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

Fei Yan, Kun Wang and Zhongke Shi

Physica A: Statistical Mechanics and its Applications, 2021, vol. 578, issue C

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.

Keywords: Perimeter control; Iterative learning control; Macroscopic fundamental diagram; Disturbances (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:578:y:2021:i:c:s0378437121003770

DOI: 10.1016/j.physa.2021.126104

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