Leveraging Emerging Data for Traffic Safety Analyses
This project will leverage emerging large-scale vehicle trajectory data to help identify high-risk roadway segments. The analysis will focus on leveraging surrogate safety indicators extracted directly from vehicle movement patterns. Key indicators such as abrupt speed changes, harsh acceleration or braking, and irregular motion signatures are used as proxies for operational risk. These indicators will be aggregated at the roadway-segment level and compared with the “traditional” crash data and crash outcomes on the KABCO scale. This is to help proactively and more quickly identify roadway locations that pose a higher potential safety risk based on data from driving behaviors. Project efforts will address technical workflows for handling high-volume trajectory data, including data preparation, event extraction, spatial segmentation, and identification of behavior-based patterns. This work aims to develop a structured approach for highlighting rural segments with surrogate safety risk indicators of elevated operational risk based on trajectory-derived metrics. As a case study, the efforts will use a dataset obtained a data aggregator for portions of the state of Nevada. The dataset contains over a billion trajectories recorded from millions of unique trips between June 2024 and June 2025. Each record includes spatial, temporal, and motion-related attributes, offering a high-resolution view of driving behavior on roadways. These data can be obtained within days or weeks compared to traditional crash data which typically takes many months to obtain. The outputs of this project include the illustration of the exploratory use of large-scale vehicle trajectory data to identify high-risk roadway segments, and the development of a structured approach to highlight road segments with surrogate safety risk indicators of elevated operational risk based on trajectory-derived metric. This work will highlight how high-resolution telematics data can support early identification of potential safety concerns on road networks. These insights can assist transportation and law enforcement agencies to identify parts of the road network for design and operations review considerations, prioritize law enforcement priorities and practices, allocate resources efficiently, and strengthen data-driven safety management practices. This could also help effect changes in policies, programs, procedures, and practices to improve traffic safety outcomes such as reduce fatalities and injuries.
Language
- English
Project
- Status: Active
- Funding: $155,721.00
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Contract Numbers:
69A3552348323
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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:
2400 6th Street, NW
Washington, DC United States 20059 -
Project Managers:
Bruner, Britain
- Performing Organizations: Las Vegas, NV United States
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Principal Investigators:
Nambisan, Shashi
- Start Date: 20250601
- Expected Completion Date: 20260531
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Case studies; Data analysis; High risk locations; Rural highways; Traffic safety; Vehicle trajectories
- Geographic Terms: Nevada
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01984621
- Record Type: Research project
- Source Agency: Research and Education for Promoting Safety (REPS) University Transportation Center
- Contract Numbers: 69A3552348323
- Files: UTC, RIP
- Created Date: Mar 29 2026 6:53PM