DriveMind: Mind-Evolving Belief Tracking for Closed-Loop Autonomous Driving
DriveMind is proposed, an MLLM-based driving framework that keeps several hypotheses about the scene alive at the same time and updates their weights as new frames arrive and improves fine-grained interactive driving abilities such as merging, emergency braking, and give-way.
Yan Shi, Ke-Hua Chen, Jia-Rui Qi et al.
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