A Bayesian Network Model of Two-Car Accidents

This paper describes the Bayesian network method for modeling traffic accident data and illustrates its use. Bayesian networks employ techniques from probability and graph theory to model complex systems with interrelated components. The model is built using two car accident data for 1998 from Slovenia, and inferences are made from the model about how knowledge of the values of certain variables influences the probabilities for values of other variables or outcomes. An advantage of the Bayesian network method presented here is its complex approach where system variables are interdependent and where no dependent and independent variables are needed.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/37387952
• Authors:
  • Simoncic, Marjan
• Publication Date: 2004

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 13-25
• Serial:
  • Journal of Transportation and Statistics
  • Volume: 7
  • Issue Number: 2/3
  • Publisher: Research and Innovative Technology Administration
  • ISSN: 1094-8848
  • Serial URL: http://www.bts.gov/publications/journal_of_transportation_and_statistics/

Subject/Index Terms

• TRT Terms: Bayes' theorem; Graph theory; Model atmosphere; Probability theory; Traffic crashes
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01000644
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: May 26 2005 2:42PM