Integrated Network Design and Demand Forecast for On-Demand Urban Air Mobility

Wu, Zhiqiang; Zhang, Yunlong

doi:10.1016/j.eng.2020.11.007

Cited by 55 publications

(29 citation statements)

References 18 publications

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“…A 3D geographic information system map was derived from lidar data and used by [105] to determine the optimal vertiport location for the Tampa Bay area (U.S.). Both, regulation constraints for eVTOL operations at vertiports and socio-demographic characteristics were additionally considered.…”

Section: Holistic Uam Network Approachesmentioning

confidence: 99%

“…Ref. [105] concludes, that UAM ride shares are small therefore congestion relief will be limited, but the passengers who choose UAM will experience substantial time savings. Inside the network design, trips fully conducted by UAM or ground transportation modes as well as multi-modal ride shares are feasible.…”

Section: Holistic Uam Network Approachesmentioning

confidence: 99%

“…[131] found out that the turnaround time has a big impact on the ratio of gates to pads, which is one of the design drivers as discussed above. Several studies found the passenger processing time, which is directly linked to the vehicle turnaround time, to be one of the most relevant factors determining the market share UAM can achieve [102,105,142]. Parameter value specification for charging speed, swapping time, boarding, etc.…”

Section: Turnaround At Gate: Boarding and Chargingmentioning

confidence: 99%

“…Short turnaround times take the perspective of a touch-and-go vertistop design, where only passenger boarding and de-boarding occurs at the gate as the minimal necessary operation. Turnaround times that are mentioned are 0.5-10 min [131], 2-10 min [105], 5 min [7] or 8 min [132]. Some of these studies leave the question open, whether charging/fueling might happen during this time, but full charging/fueling of vehicles is unlikely.…”

Section: Turnaround At Gate: Boarding and Chargingmentioning

confidence: 99%

“…[163] introduces the Unit Benefit Ratio as a metric to measure the benefit of each operator instead of each flight due to possible market share differences. Under the aspects of system costs and operator equity, and based on formerly developed vertiport locations in Tampa Bay (U.S.) by [105], ref. [163] studied the applicability of a low-altitude traffic management system.…”

Section: Strategic Measuresmentioning

confidence: 99%

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Urban Air Mobility: Systematic Review of Scientific Publications and Regulations for Vertiport Design and Operations

Schweiger

Preis

2022

Drones

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Novel electric aircraft designs coupled with intense efforts from academia, government and industry led to a paradigm shift in urban transportation by introducing UAM. While UAM promises to introduce a new mode of transport, it depends on ground infrastructure to operate safely and efficiently in a highly constrained urban environment. Due to its novelty, the research of UAM ground infrastructure is widely scattered. Therefore, this paper selects, categorizes and summarizes existing literature in a systematic fashion and strives to support the harmonization process of contributions made by industry, research and regulatory authorities. Through a document term matrix approach, we identified 49 Scopus-listed scientific publications (2016–2021) addressing the topic of UAM ground infrastructure with respect to airspace operation followed by design, location and network, throughput and capacity, ground operations, cost, safety, regulation, weather and lastly noise and security. Last listed topics from cost onwards appear to be substantially under-represented, but will be influencing current developments and challenges. This manuscript further presents regulatory considerations (Europe, U.S., international) and introduces additional noteworthy scientific publications and industry contributions. Initial uncertainties in naming UAM ground infrastructure seem to be overcome; vertiport is now being predominantly used when speaking about vertical take-off and landing UAM operations.

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Section: Holistic Uam Network Approachesmentioning

confidence: 99%

Section: Holistic Uam Network Approachesmentioning

confidence: 99%

Section: Turnaround At Gate: Boarding and Chargingmentioning

confidence: 99%

Section: Turnaround At Gate: Boarding and Chargingmentioning

confidence: 99%

Section: Strategic Measuresmentioning

confidence: 99%

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Urban Air Mobility: Systematic Review of Scientific Publications and Regulations for Vertiport Design and Operations

Schweiger

Preis

2022

Drones

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On a fair and risk‐averse urban air mobility resource allocation problem under demand and capacity uncertainties

Sun,

Deng,

Wei

et al. 2024

Naval Research Logistics

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Urban air mobility (UAM) is an emerging air transportation mode to alleviate the ground traffic burden and achieve zero direct aviation emissions. Due to the potential economic scaling effects, the UAM traffic flow is expected to increase dramatically once implemented, and its market can be substantially large. To be prepared for the era of UAM, we study the fair and risk‐averse urban air mobility resource allocation model (FairUAM) under passenger demand and airspace capacity uncertainties for fair, safe, and efficient aircraft operations. FairUAM is a two‐stage model, where the first stage is the aircraft resource allocation, and the second stage is to fairly and efficiently assign the ground and airspace delays to each aircraft provided the realization of random airspace capacities and passenger demand. We show that FairUAM is NP‐hard even when there is no delay assignment decision or no aircraft allocation decision. Thus, we recast FairUAM as a mixed‐integer linear program (MILP) and explore model properties and strengthen the model formulation by developing multiple families of valid inequalities. The stronger formulation allows us to develop a customized exact decomposition algorithm with both benders and L‐shaped cuts, which significantly outperforms the off‐the‐shelf solvers. Finally, we numerically demonstrate the effectiveness of the proposed method and draw managerial insights when applying FairUAM to a real‐world network.

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Continuous Approximation Approach to Determine the Optimal Service Area for a Drone Port in Urban Air Logistics

Jasmine,

Adikariwattage,

Rifan

2024

Lecture Notes in Logistics

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Integrated Network Design and Demand Forecast for On-Demand Urban Air Mobility

Cited by 55 publications

References 18 publications

Urban Air Mobility: Systematic Review of Scientific Publications and Regulations for Vertiport Design and Operations

Urban Air Mobility: Systematic Review of Scientific Publications and Regulations for Vertiport Design and Operations

On a fair and risk‐averse urban air mobility resource allocation problem under demand and capacity uncertainties

Continuous Approximation Approach to Determine the Optimal Service Area for a Drone Port in Urban Air Logistics

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