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Non-driving related tasks and journey types for future autonomous vehicle owners

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journal contribution
posted on 2022-07-11, 09:06 authored by Chris Wilson, Diane GyiDiane Gyi, Andrew MorrisAndrew Morris, Robert Bateman, Hiroyuki Tanaka
Highly automated vehicles (AVs) have the potential to improve the journey experience for all users by allowing them to partake in Non-Driving Related Tasks (NDRTs). Using a 42-question online survey of drivers (n = 1378, 59% males, 40% females), and in-depth interviews (n = 18, 56% males, 44% females), this study investigated NDRTs and the motivations for private ownership of highly automated vehicles (AVs). 42% of participants were identified to be more likely to own an AV and, believed that they were safer, would reduce congestion and the risk of accidents. There was also a genuine desire to actively fill the non-driving time being productive or using a device rather than passive tasks such as listening to music or watching their surroundings. Commuting was reported to be the most likely journey type amongst those more likely to own an AV. The commuting journey also showed the most diverse range of NDRTs including social (e.g., conversation, playing games), wellbeing (e.g., eating a meal, sleep), leisure (e.g., watching a video), and being productive (e.g., working on a laptop). This study provides insights into NDRTs to inform future interior vehicle design and motivations for owning highly automated vehicles.

Funding

DTP 2018-19 Loughborough University

Engineering and Physical Sciences Research Council

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Nissan Motor Co. Ltd

History

School

  • Design and Creative Arts

Department

  • Design

Published in

Transportation Research Part F: Traffic Psychology and Behaviour

Volume

85

Pages

150 - 160

Publisher

Elsevier BV

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (CC BY-NC-ND 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2022-01-04

Publication date

2022-01-21

Copyright date

2022

ISSN

1369-8478

Language

  • en

Depositor

Chris Wilson. Deposit date: 21 January 2022

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