On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

This paper proposes a new spatial multivariate count model to jointly analyze the traffic crash-related counts of pedestrians and bicyclists by injury severity. The modeling framework is applied to predict injury counts at a Census tract level, based on crash data from Manhattan, New York. The results highlight the need to use a multivariate modeling system for the analysis of injury counts by road-user type and injury severity level, while also accommodating spatial dependence effects in injury counts.

• Record URL:
  https://doi.org/10.1016/j.trb.2013.07.004
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261513001197
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Narayanamoorthy, Sriram
  • Paleti, Rajesh
  • Bhat, Chandra R
  • 0000-0002-0715-8121
• Publication Date: 2013-9

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: pp 245-264
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 55
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Bicycle crashes; Crash analysis; Econometrics; Injury severity; Multivariate analysis; Pedestrian safety; Pedestrian vehicle crashes; Spatial analysis
• Geographic Terms: Manhattan (New York, New York)
• Subject Areas: Highways; Pedestrians and Bicyclists; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning; I80: Accident Studies;

Filing Info

• Accession Number: 01493599
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 20 2013 4:31PM