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20232026
most citedScaling Planning for Automated Driving using Simplistic Synthetic Data

1 citations · 1 across the 3 of their papers we have counts for

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cs.RO2025

AGENTS-LLM: Augmentative GENeration of Challenging Traffic Scenarios with an Agentic LLM Framework

Yu Yao, Salil Bhatnagar, Markus Mazzola +5

Rare, yet critical, scenarios pose a significant challenge in testing and evaluating autonomous driving planners. Relying solely on real-world driving scenes requires collecting ma…