A two-dimensional simulation technique for quantifying the uncertainty of a combined travel demand model

Uncertainties are unavoidable in the travel demand model. The purpose of this paper is to provide a framework for analyzing and quantifying the uncertainty involved in travel demand forecasting models. Instead of using the traditional four-step approach to travel demand modeling that lacks behavioral interpretation and consistency, the combined travel demand model is adopted. A partial linearization algorithm is used for solving this multi-dimension travel choice problem. A two-dimensional Monte Carlo simulation technique is proposed to handle the uncertainties. It separately simulates the variability and uncertainty of the combined travel demand model so that individual and collective effects can be better assessed and quantified. Numerical experiment is also conducted to demonstrate the feasibility of the proposed framework.