Intelligent transportation systems data collected on drivers who presumably participated in a study of cognitive mapping and way-finding were evaluated with two basic procedures for data coding, including analysis of video data based on the occurrence or non-occurrence of a) critical behaviors during consecutive 15 second intervals of a driving trial, and b) the safe alternative when a safe behavior opportunity was available. Methods of data coding were assessed for practical use, reliability, and sensitivity to variation in driving style. A factor analysis of at-risk driving behaviors identified a cluster of correlated driving behaviors that appeared to share a common characteristic identified as aggressive/impatient driving. The relationship between personality and driving style was also assessed. That is, analysis of the demographics and personality variables associated with the occurrence of at-risk driving behaviors revealed that driver Age and Type A personality characteristics were significant predictors of vehicle speed and following distance to the preceding vehicle. Results are discussed with regard to implications for safe driving interventions and problem behavior theory.