车路协同下基于交通密度的交叉口交通信号控制方法与仿真

Traffic Signal Control Method and Simulation Based on Traffic Density in Cooperative Vehicle Infrastructure System

车路协同环境下路侧单元可实时获取车辆的位置、速度等信息,为改进交通信号控制提供了机遇和条件。本文借助感应控制方法的思路,以单个交叉口为研究对象,提出车路协同下基于交通密度的交通信号控制方法,该算法将依据交叉口进口道的交通密度,实时选择车流放行方向,并依据排队消散时间确定进口放行绿灯时间。为验证算法的有效性,以虎门大道——连升路交叉口为例,利用Vissim交通仿真软件,对高峰、平峰、低峰等3个交通需求分别进行仿真建模,并分别分析同一交通需求下,本文算法与感应控制方式、定时控制方式的平均行程时间、平均延误时间、平均停车次数及平均排队长度等各项交通信号控制指标优劣。仿真结果表明:在不同交通需求下,与感应控制方式、定时控制方式相比,本文算法各项交通信号控制指标均有明显的改善。

In a cooperative vehicle infrastructure system （ CVIS）, the road site unit can get the information about the position and speed of vehicles, which provides opportunities and conditions for improving traffic signal control. A single intersection is taken as the research object in this paper. A traffic signal control method is proposed based on traffic density in the CVIS by means of induction control method. This algorithm can choose the direction of flow based on the biggest traffic density of the import lanes, and determine entrance green time by the queue dissipation time. In order to verify the effectiveness of the algorithm, Humen-Liansheng intersection is taken as an example. Simulation models for the peak, fiat peak, and low peak are built respectively by using the Vissim traffic simulation software. Analysis is also conducted to evaluate the traffic signal control indexes for the proposed algorithm, the induction control method, and the fix control mode under the same traffic demand. These indexes include the average travel time, the average delay time, the average number of stops, and the average queue length. Results show that, compared with induction control method and the fixed control mode, all the traffic signal control indexes obtained by the proposed algorithm are obviously improved under different demands.