Real-time Transit Signal Priority Control with Queue Prediction in a V2X Environment

Abstract

Transit Signal Priority (TSP) is a control strategy that can reduce the delay of public transit. However, upon a high traffic volume, TSP may significantly increase the delay for non-priority vehicles. Hence, it is an essential issue to adjust the TSP logic at different demand levels. V2X (Vehicle to Everything) communications have been built and tested in recent years to collect vehicles’ locations and speeds. In a V2X environment, this research proposes a framework to implement TSP control along the segment of a Light Rail Transit ( LRT) route in real time. Based on V2X communications, signal states, and queue lengths can be collected. Queue prediction is further employed to compute the optimal control strategies. A real-world network over three consecutive intersections is constructed in SUMO to verify the proposed control framework. The proposed TSP control framework significantly decreases the delay of trams by 50% compared to a general TSP.