Vertiport Terminal Scheduling and Throughput Analysis for Multiple Surface Directions
<|reference_start|>Vertiport Terminal Scheduling and Throughput Analysis for Multiple Surface Directions: Vertical Take-Off and Landing (VTOL) vehicles have gained immense popularity in the delivery drone market and are now being developed for passenger transportation in urban areas to efficiently enable Urban Air Mobility (UAM). UAM aims to utilize the urban airspace \hidetxt{vertical dimension} to address the problem of heavy road congestion in dense urban cities. VTOL vehicles require vertiport terminals for landing, take-off, passengers boarding or deboarding, refuelling (or charging), and maintenance. An efficient scheduling algorithm is essential to maximize the throughput of the vertiport terminal (vertiminal)\hidetxt{ as well as efficient use of airspace} while maintaining safety protocols to handle the UAM traffic. While traditional departure and taxiing operations can be applied in the context of vertiminal, specific algorithms are required for take-off and landing schedules. Unlike fixed-wing aircraft that require a runway to take-off and climb in a single direction, VTOL vehicles can approach and climb in several directions. We propose a Mixed Integer Linear Program (MILP) formulation to schedule flights for taxiing, climbing (or approaching) using multiple directions after take-off (before landing) and turnaround on gates. We also derived equations to thoroughly analyze the throughput capacity of a vertiminal considering all its core elements. We have shown that our MILP can achieve the maximum throughput obtained through the equations. Given the input parameters, our analysis can be used to analyze the capacity of a vertiminal without running any simulation, while our MILP can be used to get the most efficient schedule.<|reference_end|>
@article{saxena2024vertiport,
    title={Vertiport Terminal Scheduling and Throughput Analysis for Multiple
  Surface Directions},
    author={Ravi Raj Saxena, T.V. Prabhakar, Joy Kuri, Manogna Yadav},
    journal={arXiv preprint arXiv:2408.01152},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.01152},
    primaryClass={cs.ET cs.SY eess.SY}
}