Anciaes, Paulo; Chaniotakis, Emmanouil; (2025) Emerging methods to collect big data on travel experiences. In: Antoniou, Constantinos and Dimitriou, Loukas and Pereira, Francisco, (eds.) Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling, Volume 2. Elsevier: Amsterdam, Netherlands. (In press).

Text Anciaes and Chaniotakis 2025 Emerging methods to collect big data on travel experiences.pdf - Accepted Version Access restricted to UCL open access staff Download (619kB)

Abstract

The emergence of flexible and low-cost solutions for the observation of travel experiences is changing the data collection landscape. Experiments traditionally focusing on the collection of user responses are increasingly enhanced through multimodal data collection methods, which use different data collection instruments and produce big data. This chapter examines data collection using electroencephalography (EEG) with virtual reality for collecting big data on passenger travel experiences, assessing the scope for using these methods to produce high-quality datasets. Through a case study, we analyse the potential of EEG to detect reactions to different stimuli related to trips in autonomous cars and buses and the potential of virtual reality to provide participants with those stimuli. We assess whether participants notice the relevant attributes of virtual scenarios and if the experience of a virtual vehicle differs from the experience of a real one. We also provide detail on data collection procedures that tend to be omitted from academic papers but should be more extensively documented, to support further studies, including technical and organisational issues, ethical aspects, and participant recruitment.

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