LLM-driven multi-planner scheduling framework turns open-ended passenger instructions into safe, traceable control signals for autonomous vehicles while cutting query costs and matching specialized safety levels.
An advanced lane-keeping assistance system with switchable assistance modes.IEEE Transactions on Intelligent Transportation Systems, 21(1): 385–396, 2020
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Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles
LLM-driven multi-planner scheduling framework turns open-ended passenger instructions into safe, traceable control signals for autonomous vehicles while cutting query costs and matching specialized safety levels.