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


Start Date
July 1, 2023

End Date
June 30, 2024

Focus Areas
Data Analytics, Modeling and Simulation

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)