The article compares different models used in transportation demand forecasting. Traditional models have limitations, while the Probit model is complex. The Mixed Logit model is a new alternative that offers flexibility and accuracy. The researchers show that Mixed Logit models can handle complex situations where traditional models fail. They demonstrate this through simulations and real data analysis, proving the model's effectiveness in predicting choices and adapting to policy changes. Overall, Mixed Logit models are a powerful tool for predicting transportation choices.