Modelling risk perception using a dynamic hybrid choice model and brain-imaging data: An application to virtual reality cycling

dc.contributor.authorBogacz, Martyna
dc.contributor.authorHess, Stephane
dc.contributor.authorCalastri, Chiara
dc.contributor.authorChoudhury, Charisma F.
dc.contributor.authorMushtaq, Faisal
dc.contributor.authorAwais, Muhammad
dc.contributor.authorNazemi, Mohsen
dc.contributor.authorvan Eggermond, Michael
dc.contributor.authorErath, Alexander
dc.date.accessioned2025-02-13T09:42:00Z
dc.date.issued2021-12-29
dc.description.abstractRoad risk analysis is one of the key research areas in transport, where the impact of perceived risk on choices, especially in a dynamic setting, has been long recognised. However, due to the lack of dynamic data and the difficulty in capturing risk perception, existing studies typically resort to static and stated approaches to infer the experienced level of risk of individuals. In this paper, we aimed to address this research gap through developing a hybrid choice model that jointly employed dynamic data on cycling behaviour in virtual reality and neural data to evaluate how the fluctuations in momentary risk perception influence the behaviour of cyclists. The results of the developed model confirm our hypotheses, demonstrating that cyclists reduce their speed when approaching a junction as the potential for a collision with passing cars increases. Moreover, the latent component allowed us to establish a link between the neural data, the amplitude of alpha brainwaves, and objective risk measures. In line wi
dc.identifier.doi10.1016/j.trc.2021.103435
dc.identifier.issn0968-090X
dc.identifier.issn1879-2359
dc.identifier.urihttps://irf.fhnw.ch/handle/11654/50128
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofTransportation Research Part C: Emerging Technologies
dc.subjectVirtual reality
dc.subjectEEG
dc.subjectHybrid Choice Model
dc.subjectCycling behaviour
dc.subjectCycling simulator
dc.subject.ddc624 - Ingenieurbau und Umwelttechnik
dc.titleModelling risk perception using a dynamic hybrid choice model and brain-imaging data: An application to virtual reality cycling
dc.type01A - Beitrag in wissenschaftlicher Zeitschrift
dc.volume133
dspace.entity.typePublication
fhnw.InventedHereNo
fhnw.ReviewTypeAnonymous ex ante peer review of a complete publication
fhnw.affiliation.hochschuleHochschule für Architektur, Bau und Geomatik FHNWde_CH
fhnw.affiliation.institutInstitut Bauingenieurwesende_CH
fhnw.openAccessCategoryClosed
fhnw.pagination103435
fhnw.publicationStatePublished
relation.isAuthorOfPublication36c327ea-52a8-4bc5-8005-6d8c47d1eb30
relation.isAuthorOfPublication16f4950d-e8fc-4510-a93b-ffb88d9be41d
relation.isAuthorOfPublication.latestForDiscovery36c327ea-52a8-4bc5-8005-6d8c47d1eb30
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