Gender and age differences in the anticipated acceptance of automated vehicles: insights from a questionnaire study and potential for application

Abstract

Automated vehicles (AVs) are promoted with numerous benefits such as enabling driver-passengers to perform non-driving-related tasks (NDRTs) while increasing road safety and reducing the environmental impact. However, public acceptance will play an essential role in the (non-)adoption of AVs. As yet, there has been scant research on the acceptance of AVs differentiated by gender across the lifespan. Therefore, we developed a questionnaire on the acceptance of automated driving (QAAD) and queried 351 female and 374 male participants aged 18–96 years in Germany. Our findings reveal substantial gender differences indicating that women assign lower ratings to the factors on positive aspects of AVs (PRO), NDRTs, and on Early Adoption, and higher values to the factors on worries about AVs (CON) and Sustainability than men, respectively. Additionally, we found that younger people reported higher scores for PRO, NDRTs, and Early Adoption than older people. However, we observed an age group effect not for all levels of automated driving and not for Sustainability. The identified evidence suggests that it is essential to address women and men separately across the lifespan if car manufacturers want AVs to be accepted in the future. Our findings may serve as a guideline for research on AVs in developing countries.

Keywords:

• Automated vehicles
• technology acceptance
• gender differences
• age
• public opinion
• mobility of the future

Acknowledgements

We are also grateful to two anonymous reviewers and the editor-in-chief for their valuable remarks.

Disclosure statement

We want to declare that the psychometric development of the questionnaire and the data set have been published in the accompanying article:

Weigl, K., Schartmüller, C., Riener, A., & Steinhauser, M. (2021). Development of the Questionnaire on the Acceptance of Automated Driving (QAAD): Data-driven models for Level 3 and Level 5 automated driving. Transportation Research Part F: Traffic Psychology and Behaviour, 83, 42-59. https://doi.org/10.1016/j.trf.2021.09.011

However, this publication is not reporting any content-related results on gender or age differences in contrast to the present manuscript, ultimately resulting in a different manuscript.

Hence, it is distinct from and extends the present submission: 1) with new and different research questions, 2) with a newly written method section describing the application of the questionnaire and not the development (in contrast to the above-mentioned publication), 3) with new and different statistical analyses, 4) with new and different Figures and new and different Tables, 5) ultimately resulting in an entirely different and new abstract, introduction, results section, discussion, limitation and future work section, and conclusion.

This work was supported by German Federal Ministry of Education and Research (BMBF) [03IHS109A (MenschINBewegung)].

Additional information

Notes on contributors

Klemens Weigl

Klemens Weigl is a psychologist and applied statistician and completed his doctoral studies in the interdisciplinary field of statistics and psychological research. He is working as a postdoc and conducts empirical research in the domain of traffic, sports, and environmental psychology with a special emphasis on gender, age, and psychometrics.

Marco Steinhauser

Marco Steinhauser is professor, cognitive psychologist and neuroscientist at the Catholic University of Eichstätt-Ingolstadt. He studied psychology at the University of Konstanz, where he also received his PhD. His research interests include cognitive control, performance monitoring, learning, decision making as well as the psychology of driving behavior.

Andreas Riener

Andreas Riener is HCI/VR-professor and founder of the interdisciplinary Human-Computer Interaction Group at Technische Hochschule Ingolstadt. He conducts hypotheses-driven experimental research in HCI/human-technology cooperation in future mobility. Riener is an IEEE, ACM, and HFES member and steering committee chair of ACM AutomotiveUI and chair of the ACM SIGCHI German Chapter.