JRM Vol.32 No.3 pp. 605-612
doi: 10.20965/jrm.2020.p0605


Effects of Demographic Characteristics on Trust in Driving Automation

Jieun Lee*, Genya Abe**, Kenji Sato**, and Makoto Itoh*

*University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

**Japanese Automobile Research Institute
2530 Karima, Tsukuba, Ibaraki 305-0822, Japan

December 20, 2019
April 2, 2020
June 20, 2020
driving automation, human-machine trust, supervisory control, gender, acceptance of automation

With the successful introduction of advanced driver assistance systems, vehicles with driving automation technologies have begun to be released onto the market. Because the role of human drivers during automated driving may be different from the role of drivers with assistance systems, it is important to determine how general users consider such new technologies. The current study has attempted to consider driver trust, which plays a critical role in forming users’ technology acceptance. In a driving simulator experiment, the demographic information of 56 drivers (50% female, 64% student, and 53% daily driver) was analyzed with respect to Lee and Moray’s three dimensions of trust: purpose, process, and performance. The statistical results revealed that female drivers were more likely to rate higher levels of trust than males, and non-student drivers exhibited higher levels of trust than student drivers. However, no driving frequency-related difference was observed. The driver ratings of each trust dimension were neutral to moderate, but purpose-related trust was lower than process- and performance-related trust. Additionally, student drivers exhibited a tendency to distrust automation compared to non-student drivers. The findings present a potential perspective of driver acceptability of current automated vehicles.

Fixed-base driving simulator for partial vehicle automation

Fixed-base driving simulator for partial vehicle automation

Cite this article as:
J. Lee, G. Abe, K. Sato, and M. Itoh, “Effects of Demographic Characteristics on Trust in Driving Automation,” J. Robot. Mechatron., Vol.32 No.3, pp. 605-612, 2020.
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