Citation

Baby T, Hee Yoon S, Lee J, Cui Z, Itoh M, Chan Lee S. Transp. Res. F Traffic Psychol. Behav. 2024; 103: 608-622.

Copyright

(Copyright © 2024, Elsevier Publishing)

DOI

10.1016/j.trf.2024.05.014

PMID

unavailable

Abstract

The Driver Behavior Questionnaire (DBQ), which is rooted in Human Factors, is a common tool used in the context of driving behavior. However, it does not consider driver behavior when automated-driving systems are active. The primary objective of this study is to construct a questionnaire with high levels of reliability to assess the driving behavior of automated-vehicle (AV) users. This paper presents the development and validation process of a 16-item automated driving behavior questionnaire, composed of three factors of the driving process (perception, cognition, and action) and two factors of automated driving systems (user literacy and dependency). Responses from 441 active AV users were collected and analyzed. The application of factor analysis resulted in the identification of a five-factor solution, and the results showed that male drivers exhibited higher levels of literacy, action, and reliance on AVs than female drivers. In terms of trust, those with complete trust reported higher AV dependency, whereas those with low trust reported lower AV dependency and higher cognitive scores. Addressing gender- and trust-based disparities is crucial for traffic safety, especially among male and less-trusting drivers. The developed ADBQ will serve as a supporting tool for system developers and researchers to assess the driving behaviors of AV users.

Keywords

Questionnaire Development; Structural Equation Modeling; ADBQ; Automated Driving Behavior Questionnaire; Automated Vehicles