A Hybrid Traffic Light Control Strategy Based on Branching Ratio Estimation and Congestion Identification

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A Hybrid Traffic Light Control Strategy Based on Branching Ratio Estimation and Congestion Identification
Title:
A Hybrid Traffic Light Control Strategy Based on Branching Ratio Estimation and Congestion Identification
Journal Title:
IEEE 58th Conference on Decision and Control
DOI:
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Publication Date:
11 December 2019
Citation:
Abstract:
Effective parameter estimation and low computational complexity are the two major challenges involved in traffic light control. Most traffic light scheduling strategies focus on developing well-tuned off-line solutions. This paper focuses on the design of a hybrid traffic light control strategy. A macroscopic traffic network model is proposed to depict the traffic dynamics and a closed-loop traffic control strategy is designed based on the estimation of branching ratios at intersections. To reduce the computational complexity, a distributed algorithm is proposed based on the congestion level identification and system partitioning method, which is based on machine learning algorithms. Simulation results show the effectiveness of the proposed methodologies.
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© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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