CMU-Drive adds up to 16 connected autonomous vehicles to closed-loop driving scenarios, and V2V-VLA shows that sharing merged occupancy views and communication suggestions improves driving score over a single-agent VLA baseline.
In: Conference on Robot Learning (CoRL) (2017)
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CMU-Drive and V2V-VLA: Cooperative Multi-agent Unified Driving with Reasoning Benchmark and Vehicle-to-Vehicle Vision-Language-Action Models
CMU-Drive adds up to 16 connected autonomous vehicles to closed-loop driving scenarios, and V2V-VLA shows that sharing merged occupancy views and communication suggestions improves driving score over a single-agent VLA baseline.