A knowledge-informed deep learning paradigm for generaliz-able and stability-optimized car-following modelsOA
A knowledge-informed deep learning paradigm for generaliz-able and stability-optimized car-following models
Chengming Wang;Dongyao Jia;Wei Wang;Dong Ngoduy;Bei Peng;Jianping Wang
School of Advanced Technology,Xi'an Jiaotong-Liverpool University,Suzhou,215123,ChinaSchool of Advanced Technology,Xi'an Jiaotong-Liverpool University,Suzhou,215123,ChinaSchool of Advanced Technology,Xi'an Jiaotong-Liverpool University,Suzhou,215123,ChinaInstitute of Transport Studies,Monash University,Clayton,3800,AustraliaDepartment of Computer Science,University of Liverpool,Liverpool,L69 7ZX,UKDepartment of Computer Science,City University of Hong Kong,Hong Kong,999077,China
Car-following models(CFMs)Large language models(LLMs)Knowledge distillationStability analysisDeep learning
Car-following models(CFMs)Large language models(LLMs)Knowledge distillationStability analysisDeep learning
《交通研究通讯（英文）》 2025 (3)
236-251,16
This work was supported in part by the National Natural Science Foundation of China(No.62372384)and in part by Suzhou Science and Technology Development Planning Programme(No.ZXL2024342).Dong Ngoduy was partially funded by LK Engineering Ltd.
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