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End-to-end replay-based trajectory planning for autonomous vehicles under multi-weather scenarios | Synapse
March 3, 2026
Open Access
End-to-end replay-based trajectory planning for autonomous vehicles under multi-weather scenarios
JD
Jinjun Dun
Tianjin University
YZ
Yuenan Zhao
Ministry of Education of the People's Republic of China
XX
Xiaoyu Xu
Shandong University
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Key Points
Effective trajectory planning results in better navigation for autonomous vehicles, enhancing safety and efficiency.
The simulation shows that the method significantly improves pathfinding accuracy in rain, snow, and fog conditions.
Analysis focused on replay-based approaches that utilize real-world data for planning trajectories in challenging weather.
These findings highlight the need for autonomous systems to adapt to environmental challenges for reliable performance.
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Dun et al. (Sun,) studied this question.
synapsesocial.com/papers/69a765d9badf0bb9e87dab3b
https://doi.org/https://doi.org/10.1016/j.birob.2026.100275
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