Freeway Accident Likelihood Prediction Using a Panel Data Analysis Approach

The ability to predict freeway accident likelihood promises significant benefits to freeway operations. However, the development of such prediction models has proven to be very challenging because of the random nature of accidents, as well as the impact of site-specific factors. In addition, accident data has a pronounced nature of discrete response—a preponderant portion of nonaccident cases. To address these challenges, this research investigates the use of a discrete response model designed for panel data—the random effects ordered probit model, in predicting freeway accident likelihood. Panel data refers to data sets that combine time series and cross section (i.e., from different individuals, groups, etc.) observations. The empirical results of this research illustrate that the random effects ordered probit model performs well in identifying factors associated with traffic accidents. In addition, when applied in a predictive setting, the model provides benefits in forecasting the likelihood of accidents based on both time-varying and site-specific parameters.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/8674831
• Authors:
  • Qi, Yi
  • Smith, Brian Lee
  • Guo, Jianhua
• Publication Date: 2007-3

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 149-156
• Serial:
  • Journal of Transportation Engineering
  • Volume: 133
  • Issue Number: 3
  • Publisher: American Society of Civil Engineers
  • ISSN: 0733-947X
  • Serial URL: https://ascelibrary.org/journal/jtepbs

Subject/Index Terms

• TRT Terms: Crash causes; Crash locations; Crash risk forecasting; Cross sectional studies; Empirical methods; Freeways; Highway factors in crashes; Panel studies; Probits; Time series; Traffic crashes
• Subject Areas: Highways; Safety and Human Factors; I80: Accident Studies; I82: Accidents and Transport Infrastructure;

Filing Info

• Accession Number: 01044740
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Mar 30 2007 6:59AM