Cycling in virtual reality: modelling behaviour in an immersive environment

ABSTRACT

Immersive technologies in transport research are gaining popularity, allowing for data collection in a controlled dynamic setting. Nonetheless, their ecological validity is still to be established hence their use in mathematical modelling in a transport setting has been scarce. We aim to fill this gap by conducting a study of cycling behaviour where non-immersive and immersive presentation methods are used in a virtual reality setting. The results confirm our hypothesis that participants behave differently when shown a choice scenario in non-immersive and immersive settings. In particular, cycling in an immersive setting is characterised by a higher degree of engagement. We also captured neural activity during task performance. We focussed on oscillations in the alpha (α) band where we found increased suppression in this signal in response to the immersive condition relative to the non-immersive. These results complement the behavioural findings and indicate that immersive environments may increase levels of task-engagement.

KEYWORDS:

• Road user behaviour
• risk
• cycling
• virtual reality
• EEG

Disclosure statement

The authors declare no conflict of interest.

Supplementary material

Supplemental data for this article can be accessed here.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1. The explanatory variables tested in the model, both with and without interactions, include age groups (18–24, 25–29, 30–39, 40–49, 50–59 years and above 60 years old), education levels (O level, A level, vocational qualifications, undergraduate, Masters and postgraduate doctoral degree), marital status, number of children (zero, one, and more than 2 children), and being an active car driver.

2. Similar figures for the road scenarios are available in the supplementary file at: www.stephanehess.me.uk/papers/Bogacz_et_al_2020_online_appendix.pdf.

Additional information

Funding

Martyna Bogacz, Stephane Hess, Charisma Choudhury, and Chiara Calastri acknowledge the support of the European Research Council through the consolidator grant 615596-DECISIONS.