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Using virtual reality and physiological data capture to understand travel behaviour in an autonomous vehicle future

Anciaes, P; Monsuur, F; Kamargianni, M; Chaniotakis, E; (2024) Using virtual reality and physiological data capture to understand travel behaviour in an autonomous vehicle future. In: Proceedings of the 17th International Conference on Travel Behaviour Research. International Association for Travel Behavior Research: Vienna, Austria. Green open access

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Abstract

Virtual reality provides an immersive experience that can realistically represent travel experiences in autonomous vehicles. However, most studies have focused on a single type of vehicle and assessed user reactions to fully autonomous vehicles in comparison with partially autonomous or conventional vehicles. However, perceptions for different types of fully autonomous vehicles (e.g. private vs public transport), and how this might influence modal choice, remain underexamined. In addition, events during the trip might trigger en-route mode-switches. This study aims to address these gaps with the design of a virtual reality covering mode choice and mode switch between autonomous cars and buses, accompanied with physiological measurements. This was deployed in experiments with 90 participants in the Netherlands, Poland, and Greece. The contributions of this work relate to 1) modelling the user experience determinants of choices between private and public autonomous vehicles, 2) measuring physiological reactions to different aspects of travelling in those vehicles, and 3) exploring user views about the realism of virtual reality scenarios.

Type: Proceedings paper
Title: Using virtual reality and physiological data capture to understand travel behaviour in an autonomous vehicle future
Event: 17th International Conference on Travel Behaviour Research
Location: Vienna
Dates: 14 Jul 2024 - 18 Jul 2024
Open access status: An open access version is available from UCL Discovery
Publisher version: https://iatbr2024.univie.ac.at/home/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: autonomous vehicles, mode choice, physiological measurement, travel behaviour, virtual reality
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10212163
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