Project: #584 Analysis of Contributing Factors in Crashes Involving Electric Vehicles and Vehicles with Warning Systems and Level 1 Automated Features: A State Level Analysis Progress Report - Reporting Period Ending: Aug. 31, 2026 Principal Investigator: Corey Harper Status: Overdue Project Start Date: July 1, 2025 End Date: June 30, 2026 Research Type: None Grant Type: Research Advanced Grant Program: US DOT BIL, Safety21, 2023 - 2028 (4811) Grant Cycle: Safety21 : 25-26 Progress Report (Last Updated: Aug. 31, 2026, 8:45 a.m.) % Project Completed to Date: None % Grant Award Expended: None % Match Expended & Document: None USDOT Requirements Accomplishments The purpose of this research is to assess how automated driving systems as well as vehicle electrification are affecting road safety. This project has supported the training of one graduate student who is developing machine learning approaches to better understand the factors contributing to crashes involving ADAS and EVs. The proposed project will create an environment that links local and state government to each other and to university students. Working closely with the City of Pittsburgh and PennDOT throughout this project, will provide an opportunity for students to network and learn the missions and goals of these organizations, providing them with pathways to obtain internships and higher paying jobs after graduation (e.g., Director of Public Policy). Over the past few months we have collected and analyzed national ADAS crash data and developed a framework to classify crashes and interpret contributing factors. We have published this work in Accident Analysis and Prevention. Other dissemination activities include preparing a paper to submit to a journal and conference presentation at 2027 TRB. Collaborations: As a part of this project we have met with representatives from PennDOT (state transportation agency) and the City of Pittsburgh (local transportation agency). Impacts The outputs of this project will help NHTSA, USDOT, and car manufacturers better understand the infrastructure, sensor improvements, and policies needed to improve traffic safety with higher ADAS and EV penetration. This project will also increase our knowledge about what the contributing factors are for EV and ADAS crashes and those policies to improve road safety. Practical applications include placing greater emphasis in scenario-based testing for combinations involving moderate and high pre-crash speeds, frontal contact, fixed-object crashes, light-to-medium duty vehicle crash partners, and late-night conditions. These findings may help manufacturers refine speed-aware system-use guidance, driver warnings, and operational design constraints for Level 2 ADAS-equipped vehicles. We have also made this framework open source so that other researchers and practitioners can make use of our model. https://github.com/wjcdavid/adas-injury-statistical-analysis/tree/main Other New methodologies, policy recommendations, and tools to assess the contributing factors in ADAS and EV crashes. Outcomes New Partners N/A Issues N/A