Spatial Bayesian Modelling of Road Accidents at the Local Authority Level

Conventional regression methods for modeling the number of road accidents at the district or county level treat the numbers of road accidents for different observational units as independent. Such models seldom take account of any spatial effects, and therefore may not fully account for in he spatial variation in the response variable – residuals from the model may be spatially autocorrelated. This paper shows how the hierarchical Bayesian model used in disease mapping can also be used to model road accidents aggregated at the local authority level in England. Models with and without spatial effects are compared. Various neighborhood relationships are considered, based on both geographical proximity and the structure of the road network. Moran’s I, a standard measure of spatial autocorrelation, is used to illustrate how the inclusion of spatial effects reduces the residual spatial autocorrelation, and to investigate how the inclusion of spatial effects reduces the residual spatial autocorrelation, and to investigate different spatial weighting schemes. Data obtained from previous research studies are used to fit the models. Results from the models are plotted on a map of England at the desired level created in AchView 3.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780080450926
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Corporate Authors:

  Elsevier

  Linacre House, Jordan Hill
  Oxford,   United Kingdom  OX2 8DP
• Authors:
  • Liu, Yilin
  • Jarrett, David
• Conference:
  • 4th IMA International Conference on Mathematics in Transport
  • Location: London , United Kingdom
  • Date: 2005-9-7 to 2005-9-9
• Publication Date: 2007

Language

• English

Media Info

• Media Type: Print
• Edition: First
• Features: Figures; References; Tables;
• Pagination: pp 167-180
• Monograph Title: Mathematics in Transport. Selected Proceedings of the 4th IMA International Conference on Mathematics in Transport

Subject/Index Terms

• TRT Terms: Crash analysis; Crash causes; Local government agencies; Local transportation; Spatial analysis; Traffic crashes; Traffic distribution; Traffic safety
• Uncontrolled Terms: Bayesian analysis
• Geographic Terms: United Kingdom
• Subject Areas: Highways; Safety and Human Factors; I80: Accident Studies;

Filing Info

• Accession Number: 01081079
• Record Type: Publication
• ISBN: 9780080450926
• Files: TRIS
• Created Date: Nov 26 2007 9:54AM