TY - JOUR
T1 - A Research of Electrical Engineering and Automation-based Intelligent Technology Application
AU - Wei, Zhiwen
AU - Li, Zhao
AU - Liang, Yaolin
AU - Huang, Xuejin
AU - Yu, Liwei
AU - Sheng, Haiyan
AU - Fan, Li
N1 - Funding Information:
The authors wish to acknowledge assistance and encouragement from our friends and families. The study was supported by information project (031900HK42180010) of China Southern Power Grid, CSG.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2019/12/6
Y1 - 2019/12/6
N2 - As a safety-security field, the transportation field always encourages and embraces advanced intelligent technologies to reduce risks. Recently, automated driving has received extensive attention from researchers and industries, as it is expected to improve the flow of traffic, to significantly reduce drivers' errors and thusly increase safety. Though many efforts have put on automated driving, many challenges remain in achieving fully autonomous, resulting in partially automated driving. The role of drivers in a partially automated car is monitoring and taking over driving in specific conditions, which is significantly different from the manual cars. The novel role of drivers induces new human factors issues and challenges to maintain traffic safety. This study tries to investigate these human factors issues involved in the human and automated driving interactions and to propose a framework of electrical engineering and automation-based intelligent technology application to mitigate risks. Specifically, trust, attention, situational awareness, and alarm fatigue were identified as significant human factors issues in automated driving. An electrical engineering and automation-based intelligent framework for monitoring cognitive states and generate warnings was proposed.
AB - As a safety-security field, the transportation field always encourages and embraces advanced intelligent technologies to reduce risks. Recently, automated driving has received extensive attention from researchers and industries, as it is expected to improve the flow of traffic, to significantly reduce drivers' errors and thusly increase safety. Though many efforts have put on automated driving, many challenges remain in achieving fully autonomous, resulting in partially automated driving. The role of drivers in a partially automated car is monitoring and taking over driving in specific conditions, which is significantly different from the manual cars. The novel role of drivers induces new human factors issues and challenges to maintain traffic safety. This study tries to investigate these human factors issues involved in the human and automated driving interactions and to propose a framework of electrical engineering and automation-based intelligent technology application to mitigate risks. Specifically, trust, attention, situational awareness, and alarm fatigue were identified as significant human factors issues in automated driving. An electrical engineering and automation-based intelligent framework for monitoring cognitive states and generate warnings was proposed.
UR - http://www.scopus.com/inward/record.url?scp=85078251092&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/688/4/044041
DO - 10.1088/1757-899X/688/4/044041
M3 - Conference article
AN - SCOPUS:85078251092
SN - 1757-8981
VL - 688
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 4
M1 - 044041
T2 - 3rd International Conference on Traffic Engineering and Transportation System, ICTETS 2019
Y2 - 20 September 2019 through 22 September 2019
ER -