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Iterative learning perimeter control method for traffic sub-region considering disturbances

Author

Listed:
  • Yan, Fei
  • Wang, Kun
  • Shi, Zhongke

Abstract

Most of the existing perimeter control methods in urban traffic regions are only suitable for the road network in an ideal state, and the impact of various uncertain factors and disturbances in the actual traffic system on the control performance is not considered. In this paper, a disturbance term is introduced into the vehicle balance equation of the road network, and an iterative learning perimeter control method of urban traffic area considering the disturbance is proposed by using the repeatability of the macroscopic traffic flow. Through iterative learning control of the perimeter intersections, the cumulative number of vehicles in the sub-region is stabilized near the expected value, and it is demonstrated that the tracking error of the system converges to a boundary under bounded disturbances. Finally, it is verified through simulation experiments that the proposed method can effectively suppress the effects of different levels of disturbances on the performance of the road network and improve the traffic conditions.

Suggested Citation

  • Yan, Fei & Wang, Kun & Shi, Zhongke, 2021. "Iterative learning perimeter control method for traffic sub-region considering disturbances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    • Handle: RePEc:eee:phsmap:v:578:y:2021:i:c:s0378437121003770
    DOI: 10.1016/j.physa.2021.126104
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    Cited by:

    1. Yan, Fei & Qiu, Jiangchen & Tian, Jianyan, 2022. "An iterative learning identification strategy for nonlinear macroscopic traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    2. Li, Sutong & Kang, Leilei & Huang, Hao & Liu, Lan, 2023. "A perimeter control model of urban road network based on cooperative-noncooperative two-stage game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).

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