Developing a Connected Vehicle Transit Signal Priority System (Part I)

Project Abstract

This study developed an advanced decentralized transit signal priority (TSP) system using a cycle-free Nash bargaining (NB) signal control system. TSP is recognized as an innovative technology solution capable of enhancing traditional transit services. TSP allows transit vehicles to utilize additional or alternative green time to clear the intersection by adjusting signal timing. TSP operations allow a transit vehicle to be promptly served and significantly reduce delay to prevent long waits at signalized intersections. The developed DNB-TSP system was applied to obtain an optimal control strategy on an isolated intersection and on an arterial corridor, considering a variable phasing sequence and free cycle length. The developed system was implemented and evaluated in INTEGRATION microscopic traffic assignment and simulation software. The new DNB-TSP system was compared to the operation of an optimum fixed time plan (FP) controller, a centralized adaptive phase split (PS) controller, a decentralized phase split and cycle length (PSC) controller, and a DNB controller without TSP to evaluate the developed controller's performance in different scenarios. The study found that the new DNB-TSP system significantly improved various margins of error at a four-legged isolated signalized intersection. In particular, the new system reduced average vehicle delay up 67.5%, 73.2%, 71.1%, and 3.4% compared to FP, PS, PSC, and DNB controllers, respectively. Further, the study found that transit vehicles reduced their average travel time up to 15.6%, average passenger travel time up to 15.2%, average total delay up to 23.3%, average stopped delay up to 68.3%, and fuel consumption up to 6.17% with the DNB-TSP system relative to the DNB controller. The study also investigated the performance of the new system at an arterial corridor. Findings revealed that the new system reduced vehicle stops, vehicle travel time, passenger travel time, vehicle total delay, vehicle stopped delay, fuel, and CO2 emissions up to 14.2%, 21.3%, 18.7%, 66.5%, 82.9%, 13.1%, and 13.1%, respectively, at a test arterial corridor compared to the other traffic signal controllers.

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Impacts and Outcomes

Transit vehicles reduced their average vehicle travel time up to 15.6%, average passenger travel time was reduced up to 15.23%, average total delay was reduced up to 23.32%, average stopped delay was reduced up to 68.27%, and fuel consumption was reduced up to 6.17%.

Universities and Sponsoring Organizations Involved

Virginia Tech, Morgan State University, U.S. Department of Transportation Office of the Secretary-Research

Principal Investigators

Kyoungho Ahn (VT) Email: kahn@vtti.vt.edu
Hesham Rakha (VT) Email: hrakha@vt.edu
Hossam Abdelghaffar (VT)

Funding Sources and Amounts

USDOT: $139,991 (Federal), Virginia Tech: $35,000 (Match), Morgan State University: $53,436 (Match)

Completion Date

March 2020

Keywords

Connected and Automated Vehicle, Connected Traffic Signal Control, Transit Signal Priority, Microscopic Traffic Simulation