This project is dedicated to enhancing pedestrian and bicyclist safety by using advanced computer vision techniques and spatial analytics. Leveraging satellite imagery and deep learning models, the project will gather and analyze data on pedestrian and bicyclist facilities and streetlight conditions to predict injury risks and identify high-risk areas. Key objectives include developing algorithms for data extraction, validating models for accurate prediction of accident hotspots, and providing actionable safety recommendations. This project’s findings will be documented in a comprehensive technical report, which will detail methodologies and offer insights to inform future safety enhancements and research. This initiative not only aims to improve transportation safety but also serves as an educational resource, promoting further academic and practical exploration in non-motorist safety.
Project Details
Project ID
CPBS 23UWM02
Status
Ongoing
Start Date
July 1, 2023
End Date
June 30, 2024
Focus Areas
Data Analytics, Modeling and Simulation
Safety
Sponsors
US Dept Of Transportation
Research Centers
Institute for Physical Infrastructure and Transportation (IPIT)
Center for Pedestrian and Bicyclist Safety (CPBS)
Principal Investigator
Qin, Xiao
Director, Institute for Physical Infrastructure and Transportation (IPIT)
Professor, Civil and Environmental Engineering University of Wisconsin-Milwaukee
Co-Principal Investigator
Schneider, Robert; Sayed, Md
Associate Professor, Department of Urban Planning University of Wisconsin-Milwaukee; Research Associate, Institute for Physical Infrastructure and Transportation (IPIT)