Estimating vertiport passenger throughput capacity for prominent eVTOL designs

Preis, Lukas

doi:10.1007/s13272-023-00650-5

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…However, with grow-ing demand, the existing facilities can become congested [31]. Furthermore, passenger throughput is a function of the aircraft utilized [32].…”

Section: Vertiport Characteristicsmentioning

confidence: 99%

Integrating Electric Vertical Takeoff and Landing Aircraft into Public Airspace: A Scenario Study

Bridgelall,

White,

Tolliver

2023

Future Transportation

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The successful deployment of Advanced Air Mobility (AAM) requires the safe integration of electric vertical takeoff and landing (eVTOL) aircraft in non-segregated airspace. However, a lack of practical deployment demonstrations can slow the regulatory progress. This study presents a practical deployment framework for the integration of eVTOL aircraft into public airspace, in accordance with the Federal Aviation Administration (FAA) special airworthiness criteria. This study focused on a corporate use case to provide a comprehensive scenario for enhancing intra-company mobility. The scenario supports early implementation and demonstration goals by removing reliance on air traffic management systems or air traffic controller separation services. The practical deployment framework included facility selection, route planning, terrain mapping, collision avoidance, aircraft selection, infrastructure requirements, vertiport placement, electric chargers, ground handling, operational staff, and cost estimates. Planners can use the framework as a template to inform the implementation of real-world AAM services using eVTOL aircraft.

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“…However, with grow-ing demand, the existing facilities can become congested [31]. Furthermore, passenger throughput is a function of the aircraft utilized [32].…”

Section: Vertiport Characteristicsmentioning

confidence: 99%

Integrating Electric Vertical Takeoff and Landing Aircraft into Public Airspace: A Scenario Study

Bridgelall,

White,

Tolliver

2023

Future Transportation

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A Research on the Design and Operation of Regional Hub-Level Vertiport

Lee,

Park

2024

J. Korean Soc. Aviat. Aeronaut.

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UAM is emerging due to the deepening population concentration in the metropolitan area and the problem of congested ground transportation in urban areas. Accordingly, along with research on eVTOL aircraft for UAM services, interest in vertiport, the interest in vertiports, the infrastructure that allows eVTOLs to take off and land, is also increasing. However, behind the concentration of population in the metropolitan area, aphenomenon of local extinction is occurring in conjunction with the aging population. AAM, which moves quickly through 3D space, can be an effective SOC facility in times of local extinction crisis. In this paper, we introduce a design plan from the perspective of a complex transper center for a regional hub-level vertiport that can connect with local high-speed rail and utilize local airports in compliance with the vertiport design guidelines issued by FAA(Federal Aviation Administration) and EASA(European union Aviation Safety Agency). We would like to present Vertiport's future operation plan.

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DeepDispatch: Deep Reinforcement Learning-Based Vehicle Dispatch Algorithm for Advanced Air Mobility

Varnousfaderani,

Shihab,

Dulia

2024

Journal of Air Transportation

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Near-future air taxi operations with electric vertical takeoff and landing aircraft will be constrained by the need for frequent recharging and limited takeoff and landing pads in vertiports and will be subject to time-varying demand and electricity prices, making the dispatch problem unique and particularly challenging to solve. Previously, the authors have developed optimization models to address this problem. Such optimization models, however, suffer from prohibitively high computational run times when the scale of the problem increases, making them less practical for real-world implementation. To overcome this issue, the authors have developed two deep reinforcement learning-based dispatch algorithms, namely, single-agent and multi-agent double dueling deep Q-network dispatch algorithms, where the objective is to maximize operating profit. A passenger transportation simulation environment was built to assess the performance of these algorithms across 36 numerical cases with varying numbers of vehicles and vertiports and amounts of demand. The results indicate that the multi-agent dispatch algorithm can closely approximate the optimal dispatch policy with significantly less computational expenses compared to the benchmark optimization model. The multi-agent algorithm was found to outperform the single-agent counterpart with respect to both profits generated and training time. Additionally, we implemented a heuristic-based algorithm, faster but less effective in generating profits compared to our two deep reinforcement learning-based algorithms.

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Estimating vertiport passenger throughput capacity for prominent eVTOL designs

Cited by 3 publications

References 21 publications

Integrating Electric Vertical Takeoff and Landing Aircraft into Public Airspace: A Scenario Study

Integrating Electric Vertical Takeoff and Landing Aircraft into Public Airspace: A Scenario Study

A Research on the Design and Operation of Regional Hub-Level Vertiport

DeepDispatch: Deep Reinforcement Learning-Based Vehicle Dispatch Algorithm for Advanced Air Mobility

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