Control priorities of signal on-ramps metering based on chaos state identification

Jianxin Wang; Yongsheng Qian; Junwei Zeng; Futao Zhang; Zhaopeng Wu; Haijun Li

doi:10.1117/12.3023769

14 March 2024 Control priorities of signal on-ramps metering based on chaos state identification

Jianxin Wang, Yongsheng Qian, Junwei Zeng, Futao Zhang, Zhaopeng Wu, Haijun Li

Proceedings Volume 13074, Fifth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2023); 130740F (2024) https://doi.org/10.1117/12.3023769
Event: Fifth International Conference on Image, Video Processing and Artificial Intelligence, 2023, Shenzhen, China

Abstract

In this paper, considering the highway traffic congestion and surrounding ramp traffic queues, a quantitative layered model was improved to construct a multi ramp control priority matrix, and a multi ramp signal control sequence method considering the influence of ramp traffic was obtained based on the recognition of traffic chaos state, in which, ramp traffic flow and queue length indicators were introduced to comprehensively consider the weight proportion of each ramp. The simulation results show that, firstly, when the demand for ramp traffic exceeds 800, the improved control model of sub-sections has a higher mainline traffic volume than ALINEA control. Secondly, compared with ALINEA control, the average speed in each zoning increased by 27.6%, 34.6% and 42.3% under the control model of sub-sections respectively. The average queue length in ramp decreased by 40.2%, 33.8% and 25.8% respectively, and the average vehicle delay decreased by 75.5%, 77.1% and 66.9% respectively. To sum up, control model of sub-sections can effectively improve the traffic flow on the congested ramp.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jianxin Wang, Yongsheng Qian, Junwei Zeng, Futao Zhang, Zhaopeng Wu, and Haijun Li "Control priorities of signal on-ramps metering based on chaos state identification", Proc. SPIE 13074, Fifth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2023), 130740F (14 March 2024); https://doi.org/10.1117/12.3023769

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