Research and Design of eVTOL Garage Scheduling and Management Systems for Urban Air Mobility

As global urbanization accelerates, traffic congestion has emerged as a crucial issue affecting the sustainable development of cities. Urban Air Mobility (UAM) has been introduced as an effective solution to alleviate ground traffic congestion. Electric Vertical Takeoff and Landing (eVTOL) vehicles, known for their speed, flexibility, and sustainability, have garnered significant attention. However, the widespread implementation of eVTOLs faces technical challenges in efficient and safe scheduling and management. This paper investigates and designs an intelligent eVTOL garage scheduling and management system tailored for urban air traffic. Through system requirement analysis, a modular system architecture was proposed, and an intelligent scheduling algorithm was developed using mathematical modeling and ant colony optimization, enhancing the scheduling process. The results demonstrate that the established mathematical model accurately describes the complex constraints and objectives of eVTOL scheduling, and the proposed ant colony algorithm effectively resolves scheduling issues, improving task allocation and resource utilization efficiency. The system design meets the real-time data processing, high concurrency, and scalability requirements of urban eVTOL operations. This study provides a scientific solution for designing and managing eVTOL garage systems in urban air traffic, enhancing the accessibility and reliability of urban air transportation.