Featured Project

Commercial Vehicle Summit

Best Practices for Advancing Safety Through Partnerships Among Law Enforcement and State Driver’s License Agencies with Universities

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Questions or Comments?

We love to talk ‘traffic safety’!
UMassSafe@umass.edu

Highlights

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Massachusetts E-Crash Manual

UMassSafe is creating a E-Crash Manual, to provide guidance on crash reporting including how the data is used, data dictionary, coding guide, guidance on new crash report fields, validation rules etc.

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Crash Data Audit

In order to improve crash data quality, UMassSafe is coordinating an investigation of police crash reports to assess current obstacles and future performance measures and monitoring criteria.

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Phone Down, Just Drive

UMassSafe is working with the Massachusetts State Police Commercial Vehicle Enforcement Section on a project to combat distracted driving among commercial motor vehicle (CMV) drivers.

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Archive

UMassSafe

UMassSafe is a multidisciplinary traffic safety research program housed in the University of Massachusetts Transportation Center in the College of Engineering at the University of Massachusetts Amherst. Working for many state and federal agencies, UMassSafe collects and analyzes crash related data, provides online data access, develops training materials and examines data quality challenges within the databases, providing recommendations for improvements.


Safety Data Warehouse

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Data Warehouse

The UMassSafe Traffic Safety Data Warehouse has been developed as a tool for maximizing the use of highway safety data. The data warehouse includes “administrative” datasets collected by state agencies and other organizations; including crash, citation, roadway inventory, etc. Currently, 14 such datasets are housed in the UMassSafe traffic Safety Data Warehouse, with over 16 years of data available. Additionally, the analysis includes linked datasets created using the aforementioned administrative databases. Crash, citation, hospital, death certificate, and roadway inventory data have been linked using advanced statistical methodologies to create a single dataset that allows analysts to consider the comprehensive crash experience; including driver behavior, crash characteristics, roadway environment, and crash.

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