摘要
针对现有交通信号控制系统的诸多不足,提出了一种用于交通信号控制的两层递阶多Agent系统解决方案。通过将交通网络进行区域划分,利用底层Agent控制各交叉口,顶层Agent控制区域,从而实现两层递阶控制。底层Agent采用经典Q学习同步学习最优策略,顶层Agent利用Tile Coding非凡的连续空间处理能力,实现Q学习的动作值函数逼近方法。仿真实验结果表明,该分层递阶控制不但提高了交通信号控制系统效率,而且也为大规模应用提供了很好的可伸缩解决方案。
In view of the existing deficiencies of traffic signal control system, this paper proposes two-layer hierarchical multi-Agent system solution for traffic signal control. Through regional division of the traffic network, it uses the bottom level Agent to control the intersection, the top level Agent to control areas, so as to achieve the two-layer hierarchical con-trol. The bottom level Agent uses the classical Q-learning to synchronize the optimal strategy, the top level Agent utilizes the special continuous space processing ability of Tile Coding to achieve Q learning of action value function approxima-tion method. The simulation test results show that, the hierarchical control not only improves the efficiency of traffic signal control system, but also provides a good scalable solution for large-scale applications.
出处
《计算机工程与应用》
CSCD
北大核心
2015年第20期246-252,共7页
Computer Engineering and Applications
基金
江苏省宿迁市科技创新专项基金(No.Z201211)
宿迁学院重点科研基金(No.2013KY15)
关键词
多AGENT系统
递阶控制
交通信号
Q-学习
Tile Coding
multi-Agent systems
hierarchical control
traffic signals
Q-learning
Tile Coding