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

Area of Science:

• Transportation science
• Human-computer interaction
• Psychophysiology

Background:

• Public transportation is crucial for sustainable mobility but faces challenges in user experience.
• Understanding user satisfaction and stress is key to making public transport more appealing than private vehicles.

Purpose of the Study:

• To create a geo-referenced dataset linking physiological stress, subjective experiences, and travel events during public transport use.
• To identify specific 'hot spots' and 'cold spots' of stress and satisfaction within public transport journeys.
• To provide a foundation for improving public transportation based on user needs.

Main Methods:

• Collected real-time data including electrocardiograms (ECG), stress, satisfaction, events, and emotions from participants using trams, trains, and buses.
• Developed an interactive experience map for visualizing geo-referenced data.
• Conducted benchmark analyses to identify significant stress and satisfaction patterns.

Main Results:

• Identified specific locations and journey segments associated with high stress and low satisfaction ('hot spots' and 'cold spots').
• Linked reported events and emotions to these identified travel experience zones.
• Analyzed data considering age and gender to explore user group differences.

Conclusions:

• The dataset provides a novel, ecologically valid foundation for understanding public transport user needs.
• Combining qualitative and quantitative data offers valuable insights for transportation researchers and providers.
• Targeted interventions in identified 'hot spots' can significantly improve the public transport experience.