The cause of the majority of road crashes can be attributed to drivers' behavior. Recent in-vehicle monitoring technologies enable continuous and detailed measurements of certain behaviors of drivers. The authors analyzedthe information received from a novel in-vehicle technology which identifies the occurrence of undesirable driving events such as extreme braking and accelerating, sharp cornering and sudden lane changing. Previous studies demonstrated the connection between these events and accident records, suggesting that events frequency (EF) is an appropriate surrogate for safety. The authors undertook an exploratory analysis to provide better understanding of EF statistical properties. Some findings are in-line with driving safety literature such as differences between males and females and between night and day. Other findings were somewhat less expected, such as differences in mean EF between trip edges (trip beginning and trip end) and middle of the trip. Use of the in-vehicle technology's continuous and high resolution measurements enabled interesting advanced statistical analyses.Future research can use our findings to build similar statistical models to predict the occurrence of undesirable driving events by other independent variables.
Abstract