AI RESEARCH
Drive-P2D: A Progressive Perception-to-Decision Benchmark for VLMs in Autonomous Driving
arXiv CS.AI
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ArXi:2601.14702v2 Announce Type: replace Autonomous driving requires reliable perception and safe decision-making in complex scenarios. Recent vision-language models (VLMs) nstrate reasoning and generalization abilities, opening new possibilities for autonomous driving; however, existing benchmarks often evaluate perception and decision-making separately, limit failure analysis with choice-only formats, or