The Development of Crash Modification Factors: Highway Safety Statistical Paper Synthesis

Donnell, Eric T.; Hanks, Ephraim; Porter, Richard J.; Cook, Lawrence; Srinivasan, Raghavan; Li, Fan; Nguyen, Maggie; Eccles, Kimberly A.; United States. Federal Highway Administration. Office of Safety Research and Development

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The Development of Crash Modification Factors: Highway Safety Statistical Paper Synthesis

2020-11-01
By Donnell, Eric T. ; Hanks, Ephraim ; Porter, Richard J. ; ...

[PDF-2.87 MB]

English

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Details:

Creators:

Donnell, Eric T. ; Hanks, Ephraim ; Porter, Richard J. ; Cook, Lawrence ; Srinivasan, Raghavan ; ... More +

Donnell, Eric T. ; Hanks, Ephraim ; Porter, Richard J. ; Cook, Lawrence ; Srinivasan, Raghavan ; Li, Fan ; Nguyen, Maggie ; Eccles, Kimberly A. Less -
Corporate Creators:

United States. Federal Highway Administration. Office of Safety Research and Development
Contributors:

Amjadi, Roya
Corporate Contributors:

VHB/Vanasse Hangen Brustlin, Inc.
Subject/TRT Terms:

[+]

Causal Inference CODES Crash Modification Factors Highway Safety Probabilistic Link Propensity Score Regression Analysis Regression Trees Statistical Analysis
Publication/ Report Number:

FHWA-HRT-20-069
Resource Type:

Tech Report
Geographical Coverage:

United States
Contracting Officer:

Amjadi, Roya
Corporate Publisher:

United States. Federal Highway Administration. Office of Safety Research and Development
Abstract:

The transportation-engineering community is transforming by integrating quantitative methods into the task development process. This report identifies opportunities to better understand the relationships between road safety and factors that affect traffic-crash occurrence and severity. In this report, current statistical-analysis methods and data sources used in road-safety research are compared with alternative methods and data sources. Causal inference methods are compared to observational before–after methods to develop safety-effect estimates of centerline and edgeline rumble strips. Regression trees and Random ForestsTM are compared to count regression methods to predict crash frequencies on freeways. Road-safety performance estimates using the Crash Outcomes Data Evaluation System are also discussed, with a focus on opportunities to link hospital and crash data to understand the relationship between crashes and site-specific contributing factors. Methods to account for underreporting in crash-frequency models are also described.
Format:

PDF
Funding:

DTFH61-13-D-00001
Collection(s):

Federal Highway Administration
Main Document Checksum:

[+]

urn:sha256:07f4e15206222c82814eeff3ec5c8a304e88902cac9881726c2d4cb212d0169c
Download URL:

https://rosap.ntl.bts.gov/view/dot/54591/dot_54591_DS1.pdf
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The Development of Crash Modification Factors: Highway Safety Statistical Paper Synthesis

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