ABSTRACT
COVID-19 pandemic may positively impact the transportation sector’s use of automated vehicles (AVs) and hasten AV adoption in areas such as contactless delivery. However, resistance or negative attitudes toward AVs and fear over safety creates unknowns about whether people are willing to adopt driverless AVs if available in similar pandemics. Two vignette-based studies (N = 1087) found that the pandemic can lead Chinese participants to be more willing to use driverless Robotaxis and exhibit more positive responses to Robotaxis than traditional, manned taxis. In Study 1, their preference for a Robotaxi was greater in the pandemic than in the normal condition. They also preferred the Robotaxi over the manned taxi in the pandemic when we manipulated the Robotaxi to be merely as safe as or superior to the manned taxi. Study 2 compared the Robotaxi and manned taxis with equal safety in both conditions. Participants expressed greater negative affect (fear and anxiety) and lower willingness to ride in a Robotaxi in the normal condition. However, in the pandemic condition, they expressed lower negative affect and greater willingness to ride in the Robotaxi. Trust in Robotaxi was lower than in the manned taxi in the normal condition, whereas there was no difference in trust in both taxis in the pandemic. There was no difference in risk acceptance across the two conditions. Our research provides unique and empirical evidence for supporting the adoption of AVs in similar situations and calls on policy support to develop and deploy AVs to meet the consumer need for driverless mobility services in these situations.
Data availability statement
See https://osf.io/h27xp/?view_only=c96bc29ae2534a3ba06ce536c778df6e.
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Tingting Li
Tingting Li is a graduate student of the College of Management and Economics, Tianjin University, China. She graduated from Nanjing Agricultural University in China. Her research focuses on human factors in automated driving.
Peng Liu
Peng Liu is a professor (research) in the Center for Psychological Sciences, Zhejiang University, China. His research focuses on human factors and ergonomics, risk analysis, and risk perception related to complex systems such as automated driving and nuclear power plants.