基于粒子群算法的交通干线协调控制的研究

Experimental study on arterial traffic coordinated control based on particle swarm optimization(PSO)

目前各大城市交通拥堵的一个重要原因是交通控制仍然为单点控制,未能实现协调优化。基于此,提出一种基于粒子群优化的干线交通总延误最小协调控制方法。首先,通过对城市交通干线协调控制进行数学抽象,建立干线交通双向绿波控制总延误模型。其次,依据总延误模型的特征,设计了一种利用历史最优共享的粒子群算法(VSHBPSO)。接着,对干线总延误模型进行优化,以总延误最小为目标,得出相位差、绿信比的最优解,进而获得交通信号相位的动态配时策略。最后以秦皇岛市交通干线为例进行仿真实验,实验结果表明,优化后的交叉口配时方案比传统的定时控制方案减少了43.1%的延误时间,有效提高了干线通行效率。

In terms of an important cause of traffic congestion in cities is the single point of traffic control and it still failed to achieve coordination optimization, this paper presents a coordinated control method to minimize the delay of arterial traffic based on particle swarm optimization. First, according to mathematics abstraction of urban traffic trunk coordination control, a delay model of arterial traffic bi-directional green-wave control is set up. Second, based on the characteristics of delay model, the Velocity Share Historical Best PSO （VSHBPSO） is established. Third, an optimization of the delay model is made to get the parameter of the phase difference and Green ratio, therefore dynamic timing of traffic signal phase is realized. Last, the experiment is made by taking the arterial traffic of Qinhuangdao for example. The experimental results show that the optimized intersection timing has effectively decreased for 43.1% of the total delay time compared with the traditional timing control and improved the traffic efficiency of artery.