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.
|IOP Conference Series: Materials Science and Engineering
|Published - 6 Dec 2019
|3rd International Conference on Traffic Engineering and Transportation System, ICTETS 2019 - Jiaozuo, China
Duration: 20 Sept 2019 → 22 Sept 2019
ASJC Scopus subject areas
- General Materials Science
- General Engineering