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arXiv · 2506.23999

Predictive Risk Analysis and Safe Trajectory Planning for Intelligent and Connected Vehicles

Zeyu Han·Mengchi Cai·Chaoyi Chen·Qingwen Meng·Guangwei Wang·Ying Liu·Qing Xu·Jianqiang Wang·Keqiang Li
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Abstract

The safe trajectory planning of intelligent and connected vehicles is a key component in autonomous driving technology. Modeling the environment risk information by field is a promising and effective approach for safe trajectory planning. However, existing risk assessment theories only analyze the risk by current information, ignoring future prediction. This paper proposes a predictive risk analysis and safe trajectory planning framework for intelligent and connected vehicles. This framework first predicts future trajectories of objects by a local risk-aware algorithm, following with a spatiotemporal-discretised predictive risk analysis using the prediction results. Then the safe trajectory is generated based on the predictive risk analysis. Finally, simulation and vehicle experiments confirm the efficacy and real-time practicability of our approach.

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Zeyu Han, Mengchi Cai, Chaoyi Chen, Qingwen Meng, Guangwei Wang, Ying Liu, Qing Xu, Jianqiang Wang, Keqiang Li. 2025-06-30. Predictive Risk Analysis and Safe Trajectory Planning for Intelligent and Connected Vehicles. https://arxiv.org/abs/2506.23999

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