Tootfinder

Work Zones challenge VLM Trajectory Planning: Toward Mitigation and Robust Autonomous Driving
Yifan Liao, Zhen Sun, Xiaoyun Qiu, Zixiao Zhao, Wenbing Tang, Xinlei He, Xinhu Zheng, Tianwei Zhang, Xinyi Huang, Xingshuo Han
https://arxiv.org/abs/2510.02803

Work Zones challenge VLM Trajectory Planning: Toward Mitigation and Robust Autonomous Driving
Visual Language Models (VLMs), with powerful multimodal reasoning capabilities, are gradually integrated into autonomous driving by several automobile manufacturers to enhance planning capability in challenging environments. However, the trajectory planning capability of VLMs in work zones, which often include irregular layouts, temporary traffic control, and dynamically changing geometric structures, is still unexplored. To bridge this gap, we conduct the \textit{first} systematic study of VLM…