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Multi-vehicle trajectory planning at unsignalised intersections based on cooperative vehicle-infrastructure system

Yangjie Ji et al.

International Journal of Vehicle Design: journal of vehicle engineering, automotive technology and components2025https://doi.org/10.1504/ijvd.2025.149113article
ABDC B
Weight
0.37

Abstract

Collaboration between infrastructures and connected and autonomous vehicles (CAVs) at unsignalised intersections has emerged as an effective strategy for improving transportation efficiency. To enhance the safety and efficiency of CAVs passing through unsignalised intersections, this paper proposes a cooperative vehicle-infrastructure system (CVIS) based multi-vehicle trajectory planning architecture. The architecture comprises a roadside planner and vehicle planners. The roadside planner formulates the problem of generating multi-vehicle trajectories as an optimisation task and addresses it using an improved particle swarm optimisation (PSO) approach along with a space-time voxels strategy to determine the times for vehicles to reach the intersection and the trajectories passing through it. Then, the vehicle planner plans according to the results of the roadside planner. The results show that our approach enables potentially conflicting CAVs to pass through unsignalised intersections without stopping and waiting, ensuring safety while improving traffic efficiency.

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https://doi.org/https://doi.org/10.1504/ijvd.2025.149113

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@article{yangjie2025,
  title        = {{Multi-vehicle trajectory planning at unsignalised intersections based on cooperative vehicle-infrastructure system}},
  author       = {Yangjie Ji et al.},
  journal      = {International Journal of Vehicle Design: journal of vehicle engineering, automotive technology and components},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijvd.2025.149113},
}

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Multi-vehicle trajectory planning at unsignalised intersections based on cooperative vehicle-infrastructure system

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.