Age Matters: Investigating Older Drivers' Perception of Level 3 Autonomous Cars as a Heterogeneous Age Group

Srour-Zreik, R., Harvey, M. and Brewster, S. A. (2023) Age Matters: Investigating Older Drivers' Perception of Level 3 Autonomous Cars as a Heterogeneous Age Group. In: 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '23), Ingolstadt, Germany, 18-22 September 2023, pp. 13-18. ISBN 9798400701122 (doi: 10.1145/3581961.3609877)

Abstract

Level 3 autonomous cars may benefit older and younger drivers, but their perspectives on the technology remain understudied. We employed a questionnaire and focus groups to examine the perceived trust, safety, and usefulness of older drivers as a heterogeneous age group (60-80 years old divided into four age groups) and younger (22-25 years old) drivers about Level 3 and the non-driving related tasks (NDRTs) they would perform. The 60-65 group was mostly resistant towards Level 3, whereas the 76-80 group saw it as a chance to stay mobile. All groups were eager to engage with NDRTs, however, prior to gaining trust they would not engage with highly distracting tasks such as reading. The 76-80 group stressed the importance of designing take over requests that consider their decline in physical and cognitive abilities. In this research, we highlight the importance of considering age-related needs in HMI design of Level 3 cars.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Brewster, Professor Stephen and Harvey, Professor Monika and Zreik Srour, Mrs Rawan
• Authors: Srour-Zreik, R., Harvey, M., and Brewster, S. A.
• College/School: College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience; College of Science and Engineering > School of Computing Science
• ISBN: 9798400701122
• Copyright Holders: Copyright © 2023 The Authors
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
303764		EPSRC CDT - Socially Intelligent Artificial Agents	Alessandro Vinciarelli	Engineering and Physical Sciences Research Council (EPSRC)	EP/S02266X/1	Computing Science