Design and Evaluation of a Crash Prediction Strategy

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Design and Evaluation of a Crash Prediction Strategy

E. J. McConnell / R. E. Hagen / R. C. Peck

The purpose of the project was to create and validate a method of identifying homogeneous groups of high risk drivers. Starting with a 6-year driver record on a sample of over 250,000 licensed drivers, five risk groups were identified based on a 3-year driver record. A regression equation was derived for each risk group to maximize the prediction of accident involvement in a future 3-year period. These equations were then cross validated. The high risk drivers identified were also compared to the drivers identified as being high risk by a surrogate negligent operator point count, a regression equation using total accidents and total convictions as predictors, a regression equation which also includes age and sex. Drivers identified by the regression equations had the highest future accident expectancy while drivers identified by the surrogate point count had the lowest. Recommendations included modifying the negligent operator point count to include total accidents and convictions, and weighting them through use of a regression equation. They also included fully automating the new selection criteria and continuing to assess the selection procedure on an ongoing basis.