor signal timing strategies. Past research has summarized the use of ATSPMs for performance-based management of a traffic signal system. The National Cooperative Highway Research Program Research Report 954 focused on many measures useful for general traffic, but did not consider transit agencies as specific stakeholders. ATSPMs do provide insights into measuring the number of preemption events, and the percentage of transit vehicles arriving on green, but additional information is needed to determine the effectiveness of transit signal priority or other transit preferential treatment strategies. This paper proposes a method for evaluating transit performance at signalized intersections more fully using the high-resolution data available within modern traffic signal controllers. The addition of transit-specific inputs within the ATSPM enumerations is used to produce transit-specific signal performance measures designed to be useful to practitioners. The methodology can be followed by other agencies seeking to enhance the capabilities of existing automatic vehicle location systems to further describe the performance at each signalized intersection. By incorporating transit into the ATSPM system, an agency can better assess the delay of buses, which can contribute to schedule adherence, on-time performance, and overall bus service. The methodology is presented as a prototype for further development and adaptation to individual agency objectives and data sources.

Development and Evaluation of Transit Signal Priority Strategies

Research describing the effectiveness of providing signal priority to transit vehicles is presented. Results from previous studies indicate that the effectiveness of transit signal priority depends on a number of factors, including the type of transit route, the transit usage level, and the time of day. This research describes and evaluates several transit signal priority provision methods during both peak and off-peak times. Results indicate that providing signal priority during off-peak times is often justified, due to excess capacity available within the transportation network However, during peak times, transit signal priority use is justified only when the transit usage level is high.

The Effect of Transit Signal Priority on Bus Rapid Transit Headway Adherence

We report the results of an experiment to evaluate the impact of transit signal priority (TSP) on headway adherence for a bus rapid transit (BRT) system in Provo / Orem, Utah. The bus requests TSP based on its unpublished schedule, but users perceive only a headway. Quantile regression models estimated on raw timepoint data from the BRT system reveal that TSP significantly improves headway adherence, after controlling for peak times, direction, and cumulative trip dwell time. We also find that requiring the bus to be 2 minutes late before requesting TSP improves headway adherence more than allowing all buses to request TSP.

Effect of transit signal priority on bus service reliability

As every user knows buses tend to bunch. To alleviate this problem, transit agencies introduce slack into their schedules and then hold buses back to schedule at pre-established control points along their routes. Unfortunately, this practice retards buses and only works with low frequency systems; i.e., when the headways are long. For higher frequency systems, which effectively operate without a schedule, headway-based control strategies show promise but unfortunately, they also retard buses. To alleviate bus retardation in all its forms, transit signal priority (TSP) is commonly used. Curiously however, the potential of TSP to enhance bus control practices has not been explored in detail.This paper evaluates a form of TSP designed for this purpose. In this version of TSP, which we call conditional signal priority (CSP), buses send priority requests only when the requests improve reliability. The evaluation includes both scheduled (low frequency) systems, and unscheduled (high frequency) systems operated by headways. A mathematical model based on Brownian motion is proposed for the former. This model allows us to optimize the CSP strategy and to develop formulas for the expectation and variance of the steady state deviations from the schedule–with CSP, with conventional TSP and with neither. Simulations confirm the accuracy of these findings. It is found that CSP improves reliability considerably and that it is better for traffic than TSP because it reduces the number of priority requests. For high frequency systems operated with a fixed number of buses CSP is shown to not just improve reliability and reduce the number of priority requests of TSP (by about 50%) but also to reduce the average headway by speeding up the buses.

Effect of Transit Signal Priority on Bus Service Reliability

Abstract As every user knows buses tend to bunch. To alleviate this problem, transit agencies introduce slack into their schedules and then hold buses back to schedule at pre-established control points along their routes. Unfortunately, this practice retards buses and only works with low frequency systems; i.e., when the headways are long. For higher frequency systems, which effectively operate without a schedule, headway-based control strategies show promise but unfortunately, they also retard buses. To alleviate bus retardation in all its forms, transit signal priority (TSP) is commonly used. Curiously however, the potential of TSP to enhance bus control practices has not been explored in detail. This paper evaluates a form of TSP designed for this purpose. In this version of TSP, which we call conditional signal priority (CSP), buses send priority requests only when the requests improve reliability. The evaluation includes both scheduled (low frequency) systems, and unscheduled (high frequency) systems operated by headways. A mathematical model based on Brownian motion is proposed for the former. This model allows us to optimize the CSP strategy and to develop formulas for the expectation and variance of the steady state deviations from the schedule-with CSP, with conventional TSP and with neither. Simulations confirm the accuracy of these findings. It is found that CSP improves reliability considerably and that it is better for traffic than TSP because it reduces the number of priority requests. For high frequency systems operated with a fixed number of buses CSP is shown to not just improve reliability and reduce the number of priority requests of TSP (by about 50%) but also to reduce the average headway by speeding up the buses. This paper has been accepted for a podium presentation at the 23rd International Symposium on Transportation and Traffic Theory (ISTTT23) July 24-26, 2019 in Lausanne, CH.

An analytical model to conduct a person-based evaluation of transit preferential treatments on signalized arterials

The complexities of urban transportation networks where multiple modes with different characteristics and needs travel in combination with constraints on space and funding make the sustainable management of these systems a challenge. In order to improve transit service, space (e.g., dedicated bus lanes) and time (e.g., transit signal priority strategies) Transit Preferential Treatments (TPT) are deployed to improve transit operations. The objective of this paper is to develop an analytical model that allows for a person-based evaluation of alternative TPTs when considered individually and in combination. In particular, the analytical model is developed to assess person delay and person discharge flow at any intersection that is part of a signalized arterial, where auto arrivals are in platoons. The performance of TPTs is evaluated using both the analytical model and through microsimulation tests on two intersections of San Pablo Avenue in Berkeley, CA. Space TPTs such as dedicated bus lanes and queue jumper lanes are beneficial in reducing bus person delay when provided in addition to the existing lanes; however, the effectiveness of time TPTs such as green extension depends on the level of auto demand in combination with signal settings. Changes in person discharge flow are not significant for any of the treatments tested with the exception of the bus lane substitution with and without green extension, which led to a significant decrease in person discharge flow. Increased bus frequency increases the effectiveness of transit signal priority in reducing total and bus person delay. The analytical model results produce ranking outcomes that are comparable with the microsimulation ones and therefore, the model may be used for a quantitative evaluation of TPTs without the need for data intensive and time consuming calibration efforts required for microsimulation models. The developed model can be used to guide infrastructure and investment decisions on where such TPTs should be implemented and under what conditions space TPTs should be combined with time TPTs to improve person mobility.

Using delay functions to evaluate transit priority at signals

In this paper a new method to evaluate the network-wide effect of transit signal priority (TSP) is presented. A delay function is developed to estimate the effect of TSP at intersections using parameters such as traffic flow and signal characteristics. The proposed method is tested in two case studies. Firstly, it is applied to a single intersection to address both TSP strategy and model efficiency. Secondly, a set of TSP implementation scenarios is defined for a corridor in South-East Queensland, Australia. Bus and car delays are calculated for each scenario and the results are compared with those obtained using microsimulation. The results confirm that the delay estimated by the proposed method closely matches microsimulation results. The proposed method reflects the effects of having TSP at each intersection without performing time consuming microsimulation analyses. This method makes it possible to evaluate the effectiveness of TSP in large networks. The new method can be used to perform preliminary evaluation of TSP schemes at the network level, thereby potentially reducing the significant computational time of network analyses.

Factors Influencing Effectiveness of Transit Signal Priority and Late-Bus Recovery at Signalized-Intersection Level

Transit priority systems have the potential to improve transit performance and address capacity constraints by giving priority to transit movements over other traffic. This research focused on the effectiveness of conditional transit priority or the manipulation of traffic signal timing plans to reduce delay of late transit buses. The integration of two transportation subsystems—traffic signals and public transit systems—was studied. These subsystems interact along a congested corridor where they share a common roadway infrastructure and transit signal priority (TSP) regulates the interaction between traffic signals, passenger traffic, and buses. Previous research has focused on the evaluation of bus TSP performance at the route level. In practice, it is important to understand not only TSP performance at the route level but also the impact of TSP at the level of the traffic signal intersection (e.g., to allow progression in major cross streets). TSP can significantly improve performance at specific intersections, even though at the route level TSP shows a more modest impact. This study proposed the integration of several data sets such as bus scheduling and location, passenger flows, and TSP requests to evaluate schedule adherence at the stop level and TSP performance at the level of the signalized intersection. A congested arterial corridor was analyzed and regression analysis was used to determine the key factors that affect bus travel time and schedule recovery for late buses. TSP was found to be most effective at lower-volume intersections where queuing was less problematic. Implications of the findings are analyzed and discussed.

Optimal Detector Location for Bus Signal Priority

A theoretical model is presented to quantitatively address the relation between bus detector location and effectiveness of transit signal priority (TSP) systems, supplemented by a sample model application and simulation experiments on a real-world arterial corridor. The simulation results agree very well with results from the theoretical model. The findings of this research contribute to a better understanding of the interaction of the various components of TSP systems, which can lead to better TSP design and implementation.