A Behavior Decision Method Based on Reinforcement Learning for Autonomous Driving-Reference-Cited by-同舟云学术

A Behavior Decision Method Based on Reinforcement Learning for Autonomous Driving

Published:2022-12-15 Issue:24 Volume:9 Page:25386-25394
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zheng Kan¹^ORCID,Yang Haojun²^ORCID,Liu Shiwen³,Zhang Kuan⁴^ORCID,Lei Lei⁵^ORCID

Affiliation:

1. College of Electrical Engineering and Computer Science, Ningbo University, Ningbo, China

2. Department of Electrical and Computer Engineering, Western University, London, ON, Canada

3. Intelligent Computing and Communications Lab, Wireless Signal Processing and Networks Lab, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China

4. Department of Electrical and Computer Engineering, University of Nebraska–Lincoln, Omaha, NE, USA

5. School of Engineering, University of Guelph, Guelph, ON, Canada

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/9973413/09851435.pdf?arnumber=9851435

Reference24 articles.

1. A driving intention prediction method based on hidden Markov model for autonomous driving

2. Applying Markov decision process to understand driving decisions using basic safety messages data

3. A point-based MDP for robust single-lane autonomous driving behavior under uncertainties

4. Probabilistic online POMDP decision making for lane changes in fully automated driving

5. Expandable-Partially Observable Markov Decision-Process Framework for Modeling and Analysis of Autonomous Vehicle Behavior

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