Air Taxi Skyport Location Problem for Airport Access

Rath, Srushti; Chow, Joseph Y. J.

doi:10.48550/arxiv.1904.01497

Cited by 7 publications

(11 citation statements)

References 24 publications

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“…The establishment of intracity operational infrastructure is one of the significant barriers for air taxi implementation (Sun et al, 2018;Vascik and Hansman, 2018;Reiche et al, 2019;Rath et al, 2019;Tarafdar et al, 2019). Many factors contribute to a location being chosen as a strategic operating station, such as the demand density, existence of adequate area for safe departure/landing, availability of space for charging stations, and easy accessibility (Percoco, 2010;Duval, 2013;Yang and Notteboom, 2016;Bozorgi-Amiri et al, 2017;Shahriari et al, 2017;Zhang et al, 2019).…”

Section: Air Taxi Network Designmentioning

confidence: 99%

“…Their model detected 21 site locations in various boroughs of NYC, especially high cluster density for two locations -John F. Kennedy International Airport and South Central Park, indicating potential sites for vertiports. Similarly, Rath and Chow (2019) proposed an integer linear programming model to determine the optimal number of skyports for minimizing the travel cost associated with airport transfers. Their analysis indicated six potential sites to be adequate to serve the airport access travel needs of commuters in NYC.…”

Section: Air Taxi Network Designmentioning

confidence: 99%

“…ii. Determining Station Capacities: Regarding the air taxi facility selection problem, prior works have attempted to determine the location of vertiports and vertistops based on the customer demand volume in metropolitan cities (e.g., Rajendran and Zack, 2019;Rath and Chow, 2019). However, it is essential to determine the size of these facilities, particularly vertiports.…”

Section: Opportunities For Future Research Directionsmentioning

confidence: 99%

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Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Rajendran

Srinivas

2020

Transportation Research Part E: Logistics and Transportation Re

118

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Expected to operate in the imminent future, air taxi service (ATS) is an aerial on-demand transport for a single passenger or a small group of riders, which seeks to transform the method of everyday commute. This uncharted territory in the emerging transportation world is anticipated to enable consumers bypass traffic congestion in urban road networks. By adopting an electric vertical takeoff and landing concept (eVTOL), air taxis could be operational from skyports retrofitted on building rooftops, thus gaining advantage from an implementation standpoint. Motivated by the potential impact of ATS, this study provides a review of air taxi systems and associated operations. We first discuss the current developments in the ATS (demand prediction, air taxi network design, and vehicle configuration). Next, we anticipate potential future challenges of ATS from an operations management perspective, and review the existing literature that could be leveraged to tackle these problems (ride-matching, pricing strategies, vehicle maintenance scheduling, and pilot training and recruitment). Finally, we detail future research opportunities in the air taxi domain.

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Section: Air Taxi Network Designmentioning

confidence: 99%

Section: Air Taxi Network Designmentioning

confidence: 99%

Section: Opportunities For Future Research Directionsmentioning

confidence: 99%

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Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Rajendran

Srinivas

2020

Transportation Research Part E: Logistics and Transportation Re

118

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“…However, until today few studies have explored UAM by bringing together stakeholders. Most of the related studies have focused on their technical characteristics including propulsion systems, battery technology, and autonomy [26][27][28]. Limited literature concerns the development of econometric models [29][30][31] to explore perceptions and attitudes [32][33][34][35] and estimate users' willingness-to-fly [36] and willingness-to-pay for air taxis [37,38].…”

Section: Introductionmentioning

confidence: 99%

A New Mobility Era: Stakeholders’ Insights regarding Urban Air Mobility

2022

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Urban Air Mobility (UAM) constitutes a future aerial mobility alternative, which concerns the use of electric and autonomous aerial vehicles for transporting people throughout a planned network of vertiports. To materialize UAM, several actors of the air and urban transport ecosystem play a vital role. This paper describes the insights gathered from 32 key stakeholders around the world to present and frame the key aspects for the future implementation of UAM. The participants include representatives from the UAM industry such as airports, airlines, aviation consulting companies, academia, and authorities. The data collection encompasses various key research areas, covering topics such as UAM strengths, weaknesses, opportunities and risks, requirements for implementation, concept integration in the existing transport system, specific use cases, business models, and end-user segments. The research aims at setting up the stakeholder scene and expanding the current literature for UAM by engaging key decision makers and experts towards shaping the new mobility era. The results demonstrate that ensuring certification standards for UAM fleets and updating the current legal and regulatory framework are the main prerequisites for UAM’s realization. In addition, the usage of UAM for transporting cargo or for air ambulance services are the most mature business models for the coming decade.

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“…Multiple tools, such as clustering algorithms (Lim and Hwang, 2019;Rajendran and Zack, 2019), mathematical models (Rath and Chow, 2019), and simulation (Balac et al, 2019), have been utilized to estimate demand and determine optimal vertiport and vertistop locations. Rajendran and Zack (2019) proposed integrating a multi-modal warm start approach with k-means clustering algorithm to determine 21 potential air taxi stations in New York City (NYC).…”

Section: Air Taxi Infrastructure Location Decisionsmentioning

confidence: 99%

A study on emerging transportation services based on efficient network design and operation

Sinha¹

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Rapid growth in modern technologies has provided new tools for flexible and convenient transportation to the public. These new avenues for commuting would enable promoting non-driving modes of conveyance while shifting the economics of movement via traditional methods such as cars, subways, buses, etc. These innovative services would be advantageous in reducing dependability on privately-owned vehicles, thereby reducing the impact on the environment while providing a faster mode of travel. They would also play a crucial role in decreasing bottleneck due to heavy traffic, which has a detrimental impact on people's health, lifestyle and productivity. Thus, logistic companies are aiming towards making use of emerging technologies, such as air taxis and hyperloop, for facilitating efficient transportation in the near future. In this dissertation, a unique two-phase procedure integrating a multi-criteria warm start technique with an iterative k-means clustering algorithm is developed for optimal air taxi infrastructure location decisions. The proposed methodology was improved by utilizing a different clustering technique called clustering large applications (CLARA) which suggests developing 14 unique sites in New York City (NYC). However, establishing all the stations simultaneously might be challenging for any business, and therefore, a mathematical model is created to recommend these centers in multiple phases while maximizing the demand satisfaction in each scenario. Based on the available transportation literature, constraints such as rental cost, number of trips per day per 1000 customers, road facilities, and the employee salary are considered to be a part of the linear model. Next, a multiple-criteria simulation optimization model is developed to determine the ideal station size, location and size of charging facilities, minimum threshold charge, number of vehicles required and, allocating customers to air taxis for a network of five skyports. The model proposes having 50 air taxis in the system for the base case. The commuter average time in system and wait time to be approximately 36 and 14 minutes respectively, with average vehicle utilization of nearly 76 percent. While air taxis are expected to be utilized for intra-city commute, Hyperloop and High-Speed Rail (HSR) services would enable passengers for inter-city transport . A brief investigation is performed to examine the substitutability of HSR with Hyperloop services based on vehicle and passenger characteristics. A simulation model is developed to compare the performance of both these alternate transportation modes for a network of three major cities in Europe (Amsterdam, Paris, and Frankfurt). Our results indicate that with a significantly lower pod capacity, the Hyperloop system will still be able to serve more customers compared to the HSR services, while the vehicle utilization is observed to be higher in the latter alternative for a given period of time. We further compare the two transportation modes with respect to their estimated infrastructure and operational costs as well as CO2 emission. Finally, a cost-benefit analysis is conducted to estimate the passenger ticket price for Hyperloop services.

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Air Taxi Skyport Location Problem for Airport Access

Cited by 7 publications

References 24 publications

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

A New Mobility Era: Stakeholders’ Insights regarding Urban Air Mobility

A study on emerging transportation services based on efficient network design and operation

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