Personalized Car-Following Strategy Based on Convolutional Variational Autoencoder and Mildly Conservative Q-Learning

With the development of intelligent vehicles, the importance of imitating, learning, and optimizing human driving strategies is increasingly recognized. Offline reinforcement learning offers a promising approach, capable of directly extracting driving strategies from diverse real-world datasets, par...

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Vydané v:	IEEE transactions on vehicular technology Ročník 74; číslo 9; s. 13372 - 13386
Hlavní autori:	He, Rui, Chang, Yupeng, Zhang, Sumin, Meng, Zhiwei, Li, Wenfeng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.09.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptation models Behavioral sciences Car following Car-following control Customization Data models Datasets Driver behavior Driving Feature extraction generative model Human performance intelligent vehicle Intelligent vehicles Machine learning offline reinforcement learning personalized Prediction models Predictive models Reinforcement learning Training Uncertainty Vehicle safety Vehicles
ISSN:	0018-9545, 1939-9359
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