Development of a Simulation Model for UAM Demand Forecasting Using System Dynamics

This study develops a demand forecasting model for Urban Air Mobility (UAM) by analyzing and structuring the causal relationships among various factors influencing UAM demand. To systematically categorize these factors, they were classified into external factors, supply factors, diffusion factors, and imitation factors. Based on an extensive literature review, 18 key variables were identified. A Causal Loop Diagram (CLD) was constructed to illustrate the interrelationships among these variables. The causal structure indicates that potential UAM demand is converted into actual UAM demand through the influence of diffusion and imitation factors, while UAM demand is constrained by vertiport capacity. Building on the causal relationships, a Stock Flow Diagram (SFD) was developed as the foundation of the UAM demand forecasting model. The model predicts that by 2050, the annual UAM demand in the Seoul Metropolitan Area will reach approximately 37.02 million passengers (101,432 passengers per day). The primary objective of this study is to establish a demand forecasting model that incorporates various factors affecting UAM demand and enables adaptation to future environmental changes. The proposed model offers policymakers a more robust and reliable basis for informed decision-making. Furthermore, the methodology and findings of this study hold significant applicability not only within South Korea but also in international contexts, providing a valuable framework for global UAM demand forecasting.