Conflict Resolution Strategies for Connected and Autonomous Vehicles at Unsignalized Irregular Intersections: Path Planning and Speed Control

This study focuses on irregular intersections and proposes a novel non-stop traffic control approach that integrates precise trajectory modeling with optimization-based control. Firstly, a trajectory model composed of straight lines and circular curves is developed to accurately describe vehicle movement paths within irregular intersections. Then, for the three typical conflict scenarios of diverging, crossing and merging, the conflict zone action distance calculation models are established, and the corresponding conflict resolution strategies are designed to ensure safe vehicle interactions. In terms of optimization and control, a joint optimization model of vehicle path planning and speed control (PPSC) is constructed with the objective of minimizing the total vehicle delay, and a rolling horizon control scheme is employed to efficiently solve the model. Finally, numerical experiments are conducted to validate the effectiveness and advancement of the proposed method. The simulation results indicate that the PPSC method achieves significant improvements in reducing average vehicle delay, enhancing intersection throughput, and lowering fuel consumption. Moreover, the effects of different safe interval times, adjustment section lengths, and planning time horizons on the performance of the PPSC method are further investigated through sensitivity analysis.

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Publication Details

Journal
IEEE Transactions on Vehicular Technology
Published
2025-08-04
DOI
https://doi.org/10.1109/tvt.2025.3595392
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

Conflict Resolution Strategies for Connected and Autonomous Vehicles at Unsignalized Irregular Intersections: Path Planning and Speed Control

Yugang Liu, You Zhang, Shuai Zheng, Shengli Ren et al.
IEEE Transactions on Vehicular Technology
Autonomous Vehicle Technology and Safety
article

Conflict Resolution Strategies for Connected and Autonomous Vehicles at Unsignalized Irregular Intersections: Path Planning and Speed Control

Yugang Liu, You Zhang, Shuai Zheng, Shengli Ren, Lining Liu
article en

Abstract

This study focuses on irregular intersections and proposes a novel non-stop traffic control approach that integrates precise trajectory modeling with optimization-based control. Firstly, a trajectory model composed of straight lines and circular curves is developed to accurately describe vehicle movement paths within irregular intersections. Then, for the three typical conflict scenarios of diverging, crossing and merging, the conflict zone action distance calculation models are established, and the corresponding conflict resolution strategies are designed to ensure safe vehicle interactions. In terms of optimization and control, a joint optimization model of vehicle path planning and speed control (PPSC) is constructed with the objective of minimizing the total vehicle delay, and a rolling horizon control scheme is employed to efficiently solve the model. Finally, numerical experiments are conducted to validate the effectiveness and advancement of the proposed method. The simulation results indicate that the PPSC method achieves significant improvements in reducing average vehicle delay, enhancing intersection throughput, and lowering fuel consumption. Moreover, the effects of different safe interval times, adjustment section lengths, and planning time horizons on the performance of the PPSC method are further investigated through sensitivity analysis.

IEEE Transactions on Vehicular TechnologyVol. 75(1)
Southwest Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 80%
Autonomous Vehicle Technology and Safety
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Conflict Resolution Strategies for Connected and Autonomous Vehicles at Unsignalized Irregular Intersections: Path Planning and Speed Control — Yugang Liu, You Zhang, et al. · IEEE Transactions on Vehicular Technology (2025) | TGRS Research Map | TGRS