An Automated Driving Strategy Generating Method Based on WGAIL–DDPG

An Automated Driving Strategy Generating Method Based on WGAIL–DDPG

Reliability, efficiency and generalization are basic evaluation criteria for a vehicle automated driving system. This paper proposes an automated driving decision-making method based on the Wasserstein generative adversarial imitation learning–deep deterministic policy gradient (WGAIL–DDPG(λ)). Here...

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Bibliographic Details
Main Authors: Zhang Mingheng, Wan Xing, Gang Longhui, Lv Xinfei, Wu Zengwen, Liu Zhaoyang
Format: Article
Language:English
Published: Sciendo 2021-09-01
Series:International Journal of Applied Mathematics and Computer Science
Subjects:
automated driving system
deep learning
deep reinforcement learning
imitation learning
deep deterministic policy gradient
Online Access:https://doi.org/10.34768/amcs-2021-0031

Internet

https://doi.org/10.34768/amcs-2021-0031

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