A passing time optimization algorithm for intelligent connected vehicles at unsignalized multi-arm intersections

This paper presents a control framework for intelligent connected vehicles (ICVs) passing through unsignalized multi-arm intersections. A conflict detection model is established by mapping entrance–exit lane pairs onto intervals on a numerical axis, where interval overlap indicates the existence of potential collision points. Based on this representation, the minimum safe time interval between vehicles is derived. Building on these results, a longitudinal acceleration optimization algorithm is developed to satisfy safety constraints while coordinating vehicle passing times. Simulation studies conducted in a five-arm intersection scenario with different numbers of vehicles demonstrate that the proposed method can effectively ensure collision-free passing while maintaining a high level of operational efficiency. The results indicate that the proposed framework provides a scalable and efficiency-oriented coordination approach for intelligent vehicles at complex urban intersections.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Published
2026-03-23
DOI
https://doi.org/10.1177/09544070261432012
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00
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article

A passing time optimization algorithm for intelligent connected vehicles at unsignalized multi-arm intersections

Kuoran Zhang, Lin Yang, Weiqi Feng, Dong Liang Guo et al.
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Traffic control and management
article

A passing time optimization algorithm for intelligent connected vehicles at unsignalized multi-arm intersections

Kuoran Zhang, Lin Yang, Weiqi Feng, Dong Liang Guo, Feng Xiong
article en

Abstract

This paper presents a control framework for intelligent connected vehicles (ICVs) passing through unsignalized multi-arm intersections. A conflict detection model is established by mapping entrance–exit lane pairs onto intervals on a numerical axis, where interval overlap indicates the existence of potential collision points. Based on this representation, the minimum safe time interval between vehicles is derived. Building on these results, a longitudinal acceleration optimization algorithm is developed to satisfy safety constraints while coordinating vehicle passing times. Simulation studies conducted in a five-arm intersection scenario with different numbers of vehicles demonstrate that the proposed method can effectively ensure collision-free passing while maintaining a high level of operational efficiency. The results indicate that the proposed framework provides a scalable and efficiency-oriented coordination approach for intelligent vehicles at complex urban intersections.

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Zhejiang University of Science and Technology (CN), Ministry of Education (ME), Taiyuan University of Science and Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 12%
Traffic control and management
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