도심-공항 간 승객 이송을 위한 도심항공모빌리티 운영 최적화 및 시뮬레이션 연구

초록

Urban Air Mobility (UAM) is gaining attention as a potential solution to urban traffic congestion. This study proposes an optimal UAM operation strategy for bi-directional passenger transport between Seoul and Incheon International Airport and evaluates its effectiveness using discrete event simulation. First, optimal vertiport locations were identified by applying K-means clustering to airport bus demand data in Seoul. A genetic algorithm was then used to determine the required number of UAM vehicles for passenger transport. A simulation model was developed in Simio, incorporating key elements such as departure and arrival points, charging facilities, UAM vehicles, and passengers. Simulation experiments were conducted to analyze how independent variables including the number and placement of charging stations and flight range affect system throughput and average passenger waiting time. The results suggest that strategically positioning charging stations based on flight range is crucial for enhancing operational efficiency. Unlike previous studies that mainly focused on aircraft design and infrastructure development, this study distinguishes itself by proposing an operation optimization approach that reflects actual passenger demand data. The findings are expected to contribute to the formulation of UAM operation strategies and support its practical implementation as a shared mobility service.

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