Analysis of stakeholder benefits of NextGen Trajectory-Based Operations

Calderon-Meza, Guillermo; Sherry, Lance

doi:10.1109/icnsurv.2010.5503242

Cited by 3 publications

(4 citation statements)

References 4 publications

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“…Furthermore, due to the high degrees of freedom available in flight plan route selection and the varying constraints in the NAS, flight plan route selection can contribute to the stochasticity and performance of the NAS [2]. In the past efforts have been made to analyze benefits direct routing and free flights [1,3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the contribution of flight plan route selection to delays and conflicts

Belle¹,

Sherry²

2011

2011 Integrated Communications, Navigation, and Surveillance Conference Proceedings

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The absence of predictability of flight operations in the National Airspace System (NAS) is a significant source of excess cost, requiring airlines to pad flight schedules, staff for worst-case scenarios, and build and maintain mitigation plans and equipment. Flight plan routes are selected by airlines to optimize their operations (e.g. minimize crew time, fuel burn and delays). In the absence of coordination of 4-D flight plan route selection, flights can converge at the intersection of the flight plan routes, creating delays and fluctuations in Air Traffic Control (ATC) workload. Furthermore, due to the high degrees of freedom available in flight plan route selection and the varying constraints in the NAS, flight plan route selection can contribute to the stochasticity of the NAS. This paper evaluates the role of flight plan route selection in the stochasticity and performance of the NAS. One hundred simulations were run using Reorganized Air Traffic Control (ATC) Mathematical Simulator (RAMS). For every run, flights were randomly assigned flight plan routes.The results indicated that by randomly varying flight plan routes for 32% of the flight, the overall total delay had a standard deviation of 6849 minutes about the mean total delay of 161358 minutes The maximum total delay was 174559 minutes (8% above the mean) and the minimum total delay was 141876 (12% below the mean). The total number of en-route conflicts had a standard deviation of 201 about a mean of 29202 conflicts. The maximum number of conflicts recorded was 29751 (2% above the mean) and the minimum number of conflicts recorded was 28760 (2% below the mean). There was no correlation between the number of en-route conflicts and the total delays though the variance in total delays was more than en-route conflicts. An analysis of conflicts showed that about 80% of the conflicts were between flights flying in opposite direction to each other; about 15% were between flights flying in same direction, and the remaining 5% were between flight flying in perpendicular to each other.

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Section: Introductionmentioning

confidence: 99%

Analysis of the contribution of flight plan route selection to delays and conflicts

Belle¹,

Sherry²

2011

2011 Integrated Communications, Navigation, and Surveillance Conference Proceedings

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“…Treatment 2 results in the wider range of improvement (up to 2.2 million gallons). In the absence of weather effects (e.g., no wind) saving of fuel can only come from selecting shorter paths to fly as shown in previous studies [12] [13]. Studying the routes selected by the airlines shows that the shortest path, i.e., the Great Circle Distance path between origin and destination, is one of the most frequently selected routes.…”

Section: Results For the Airlinesmentioning

confidence: 78%

“…Route selection is of little help for this metric under this level of demand. Previous studies with similar levels of demand [12] [13] showed that airlines selecting shorter paths reduce their delays and the total number of conflicts in the system as well as their fuel-burn, but not the congestion at destination airports.…”

Section: Results For the Airlinesmentioning

confidence: 94%

The Effects of Airline Adaptive Route Selection in NAS-Wide Performance

Calderon-Meza

Sherry

2010

10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference

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NAS-wide simulations are used to evaluate concepts of operations, technologies, and their cost/benefits. When modeling stakeholder behavior, users of state-of-the-art NAS-wide simulators must encode decision-making in fixed sets of rules before executing the simulations. Adaptability and evolution in stakeholder decision-making is a next step to accommodate progressively realistic modeling of the NAS. This paper introduces adaptable behavior for airlines into a NAS-wide simulation tool. Adaptability is achieved by the application of Reinforcement Learning and the concept of domination to compare performance of multi-valued functions. The paper studies the effects on the NAS of adaptable route selection behavior of airlines in the presence of local and system-wide historic performance information. The results show the effectiveness of adaptive route selection in improving NAS-wide performance (even) when all agents seek use of the same resources simultaneously. It is also effective when the airlines have only information about their own past and current performance and do not have access to system-wide information. This effectiveness results in benefits for multiple stakeholders. The implications of these results are discussed.

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“…Currently, aircraft do not normally fly great circle routes because of sector route structures, and they may also be subject to delay – e.g., stacking because of airport capacity limits. The excess distances flown by aircraft have been the subject of considerable research interest, e.g., Magill (1998) and Calderon-Meza and Sherry (2010) for European and USA flights respectively. Fuel's contribution to the total costs incurred obviously varies with the relative price of jet kerosene compared to other operational costs.…”

Section: Fuel Efficiency Killer Appsmentioning

confidence: 99%

4D-Trajectory Air Traffic Management: Are There ‘Killer Apps’? – Part 2

Brooker

2012

J. Navigation

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The USA and Europe are developing plans -NextGen and SESAR -to transform the processes of Air Traffic Management (ATM). These will improve safety and efficiency, and match predicted increases in air transportation demand. They use advanced networking technology updated with information from satellite navigation and digital non-voice communication. The strategic goal, envisaged for 15-20 years hence, is a new ATM paradigm. Aircraft would fly on Four-Dimensional (4D) trajectories, incorporating altitude, position, time, and other aircraft positions and vectors. This vision would involve extremely large investments from the airline industry and ATM service providers. Thus, development priorities need to be based on sound business cases. But will these necessarily lead to the strategic vision of a 4D-trajectory system? Will the changes in practice be limited to a series of short and medium term operational improvements rather than strategic improvements? So, are there 'Killer Apps' for 4D-trajectory ATM? 'Killer App(lication)s' is jargon for innovations so valuable that they prove the core value of some larger technology. Killer Apps generate high degrees of stakeholder technical and financial cooperation. Ironically, most past ATM Killer Apps have improved safety, e.g., modern radar data processing led to collision avoidance systems. The analysis here attempts to identify and then size potential 4D-trajectory ATM Killer Apps. The evidence for Killer Apps has to pass key tests. Killer Apps obviously have to offer enormous benefits to stakeholders in the context of the potential costs. The bulk of these benefits must not be obtainable through technologically 'cut down' non − 4D-trajectory versions. Part 1 of this paper (Brooker, 2012a) sets out the framework for investigating these questions.

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Analysis of stakeholder benefits of NextGen Trajectory-Based Operations

Cited by 3 publications

References 4 publications

Analysis of the contribution of flight plan route selection to delays and conflicts

Analysis of the contribution of flight plan route selection to delays and conflicts

The Effects of Airline Adaptive Route Selection in NAS-Wide Performance

4D-Trajectory Air Traffic Management: Are There ‘Killer Apps’? – Part 2

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