Adaptive multi-objective traffic signal control using NLRMNSGA-II algorithm

Zou, Yuanyang; Xu, Xueguo; Lin, Guo

doi:10.1139/cjce-2017-0354

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…e arrival rates for each phase are different in general. On the contrary, the linear model was also studied by Zou and Hu [65] and Zou et al [66]. In the former study, the complementary constraints of the model were embraced and it was a nonconvex problem; thus, a model by nonlinear constraints was employed to approximate the nonconvex model.…”

Section: Introductionmentioning

confidence: 99%

MTGPLP Approach for Traffic Signal Intelligent Control

Liu

Zou

et al. 2020

Mathematical Problems in Engineering

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In this paper, we state a combining programming approach to optimize traffic signal control problem. The objective of the model is to minimize the total queue length with weight factors at the end of each phase. Then, modified Twin Gaussian Process (MTGP) is employed to predict the arrival rates for the traffic signal control problem. For achieving automatic control of the traffic signal, an intelligent control method of the traffic signal is proposed in view of the combining method, that is to say, the combining method of MTGP and LP, called MTGPLP, is embraced in the intelligent control system. Furthermore, some numerical experiments are proposed to test the validity of the model and the MTGPLP approach. In particular, the results of numerical experiments show that the model is effective with different arrival rates, departure rates, and weight factors and the combining method is successful.

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Section: Introductionmentioning

confidence: 99%