AI RESEARCH
CogDriver: Integrating Cognitive Inertia for Temporally Coherent Planning in Autonomous Driving
arXiv CS.CV
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ArXi:2509.00789v2 Announce Type: replace The pursuit of autonomous agents capable of temporally coherent planning is hindered by a fundamental flaw in current vision-language models (VLMs): they lack cognitive inertia. Operating on isolated snapshots, these models cannot form a continuous understanding of the environment, leading to erratic decision jitter and a failure to execute complex, multi-step maneuvers. To remedy this, we