Market Basket Analysis: Novel Way to Find Patterns in Crash Data from Large Jurisdictions

Data mining applications are becoming increasingly popular for many applications across a set of very divergent fields. Analysis of crash data is no exception. There are many data mining methodologies such as neural network, clustering etc. that have been applied to crash data in the recent past. However, one particular application conspicuously missing from the traffic safety literature is association analysis or market basket analysis. The methodology is used by retailers all over the world to determine which items are purchased together. In this study, crashes are analyzed as supermarket transactions to detect interdependence among crash characteristics. The results from the analysis include simple rules that indicate which crash characteristics are associated with each other, i.e., they are found together in the crashes. The application is demonstrated using data for non-intersection crashes from the state of Florida that occurred during the year 2004. The proposed methodology is useful in identifying previously unknown patterns in the data obtained from large jurisdictions (such as the State of Florida) as opposed to a single roadway or intersection. Based on the association rules discovered from the analysis it was concluded that that there is a significant correlation between lack of illumination and high severity of crashes. Furthermore, it was found that under rainy conditions straight sections with vertical curves are particularly crash prone. Results are consistent with the understanding of crash characteristics and point to the potential of this methodology for providing directions for future investigation to the federal and state agencies.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: References; Tables;
  • Pagination: 15p
  • Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

Filing Info

  • Accession Number: 01044953
  • Record Type: Publication
  • Report/Paper Numbers: 07-0055
  • Files: BTRIS, TRIS, TRB
  • Created Date: Feb 8 2007 4:37PM