Development of an Aircraft Routing System for an Air Taxi Operator

Zwan, F.M. Van der; Wils, K.; Ghijs, S.S.A.

doi:10.5772/25655

Cited by 5 publications

(6 citation statements)

References 34 publications

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“…A request indicates information, such as origin and destination stations, number of passengers traveling, and earliest pickup time. Each requisition may be accepted or rejected, depending on various financial and strategic factors (van der Zwan et al, 2011). Depending on the application area, the objective of DAFP can be to minimize cost, maximize service level, or maximize profits, while satisfying the problem constraints (Cordeau et al, 2007;Espinoza et al, 2008a).…”

Section: Ride-matchingmentioning

confidence: 99%

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

138

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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: Ride-matchingmentioning

confidence: 99%

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

138

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“…Constraints (2) ensure that all request r ∈ R are serviced by exactly one aircraft of type p r as required by the customer. Constraints (3) impose that to service request r, the aircraft must come from an airport (which can be the same as the current one in case k = i r ).…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Another phenomenon observed in the last years concerns the increasing of on-demand air transport services, mainly represented by air taxi and fractional ownership companies [2][3][4]. Differently from the traditional commercial airlines these services are oriented to individual customers and do not work with pre-scheduled flights.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…As a result, air companies are recurring to scientific methods to support decision making. Mathematical models and computational methods have became a must in their planning process [1,2].Another phenomenon observed in the last years concerns the increasing of on-demand air transport services, mainly represented by air taxi and fractional ownership companies [2][3][4]. Differently from the traditional commercial airlines these services are oriented to individual customers and do not work with pre-scheduled flights.…”

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confidence: 99%

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Mathematical modeling in the airline industry: optimizing aircraft assignment for on-demand air transport

Munari¹

2017

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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Abstract. This paper addresses a problem faced by air companies that offer on-demand flight services. Given a list of flight requests, the company has to assign its aircrafts to these requests, so that operational costs are minimized. The main issue in this planning process regards the repositioning of aircrafts when they are not available at the airports of customer departure. The cost of this repositioning should be the least possible, as customers pay proportionally to their requested flights only. We propose an optimization model to support decision making in these situations. Computational experiments with real-life data provided by an on-demand air transport company indicate that the proposed model is appropriate and may significantly reduce the time spent on repositioning flights.Keywords. airline industry, aircraft assignment, mathematical model, optimization. IntroduçãoThe airline industry is well known by its complexity and costly activities. To run efficiently, an air company must plan its operations very carefully, from aircraft choices to ticket prices. This need for efficiency has become even stronger in the last years, due to an increasing in competitiveness and to the current economic crisis. As a result, air companies are recurring to scientific methods to support decision making. Mathematical models and computational methods have became a must in their planning process [1,2].Another phenomenon observed in the last years concerns the increasing of on-demand air transport services, mainly represented by air taxi and fractional ownership companies [2][3][4]. Differently from the traditional commercial airlines these services are oriented to individual customers and do not work with pre-scheduled flights. Customers impose their departure times and airports and the company has to assign aircraft and crew to each customer request or to a group of them. The flights are point-to-point, outside hub airports and allow around six passengers. In per-seat services, the customer buys a single seat on the flight, while in per-aircraft services the customer gets the whole aircraft.In this paper, we address the aircraft allocation problem that arises in the planning process of per-aircraft on-demand air transport services. This research have been motivated by a case study developed with an air company that offers this service to European

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Applications and classifications of unmanned aerial vehicles: A literature review with focus on multi-rotors

2022

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During the past two decades, with the advancement of avionics, control systems, design, product methods, and communication systems, UAVs have gained more interest from both civil and military customers. Hence, more researchers have dedicated their time to developing new applications for drones and improving their performance. In this study, a literature review on drone applications is conducted. It is explained that they can be more effective and beneficial when merged with preexisting systems, and thus making a system of systems. Further, we have classified UAV applications more comprehensively. This classification can be very useful for providing insights when designing new UAVs. Finally, previous works are discussed thoroughly and diagrams are developed to show the research focus in this field. These statistical diagrams can also be used as a gap analysis tool.

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Development of an Aircraft Routing System for an Air Taxi Operator

Cited by 5 publications

References 34 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

Mathematical modeling in the airline industry: optimizing aircraft assignment for on-demand air transport

Applications and classifications of unmanned aerial vehicles: A literature review with focus on multi-rotors

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