Iterative learning approach for traffic signal control of urban road networks. Issue 4 (1st February 2017)

• Record Type: Journal Article
• Authors: Yan, Fei; Tian, Fuli; Shi, Zhongke
• Is Part Of: IET control theory & applications. Volume 11:Issue 4(2017)
• Page Start: 466
• Page End: 475
• Publication Date: 2017-02-01
• Subjects: iterative learning control -- traffic control; urban road networks -- iterative learning control -- ILC theory -- urban traffic signal control problem -- macroscopic level traffic environment -- disturbance rejection problem -- repeatability feature -- traffic flow -- ILC strategy -- traffic‐responsive urban control framework -- traffic conditions -- control system design -- asymptotic convergence -- ILC‐based traffic signal control -- iteration cycle; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2016.0376
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : In this study, the authors apply iterative learning control (ILC) theory to address the urban traffic signal control problem in a macroscopic level traffic environment. The original urban traffic signal control problem is first formulated into an output regulating and disturbance rejection problem, and the ILC approach is applied to deal with this class of control problem using the repeatability feature of traffic flow. Then, the ILC strategy is further integrated with the traffic‐responsive urban control framework to cope with the random disturbances of traffic conditions in iteration cycle. Theoretical analysis shows that the proposed ILC‐based traffic signal control methods can guarantee the asymptotic convergence of the link occupancies to the desired ones. The main advantage of the proposed approaches is that they require less prior modelling knowledge in the control system design. The effectiveness of the proposed methods is further verified by extensive simulations.