Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies

Abstract

Crash-prone drivers should be effectively targeted for various safety education and regulation programs because their over-involvement in crashes presents a big adverse effect on highway safety. By analyzing seven years of crash data from Louisiana, this paper investigates crash-prone drivers’ characteristics and estimates their risk to have crashes in the seventh year based on these drivers crash history of the past six years. The analysis results show that quite a few drivers repeatedly had crashes; seven drivers had 13 crashes in seven years; and the maximum number of crashes occurring in a single year to a single driver is eight. The probability of having crash(es) in any given year is closely related to a driver’s crash history: less than 4% for drivers with no crash in the previous six years; and slightly higher than 30% for drivers with nine or more crashes in the previous six years. Based on the results, several suggestions are made on how to improve roadway safety through reducing crashes committed by drivers with much higher crash risk as identified by the analysis.

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X. Sun, S. Das and Y. He, "Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies," Journal of Transportation Technologies, Vol. 4 No. 1, 2014, pp. 93-100. doi: 10.4236/jtts.2014.41009.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] M. Greenwood and U. Yule, “An Inquiry into the Nature of Frequency Distributions Representative of Multiple Happenings with Particular Reference to the Occurrence of Multiple Attacks of Disease or of Repeated Accidents,” Journal of Royal Statistical Society, Vol. 83, No. 2, 1920, pp. 255-279. http://dx.doi.org/10.2307/2341080
[2] R. D. Blasco, J. M. Prieto and J. M. Cornejo, “Accident Probability after Accident Occurrence,” Safety Science, Vol. 4, No. 6, 2003, pp. 481-501.
http://dx.doi.org/10.1016/S0925-7535(01)00080-7
[3] R. C. Peck, R. S. McBride and R. S. Coppin, “The Distribution and Prediction of Driver Accident Frequencies,” Accident Analysis & Prevention, Vol. 15, No. 5, 1971, pp. 371-393.
http://dx.doi.org/10.1016/0001-4575(83)90015-5
[4] N. Stamatiadis, K. R. Agent, J. Pigman and M. Ridgeway, “Evaluation of Retesting in Kentucky’s Driver License Process,” Research Report KTC-99-Kentucky Transport Cabinet, 1999.
[5] G. Daigneault, P. Joly and J. Frigon, “Previous Convictions or Accidents and the Risk of Subsequent Accidents of Older Drivers,” Accident Analysis & Prevention, Vol. 34, No. 2, 2002, pp. 257-261.
http://dx.doi.org/10.1016/S0001-4575(01)00014-8
[6] E. Hauer, B. N. Persaud, A. Smiley and D. Duncan, “Estimating the Accident Potential of an Ontario Driver,” Accident Analysis & Prevention, Vol. 23, No. 2-3, 1991, pp. 133-152.
http://dx.doi.org/10.1016/0001-4575(91)90044-6
[7] W. Chen, P. Cooper and M. Pinili, “Driver Accident Risk in Relation to the Penalty Point System in British Columbia,” Accident Analysis & Prevention, Vol. 26, No. 1, 1995, pp. 9-18.
[8] M. A. Gebers, “Strategies for Estimating Driver Accident Risk in Relation to California’s Negligent-Operator Point System,” California Department of Motor Vehicles Research and Development Branch, Technical Monograph 183, 1999.
[9] M. A. Gebers and R. C. Peck, “Using Traffic Conviction Correlates to Identify High Accident-Risk Drivers,” Accident Analysis & Prevention, Vol. 35, No. 6, 2003, pp. 903-912.
http://dx.doi.org/10.1016/S0001-4575(02)00098-2
[10] National Highway Traffic Safety Administration (NHTSA), “An Examination of Driver Distraction as Recorded in NHTSA Databases,” Traffic Safety Facts, DOT HS 811 216, 2009.

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