Modeling Car-Following Behaviors and Driving Styles with Generative Adversarial Imitation Learning

Building a human-like car-following model that can accurately simulate drivers’ car-following behaviors is helpful to the development of driving assistance systems and autonomous driving. Recent studies have shown the advantages of applying reinforcement learning methods in car-following modeling. H...

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Auteurs principaux:	Yang Zhou, Rui Fu, Chang Wang, Ruibin Zhang
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2020-09-01
Collection:	Sensors
Sujets:	human-like car-following model driving styles generative adversarial imitation learning gated recurrent units
Accès en ligne:	https://www.mdpi.com/1424-8220/20/18/5034
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