The study aimed to predict highway passenger and freight volume by understanding the factors that influence traffic in 117 regions. Researchers used a method called multiple linear regression to create a model that could forecast traffic volume. By including various variables into the equation and simplifying the process using stepwise multiple regression, they effectively reduced the number of factors considered while maintaining accurate predictions. This approach also helped address issues like variable relationships and inconsistency between predicted and actual results. The results indicated that the stepwise multiple regression method was successful in creating a reliable model for forecasting highway passenger and freight volume, offering valuable insights for similar forecasting in different regions.