A New Approach for Identifying Safety Improvement Sites on Rural Highways: A Validation Study

Details

• Creators:
  Dhakal, Bishal ; Al-Kaisy, Ahmed
• Corporate Creators:
  Montana State University (Bozeman, Mont.). Department of Civil Engineering
• Contributors:
  Xie, Suchao
• Subject/TRT Terms:
  Crashes Fatalities Highway Safety Highway Safety Improvement Programs Networks Network Screening Predictive Models Rural Roads Safety Ranking (Statistics) Regression Analysis Roads Rural Transportation Safety Programs

  More +
• DOI:
  https://doi.org/10.3390/app14041413
• Resource Type:
  Journal Article
• Right Statement:
  Open access
• Geographical Coverage:
  Oregon;United States
• Corporate Publisher:
  MDPI
• Abstract:
  The research presented in this paper examines a new proposed approach for identifying safety improvement sites on rural highways. Unlike conventional approaches, the proposed approach does not require crash history, but rather utilizes classified variables for traffic volume, geometric features, and roadside characteristics that do not require access to exact data or extensive technical expertise. The research validates the performance of the proposed approach using field data from a large sample of rural two-lane highway segments in the state of Oregon including traffic, roadway, and crash data. A mathematical model for the prediction of the EB expected number of crashes using multivariate regression analysis is developed and used as the network screening criterion. The model’s independent variables include roadway geometry, roadside characteristics, and traffic exposure, while the dependent variable is the EB expected number of crashes. Using observed crash history as a reference, the performance of the proposed approach was compared to two of the well-established methods in practice, namely, the Empirical Bayes (EB) and the potential for safety improvement (PSI) methods. The study results suggest that by using crash density for highway segments, the performance of the proposed method was lower than that of the EB and PSI methods. This is despite the high R-square value of the predictive model used in the proposed method. However, when using crash frequencies for highway segments, the performance of the proposed method was found comparable to the well-established EB and PSI methods.
• Content Notes:
  This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Please cite this article as: Dhakal, B.; Al-Kaisy, A. A New Approach for Identifying Safety Improvement Sites on Rural Highways: A Validation Study. Appl.Sci. 2024, 14, 1413. https://doi.org/10.3390/app14041413.
• Format:
  PDF
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:b38c8507b403b09936e4dcfae86c24f164cdeda4cdd42afaa978220e0a8b8c0ef67391c9c33a8e6f706d8a622135adef6d1d06d1becdbfa07351f5ac31c8905d
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/78504/dot_78504_DS1.pdf
• File Type:
  [PDF - 3.04 MB ]