Abstract
Although transportation safety has greatly improved over the past 2 decades, motor vehicle crash injuries remain a leading cause of morbidity and mortality, particularly among young drivers. Driver errors and behaviors such as speeding and distraction contribute disproportionately to crashes among inexperienced novices, who develop safe driving judgment only with substantial driving experience, commonly described as the "young driver problem." Research on young drivers has applied a range of research methods, including analyses of national archival data (mainly from police reports), crash analyses, observation of driver behavior, surveys of driver behavior and dispositions, and experimental research on driver behavior and vehicle crash worthiness. Prominent research questions regarding young driver safety include what and how do novices learn to drive safely, what are the predictors of young driver crashes, what is the variability and overtime trajectories of young driver performance and outcomes, and to what extent is the young driver problem due mainly to average population risk or high-risk groups? Current research on young drivers is complicated by small sample sizes, relatively rare events, high within and between group variability, missing data, the need to estimate exposure, and the lack of longitudinal and experimental designs, problems that require complex analytic methods. In this paper, we provide an overview of driving research methods, examples of research addressing the young driver problem, and examples of statistical collaboration on young driver research, focusing particularly on estimating prediction of crash risk and estimating variability in young driver performance and outcomes.