The study developed a new way to predict traffic crashes on highways by using individual vehicle data. They found that a measure called safe headway distance was effective in predicting crash likelihood. The researchers used statistical models, including hurdle models, to analyze the data. The results showed that the hurdle negative binomial model was the most accurate in predicting crash occurrences compared to other models.