A Takeover Risk Assessment Approach Based on an Improved ANP-XGBoost Algorithm for Human–Machine Driven Vehicles-Reference-Cited by-同舟云学术

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A Takeover Risk Assessment Approach Based on an Improved ANP-XGBoost Algorithm for Human–Machine Driven Vehicles

Published:2024 Issue: Volume:12 Page:48379-48387
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wang Tao¹,Han Yaxi¹^ORCID,Li Wenyong¹^ORCID,Ye Xiaofei²^ORCID,Yuan Quan³

Affiliation:

1. Guangxi Key Laboratory of Intelligent Transportation System, Guilin University of Electronic Technology, Guilin, China

2. Faculty of Maritime and Transportation, Ningbo University, Ningbo, China

3. State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Guilin Key R&D Program

Liuzhou Key R&D Program

Innovation Project of Guilin University of Electronic Technology Graduate Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10477987.pdf?arnumber=10477987

Reference42 articles.

1. Effects of environmental, vehicle and human factors on comfort in partially automated driving: A scenario-based study

2. The human factors of the take-over process in conditional automated driving based on cognitive mechanism;Ma;Adv. Psychol. Sci.,2020

3. Research on safety of the intended functionality of automobile AEB perception system in typical dangerous scenarios of two-wheelers

4. Risk reduction for safety of the intended functionality of CACC with complex uncertainties: A cooperative robust non-fragile fault tolerant strategy

5. Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

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