HCI in Mobility, Transport and Automotive Systems Best Paper Award

Certificate for best paper award of the 2nd International Conference on HCI in Mobility, Transport and Automotive Systems. Details in text following the image

Certificate for Best Paper Award of the 2nd International Conference on HCI in Mobility, Transport and Automotive Systems

The award has been conferred to
Norah Neuhuber (Virtual Vehicle Research Center / University of Graz, Austria),
Gernot Lechner (University of Graz, Austria), Tahir Emre Kalayci, Alexander Stocker
(Virtual Vehicle Research Center, Austria), Bettina Kubicek (University of Graz, Austria)

Norah Neuhuber

for the paper entitled

"Age-related Differences in the Interaction with Advanced Driver Assistance Systems - A Field Study"

Presented in the context of
HCI International 2020
19-24 July 2020

Paper Abstract
"The automotive industry invests enormous sums in vehicle automation. However, for people to buy such (semi-)automated vehicles, trust and acceptance are essential requirements. In addition to trust and acceptance, situation awareness, that is the perception of one’s environment, was shown to be influenced by automation usage. To examine how drivers of different age-groups (“younger” 21–29 years, “middle-aged” 30–49 years, “older” 50–77 years) interact with semi-automated vehicles (level 2) in terms of trust, acceptance and situation awareness, we conducted a comprehensive field study with 100 drivers (49 female), carefully examining questionnaire and thinking-aloud data. Each participant drove once within a “manual” condition and once within a “semi-automated” condition for around 25 min. Within the semi-automated drive, participants could voluntarily use vehicle automation. Our results show that self-reported levels of trust increased after the semi-automated drive. However, we found no significant differences in trust or acceptance ratings between young, middle and older participants. We did find significant differences in self-reported levels of situational awareness between the three age groups after the manual drive. Older drivers reported a significantly lower situation awareness compared to younger drivers. The recorded thinking-aloud data allowed us to gain deeper insights into system interaction: Older participants verbally reported a significantly higher amount of difficulties in understanding and interacting with vehicle automation. Nevertheless, they did not rate the automation system differently in terms of trust and acceptance, indicating that older drivers might acknowledge the possible support provided by the vehicle automation. These results have implications especially for the design of advanced driver assistance systems."

The full paper is available through SpringerLink, provided that you have proper access rights.