Dynamic Spatiotemporal Priority Control of Connected Vehicles Public Transport System
To improve the utilization efficiency of bus lanes and reduce vehicle delays at intersections of continuous bus lanes,this paper investigates dynamic spatiotemporal priority control of connected public transport systems from spatial and temporal dimensions and analyzes the applicable traffic flow conditions.In the spatial dimension,intermittent bus entrance lanes are introduced and vehicle operation control strategies are formulated for four dynamic intervals,including clearance distance.In the temporal dimension,based on deep reinforcement learning,signal timing is dynamically adjusted through time extension of the green light and time interruption of the red light.A simulation verification platform is constructed using SUMO and Python,and comparative simulation experiments and three saturation scenarios are designed for four control schemes concluding the original scheme,spatial priority scheme,temporal scheme,and spatiotemporal collaborative priority scheme.The results show that at saturation levels of 0.2,0.5,and 0.8,the spatiotemporal collaborative priority scheme reduces the average delay compared to the original scheme by respectively 40.96%,39.93%,and 28.20%.At low saturation,the spatial priority effect is obvious;at medium saturation,the temporal effect is obvious.Using intermittent bus entrance lanes may lead to a slight increase in bus delays,but the average delay at the entire intersection is significantly reduced.The proposed dynamic spatiotemporal priority control method for connected vehicle bus systems can effectively improve intersection traffic efficiency while ensuring bus priority.
万方数据
维普
