基于粒子群算法的道路交叉口信号配时优化模型——以昆明市为例

在现有交通资源下,利用交通信号的动态调控缓解交通拥堵是一种行之有效的方式。首先探讨了道路交叉口信号控制的空间和时间优化思路,在时间优化方面提出基于粒子群算法的信号配时优化模型。以昆明市学府路为例,在分析大量交通流数据的基础上,根据三相交通流理论,对交通状态进行划分并提出有针对性的控制策略。将信号配时优化模型应用于学府路3个相邻的关键交叉口。交通仿真和方案试运行结果显示,优化前后同步流状态下交叉口延误平均降低21.0%,车辆排队长度平均降低12.4%;堵塞状态下交叉口延误平均降低32.0%,车辆排队长度平均降低24.9%。这一结果表明该模型在道路交叉口信号配时优化中具有合理性和有效性。

Signal Timing Model Based on Particle Swarm Optimization:A Case Study of Kunming

Dynamic signal control is an effective method to relief traffic congestion,which does not require additional resources.By discussing the signal control improvement in space and time,this paper first develops a signal timing model based on Particle Swarm Optimization（PSO）.Taking Xuefu Road in Kunming City as an example,the paper classifies different traffic performance and proposes corresponding traffic control strategies based on the massive data of traffic flow and three-phase signal timing theory.The traffic simulation results on three adjacent intersections on Xuefu Road show an average 21.0% reduction in intersection delay and a 12.4% decrease in queue length under the same flow condition before and after signal timing improvement.Under the traffic congestion,the reduction in average delay is 32.0% and in average queue length is 24.9%.The results demonstrate the efficiency of the model in improving signal timing.