基于再励学习与遗传算法的交通信号自组织控制

SELF-ORGANIZED CONTROL OF TRAFFIC SIGNALS BASED ON REINFORCEMENT LEARNING AND GENETIC ALGORITHM

提出一种基于再励学习和遗传算法的交通信号自组织控制方法 .再励学习针对每一个道路交叉口交通流的优化 ,修正每个信号灯周期的绿信比 .遗传算法则产生局部学习过程的全局优化标准 ,修正信号灯周期的大小 .这种方法将局部优化和全局优化统一起来 ,克服了现有的控制方法需要大量数据传输通讯、准确的交通模型等缺陷 .

A combinative algorithm of reinforcement learning and genetic algorithm is proposed and is applied to self-organized control of the traffic signals. The reinforcement learning focuses on the optimization of intersection's traffic flow which modifies the split of traffic signal cycle, while the genetic algorithm intends to introduce a global optimization criterion to each of the local learning processes which modifies the cycle itself of traffic signals. This approach overcomes the drawbacks in existing control method such as huge data transfer and communication, accurate traffic model and so on.