The cause of the majority of road crashes can be attributed to drivers' behavior. Recent in-vehicle monitoring technologies enable continuous and high resolution measurements of drivers' behaviors. We analyzed the information received from a novel in-vehicle technology which identifies the occurrences of undesirable driving events such as extreme braking and accelerating, sharp cornering and sudden lane changing. We undertook an exploratory analysis to provide better understanding of events frequency (EF) statistical properties. Our findings show higher EF in trip edges (trip beginning and trip end) than in the middle of the trip, higher EF for males than for females and higher EF at nighttime than at daytime. 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. (A) Reprinted with permission from Elsevier.
Abstract