Identification of Crash Causal Factors: Effects of Sample Data Size

This paper utilizes data for a county to identify the main crash contributing factors for several counties. For this analysis, the counties of Arkansas are categorized based on crash frequency and crash severity index into five categories. For each category, sample crash data for a county or a group of counties and the remaining data (for several counties) are analyzed and based on the results crash contributing factors are identified. The selection of sample data for each category is based in the order of highest crash severity index (CSI) or highest crash frequency. The crash contributing factors are identified using multinomial logistic regression (MLR). The results indicate that most of the factors identified within each category were also identified for the sample data. Sample size, however, changed for each category. This paper presents the effects of this difference in sample size and the effect of categorization of counties based on crash severity index and crash frequency in identification of crash contributing factors. This study will help better allocate funds by the departments of transportation to identify factors that are positively associated with crash severity. Three years of rural two-lane highway crash data from Arkansas is used in this analysis. Results indicate that division of counties based on crash frequency and identification of crash contributing factors using MLR would ensure better allocation of funds. Rural two-lane undivided highways were selected for analysis as severe crashes are common on these highways.

• Record URL:
  • http://onlinepubs.trb.org/onlinepubs/conferences/2011/RSS/2/Manepalli,U.pdf
• 
• Supplemental Notes:
  • Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
• Corporate Authors:

  Transportation Research Board

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• Authors:
  • Manepalli, Uday R R
  • Bham, Ghulam H
• Conference:
  • 3rd International Conference on Road Safety and Simulation
  • Location: Indianapolis Indiana, United States
  • Date: 2011-9-14 to 2011-9-16
• Publication Date: 2011

Language

• English

Media Info

• Media Type: Digital/other
• Features: Maps; References; Tables;
• Pagination: 18p
• Monograph Title: 3rd International Conference on Road Safety and Simulation

Subject/Index Terms

• TRT Terms: Crash data; Crash severity; High risk locations; Logistic regression analysis; Rural areas; Two lane highways
• Uncontrolled Terms: Causal factors
• Geographic Terms: Arkansas
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; I81: Accident Statistics;

Filing Info

• Accession Number: 01504360
• Record Type: Publication
• Files: TRIS, TRB, ATRI
• Created Date: Jan 24 2014 2:29PM