Abstract Details
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Activity Number:
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437
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Government Statistics Section
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| Abstract - #308978 |
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Title:
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Evaluate Crash and Near-Crash Risk for Naturalistic Driving Data Using Recurrent Event Models
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Author(s):
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Chen Chen*+ and Feng Guo
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Companies:
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and Virginia Tech Transportation Institute
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Keywords:
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Recurrent event ;
AFT model ;
Frailty model ;
Transportation safety
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Abstract:
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The naturalistic driving study provides high-resolution data for evaluating driving risk at individual driver level. In this paper, we used recurrent event models to model time gap between crashes. The models were based on several alternative hazard based models. Two broad categories of recurrent event models, the gap-time model under the assumption of renewal process and modulated gap-time model were evaluated. In addition, we evaluated crash effect on driving risk which is measured by near crash, to see whether or not driving risk dropped after each crash. The proposed models were implemented to the 100-Car Naturalistic Driving Study.
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