Analytical Method for Estimating the Impact of Transit Signal Priority on Vehicle Delay

作者：Abdy Zeeshan R^*; Hellinga Bruce R

来源：Journal of Transportation Engineering-ASCE, 2011, 137(8): 589-600.

DOI：10.1061/(ASCE)TE.1943-5436.0000242

• Transit signal priority
• Queuing theory
• Vehicular delays
• Microscopic simulation

Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, because of financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP before implementation to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated by using microscopic simulation models. However, the application of these models is resource intensive and requires specialized expertise that is often not available in-house to transit agencies. In this paper, we propose and validate an analytical model for estimating the delay impacts of green extension and early green (red truncation) TSP strategies. The model is applied to individual intersections and can reflect the effect of coordination on arrivals to the intersection; however, it does not consider the impact of TSP on coordination at downstream intersections. The results show that the proposed model provides estimates of the delay impacts of TSP that closely match those obtained from microsimulation modeling analysis (using VISSIM) for volume-to-capacity (v/c) ratios up to 0.8. The proposed model is suitable for implementation within a spreadsheet and requires considerably less effort and technical expertise to apply than a typical microsimulation model and therefore may be a more suitable tool for transit agencies to use for prioritizing TSP deployment. DOI: 10.1061/(ASCE)TE.1943-5436.0000242.

• 出版日期2011-8