Effects of geometric attributes of horizontal and sag vertical curve combinations on freeway crash frequency

The geometric design of the combinations of horizontal and sag vertical curves (sag combinations or sag combined curves) is vital to road safety. However, there is little research that investigates the safety effects of their geometric attributes based on the analysis of real-world crash data. To this end, the crash, traffic, geometric design, and roadway configuration data are collected from 157 sag combinations on six freeways in Washington State, during 2011–2017. Poisson, negative binomial (NB), hierarchical Poisson, and hierarchical NB models are developed for analyzing the crash frequency of sag combinations. The models are estimated and compared in the context of Bayesian inference. The results indicate that significant over-dispersion and cross-group heterogeneity exist in the crash data and that the hierarchical NB model yields the best overall performance. The parameter estimates show that: five geometric attributes, including horizontal curvature, vertical curvature, departure grade, the ratio of horizontal curvature to vertical curvature, and the layout of front dislocation, have significant effects on the crash frequency of sag combinations. Freeway section length, annual average daily traffic, and speed limits are also important predictors of crash frequency. The analysis results and the proposed model are useful for evaluating the safety performance of freeway sag combinations and optimizing their geometric design based on substantive safety evaluation.

• Record URL:
  • https://doi.org/10.1016/j.aap.2023.107056
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0001457523001033
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Wang, Xiaofei
  • Li, Siyu
  • Li, Xinwei
  • Wang, Yinhai
  • Zeng, Qiang
• Publication Date: 2023-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 107056
• Serial:
  • Accident Analysis & Prevention
  • Volume: 186
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Crash rates; Freeways; Geometric segments; Highway curves; Predictive models
• Geographic Terms: Washington (State)
• Subject Areas: Design; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01880761
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 24 2023 9:51AM