基于蚁群算法的交叉路口多相位信号配时优化

Multiphase traffic signal timing optimization of intersection based on ant colony algorithm

针对城市道路交叉口的交通流特性,提出一种交叉路口多相位配时的TSP模型,采用新的优化算法——蚁群算法(ACA)来优化交叉路口多相位配时信号,并以每周期内交叉路口车辆总延误最小作为性能指标进行仿真实验。实验表明:在相同的时间和车辆到达率的情况下,采用蚁群算法优化相位和绿信比的配时方法明显优于定时配时方法,也优于定相位优化绿信比的配时方法,降低了交叉口的车辆延误,提高了通行能力;且该算法的求解速度快,稳定性好。

Based on the character of urban traffic flow,this paper describes a multiphase traffic signal timing TSP model,and adopts a novel optimization algorithm-Ant Colony Algorithm（ACA）,which optimizes the multiphase traffic signal timing of intersection,and takes simulation experiments with the least vehicle total delay of every cycle as the performance index.The experiments show that on the same time and the same vehicle arrival rate conversation,the timing method used by ACA to optimize phase and green split is better than the classical fixed-time method,and also better than the fixed-phase optimizing green split,and it can be reduced vehicle delay and improved traffic capacity in isolated intersection.The ACA can be solved problems quickly with good stability.