Formulating Vehicle Aggressiveness Towards Social Cognitive Autonomous Driving-Reference-Cited by-同舟云学术

Formulating Vehicle Aggressiveness Towards Social Cognitive Autonomous Driving

Published:2023-03 Issue:3 Volume:8 Page:2097-2109
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Hu Wen¹^ORCID,Deng Zejian²^ORCID,Wu Yang¹,Zhang Bangji³,Li Wenbo¹,Xiao Xiaofeng⁴,Li Bai⁵^ORCID,Cao Dongpu¹^ORCID

Affiliation:

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

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

3. Intelligent Transportation System Research Center, Hangzhou City University, Hangzhou, China

4. University of Science and Technology Beijing, Beijing, China

5. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10109992/10007052.pdf?arnumber=10007052

Reference41 articles.

1. Car-Following and Lane-Changing Behavior Involving Heavy Vehicles:

2. The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems

3. Understanding the Dynamics of Heavy Vehicle Interactions in Car-Following

4. Towards the Unified Principles for Level 5 Autonomous Vehicles

5. Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

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