Traffic Signal Priority Control Based on Traffic Wave Theory

With the continuous growth in vehicle ownership, urban traffic congestion has become increasingly severe. Traditional transportation systems and urban road expansion are no longer sufficient to alleviate congestion or meet the mobility needs of residents. In recent years, the rapid development of the Internet of Vehicles (IoV) and vehicle–infrastructure cooperative technologies has opened new avenues for intelligent traffic management. In particular, how to effectively utilize the real-time information from connected vehicles and smart infrastructure to control the movement of connected buses and optimize traffic signal phases at intersections has become a key strategy for improving urban traffic efficiency. This study focuses on signal timing optimization at connected signalized intersections. First, a vehicle waiting time prediction method based on traffic wave theory is introduced to estimate queue dynamics more accurately. Then, a connected transit signal priority (TSP) control model is developed, aiming to minimize the weighted waiting time of both connected buses and general traffic. The model is solved using a genetic algorithm to obtain the optimal signal timing strategy, thereby achieving effective signal priority control for connected buses.