Dynamic demand prediction model and application for competitive transportation market

Despite the importance of transportation demand forecasting, predicted demand for transportation service in the project feasibility phase is barely reached in the operation phase due to optimism bias, strategic bias, and uncertainty. Although many researchers have made efforts to predict transportation demand, competitive market dynamics were neglected in most demand forecasting methods, while factors affecting the demand are interactive, complex, and dynamic. The objective of this thesis is to propose a novel competitive dynamic model for transportation demand prediction. The System Dynamics (SD) model was developed and validated with three datasets: New York City, Tokyo 23 Wards, and Namma Metro in India. The results demonstrate the validity and applicability of the model to both city-level and project-level transportation demand prediction with high accuracy. After the model was validated, the model was employed to predict transportation demand and analyze the project's financial feasibility for the Pune Metro PPP project with different parameters in different conditions. In addition to the viability gap funding (VGF) at the initial stage, the minimum revenue guarantee (MRG) was added as another government subsidy for improving project feasibility, and both the government and the project cash were compared. The results show that the optimal financial structure depends on project profitability. The model developed in this thesis is likely to help decision-makers make more informed decisions.