Relating emotions, psychophysiological indicators and context in public transport trips: Case study and a joint framework for data collection and analysis
Document Type
Journal Article
Publication Date
2023
Subject Area
place - south america, technology - passenger information, planning - methods
Keywords
Public transport, psychophysiological indicators, emotions, user satisfaction
Abstract
This study proposes an experimental framework for collecting on-board data on users' emotions, psychophysiological indicators, and context, to characterize their experience in a granular, scalable, non-intrusive, and ecological way. To gather emotions data, clustering techniques are used to adapt Russell's circumplex model to a transport framework, allowing data to be collected on-board using a smartphone application. For psychophysiological indicators, a specially designed portable PCB (Biomonitor 2.0) is used to record heart rate, heart rate variation, skin temperature, and electrodermal activity with high frequency and fidelity. Context information is collected using ambient sensors and a smartphone application. A proof-of-concept case study is conducted on 44 engineering students traveling for 2.5 hours on various public transport modes in Santiago, Chile, including an autonomous vehicle. The results show that the framework is feasible, and that emotions data can be effectively related to granular records of psychophysiological indicators and context using a discrete choice model. This study sets a precedent for future research to incorporate new granular public transport user satisfaction indicators based on emotions inferred from psychophysiological data and detect causal factors related to users' physical, emotional, and cognitive state.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
Barría, C., Guevara, C. A., Jimenez-Molina, A., & Seriani, S. (2023). Relating emotions, psychophysiological indicators and context in public transport trips: case study and a joint framework for data collection and analysis. Transportation Research Part F: Traffic Psychology and Behaviour, 95, 418-431.
Comments
Transportation Research Part F Home Page:
http://www.sciencedirect.com/science/journal/13698478