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Extended exposure to reliable automation may lead to overreliance as evidenced by poor responses to auto-mation errors. Individual differences in trust may also influence responses. We investigated how these factors affect response to automation errors in a driving simulator study comprised of stop-controlled and uncon-trolled intersections. Drivers experienced reliable vehicle automation during six drives where they indicated if they felt the automation was going too slow or too fast by pressing the accelerator or brake pedal. Engage-ment via pedal presses did not affect the automation but offered an objective measure of trust in automation. In the final drive, an error occurred where the vehicle failed to stop at a stop-controlled intersection. Drivers’ response to the error was inferred from brake presses. Mixture models showed bimodal response times and revealed that drivers with high trust were less likely to respond to automation errors than drivers with low trust. 

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.