A Decision-Making Strategy for Car Following Based on Naturalist Driving Data via Deep Reinforcement Learning

To improve the satisfaction and acceptance of automatic driving, we propose a deep reinforcement learning (DRL)-based autonomous car-following (CF) decision-making strategy using naturalist driving data (NDD). This study examines the traits of CF behavior using 1341 pairs of CF events taken from the...

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Detalles Bibliográficos
Autores principales: Li, Wenli, Zhang, Yousong, Shi, Xiaohui, Qiu, Fanke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608473/
https://www.ncbi.nlm.nih.gov/pubmed/36298405
http://dx.doi.org/10.3390/s22208055

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608473/
https://www.ncbi.nlm.nih.gov/pubmed/36298405
http://dx.doi.org/10.3390/s22208055

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