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SDI

Rural Speed Safety Pilot Project

 

Overview

Current crash prediction methods, such as those in the first edition of the Highway Safety Manual (HSM) use traffic volume data along with geometric characteristics to predict the annual average crash frequency of roadway segments and intersections. One limitation of the HSM is the omission of speed-related factors from all aspects of safety predictive methods. Recent research has made little substantive progress in incorporating speed-related factors into crash...

State and Local Government Data Analysis Tools for Roadway Safety - Notice of Funding Opportunity

 

In November 2019, USDOT released a NOFO titled “State and Local Government Data Analysis Tools for Roadway Safety ,” which focused on building the capacity of State, local, and tribal governments to use innovative data tools and information to improve roadway safety. The NOFO made available over $3 million for up to 12 awards. Eligible applicants included State or local governments, metropolitan planning organizations (MPO) and regional governments, other political subdivisions of a...

SDI Waze Project Summary Documents

The U.S. DOT Safety Data Initiative (SDI) aims to leverage and integrate datasets, and use advanced analytical tools and compelling visualizations to provide new insights to identify and address surface transportation safety risks. Crowdsourced mobile applications from the private sector—such as Waze—offer real-time and historical data about roadway conditions, including user-reported crashes. Funded by the SDI, Volpe Center researchers are integrating these new data sources with other...