A Signal Control Algorithm of Urban Intersections based on Traffic Flow Prediction

Abstract

Traffic signals play an important role in traffic management, and traffic dynamics on the road can be adjusted by changing signal timing. Signal timing optimization and traffic flow prediction are traditionally separate. To improve the effect of signal control, a traffic signal control algorithm for urban intersections based on traffic flow prediction is proposed by combining these two technologies. The goal is to minimize the average delay time of the total vehicles at all signalized intersections in the road network. First, a new Prediction-based Signal Control (PSC) model is proposed, which includes a traffic flow prediction module and a signal timing optimization module. Secondly, a traffic flow prediction strategy and a quantum particle swarm optimization algorithm based on phase angle coding is designed to form the signal control algorithm proposed in this paper. Finally, the PSC algorithm is verified with real traffic data. The results show that the proposed algorithm is better than the fixed signal control and traditional adaptive control algorithms, and the reduction of total queue length and average delay time is significantly improved.