Eliciting User Needs and Design Requirements for User Experience in Fully Automated Vehicles

ABSTRACT

The introduction of fully automated vehicles (FAVs) will change user experiences (UX) in personal transportation. In order for FAVs to become a life enhancing technology, it is required to design vehicular applications and user interfaces based on users’ expectations. To this end, we investigated user needs and design requirements. First, we elicited design taxonomy and use cases through literature review and trend analysis. Using these materials, expert interviews (N = 9) and focus group interviews (N = 10) were conducted. Through the qualitative analysis, we obtained twelve categories of user needs and devised design requirements based on the updated design taxonomy. While some of them have been an extension of current experiences in manual driving, completely new demands have also emerged within FAVs. Our findings contribute to designing UX in FAVs by satisfying users’ expectations and key values that can guide designers.

Acknowledgments

A part of this study was published as an extended abstract form in the ACM CHI conference: Lee, S. C., Nadri, C., Sanghavi, H., & Jeon, M. (2020, April). Exploring user needs and design requirements in fully automated vehicles. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-9). ACM Press.

Disclosure of potential conflict of interest

The authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Data availability statement

Data available on reasonable request (due to privacy/ethical restrictions).

Additional information

Notes on contributors

Seul Chan Lee

Seul Chan Lee is an Assistant Professor in the Department of Industrial and Systems Engineering at Gyeongsang National University. His research goal is to make systems and devices better based on the theories and methodologies of Human Factors and Human-Computer Interaction, especially in the fields of autonomous vehicle, VR/AR, smart factory.

Chihab Nadri

Chihab Nadri is a PhD student in Industrial and Systems Engineering with a focus on Human Factors. He completed his undergraduate studies in Industrial Engineering at Purdue University in 2017. His research interests include Human Factors, Human-Computer Interaction, Sound and Music Computing, and Automotive User Interfaces.

Harsh Sanghavi

Harsh Sanghavi is a Human Factors Consultant in Carilion Clinic. He received his MS in Industrial and Systems Engineering at Virginia Tech in 2020. His MS thesis is entitled, “Measuring the influence of anger on takeover performance in semi-automated vehicles”.

Myounghoon Jeon

Myounghoon Jeon is an Associate Professor in Industrial and Systems Engineering at Virginia Tech. He received his PhD from Georgia Tech in 2012. His Mind Music Machine Lab conducts research on HCI and HRI with a focus on auditory displays, affective computing, assistive technologies, esthetic computing, and automotive user interfaces.