REGRESSION MODELS AND CASUAL INFERENCE IN INVESTIGATIONS OF THE RELATIONSHIP BETWEEN TRAFFIC ACCIDENTS AND ROAD AND TRAFFIC CHARACTERISTICS

REGRESSIONMODELLER OCH KAUSALSAMBAND VID STUDIER AV TRAFIKOLYCKORS VAEG- OCH TRAFIKINSTITUT

VTI carries out studies sponsored by the National Swedish Road Administration, which deal with the relationship between road traffic accidents and different road and traffic characteristics. For these studies VTI has developed a special data system which contains information on road traffic accidents, road layout, and traffic volume for a large part of the main road network. This part of the road network comprises 556 stretches of road with a total length of 2300 km. The stretches of road were chosen so that the road width and the average annual daily traffic is uniform for one and the same stretch of road. The accident material consists of road traffic accidents reported by the police and which occurred during 1962-1964. To begin with, the correlation between each and every one of the variables in question was studied as well as the correlation between the road variables and different accident variables such as the number of accidents, the number of accidents per km and year (accident density), and the number of accidents per million vehicle kms (accident rate) for various types of accidents. Then different kinds of multiple regression analysis were carried out regarding different road categories and accident types. Finally, by using partial correlation coefficients, an attempt was made to explain the casual relationship between different measures for road traffic accident and various road and traffic variables. /TRRL/

Language

  • Swedish

Media Info

  • Features: Figures; References; Tables;
  • Pagination: 49 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00096350
  • Record Type: Publication
  • Source Agency: Swedish National Road and Traffic Research Institute
  • Report/Paper Numbers: Report 43 R&D Rpt.
  • Files: ITRD, TRIS
  • Created Date: Oct 18 1975 12:00AM