Keywords: Beta-Binomial, Data Science, Crash Data, Dashboard, Vehicle Safety Ratings
Each year the National Highway Traffic Safety Association and Insurance Institute for Highway Safety release safety ratings for popular makes and models of vehicles produced. We link these safety ratings with the crash data provided in the National Automotive Sampling System General Estimates System to study the efficacy of safety ratings as a predictor of the likelihood a passenger will be injured in a crash. We also consider the case of predicting a severe injury or death as a function of safety rating. A web-based dashboard was developed to graphically explore the relationship among these datasets. By considering the proportion of occupants (severely) injured per crash, we find that vehicle safety ratings generally do not have as much of an effect on likelihood of injury as one might expect, although vehicles with higher ratings can result in significant relative improvement. Our web application allows a user to explore different aspects of crashes (e.g., use of alcohol, speeding, etc.) and compare injuries and safety rating performance based on these conditions. Lastly, our dashboard allows a user to see differences between the NHTSA and IIHS ratings systems and how they correspond to the crash records.