Assessing Time-Varying Crash Effect in Semiparametric Recurrent Events Model

• Activity Number: 566
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Section on Risk Analysis
• Author(s): Chen Chen*+ and Feng Guo
• Companies: Virginia Tech and Virginia Tech
• Keywords: B-spline ; Frailty Model ; Naturalistic Driving Study ; Recurrent event ; Stratification

Abstract

In this paper, we developed a recurrent event model with time-varying coefficient to evaluate the impacts of crash on driver behavior. This model extends the commonly used semiparametric proportional recurrent event approach by allowing the regression coefficient to change over time. We adopted the B-spline function with respect to a given smoothness to estimate the time varying effects. The developed model is applied to the 100-Car Naturalistic Driving Study data to evaluate the impacts of crashes on driver behavior, as measured by the crash-relevant conflicts. For this specific data, we also use frailty to address correlation among recurrent events and stratified baseline functions to accommodate drivers with various risks.