Smart Sensing and Visualization of Human Mobility Experience

Kurzfassung

My research investigates how human cognitive, emotional, and experiential states can be measured, understood, and visualized across diverse mobility contexts. Whether traveling by public transport [1], driving a car [2], operating a train [3], or cycling through the city, people continuously experience the mobility system not only as infrastructure but as lived experience. Capturing these experiences systematically offers a powerful way to identify where change in the mobility system is most urgent. To this end, I combine valid and reliable subjective measures of travel experience with physiological and contextual data. These include signals from the cardiovascular system, facial expressions, and electrodermal responses, alongside real-world context such as location, time, and traffic conditions. By linking subjective, contextual and physiological indicators, my work aims to model and visualize travel experience dynamically, enabling transport providers, cities, and communities to see mobility from the traveler’s perspective [4]. The broader goal is to make human experience a measurable and actionable component of mobility planning, guiding decisions toward more sustainable and user-centered systems. In the long term, I envision experience measurement that requires minimal user input, grounded in a deep understanding of the relationship between subjective experience and physiological signals. This approach bridges human factors research, psychophysiology, and mobility data science to make the invisible dimensions of travel, such as goal-relevant hindrances, experience compared to expectations, and overall traveler state, visible and usable for design and policy.