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Juntong Peng

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Review Open access Aug 2026

Generative AI for Autonomous Driving: Frontiers and Opportunities

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.

Yuping Wang, Shuo Xing, Cui Can et al. · 56 citations · ⚡2
Case report 2026

RampCast Phase II: Connected Vehicles Traffic Management Application on Indiana Highways

The AI framework was successfully shown to reorder and present messages based on real-time context, improving the clarity and usefulness of information provided to the driver, and support a hybrid C-V2X architecture as a robust model for future smart highway deployments.

Abin Mathew, A. Sundar, Juntong Peng et al. · 0 citations

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