Planning with Adaptive World Models for Autonomous Driving

Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CARLA. However, such synthetic benchmarks do not capture real-world multi-agent interactions. nuPlan, a recently released...

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Veröffentlicht in:	arXiv.org 2024-09
Hauptverfasser:	Arun Balajee Vasudevan, Peri, Neehar, Schneider, Jeff, Ramanan, Deva
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Benchmarks Cities Closed loops Flight simulators Graph neural networks Motion planning Multiagent systems Planning Predictive control Tailgates Urban environments
Online-Zugang:	Volltext
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