Self-Learned Autonomous Driving at Unsignalized Intersections: A Hierarchical Reinforced Learning Approach for Feasible Decision-Making-Reference-Cited by-同舟云学术

Self-Learned Autonomous Driving at Unsignalized Intersections: A Hierarchical Reinforced Learning Approach for Feasible Decision-Making

Published:2023-11 Issue:11 Volume:24 Page:12345-12356
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Al-Sharman Mohammad¹^ORCID,Dempster Rowan¹^ORCID,Daoud Mohamed A.²^ORCID,Nasr Mahmoud¹,Rayside Derek¹,Melek William²

Affiliation:

1. Department of Electrical and Computer Engineering, Waterloo Autonomous Vehicle Team (WATonomous), SAE AutoDrive Challenge (Watonomous.ca), University of Waterloo, Waterloo, ON, Canada

2. Department of Mechanical and Mechatronics Engineering, and the WATonomous, University of Waterloo, Waterloo, ON, Canada

Funder

Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Research and Development

General Motors Canada and the Society of Automotive Engineers (SAE) AutoDrive Challenge

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10304348/10159573.pdf?arnumber=10159573

Reference47 articles.

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2. Decision-making at unsignalized intersection for autonomous vehicles: Left-turn maneuver with deep reinforcement learning;wang;arXiv 2008 06595,2020

3. Lane-Level Localization Using an AVM Camera for an Automated Driving Vehicle in Urban Environments

4. Deep variational reinforcement learning for POMDPS;igl;Proc Int Conf Mach Learn,2018

5. Development of an Efficient Driving Strategy for Connected and Automated Vehicles at Signalized Intersections: A Reinforcement Learning Approach

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