Q学习算法在多十字路口交通信号控制模型中的运用分析

在城市多十字路口交通环境、面对复杂和瞬息万变的交通条件之间的相互作用,通常采用的交通信号控制方法常常暴露出效率低和实用性差。一个采用以Q学习为基础的交通信号控制模型,提出了处理没有规律和瞬息万变的交通流量的问题。利用专业的自主学习—Q学习中固有的,自主适应能力的最优控制策略应对的不同交通条件。这个模型的主要优点是没有固定的数学控制模型,正好适合这个环境。在仿真环境下的实验研究结果也说明该算法是切实可行、有效的。

Analysis of the Application of Q-Learning Algorithm in Multi-intersection Traffic Signal Control Model

In multi-intersection urban traffic environment,conventional fixed-time traffic signal control methods expose low performance when face with complex and stochastic traffic conditions which caused by the interaction among multiple intersections.A Q-Iearning based traffic signal control model is proposed to deal with time-varying and stochastic traffic flow problem,which takes advantage of the specialty of autonomous learning inherent in Q-learning.The capacity of discovering autonomously optimal control policy corresponding to varying traffic conditions and no fixed mathematic control model is needed which are the major advantages of this method.The experiment results in simulation environment also demonstrate this method is applicable and effective.