An LLM-supported framework maps natural-language commands to distinguishable Apollo lane-change parameters for three driving styles via clustering and RAG, with experiments showing improved interpretation of implicit preferences.
A communication-latency-aware co-simulation platform for safety and comfort evaluation of cloud-controlled icvs,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.RO 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios
An LLM-supported framework maps natural-language commands to distinguishable Apollo lane-change parameters for three driving styles via clustering and RAG, with experiments showing improved interpretation of implicit preferences.