Urban Air Mobility (UAM)

Research

Data-driven future demand forecasting for UAM

As the public interest in UAM is getting higher and the underlying technology for UAM becomes sophisticated, the need to forecast the future demand for UAM increases. As the data-driven demand forecasting method has become more accurate than the traditional modeling-based forecasting method, TRUE lab utilized Seoul taxi GPS data to forecast the potential demand for UAM. Our assumption is based on the idea that part of the long-range taxi trip will be replaced by the emerging mobility service - UAM. As our first step toward UAM demand forecasting, we considered the case of using existing helipads. We plan to expand our scope in future work to UAM routing, fleet rebalancing, and scheduling. For details, please visit our blog.