Identifying and understanding the relationships between observed driving behavior over long-term periods and corresponding crash involvement rates is paramount to enhancing safety improvement programs and providing useful insights for transportation safety engineers, policy markers, insurance industries, and the public. Unlike previous data collection methods, recent advancement in mobile computing and accuracy of global positioning systems (GPS) allow researchers to monitor driving activities of large fleets of vehicles, for long-time study periods, at great detail. This study investigates the driving patterns of drivers who have and who have not experienced crashes during a 14-month study period using the longitudinally collected GPS data during a six-month Commute Atlanta study. This investigation allows an empirical investigation to assess whether drivers with recent crash experiences exhibit different driving or activity patterns (travel mileage, travel duration, speed, acceleration, speed stability duration, frequency of unfamiliar roadway activities, frequency of turn movement activities, and previous crash location exposures). This study also discusses various techniques of implementing GPS data streams in safety analyses. Finally, this study provides useful guidance for researchers who plan to evaluate the relationships between driver driving behavior and crash risk with large sample data and proposes driving behavior activity exposure metrics of individual drivers for possible safety surrogate measures as well as for driver re-training and education programs.