Vehicle cybersecurity is a serious concern, as modern vehicles are vulnerable to cyberattacks. How drivers respond to situations induced by vehicle cyberattacks is safety critical. This paper sought to understand the effect of human drivers’ risky driving style on response behavior to unexpected vehicle cyberattacks. A driving simulator study was conducted wherein 32 participants experienced a series of simulated drives in which unexpected events caused by vehicle cyberattacks were presented. Participants’ response behavior was assessed by their change in velocity after the cybersecurity events occurred, their post-event acceleration, as well as time to first reaction. Risky driving style was portrayed by scores on the Driver Behavior Questionnaire (DBQ) and the Brief Sensation Seeking Scale (BSSS). Half of the participants also received training regarding vehicle cybersecurity before the experiment. Results suggest that when encountering certain cyberattack-induced unexpected events, whether one received training, driving scenario, participants’ gender, DBQ-Violation scores, together with their sensation seeking measured by disinhibition, had a significant impact on their response behavior. Although both the DBQ and sensation seeking have been constantly reported to be linked with risky and aberrant driving behavior, we found that drivers with higher sensation seeking tended to respond to unexpected driving situations induced by vehicle cyberattacks in a less risky and potentially safer manner. This study incorporates not only human factors into the safety research of vehicle cybersecurity, but also builds direct connections between drivers’ risky driving style, which may come from their inherent risk-taking tendency, to response behavior to vehicle cyberattacks.

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Modern vehicles are embedded with numerous electronic components, making them more advanced and automated, while also making them vulnerable to cyberattacks. This study investigated how drivers respond to unexpected, cyber-attack-induced situations through a driving simulator study. It also examined differences in driver responses if they were trained or received warning messages on how to mitigate the effect of a vehicle cyberattack. The findings suggest that drivers' responses to cyberattacks vary based on the severity of the event. Those who receive training are much more likely to drive cautiously when the vehicle behaves unexpectedly and those who receive warning messages are likely to view them, but not necessarily take action. These results have far reaching implications into the utility of training programs in improving driver behavior and leave future work in terms of optimizing warning message systems.

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