Evolutionary Decision-Making and Planning for Autonomous Driving: A Hybrid Augmented Intelligence Framework-Reference-Cited by-同舟云学术

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Evolutionary Decision-Making and Planning for Autonomous Driving: A Hybrid Augmented Intelligence Framework

Published:2024-07 Issue:7 Volume:25 Page:7339-7351
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Yuan Kang¹^ORCID,Huang Yanjun²^ORCID,Yang Shuo²^ORCID,Wu Mingzhi³,Cao Dongpu⁴^ORCID,Chen Qijun¹^ORCID,Chen Hong¹^ORCID

Affiliation:

1. College of Electronic and Information Engineering, Tongji University, Shanghai, China

2. School of Automotive Studies, Tongji University, Shanghai, China

3. Nanchang Automotive Institute of Intelligence and New Energy, Tongji University, Nanchang, China

4. School of Vehicle and Mobility, Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

Shanghai Municipal Science and Technology Major Project

Fundamental Research Funds for the Central Universities

Shanghai Gaofeng and Gaoyuan Project for University Academic Program Development

Frontiers Technologies Project of Nanchang Automotive Institute of Intelligence and New Energy of Tongji University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6979/10582787/10400976.pdf?arnumber=10400976

Reference38 articles.

1. Lane Change Maneuvers for Automated Vehicles

2. Decision making framework for autonomous vehicles driving behavior in complex scenarios via hierarchical state machine

3. Decision-Making Framework for Autonomous Driving at Road Intersections: Safeguarding Against Collision, Overly Conservative Behavior, and Violation Vehicles

4. Autonomous lane-change controller

5. Optimal trajectory planning and decision making in lane change maneuvers near a highway exit

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