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Article | Open Access

An Optimal Right-Turn Coordination System for Connected and Automated Vehicles at Urban Intersections

Mahmudul Hasan1Shuji Doman1A. S. M. Bakibillah2Md Abdus Samad Kamal1( )Kou Yamada1
Department of Mechanical Science and Technology, Graduate School of Science and Technology, Gunma University, Kiryu, 376-8515, Japan
Department of Systems and Control Engineering, School of Engineering, Institute of Science Tokyo, Tokyo, 152-8552, Japan
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Abstract

Traffic at urban intersections frequently encounters unexpected obstructions, resulting in congestion due to uncooperative and priority-based driving behavior. This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles (CAVs) at single-lane intersections, particularly in the context of left-hand side driving on roads. The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks. We consider that all approaching vehicles share relevant information through vehicular communications. The Intersection Coordination Unit (ICU) processes this information and communicates the optimal crossing or turning times to the vehicles. The primary objective of this coordination is to minimize overall traffic delays, which also helps improve the fuel consumption of vehicles. By considering information from upcoming vehicles at the intersection, the coordination system solves an optimization problem to determine the best timing for executing right turns, ultimately minimizing the total delay for all vehicles. The proposed coordination system is evaluated at a typical urban intersection, and its performance is compared to traditional traffic systems. Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.

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Computers, Materials & Continua
Pages 1-17

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Cite this article:
Hasan M, Doman S, Bakibillah ASM, et al. An Optimal Right-Turn Coordination System for Connected and Automated Vehicles at Urban Intersections. Computers, Materials & Continua, 2026, 86(1): 1-17. https://doi.org/10.32604/cmc.2025.070222

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Received: 10 July 2025
Accepted: 10 October 2025
Published: 10 November 2025
© The Author 2025.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.