基于PSO优化的交通信号预测控制

Predictive Control of Traffic Signal Based on Particle Swarm Optimization

在神经网络车流预测的基础上,利用PSO算法在参数解空间内并行寻找交叉路口信号绿信比的最优解,提出了交通信号预测控制方法。仿真实验结果表明,该控制方法优于传统的定时控制和遗传算法优化控制,具有很好的控制效果。

Based on neural network traffic flow prediction, the PSO is introduced to solve the optimization problem of signal green time rate, which formed the traffic signal predictive control. Simulation results show that PSO bare better performance than time-lapse control and genetic algorithm.