DOI: 10.1145/3838726 ISSN: 0360-0300

Generative AI for Autonomous Driving: Frontiers and Opportunities

Yuping Wang, Shuo Xing, Can Cui, Renjie Li, Hongyuan Hua, Kexin Tian, Zhaobin Mo, Xiangbo Gao, Marco Pavone, Yang Zhou, Jiachen Li, Zhengzhong Tu

Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation, reasoning, planning, and multimodal understanding. This revolutionary force offers the most promising path yet toward solving one of engineering’s grandest challenges: achieving reliable, fully autonomous driving, particularly the pursuit of Level 5 autonomy. This survey delivers a comprehensive and critical synthesis of the emerging role of GenAI across the autonomous driving stack. We delve into the frontier applications of GenAI in image, LiDAR, trajectory, occupancy, and video generation, as well as LLM-guided reasoning and decision-making. We categorize practical applications, such as end-to-end driving strategies and closed-loop simulations. We identify key obstacles and possibilities such as comprehensive generalization across rare cases, evaluation, safety, and onboard deployment. By unifying these threads, the survey provides a forward-looking reference for researchers, engineers, and policymakers navigating the convergence of generative AI and advanced autonomous mobility. An actively maintained repository of cited works is available at https://github.com/taco-group/GenAI4AD.

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