Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field-Reference-Cited by-同舟云学术

Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field

Published:2022-11 Issue:11 Volume:23 Page:21531-21547
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Xie Songtao¹,Hu Junyan²^ORCID,Bhowmick Parijat³^ORCID,Ding Zhengtao¹^ORCID,Arvin Farshad⁴

Affiliation:

1. Department of Electrical and Electronic Engineering, The University of Manchester, Manchester, U.K

2. Department of Computer Science, University College London, London, U.K

3. Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, India

4. Department of Computer Science, Swarm and Computational Intelligence Laboratory (SwaCIL), Durham University, Durham, U.K

Funder

EU H2020-FET-OPEN RoboRoyale Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9942712/09830995.pdf?arnumber=9830995

Reference55 articles.

1. A Deep Reinforcement Learning Based Approach for Autonomous Overtaking

2. Overtaking Maneuvers in Simulated Highway Driving using Deep Reinforcement Learning

3. Cooperative Multiple Vehicle Trajectory Planning using MIQP

4. A Linear Model Predictive Planning Approach for Overtaking Manoeuvres Under Possible Collision Circumstances

5. Design and experimental evaluation of a hierarchical controller for an autonomous ground vehicle with large uncertainties;li;IEEE Trans Control Syst Technol,2021

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