Long-Term Travel Forecasting using Trip-Chain-Based User Equilibrium Model: Proposal and Validation of a Quick Method

Abstract

Existing trip-chain-based user equilibrium assignment can provide only a short-term travel demand forecasting and it cannot provide long-term forecasting. This is because the method assumes the simple short-term direct demand functions and it is not suitable for long-term forecasting. Meanwhile, some practitioners propose a simple method to forecast future master data of Person Trip survey. They make the forecasting by changing expansion factors of current master data considering the distribution of future population. This study integrates these two methods and proposes a simple long-term travel demand forecasting method. This method is trip-chain-based variable demand model considering network congestion consistently. Then, we validate the method by post evaluation using 1997 and 2012 Kumamoto Metropolitan Area Person Trip survey data. Although the method has limitation that it cannot capture the structural changes such as increase of automobile trip by the elderly, we confirm that this method can be applicable easily to long-term travel demand forecasting.