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Turner-Fairbank Highway Research Center

 
 
 
 
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Contributing Factors for Focus Crash and Facility Types

Product Type

Research Report

Author

Taha Saleem, Richard Porter, Raghavan Srinivasan, Daniel Carter, Scott Himes, and Thanh Le

Date

Nov-20

Abstract

The main goal of this project was to identify focus crash and facility types (FCFTs) and associated contributing factors to better inform applications of systemic safety improvements. The selection of FCFTs was guided by the use of the Fatality Analysis Reporting System and the Highway Safety Information System (HSIS) databases (NHTSA 2018a; FHWA 2018c). The method used to select potential FCFTs was based on the number of fatal crashes and number of fatal-plus-incapacitating-injury crashes associated with various crash-related variables. A total of 17 FCFTs (8 intersection FCFTs and 9 nonintersection FCFTs) were identified for analysis to identify contributing factors. Three data sources were used to conduct the contributing-factor analysis: crash and roadway inventory from HSIS, climate data from the National Oceanic and Atmospheric Administration, and socioeconomic census data from the U.S. Census Bureau (FHWA 2018c; NOAA 2018; U.S. Census Bureau 2018). For the analysis, the research team used the random-forest method to identify the most predictive variables and then created plots of random forest–predicted crash frequencies as a function of the predictor variables to observe the general trends in the relationships. The research laid out a process for identifying and selecting countermeasures for focus crash types based on contributing factors. The countermeasure guidance focused on traffic and roadway findings. Findings linked to socioeconomic- and weather-related factors showed promise, but there is not yet a significant amount of theory to support or refute the socioeconomic- and weather-related results of this effort.

Link To Research Report

Contributing Factors for Focus Crash and Facility Types

Keywords

Systemic safety
focus crash types
contributing factors
random forests
crash prediction
proven countermeasures


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HSIS Summaries

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