Development of a Transportation Model for the Greater Moncton Area

Abstract

This thesis develops a four-stage travel demand model for the Greater Moncton Area using spatial transferability and local estimation. Spatial transferability is explored as a cost-effective solution for small to mid-size cities with limited resources. The method’s feasibility is demonstrated, and its limitations are highlighted. Next, the study analyzes local data from the 2023 Canadian Travel Activity (CanTRAC) Survey and provides insights into Moncton residents’ socio-demographics and travel behavior, including trip frequency, distance, mode choices, and preferences for sustainable policies. A localized model is then developed using this data. The localized model is found to outperform the transferred model in predicting trip length distribution, mode shares, and traffic flows. These findings emphasize the importance of localized data in ensuring model accuracy and provide strategies for addressing Moncton’s urban growth and sustainability challenges. The study offers scalable solutions for developing transportation models and enable evidence-based policymaking.