Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust

Abstract

Purpose Self-driving cars are an extremely high level of autonomous technology and represent a promising technology that may help older adults safely maintain independence. However, human behavior with automation is complex and not straightforward ( Parasuraman and Riley, 1997 ; Parasuraman, 2000 ; Rovira et al., 2007 ; Parasuraman and Wickens, 2008 ; Parasuraman and Manzey, 2010 ; Parasuraman et al., 2012 ). In addition, because no fully self-driving vehicles are yet available to the public, most research has been limited to subjective survey-based assessments that depend on the respondents’ limited knowledge based on second-hand reports and do not reflect the complex situational and dispositional factors known to affect trust and technology adoption. Methods To address these issues, the current study examined the specific factors that affect younger and older adults’ trust in self-driving vehicles. Results The results showed that trust in self-driving vehicles depended on multiple interacting variables, such as the age of the respondent, risk during travel, impairment level of the hypothesized driver, and whether the self-driving car was reliable. Conclusion The primary contribution of this work is that, contrary to existing opinion surveys which suggest broad distrust in self-driving cars, the ratings of trust in self-driving cars varied with situational characteristics (reliability, driver impairment, risk level). Specifically, individuals reported less trust in the self-driving car when there was a failure with the car technology; and more trust in the technology in a low risk driving situation with an unimpaired driver when the automation was unreliable.

Perceived benefits and constraints in vehicle automation: Data to assess the relationship between driver's features and their attitudes towards autonomous vehicles

“…In accordance with the pursued analyses and some previous research experiences dealing with different gender and age-based groups of population [2,3], the data was analyzed considering both the full sample and specific sub-groups built up bearing in mind these individual features, already supported by literature as potential key factors on decision-making in urban mobility-settings [[4], [5], [6]]. Thus, for making comparisons in the study variables, the full sample was divided: a ) by gender (538 females, and 667 males); and b ) in five intervals, composed as follows: <25 years ( n = 113, composing 9.4% of the sample); 25–35 years ( n = 271, composing 22.4% of the sample); 36–45 years ( n = 359, composing 29.8% of the sample); 46–55 years ( n = 326, composing 27.1% of the sample); and >55 years ( n = 136, composing 11.3% of the sample).…”

“…Thus, for making comparisons in the study variables, the full sample was divided: a ) by gender (538 females, and 667 males); and b ) in five intervals, composed as follows: <25 years ( n = 113, composing 9.4% of the sample); 25–35 years ( n = 271, composing 22.4% of the sample); 36–45 years ( n = 359, composing 29.8% of the sample); 46–55 years ( n = 326, composing 27.1% of the sample); and >55 years ( n = 136, composing 11.3% of the sample). Additionally, it was taken into account the size of the town/city of residence of the driver, as recent evidences suggest that attitudes towards autonomous vehicles may differ according to the place of residence [6] and other settings related to driving habits and lifestyle [3,4].…”

Age and experience in driving a vehicle and psychomotor skills in the context of automation

“…The results of the study by Hulse [8] confirm the conclusions of the study by Abraham [1,2] that many older drivers generally want to use partial automation, declaring less interest in full autonomy compared to younger drivers. Rovira et al [19] draw attention to the fact that the ratings of confidence in autonomous cars may differ depending on the situation (reliability, driver disability, level of risk). Moreover, when drivers receive additional in-formation, their perception of driving technologies changes accordingly [3,19].…”

“…Rovira et al [19] draw attention to the fact that the ratings of confidence in autonomous cars may differ depending on the situation (reliability, driver disability, level of risk). Moreover, when drivers receive additional in-formation, their perception of driving technologies changes accordingly [3,19].…”

A Comparison of Unimodal and Multimodal Measurements of Driver Stress in Real-World Driving Conditions

“…People's trust in this type of technology may vary [21] [22]-drivers with low levels of trust may remain in an unpleasant, tense state from the point of relinquishing control right up until the point of regaining control of their vehicle. This situation is not ideal as the experience of stress can impair drivers' ability to retrieve control from the automated system [23] [24], may cause non-optimal manual driving performance, and may even result in a reduced tendency to engage with the assisted system in the future.…”