Travel experience in public transport: Experience sampling and cardiac activity data for spatial analysis

TL;DR

This study addresses the lack of ecologically valid, real-time multimodal data on public transport travel experiences by collecting geo-referenced data that combine subjective experience sampling with physiological signals. It presents a geo-referenced dataset from 44 adult participants traveling a predefined 15 km intermodal route (tram, bus, and train) with GPS, ECG/HR data, HRV, and real-time reports of travel stress, satisfaction, emotions, and events, along with demographic information. The authors visualize and analyze the data via an interactive experience map and hotspot analysis using the $Getis-Ord Gi^*$ statistic to identify stress hot spots and satisfaction cold spots, complemented by permutation tests to assess cardiac activity differences. Despite the small, geographically limited sample, the dataset enables integrated analysis of subjective, physiological, and contextual factors to inform transportation research and mobility planning; the data and code are openly available (CC-BY 4.0) to support replication and further methodological development.

Abstract

The transportation sector has the potential to enable a greener future if aligned with increasing mobility needs. Making public transport an attractive alternative to individual transportation requires real-world data to investigate reasons and indicators of positive and negative travel experiences. These experiences manifest not only in subjective evaluations but also in physiological reactions like cardiac activity. We present a geo-referenced dataset where participants wore electrocardiograms and reported real-time stress, satisfaction, events, and emotions while traveling by tram, train, and bus. An interactive experience map helps to visually explore the data, with benchmark analyses identifying significant stress hot spots and satisfaction cold spots during journeys. Events and emotions in these spots highlight positive and negative travel experiences in an ecologically valid setting. Data on age and self-identified gender provide insights into differences between user groups. Despite including only 44 participants, the dataset offers a valuable foundation for transportation researchers and mobility providers to combine qualitative and quantitative methods for identifying public transportation users' needs.

Figures (10)

• Figure 1: Study procedure.
• Figure 2: Travel modes on the route.
• Figure 3: Event categories reported top: overall, middle: in the stress hot spot and bottom: the satisfaction cold spot.
• Figure 4: Travel satisfaction by event.
• Figure 5: Travel satisfaction (left) and stress (right) by day (upper plots) and year (lower plots). Blue numbers indicate the number of observations in the time bin.