基于SARSA(λ)的实时交通信号控制模型

摘要

针对现有交通灯控制器缺乏过去经验的学习能力,导致其无法适应实际交通环境的动态变化,提出了一种基于SARSA(λ)的实时交通信号控制模型,并给出了一种交通信号优化模型及算法,该模型采用强化学习算法,得出交通控制的最优调度策略.仿真实验结果表明,所提模型优于现有交通控制模型,能更好地促进实时动态交通控制实现.%In view of the existing traffic light controller lack of the past experience of learning ability, unable to adapt to the dynamic change of the actual traffic environment, this paper proposes a SARSA(λ)-based control model for real-time traffic signal, and gives a traffic signal optimization model and algorithm. The model uses reinforcement learning algo-rithm to obtain the optimized scheduling strategy for traffic control. Simulation results show that the proposed model is superior to the existing traffic control model, and can improve the real-time dynamic traffic control to achieve better.