M. Li, J. Wang, X. Gou, X. Jin, M. Li, S. Yu
Pages: 227-242
Abstract
Congestion on expressways usually occurs during the peak hours of urban traffic flow, mainly in the bottleneck area of expressways with reduced capacity. the congestion leads to vehicle queuing, and the traffic flow forms a "stop and go" wave, resulting in frequent vehicle starts, which further reduces the traffic efficiency in the bottleneck area and forms a vicious circle. Aiming at the congestion in the bottleneck area of expressway during peak hours, based on the simulation of expressway traffic flow using the cellular transmission model, an optimization model of variable speed limit control based on the cellular transmission model is established. First, use python programming to complete the realization of the basic traffic flow simulation function and speed limit control function of the CTM model, and build the simulation model with the Chengdu Riyue Avenue Expressway as an example. Then, the closed-loop control method is used in the simulation model to realize the variable speed limit control of the traffic flow system. Finally, the two evaluation indexes of the total delay time and the total ideal vehicle speed difference are used to evaluate the implementation effect of the optimal control plan of the speed limit control strategy. The results show that the variable speed limit control has an obvious optimization effect on reducing the total delay time (TTD) and the total ideal speed difference (TVD) of the system during congestion: using the variable speed limit control optimization strategy and infinite speed control conditions in comparison, the total delay time has been reduced by 35.8%, and the total ideal speed difference has been reduced by 10.7%. When the traffic density is in the critical state of congestion, the implementation of variable speed limit control on the upstream of the bottleneck area can effectively alleviate the overall congestion of the system.
Keywords: urban traffic; variable rate limiting control policy; predictive control algorithm; cellular transport model; traffic simulation