ABSTRACT
Automated driving has many potential benefits, such as improving driving safety and reducing drivers’ workload. However, from a human factors’ perspective, one concern is that drivers become increasingly out of the control loop once they start to engage in non-driving-related tasks, which makes it difficult for the drivers to take over control in some situations. In the present study, we examined reviewers’ comments of YouTube videos featuring takeover transitions on commercially available autonomous vehicles and categorized the comments into four topics: Non-driving related tasks, automation capability awareness, situation awareness, and warning effectiveness. Then we investigated people’ opinions on the design of the takeover mechanism of commercially available autonomous vehicles using topic mining and sentiment analysis, and we found that 1) the topic of automation capability awareness received many more positive comments than both negative and neutral comments while the distributions of positive, negative, and neutral comments were fairly even in other topics and 2) people had extreme positive and negative opinions in non-driving related tasks than other topics. Finally, we discussed possible design recommendations in order to facilitate takeover transitions.
Additional information
Notes on contributors
Feng Zhou
Feng Zhou is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Michigan, Dearborn. He obtained a Ph.D. degree in Engineering Design from Georgia Institute of Technology in 2014 and another Ph.D. degree in Human Factors Engineering from Nanyang Technological University, Singapore, in 2011.
X. Jessie Yang
X. Jessie Yang is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan, Ann Arbor. She obtained a Ph.D. degree in Mechanical and Aerospace Engineering (Human Factors) from Nanyang Technological University, Singapore, in 2014.
Xin Zhang
Xin Zhang is a product marketing manager at Microsoft’s Cloud division. His work spans from product management, business strategy to marketing for the cutting-edge cloud services at Microsoft. Xin earned a BS degree in Industrial Engineering from the Pennsylvania State University and an MBA and MS degree in Industrial & Operations Engineering from University of Michigan.