Back-Pressure Based Adaptive Traffic Signal Control and Vehicle Routing with Real-Time Control Information Update

Liu Ying (1751133)


Back-pressure algorithm has been shown to be effective in reducing traffic congestion. However, available works on back-pressure based traffic control usually ignore the fact that vehicles need time to travel across roads, resulting in inconsistency between controllers’ viewpoint of traffic congestion situation and real traffic situation and thus misleading controllers. In this paper, we propose back-pressure based adaptive traffic signal control and vehicle routing with real-time control information update such that controllers always have consistent viewpoint of traffic congestion with real traffic situation and make wise signal control and vehicle routing decisions. As verified by simulations, our algorithm significantly reduces traffic congestion. For example, it reduces average vehicle traveling time by percentage ranging from 67% to 83% under high vehicle arrival rates when compared to other three algorithms.