垂直停机坪终端调度与多方向表面的吞吐量分析
Vertiport Terminal Scheduling and Throughput Analysis for Multiple Surface Directions
AI总结：
本文提出了一种混合整数线性规划方法，用于优化垂直停机坪的操作，包括滑行、爬升（或接近）多方向使用以及在闸口的转换，并通过理论最大值方程验证了其吞吐量水平，同时通过案例研究验证了框架的有效性。
摘要：
垂直起降（VTOL）车辆在配送无人机市场和乘客运输中日益普及，推动了城市空中出行（UAM）系统的发展。UAM旨在通过利用城市空域缓解密集城市区域的交通拥堵。为处理UAM交通，垂直停机坪（vertiminals）在支持VTOL车辆的操作如起飞、着陆、滑行、乘客登机、加油或充电以及维护方面起着关键作用。高效的调度算法对于管理这些操作并优化vertiminal吞吐量同时确保安全协议至关重要。与固定翼飞机不同，VTOL车辆可以利用多个表面方向进行爬升和接近。这种灵活性需要专门的调度方法。我们提出了一种混合整数线性规划（MILP）公式，以全面优化vertiminal操作，包括滑行、使用多个方向爬升（或接近）以及在闸口的转换。所提出的MILP可将延迟减少高达50%。此外，我们推导了计算vertiminal吞吐量容量上界方程，考虑其核心要素：TLOF垫系统、滑行道系统和闸系统。我们的结果表明，MILP达到的吞吐量水平与这些方程推导出的理论最大值一致。我们还通过使用文献中已确立的vertiminal拓扑结构的案例研究验证了我们的框架。我们的MILP可用于找到vertiminal的最佳配置。这种双方法，MILP和吞吐量分析，允许在不需要模拟的情况下进行全面容量分析，同时通过MILP公式实现高效的调度。
英文摘要：
Vertical Take-Off and Landing (VTOL) vehicles are gaining traction in both the delivery drone market and passenger transportation, driving the development of Urban Air Mobility (UAM) systems. UAM seeks to alleviate road congestion in dense urban areas by leveraging urban airspace. To handle UAM traffic, vertiport terminals (vertiminals) play a critical role in supporting VTOL vehicle operations such as take-offs, landings, taxiing, passenger boarding, refueling or charging, and maintenance. Efficient scheduling algorithms are essential to manage these operations and optimize vertiminal throughput while ensuring safety protocols. Unlike fixed-wing aircraft, which rely on runways for take-off and climbing in fixed directions, VTOL vehicles can utilize multiple surface directions for climbing and approach. This flexibility necessitates specialized scheduling methods. We propose a Mixed Integer Linear Program (MILP) formulation to holistically optimize vertiminal operations, including taxiing, climbing (or approach) using multiple directions, and turnaround at gates. The proposed MILP reduces delays by up to 50%. Additionally, we derive equations to compute upper bounds of the throughput capacity of vertiminals, considering its core elements: the TLOF pad system, taxiway system, and gate system. Our results demonstrate that the MILP achieves throughput levels consistent with the theoretical maximum derived from these equations. We also validate our framework through a case study using a well-established vertiminal topology from the literature. Our MILP can be used to find the optimal configuration of vertiminal. This dual approach, MILP and throughput analysis, allows for comprehensive capacity analysis without requiring simulations while enabling efficient scheduling through the MILP formulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
