ANALYSING RAILWAY CROSSING ACCIDENT DATA

This paper discusses the application of maximum likelihood analysis to the prediction of long-term accident rates at road/rail grade crossings. Theoretical concepts of the method are developed, including significance testing, and it is shown that traditional regression techniques are not usually applicable to sparse data of this type since accidents cannot be assumed normally distributed. Various model forms are developed and discussed from both a theoretical and practical viewpoint. Finally, the application of maximum likelihood methods to a fairly large set of accident data is described and some general conclusions given. /TRRL/

• Record URL:
  http://arrbknowledge.com
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00050164
• Corporate Authors:

  ARRB

  Melbourne, Victoria  Australia 
• Authors:
  • HERBERT, A J
  • Smith, NMH
• Publication Date: 1976-9

Language

• English

Media Info

• Features: References; Tables;
• Pagination: p. 24-33
• Serial:
  • Australian Road Research
  • Volume: 6
  • Issue Number: 3
  • Publisher: ARRB
  • ISSN: 0005-0164

Subject/Index Terms

• TRT Terms: Analysis; Crash investigation; Crashes; Forecasting; Mathematical analysis; Mathematical models; Probability; Railroad grade crossings; Risk analysis; Safety; Statistics; Traffic crashes
• Geographic Terms: Australia
• Old TRIS Terms: Analytical techniques; Grade crossing accidents
• ITRD Terms: 1643: Accident; 6471: Analysis (math); 132: Forecast; 452: Level crossing; 6534: Probability; 1665: Safety; 6555: Statistics
• Subject Areas: Data and Information Technology; Railroads; Safety and Human Factors; I81: Accident Statistics;

Filing Info

• Accession Number: 00147872
• Record Type: Publication
• Source Agency: Transport and Road Research Laboratory (TRRL)
• Files: ITRD, TRIS, ATRI
• Created Date: Feb 16 1977 12:00AM