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Research Article | Open Access

A communication channel allocation approach considering competition at the intersection

Yining Ren1Zhizhou Wu1Yunyi Liang2Tianjun Yang3( )
The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China
Business School, University of Shanghai for Science & Technology, Shanghai 200093, China
China Academy of Transportation Sciences, Beijing 100088, China
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Abstract

This study investigates the problem of V2R (Vehicle to Road Side Units,V2R) communication channel allocation at an intersection considering communication channel competition among each vehicles. This problem is formulated as a mixed-integer nonlinear program with equilibrium constraints. The object of this problem to minimize V2R communication delays of the whole system by optimizing the number of connected autonomous vehicles (CAVs) communicating with each RSU (Road Side Units, RSU). Complementary constraints based on User Equilibrium is introduced to guarantee each CAV can connect with RSU with their least delay in the competition. A piecewise linearization method is introduced to linearize and help solve the model. In the numerical experiment, the proposed model is compared with the models following System Optimum principle. By comparison, the results show that the proposed model can better achieve the balance between the benefits of the whole V2R system and each CAV individuals. The finding of this study can be applied to the situation where communication channel is crowded at the intersection.

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Journal of Highway and Transportation Research and Development (English Edition)
Pages 72-76

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Cite this article:
Ren Y, Wu Z, Liang Y, et al. A communication channel allocation approach considering competition at the intersection. Journal of Highway and Transportation Research and Development (English Edition), 2025, 19(3): 72-76. https://doi.org/10.26599/HTRD.2025.9480066

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Received: 21 August 2024
Revised: 13 November 2024
Accepted: 14 January 2025
Published: 05 September 2025
© The Author(s) 2025. Published by Tsinghua University Press.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).