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Title:

Crash Prediction Modeling for Curved Segments of Rural Two-lane Two-way Highways in Utah
Cover of Crash Prediction Modeling for Curved Segments of Rural Two-lane Two-way Highways in Utah

Accession Number:

01592111

Record Type:

Component

Abstract:

Crash prediction models for curved segments of rural two-lane two-way highways in the state of Utah were developed. The modeling effort included the calibration of the predictive model found in the Highway Safety Manual (HSM) as well as the development of Utah-specific models developed using negative binomial regression. The data for these models came from randomly sampled curved segments in Utah, with crash data coming from years 2008-2012. The total number of randomly sampled curved segments was 1,495. For this research, two sample periods were used: a three-year period from 2010 to 2012 and a five-year period from 2008 to 2012. The calibration factor for the HSM predictive model was determined to be 1.50 for the three-year period and 1.60 for the five-year period. A negative binomial model was used to develop Utah-specific crash prediction models based on both the three-year and five-year sample periods. The independent variables used for negative binomial regression included the same set of variables used in the HSM predictive model along with other variables such as speed limit and truck traffic that were considered to have a significant effect on potential crash occurrence. The significant variables were found to be average annual daily traffic, segment length, total truck percentage, and curve radius. The main benefit of the Utah-specific crash prediction models is that they provide a reasonable level of accuracy for crash prediction yet only require four variables.

Supplemental Notes:

This paper was sponsored by TRB committee ANB25 Standing Committee on Highway Safety Performance.

Monograph Accession #:

01584066

Report/Paper Numbers:

16-1859

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Knecht, Casey S
Saito, Mitsuru
Schultz, Grant G

Pagination:

16p

Publication Date:

2016

Conference:

Transportation Research Board 95th Annual Meeting

Location: Washington DC, United States
Date: 2016-1-10 to 2016-1-14
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Identifier Terms:

Highway Capacity Manual

Geographic Terms:

Utah

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors; I72: Traffic and Transport Planning; I82: Accidents and Transport Infrastructure

Source Data:

Transportation Research Board Annual Meeting 2016 Paper #16-1859

Files:

PRP, TRIS, TRB, ATRI

Created Date:

Jan 12 2016 4:48PM