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.

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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.

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