基于车速引导和感应控制的干线协调优化方法

Arterial Coordination Optimization Method Based on Vehicle Speed Guidance and Inductive Control

干线信号协调通常基于固定带速和时段性统计流量,但实际运行中,车辆的行驶车速和交通流量往往呈波动变化,导致信号方案与实际最优带速和交通流需求不相匹配,影响交叉口的通行效率。基于车路协同环境,运用Maxband模型,以绿波带宽最大、干线车辆延误、干线停车次数与次路方向延误最小为优化目标,建立了干线信号协调多目标优化模型,并采用改进的多目标粒子群算法对模型求解,获得协调路口全局控制方案参数;根据交叉口进口道车辆位置和信号状态提出了车速引导模型;根据干线交叉口进口道的车辆饱和度情况,应用感应控制策略在全局协调的基础上对各路口绿灯时间进行实时调整。仿真结果表明:优化模型将车速引导和信号协调相结合,考虑主线路口负荷度情况,动态调整绿灯时间,降低了交叉口处的延误和停车次数,有效提升了干线协调控制效率。

Arterial signal coordination is usually based on fixed belt speeds and time-of-day statistical flows.Actually,vehicle speeds and traffic flows are fluctuating,which causes to the mismatch between the signal scheme and the actual optimal belt speeds and traffic flow demands,and affects the intersection's traffic efficiency.Based on the vehicle infrastructure cooperation,by applying Maxband model and the maximum green wave bandwidth,the minimum number of arterial vehicle delays,arterial stops and the minor direction delays being the optimization objectives,a multi-objective optimization model for arterial signal coordination is established.Through using an improved multi-objective particle swarm algorithm the model is solved to obtain the parameters of the coordinated intersection global control scheme.A vehicle speed guidance model is proposed based on the intersection inlet lane vehicle location and signal state.According to the vehicle saturation of the inlet lane of the arterial intersection,an inductive control strategy is applied to adjust the green light timing of each intersection in real time on the basis of global coordination.The results show that the optimization model combines the speed guidance and signal coordination,considers the mainline intersection loading degree situation,dynamically adjusts the green time,reduces the number of delays and stops at intersections,and can effectively improve the efficiency of arterial coordination control.