Abstract
The purpose of this study is to develop a framework that can identify critical human factors (HFs) that can generate human errors and, consequently, accidents in autonomous driving level 3 situations. Although much emphasis has been placed on developing hardware and software components for self-driving cars, interactions between a human driver and an autonomous car have not been examined. Because user acceptance and trust are substantial for the further and sustainable development of autonomous driving technology, considering factors that will influence user satisfaction is crucial. As autonomous driving is a new field of research, the literature review in other established fields was performed to draw out these probable HFs. Herein, interrelationship matrices were deployed to identify critical HFs and analyze the associations between these HFs and their impact on performance. Age, focus, multitasking capabilities, intelligence, and learning speed are selected as the most critical HFs in autonomous driving technology. Considering these factors in designing interactions between drivers and automated driving systems will enhance users’ acceptance of the technology and its sustainability by securing good usability and user experiences.
Highlights
Artificial intelligence (AI) technology is profoundly changing our daily lives, including the way humans drive vehicles
The goal of this study is to find critical human factors (HFs) that may yield the difference in these chances of making errors
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Summary
Artificial intelligence (AI) technology is profoundly changing our daily lives, including the way humans drive vehicles. Autonomous driving technology started to emerge in the form of partial automation based on advanced driving assistance systems (ADAS) and has since evolved into full automation through partial and high automation [1]. This technology has been continuously developing to assist drivers, reduce their cognitive workload, and provide more pleasant driving experiences. According to Fagnant et al [2], self-driving cars will reduce crashes by 90%. Their basic assumption for this hypothesis is that 90% of recent traffic accidents involve human errors. The human role in transportation should be changed from drivers to passengers, who should stay out of the control loop to avoid making errors
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