Evaluating Urban Bicycle Infrastructures through Intersubjectivity of Stress Sensations Derived from Physiological Measurements

Abstract

A continued shift of human mobility towards sustainable and active mobility modes is a major concern for society in order to reduce the human contribution to climate change as well as to improve liveability and health in urban environments. For this change to succeed, non-motorized modes of transport need to become more attractive. Cycling can play a substantial role for short to medium distances, but perceived safety and stress levels are still major concerns for cyclists. Therefore, a quantitative assessment of cyclists' stress sensations constitutes a valuable input for urban planning and for optimized routing providing low-stress routes. This paper aims to investigate stress sensations of cyclists through quantifying physiological measurements and their spatial correlation as an intersubjective indicator for perceived bikeability. We developed an automated workflow for stress detection and aggregation, and validated it in a case study in the city of Salzburg, Austria. Our results show that measured stress generally matches reported stress perception and can thus be considered a valuable addition to mobility planning processes.

An Interdisciplinary Mixed-Methods Approach to Analyzing Urban Spaces: The Case of Urban Walkability and Bikeability

“…The rapid development of high-performance sensor technology has led to small and flexible wearable biosensors that allow human emotions (based on individual perceptions) to be captured by measuring physiological parameters. These sensors are useful for evaluating the walkability and bikeability of cities better than using self-reported impressions in post-hoc interviews [ 17 , 19 , 20 ]. Simple and direct sensations, together with more complex emotions, are reflected in physiological parameters that can be registered in real-time, such as ST, GSR, or HRV [ 21 , 22 ].…”

“…In conclusion, most previous studies used a limited set of methods (mostly analysis of measurements from wearables and/or questionnaires at the end of a field test), and all investigated the variations in GSR for detecting stress [ 44 , 45 , 46 ]. The one exception is [ 17 ], who recorded both GSR and ST and detected stress through a specific algorithm they had developed. Birenboim (2019) also used wearables and questionnaires but scrutinized the variations of GSR and HR to detect stress [ 35 ].…”

“…At the same time, human sensor data, i.e., measurements from physiological sensors to infer citizens’ emotion-psychological states like stress, relaxation, wellbeing, safety or distinct emotions, have increasingly sparked interest in urban research. Conclusions can now be drawn on urban conditions like walkability (a city’s attractiveness or its opportunity for walking) [ 15 , 16 ], bikeability (a city’s attractiveness or its opportunity for bicycling) [ 17 ], urban safety, and other aspects based on human experiences. Inferring emotion-psychological processes from physiological measurements is still challenging—and, surprisingly, underrepresented in the scientific literature.…”

Human-Centric Data Science for Urban Studies

“…Four issue papers focused on cycling, exploring the stress challenges experienced in urban environments by the vulnerable demographic of cyclists [49][50][51][52]. Werner et al [49] and Pajarito and Gould [52] focused on improving livability through cycling, investigating cyclists' stress sensations through route analysis. Pritchard et al [50] also studied cycling stress, but considered a mix of indicators for assessing bicycle level of service.…”

Developing a Citizen Social Science approach to understand urban stress and promote wellbeing in urban communities

“…Zeile et al used the 'People as sensors' mobile application to gather this data alongside subjectively reported emotions, and analysed it spatially to develop maps of distinct emotions such as fear and anger, to inform urban planning on cycling safety. Similarly, Werner et al (2019) have developed a mixed-methods approach to evaluate urban bicycle infrastructures, involving biosensors, an eDiary app and qualitative questionnaires.…”