Comparing deep reinforcement learning architectures for autonomous racing

Comparing deep reinforcement learning architectures for autonomous racing

In classical autonomous racing, a perception, planning, and control pipeline is employed to navigate vehicles around a track as quickly as possible. In contrast, neural network controllers have been used to replace either part of or the entire pipeline. This paper compares three deep learning archit...

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Bibliographic Details
Main Authors: Benjamin David Evans, Hendrik Willem Jordaan, Herman Arnold Engelbrecht
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Machine Learning with Applications
Subjects:
Deep reinforcement learning
End-to-end driving
Autonomous racing
Trajectory planning
Online Access:http://www.sciencedirect.com/science/article/pii/S266682702300049X

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