Which model estimates the probability of choosing a mode of transportation?

The Logit model is widely used in transportation studies to estimate the probability of choosing a specific mode of transportation based on various attributes and individual preferences. This statistical model is particularly effective for scenarios where the dependent variable is categorical, such as the selection between different transport modes like car, bus, bike, or walking.

The Logit model calculates the odds of choosing one option over others considering influencing factors such as travel time, cost, comfort, and environmental consciousness. It provides insights into how likely individuals are to choose a particular mode under given circumstances and helps in analyzing choices under uncertainty.

In contrast, while the Gravity model is valuable for predicting trip distribution based on the interaction between origins and destinations, it does not specifically estimate the probability of choosing among different modes of transport. Forecast models and adjustment models serve different purposes—they are generally used for predicting future trends and managing changes rather than focusing on mode choice probability. Thus, the Logit model is the most suitable tool for assessing transportation mode choice.