Door-to-Door Travel Time Comparative Assessment for Conventional Transportation Methods and Short Takeoff and Landing On Demand Mobility Concepts

Wei, Lansing; Justin, Cedric Y.; Briceño, Simon I.; Mavris, Dimitri N.

doi:10.2514/6.2018-3055

Cited by 10 publications

(4 citation statements)

References 1 publication

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“…The airpark fitting algorithm used in this paper will be updated to incorporate wind effects by imposing a penalty function related to the local wind magnitude and direction on the maximum calculated runway length for each heading. The results produced by this paper will be used in future studies related to system performance characteristics such as the travel time of commuters using the STOL ODM system [22]. These results will also be used to drive balanced field length requirements for STOL vehicle designs, allowing a detailed economic assessment of the system to be performed.…”

Section: Discussionmentioning

confidence: 99%

Development of a Methodology for Parametric Analysis of STOL Airpark Geo-Density

Robinson

Sokollek

Justin

et al. 2018

2018 Aviation Technology, Integration, and Operations Conference

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Vehicles designed for urban air mobility (UAM) or on-demand mobility (ODM) applications typically adopt an architecture enabling vertical takeoff and landing (VTOL) capabilities. UAM or ODM systems featuring these capabilities typically have a smaller ground footprint but are subject to a number of performance compromises that make sizing and optimizing the vehicles more challenging. These design challenges can be further compounded when additional environmental considerations are taken into account and in particular if electric propulsion is considered. Alternative architectures such as short takeoff and landing (STOL) and super-short takeoff and landing (SSTOL) vehicles are thus investigated because they present possible advantages in terms of energy efficiency, overall vehicle performance, and noise footprint. However, the larger ground footprint of the infrastructure necessary to operate these systems means that these systems may be more difficult to integrate into a urban and suburban environment. One objective of this research is to estimate the geo-density of airparks suitable for STOL and SSTOL operations based on vehicle performance and ground footprint parameters. In turn, this helps establish requirements for the field performances of STOL and SSTOL vehicles to be considered for ODM and UAM applications. This research proposes and interactive and parametric design and trade-off analysis environment to help decision makers assess the suitability of candidate cities for STOL and SSTOL operations. Preliminary results for the Miami metropolitan area show that an average airpark geo-density of 1.66 airparks per square mile can be achieved with a 300 foot long runway.

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Section: Discussionmentioning

confidence: 99%

Development of a Methodology for Parametric Analysis of STOL Airpark Geo-Density

Robinson

Sokollek

Justin

et al. 2018

2018 Aviation Technology, Integration, and Operations Conference

Self Cite

View full text Add to dashboard Cite

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“…Finally, studies have also conducted exploratory demand modeling and travel time analyses, often comparing AAM with private vehicle use and other modes of transportation. Wei et al [15] compared door-to-door travel times of private vehicles with short take-off and landing (STOL) aircraft. Using a case study of South Florida, the study found potential demand for AAM trips greater than 45 min.…”

Section: Overview Of Studies Forecasting Aam Demandmentioning

confidence: 99%

“…Al Haddad et al [21] also concluded that the value of time savings, among other factors, were highly influential on the potential adoption and use of AAM. All of these studies suggest that AAM demand could be influenced by the quality of first-and last-mile connections because of their impacts on total travel time, cost, and convenience (i.e., number of connections) [12,[15][16][17][18][19][20][21].…”

Section: Overview Of Studies Forecasting Aam Demandmentioning

confidence: 99%

Advanced Air Mobility: Demand Analysis and Market Potential of the Airport Shuttle and Air Taxi Markets

et al. 2021

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Advanced air mobility (AAM) is a broad concept enabling consumers access to on-demand air mobility, cargo and package delivery, healthcare applications, and emergency services through an integrated and connected multimodal transportation network. However, a number of challenges could impact AAM’s growth potential, such as autonomous flight, the availability of take-off and landing infrastructure (i.e., vertiports), integration into airspace and other modes of transportation, and competition with shared automated vehicles. This article discusses the results of a demand analysis examining the market potential of two potential AAM passenger markets—airport shuttles and air taxis. The airport shuttle market envisions AAM passenger service to, from, or between airports along fixed routes. The air taxi market envisions a more mature and scaled service that provides on-demand point-to-point passenger services throughout urban areas. Using a multi-method approach comprised of AAM travel demand modeling, Monte Carlo simulations, and constraint analysis, this study estimates that the air taxi and airport shuttle markets could capture a 0.5% mode share. The analysis concludes that AAM could replace non-discretionary trips greater than 45 min; however, demand for discretionary trips would be limited by consumer willingness to pay. This study concludes that AAM passenger services could have a daily demand of 82,000 passengers served by approximately 4000 four- to five-seat aircraft in the U.S., under the most conservative scenario, representing an annual market valuation of the 2.5 billion USD.

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“…Urban air mobility (UAM) has become a rising trend that has garnered significant attention from scholars and practitioners, aiming to establish a sustainable and resilient transport infrastructure. However, UAM encounters numerous technological and legislative challenges, including air traffic control, cybersecurity concerns, noise pollution [1], and ecological considerations.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Turbo-Shaft Engine Digital Twinning for Autonomous Aircraft via AI and Synthetic Data Generation

Aghazadeh Ardebili,

Ficarella,

Longo

et al. 2023

Aerospace

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Autonomous aircraft are the key enablers of future urban services, such as postal and transportation systems. Digital twins (DTs) are promising cutting-edge technologies that can transform the future transport ecosystem into an autonomous and resilient system. However, since DT is a data-driven solution based on AI, proper data management is essential in implementing DT as a service (DTaaS). One of the challenges in DT development is the availability of real-life data, particularly for training algorithms and verifying the functionality of DT. The current article focuses on data augmentation through synthetic data generation. This approach can facilitate the development of DT in case the developers do not have enough data to train the machine learning (ML) algorithm. The current twinning approach provides a prospective ideal state of the engine used for proactive monitoring of the engine’s health as an anomaly detection service. In line with the track of unmanned aircraft vehicles (UAVs) for urban air mobility in smart city applications, this paper focuses specifically on the common hybrid turbo-shaft in drones/helicopters. However, there is a significant gap in real-life similar synthetic data generation in the UAV domain literature. Therefore, rolling linear regression and Kalman filter algorithms were implemented on noise-added data, which simulate the data measured from the engine in a real-life operational life cycle. For both thermal and hybrid models, the corresponding DT model has shown high efficiency in noise filtration and a certain amount of predictions with a lower error rate on all engine parameters except the engine torque.

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Door-to-Door Travel Time Comparative Assessment for Conventional Transportation Methods and Short Takeoff and Landing On Demand Mobility Concepts

Cited by 10 publications

References 1 publication

Development of a Methodology for Parametric Analysis of STOL Airpark Geo-Density

Development of a Methodology for Parametric Analysis of STOL Airpark Geo-Density

Advanced Air Mobility: Demand Analysis and Market Potential of the Airport Shuttle and Air Taxi Markets

Hybrid Turbo-Shaft Engine Digital Twinning for Autonomous Aircraft via AI and Synthetic Data Generation

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