LC-LLM:Explainable lane-change intention and trajectory predictions with Large Language ModelsOA
LC-LLM:Explainable lane-change intention and trajectory predictions with Large Language Models
Mingxing Peng;Xusen Guo;Xianda Chen;Kehua Chen;Meixin Zhu;Long Chen;Fei-Yue Wang
Intelligent Transportation(INTR),Systems Hub,The Hong Kong University of Science and Technology(Guangzhou),Guangzhou,511400,ChinaIntelligent Transportation(INTR),Systems Hub,The Hong Kong University of Science and Technology(Guangzhou),Guangzhou,511400,ChinaIntelligent Transportation(INTR),Systems Hub,The Hong Kong University of Science and Technology(Guangzhou),Guangzhou,511400,ChinaDivision of Emerging Interdisciplinary Areas(EMIA),Academy of Interdisciplinary Studies,The Hong Kong University of Science and Technology,Hong Kong,999077,ChinaGuangdong Provincial Key Lab of Integrated Communication,Sensing and Computation for Ubiquitous Internet of Things,Guangzhou,511400,ChinaState Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing,100190,ChinaState Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing,100190,China
Lane change(LC)Large language models(LLMs)Intention predictionTrajectory predictionFine-tuningInterpretabilityAutonomous driving
Lane change(LC)Large language models(LLMs)Intention predictionTrajectory predictionFine-tuningInterpretabilityAutonomous driving
《交通研究通讯（英文）》 2025 (2)
48-60,13
This study is supported by the National Natural Science Foundation of China(No.52302379),Guangdong Provincial Natural Science Foundation-General Project(No.2024A1515011790),Guangdong Province General Universities Youth Innovative Talents Project(No.2023KQNCX100),Guangzhou Municipal Science and Technology Project(No.2023A03J0011),and Nansha District Key R&D Project(No.2023ZD006).
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