流量处理能力均衡的无模型自适应迭代学习交通信号控制  

Model free adaptive iterative learning traffic signal control for balancingthe intersection traffic flow

作　　者：王洪力 侯忠生 WANG Hong-li;HOU Zhong-sheng(School of Automation,Qingdao University,Qingdao 266071,China)

机构地区：[1]青岛大学自动化学院,山东青岛266071

出　　处：《控制与决策》2024年第9期3033-3042,共10页Control and Decision

基　　金：国家自然科学基金项目(61833001)。

摘　　要：针对城市多交叉口系统具有强非线性、时变以及周期性等特点,同时考虑道路固有容量以及道路拥堵缓解的迫切程度等因素,在分布式控制架构下,设计基于分散估计分散控制的无模型自适应迭代学习信号配时方案.该方案通过实时调整各交叉口信号配时来调节各路口的流量,使每个交叉口流量处理能力均衡,从而提高道路资源的利用率,达到缓解城市交通拥堵的目的.最后,通过仿真分析进一步验证了所提方案的有效性.For the characteristics of urban multi-intersection systems,such as strong nonlinearity,time-varying and periodicity,at the same time considering factors such as the inherent capacity of the road and the urgency of alleviating road congestion,under a distributed control architecture,a model free adaptive iterative learning signal timing scheme based on decentralized estimation and decentralized control is designed.By adjusting the signal timing of each intersection in real time,the traffic processing of each intersection is adjusted,and the traffic processing capacity of each intersection is balanced.Furthermore,it can improve the utilization rate of road resources and alleviate urban traffic congestion.Finally,the effectiveness of the proposed scheme is further verified through simulation analysis.

关 键 词：多交叉口 无模型自适应迭代学习控制 流量处理能力均衡 分散估计分散控制 信号配时 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]