Evaluating the Cumulative Impact of Environmental Conditions on Stress Levels in Micromobility Users: An AI-Driven Multimodal Approach
Micromobility solutions, such as e-scooters and bicycles, are increasingly utilized in urban transportation, providing flexible and sustainable mobility options. However, micromobility users face significant exposure to environmental stressors, including air pollutants emitted by motorized traffic. While prior studies have explored the physiological effects of transportation emissions, the psychological impacts, particularly stress, remain underexplored. This study aims to bridge this gap by developing an AI-driven predictive model that evaluates the cumulative impact of transportation-related air pollutants on stress levels in micromobility users. By integrating wearable sensor data (e.g., electrodermal activity, heart rate variability, and skin temperature), air pollutant concentration data (e.g., PM2.5, NOx, and CO), and spatial context data (e.g., GPS and accelerometer readings), this research will leverage Temporal Fusion Transformer (TFT) models to predict real-time stress levels and generate stress heatmaps. The results will inform policymakers, transportation planners, and public health officials, contributing to more sustainable and inclusive urban transportation systems. Additionally, the project will provide hands-on research opportunities for students, fostering workforce development in AI-driven transportation health studies.
Language
- English
Project
- Status: Active
- Funding: $112,000.00
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Contract Numbers:
69A3552348329
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
1111 Rellis Parkway
Bryan, Texas United States 77807 -
Project Managers:
Ocon, Monica
- Performing Organizations: El Paso, TX United States
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Principal Investigators:
Kim, Jaeyoon
- Start Date: 20250301
- Expected Completion Date: 20260831
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
- Source Data: 02-05-UTEP
Subject/Index Terms
- TRT Terms: Air pollution; Artificial intelligence; Cyclists; Micromobility; Pedestrians; Physiological stress; Predictive models
- Subject Areas: Data and Information Technology; Environment; Pedestrians and Bicyclists; Research;
Filing Info
- Accession Number: 01976239
- Record Type: Research project
- Source Agency: Center for Advancing Research in Transportation Emissions, Energy, and Health (CARTEEH)
- Contract Numbers: 69A3552348329
- Files: UTC, RIP
- Created Date: Jan 13 2026 3:55PM