A global gravity model for air passenger demand between city pairs and future interurban air mobility markets identification.

Becker, Kristin; Terekhov, Ivan; Niklaß, Malte; Gollnick, Volker

doi:10.2514/6.2018-2885

Cited by 17 publications

(12 citation statements)

References 11 publications

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“…Since the gravitational model is suitable for analyzing the flow changes between two different locations and has good generalization, it is widely used in various areas such as immigration, transportation, tourism, etc., even though its parameters and variables need to be appropriately tuned [35]- [37]. We can revise a gravity model such as a trade gravity model for the purpose of predicting electricity consumptions.…”

Section: A Le_gra Modelmentioning

confidence: 99%

Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

2019

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The accurate prediction approach of urban buildings' electricity consumption is an important foundation for smart urban energy management. It provides a decision basis for reasonable electricity deployments upon different scenarios. Usually, a single model cannot solve linear and nonlinear problems that may occur in electricity consumption prediction effectively and may produce predictions with unsatisfactory accuracy and stability. Moreover, some prediction models are also poorly interpretable and generalized, which makes them difficult to be applied in practice. To overcome these problems, this paper proposes an ensemble prediction model called gravity gated recurrent unit electricity consumption model which integrates the gated recurrent unit model and the proposed logarithmic electricity consumption gravity model. The weights are derived from average mutual information and weighted entropy. We use two years (17 520 hours) electricity consumption of a five-star hotel building in Shanghai, China, as the study case to illustrate our approach, and apply nine common prediction models as the benchmarks to conduct the computational experiments and comparisons. Furthermore, we also employ the electricity consumption data of another type of building (office building) to evaluate the generalization capability of the proposed ensemble model. Our approach outperforms all benchmarks in terms of accuracy, stability, and generalization.

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Section: A Le_gra Modelmentioning

confidence: 99%

Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

2019

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“…Several market studies forecast that AAM passenger and emergency services will begin to transition to VTOL and electric VTOL (eVTOL) aircraft in the mid to late 2020s. Broadly, these market studies estimate a passenger mobility market of 2.8 to 4 billion USD by 2030, and a global AAM market potential of 74 to 641 billion USD in 2035 [2][3][4][5][6][7][8]. Herman et al [6] conducted a market study examining 74 global cities using a metanalysis approach of existing studies coupled with an analytical forecasting model that included variables such as city demographics, infrastructure costs, aircraft and supply chain, demand assumptions, and community and regulatory constraints.…”

Section: Introductionmentioning

confidence: 99%

“…Another study by Porsche Consulting estimates a global demand for 23,000 eVTOL aircraft in 2035. Using a gravity model, [7] forecasts demand in 2042 for regional air taxis (up to 300 km). Mayor and Anderson [8] estimates that air taxis could have upwards of 400 million enplanements representing 4% of domestic trips by 2050.…”

Section: Introductionmentioning

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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“…Except metrics such as income and population levels, socio-economic mobility has been considered as an important characteristic for the socio-economic fabric of market areas. As to the growing urbanization and subsequently increasing traffic, Becker et al 2 aimed to discover future potential worldwide markets for interurban air mobility up to 300 km. Forecasting of air passenger and cargo had a major influence on the master plan of the airport infrastructure development and investment by the civil airline.…”

Section: Introductionmentioning

confidence: 99%

Air passenger travel forecasting model based on both dynamical individual behavior and social influence force

Wang

Liu

Ding

2019

Journal of Algorithms & Computational Technology

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Air passenger travel forecasting is necessary and becomes very valuable for airline company, because accurately obtaining practical requirements of air passenger, which can not only help airline company to improve air passenger satisfaction degree and enhance user experience so as to gain huge revenue, but also can help air passengers discover suitable travel plan quickly. In order to generate the air passenger travel forecasting model, this paper aims to analyze the internal driving force and social affect factor simultaneously, which was based on dynamical personal behaviors and air passenger social relationship exactly. In particular, three aspects in terms of dynamical personal behaviors, effect of fellow air passenger, and influence of similar air passenger are all considered simultaneously, and then the data from these aspects are further trained so as to obtain weight allocation in many different scenarios. Besides, workday and non-workday are separately considered in order to make the forecasting model feasible and effective.

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A global gravity model for air passenger demand between city pairs and future interurban air mobility markets identification.

Cited by 17 publications

References 11 publications

Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

Forecasting the Short-Term Electricity Consumption of Building Using a Novel Ensemble Model

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

Air passenger travel forecasting model based on both dynamical individual behavior and social influence force

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