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...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on vehicular technology Vol. 74; no. 9; pp. 13372 - 13386
Main Authors:	He, Rui, Chang, Yupeng, Zhang, Sumin, Meng, Zhiwei, Li, Wenfeng
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!