Evaluating the influence of crashes on driving risk using recurrent event models and Naturalistic Driving Study data

被引:9
|
作者
Chen, Chen [1 ]
Guo, Feng [1 ,2 ]
机构
[1] Virginia Tech, Dept Stat, Blacksburg, VA 24061 USA
[2] Virginia Tech, Transportat Inst, Blacksburg, VA 24061 USA
关键词
Recurrent event models; frailty models; Naturalistic Driving Study; driving risk; transportation safety; ACCIDENT OCCURRENCE; DRIVERS LEARN; REGRESSION; EXPERIENCE; TIME; PATTERNS; FRAILTY;
D O I
10.1080/02664763.2015.1134449
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Dramatic events such as crashes could alter driver behavior and change driving risk during post-event period. This study investigated the influence of crashes on driving risk using the 100-Car Naturalistic Driving Study data. The analysis is based on 51 crashes from primary drivers. Driving risk is measured by the intensity of safety-critical incidents (SCI) and near-crashes (NC), which typically occur at a high frequency both before and after a crash. We applied four alternative recurrent event models to evaluate the influence of crashes based on actual driving time. The driving period was divided into several phases based on the relationship to crashes, and the event intensities of these periods were compared. Results show a reduction in SCI intensity after the first crash (intensityrateratio = 0.82; 95% CI [0.693, 0.971]) and the second crash (intensityrateratio = 0.47; 95% CI [0.377, 0.59]) for male drivers. No significant response to the first crash was observed for females, but SCI intensity decreased after the second crash (intensityrateratio = 0.43; 95% CI [0.342, 0.547]). The findings of this study provide crucial information for understanding driver behavior and for developing effective safety education programs as well as safety counter measures.
引用
收藏
页码:2225 / 2238
页数:14
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