ERI: From Data to Design: Enhancing Pedestrian Infrastructure for Well-Being through Mobile Sensing and Experience Sampling in the Wild

This Engineering Research Initiation (ERI) award will advance research in understanding the impact of pedestrian infrastructure on various aspects of well-being, including emotions, stress, and cognitive abilities. Pedestrian infrastructure plays a crucial role in influencing well-being metrics and can either encourage or discourage walking as a mode of transportation, even in areas with safe walkways.

By employing innovative human sensing techniques, this project will establish a comprehensive pedestrian data collection framework. Through collaboration with practitioners and road users in focus groups, alternative infrastructure designs will be developed and evaluated using immersive virtual environments. This research bridges the gap between real-world data, infrastructure design, and behavioral aspects of walking adoption.

This project has the potential to drive positive changes in urban planning, design, and public policy through data-driven insights. The resulting naturalistic dataset can benefit research in various disciplines such as behavioral science, psychology, and computer science. This project will bring opportunities for graduate and undergraduate researchers as well as Ph.D. students from all walks of life to learn, grow, become trained in an academic environment, and contribute to the science of human-centered infrastructure design.

Current pedestrian research predominantly concentrates on safety, leaving a substantial gap in well-being-related data, especially in real-world settings. Well-being metrics while including physical aspects, encompass different parameters such as perceived stress, valence, and arousal and emotion metrics, creativity, social interactions, and cognitive abilities among other factors.

The first component of this study introduces a novel naturalistic framework to comprehensively monitor and collect data on various aspects of pedestrian well-being. This framework intelligently integrates data from mobile sensing devices, such as smartwatches, with in-the-wild experience sampling techniques through a specifically designed app. In the second component, this framework is applied in a suburban area to create a first-of-its-kind, longitudinal, and naturalistic dataset, addressing the scarcity of pedestrian well-being data.

This component will yield quantitative and qualitative models connecting infrastructural elements with real-world pedestrian well-being metrics, employing observational studies and computer vision techniques. The project will develop heatmaps highlighting regions associated with different well-being metrics that will be shared with broader research communities.

The third component will result in preliminary guidelines for identifying design flaws in pedestrian infrastructure considering human well-being. Lastly, Immersive Virtual Environments will be utilized to assess alternative designs objectively and subjectively, closing the loop in enhancing pedestrian infrastructure prior to construction.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.