Evaluation of transit signal priority at signalized intersections under connected vehicle environment

ABSTRACT

Conventional transit signal priority (TSP) control strategies generally have negative impacts on other traffic. In this study, two typical signal control strategies under connected vehicle (CV) environment that give priority to transit vehicles at signalized intersections are investigated, i.e. actuated TSP with CV and optimized TSP with CV. The optimization algorithm used in this study is genetic algorithm (GA) and the goal of the optimization is to minimize the total person delay. A real-world intersection is modeled in a microsimulation environment to evaluate the performance. The results are compared with fully actuated signal control strategies with and without TSP. Results show that the proposed optimization control strategy can reduce the average bus delay by 24.5% during peak hours while minimizing the negative impacts on conflicting traffic. Under the low traffic demand condition, the actuated controller with TSP using CV has a better performance in terms of average delay.

KEYWORDS:

• Connected vehicle
• transit signal priority
• genetic algorithm
• microsimulation
• actuated signal control

View correction statement:

Correction

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors want to express their deepest gratitude to the financial support by the United States Department of Transportation, University Transportation Center through the Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE) at The University of North Carolina at Charlotte (Grant Number: 69A3551747133).