Investigating the spatial heterogeneity of factors influencing speeding-related crash severities using correlated random parameter order models with heterogeneity-in-means

Speeding has been acknowledged as a critical determinant in increasing the risk of crashes and their resulting injury severities. This paper employs Global Moran’s I coefficient and local Getis – Ord G* indexes to systematically account for the spatial distribution feature of speeding-related crashes, study the global spatial pattern of speeding-related crashes, and identify severe crash cluster districts. The findings demonstrate that severe speeding-related crashes within the state of Pennsylvania have a spatial clustering trend, where four crash datasets are extracted from four hotspot districts. Two log-likelihood ratio (LR) tests were conducted to determine whether speeding-related crashes classified by hotspot districts should be modeled separately. The results suggest that separate modeling is necessary. To capture the unobserved heterogeneity, four correlated random parameter order models with heterogeneity in means are employed to explore the factors contributing to crash severity involving at least one vehicle speeding.

• Record URL:
  • https://doi.org/10.1080/19427867.2023.2262201
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
• Supplemental Notes:
  • © 2023 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Yuan, Renteng
  • Ding, Shengxuan
  • Fang, Zhiheng
  • Gu, Xin
  • Xiang, Qiaojun
• Publication Date: 2024-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 989-1001
• Serial:
  • Transportation Letters: The International Journal of Transportation Research
  • Volume: 16
  • Issue Number: 9
  • Publisher: Taylor & Francis
  • ISSN: 1942-7867
  • EISSN: 1942-7875
  • Serial URL: http://www.tandfonline.com/toc/ytrl20/current

Subject/Index Terms

• TRT Terms: Crash causes; Crash severity; Heterogeneity; High risk locations; Spatial analysis; Speeding
• Geographic Terms: Pennsylvania
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01938173
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 27 2024 1:42PM