Toward Learning Human-Like, Safe and Comfortable Car-Following Policies With a Novel Deep Reinforcement Learning Approach

Toward Learning Human-Like, Safe and Comfortable Car-Following Policies With a Novel Deep Reinforcement Learning Approach

In this paper, we present an advanced adaptive cruise control (ACC) concept powered by Deep Reinforcement Learning (DRL) that generates safe, human-like, and comfortable car-following policies. Unlike the current trend in developing DRL-based ACC systems, we propose defining the action space of the...

Full description

Bibliographic Details
Main Authors: M. Ugur Yavas, Tufan Kumbasar, Nazim Kemal Ure
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Adaptive cruise control
reinforcement learning
deep learning
naturalistic driving
advanced driving assistance systems
Online Access:https://ieeexplore.ieee.org/document/10045659/

Internet

https://ieeexplore.ieee.org/document/10045659/

Similar Items