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Research Article | Open Access

Novel algorithm of traffic signals adaptive control on urban roads intersections

Zhejiang Institute of Transport, Hangzhou, Zhejiang 310023, China
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Abstract

The control of traffic flows on urban roads intersections through the traffic control signals is very important, not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability increase, but also the traffic accidents evidently decrease. In this paper, an adaptive algorithm of traffic control signals on the urban roads intersections is designed in , this new algorithm can actively adjust the concrete control times of the traffic control signals based on the perceiving information of the waiting vehicles in real time, then the dynamic balance between the traffic control signals and the traffic flows can be realized. Furthermore, through experiment testing and demonstrating, this adaptive algorithm expresses some fine performances, it also shows good application prospect in the field of smart city.

References

[1]
Liu XX. Research on the traffic organization optimization method of continuous light control on intersections. Smart City, 2019, 5(9): 87−88.
[2]
Jin JC, Ma XL, Guo HF. A generalized and stochastic optimization framework for road traffic controls. Processing of the 13 thITS. Tianjin, China: 2018.
[3]
Wang YP, Guo G. Joint optimization of vehicle speed and traffic signals at a signalized intersection. Control and Decision, 2019: 2397−2406.
[4]
Li GL. The research and system design of urban traffic signals control based on the forecast of traffic flow. Guangzhou: South China of Technology, 2018.
[5]
Shu LZ. Research on urban road traffic control algorithm based on deep learning theorem. Chengdu: University of Electric Science And Technology Of China, 2020.
[6]
Davis LC. Journal of controlling traffic flow near the transition to the synchronous flow phase. Physica A: Statistical Mechanics and its Applications, 2006, 368(2): 541−550.
[7]
Zhang HJ. A novel method of traffic lights adaptive control on the urban road intersections. Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering. Guangzhou: Atlantis Press, 2015. https://doi.org/10.2991/iccmcee-15.2015.69.
[8]

Jiang R, Jia B, Wu QS. The stochastic randomization effect in the on-ramp system: single-lane main road and two-lane main road situations. Journal of Physics A: Mathematical and General, 2003, 36(47): 11713–11723.

[9]

Zhao X, Gao Z. Controlling traffic jams by a feedback signal. The European Physical Journal B - Condensed Matter and Complex Systems, 2005, 43(4): 565–572.

[10]
Helbing D, Tilch B. Generalized force model of traffic dynamics. Physical Review E, 1998, 58(1): 133−138.
[11]
Transportation Research Board. Highway capacity manual. Beijing: China Communications Press Co., Ltd, 2007: 75−91.
[12]
Zhang HJ. Some novel development of ITS. Beijing: China Communications Press Co., Ltd, 2015: 80−123.
Journal of Highway and Transportation Research and Development (English Edition)
Pages 25-28
Cite this article:
Zhang H. Novel algorithm of traffic signals adaptive control on urban roads intersections. Journal of Highway and Transportation Research and Development (English Edition), 2025, 19(1): 25-28. https://doi.org/10.26599/HTRD.2025.9480047

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Received: 10 May 2024
Revised: 17 September 2024
Accepted: 08 October 2024
Published: 01 April 2025
© The Author(s) 2025.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0, http://creativecommons.org/licenses/by/4.0/).

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