Effect of radii of exemption on ground delay programs with operating cost based cruise speed reduction

When a ground delay program (GDP) is defined, a radius of exemption is typically set to exclude from having to realize ground delay aircraft departing from greater distances than the selected radius distance. A trade-off exists when defining this radius: big radii distribute the required delay among more aircraft and reduce the airborne holding delay close to the destination airport, while the probability to realize unnecessary delay increases if the program is canceled before planned. In order to overcome part of this drawback, a cost based cruise speed reduction strategy aiming at realizing airborne delay was suggested by the authors in previous publications. By flying slower, at a specific speed, aircraft that are airborne can recover part of their initially assigned delay without incurring extra cost if the GDP is canceled before planned. In this paper, the effect of the exemption radius is assessed when applying this strategy and a case study is presented by analyzing all the GDPs that took place at Chicago O’Hare International Airport during one year. Results show that by the introduction of this technique, more delay can be saved. Thus, it is possible to define larger radii of exemption, reducing partially the drawbacks associated with smaller radii

ATFM airborne delays without extra fuel consumption in wind conditions

Air Traffic Flow Management (ATFM) regulations, such as ground holdings, are often canceled before their initially planned ending time. The ground delays impact on the cost of recovering part of the delay if the regulation is canceled, as aircraft are still at the origin airport. In previous publications, the authors have suggested a speed reduction strategy to split the assigned ATFM delay between ground delay and airborne delay. By flying at the the minimum speed that gives the same fuel consumption as initially planned, the airline can maximize the airborne delay without any extra fuel consumption. In this paper, the effect of wind on the amount of airborne delay is assessed and a case study of Chicago O’hare airport is presented. Results show that wind has a great effect on the airborne delay that can be achieved and that, in some cases, even tail winds might lead to an increase of airborne delay

Simulation of airborne ATFM delay and delay recovery by cruise speed reduction

Air Traffic Flow Management (ATFM) regulations, such as ground holdings, are often cancelled before their initially planned ending time. This early cancellation leads to an unnecessary ground delay and a misuse of airport or airspace resources. In previous publications, the authors have suggested a speed reduction strategy aiming at splitting the assigned ATFM delay between ground delay and airborne delay. If the aircraft flies at the minimum speed that gives the same fuel consumption as initially planned, the airline can maximise the airborne delay without any extra fuel consumption. If the regulation is cancelled before it was initially planned, the aircraft already airborne will be in a better position to recover part of the delay without incurring in additional fuel costs. In this paper, this speed reduction strategy has been simulated with the FACET tool for a whole day of flights inbound San Francisco airport (California). For each flight in the data set, it has been computed the maximum amount of airborne delay that can be performed. Moreover, the amount of delay that can be recovered has been also computed as a function of the time the regulation is cancelled. Preliminary results show, at first glance, a linear relationship between this cancellation time and the delay recovery which encourages as future work, to develop a parametric model of this delay recovery

An optimisation framework for aircraft operators dealing with capacity-demand imbalances in SESAR

This paper presents a framework for the negotiation phase that is foreseen in the new operational concept proposed in the Single European Sky Research (SESAR) program. In particular, this paper describes a possible strategy for the airspace users in order to deal with the Collaborative Decision Making (CDM) process that is expected in this future scenario. In the SESAR scenario, airspace users will become owners of their trajectories and they will be responsible to solve possible mismatches between capacity and demand in a particular airspace sector. The aim of this strategy is to improve the efficiency in the CDM process by computing the different operational costs associated to different solutions that may solve a particular demand-capacity imbalance in the airspace. This will allow them to optimise their operating costs while reducing fuel consumption and therefore being more environmentally friendly. Some suggestions have already been done for the CDM mechanism, for instance the use of auctions. However, the different options that aircraft operators might use have not yet been sufficiently investigated. In this paper, the authors propose an optimisation framework for aircraft operators aimed at computing 4D trajectories with time constraints to deal, in this way, with possible airspace regulations. Once a nominal flight plan and a potential regulation is known, it is suggested to compute several possible alternative flight plans (including rerouting, but also altitude and speed profiles) that may solve the capacity-demand problem. If more than one regulation is applied to the flight, a tree of options is subsequently computed. The cost of each optimised the option is also calculated in order to allow the airspace users to initiate the negotiation process with other airlines. Finally, a preliminary example is given at the end of this paper in order to better illustrate the proposed methodology

Fuel consumption assessment for speed variation concepts during the cruise phase

In recent years, some research studies in Air Traffic Management (ATM) have proposed the idea of adjusting the speed of aircraft for several applications, like for instance, conflict resolution, 4D trajectory management, and airspace capacity and demand balance. In this paper an initial assessment on how this kind of speed variations may affect to fuel consumption is presented. Only the cruise phase is considered and the relationships existing among different variables such as the speed, the flight level, the aircraft mass etc. are arisen. In addition, it is emphasised in what conditions a speed reduction strategy can be implemented without penalising the fuel consumption. Thence, it is shown that there is a range of speeds, lower than the nominal cruise speed, that do not suppose an increase in fuel consumption regarding the nominal block fuel. However, a certain sensibility with the selected Cost Index is identified. High values of the Cost Index allow more speed margin without a negative fuel impact, while low values of the Cost Index reduce the impact on fuel consumption in the case the nominal cruise speed is increased

An assesment for UAS traffic awareness operations

Technology evolution in the field of Unmanned Aircraft Systems (UAS) will affect the Air Traffic Management (ATM) performance regarding to new military and civil applications. UAS, as new airspace users, will represent new challenges and opportunities to design the ATM system of the future. The goal of this future ATM network is to keep intact (or improve) the network in terms of security, safety, capacity and efficiency level. On the other hand, most UAS are, at present, designed for military purposes and very few civil applications have been developed mainly because the lack of a regulation basis concerning their certification, airworthiness and operations. Therefore, UAS operations have always been solutions highly dependent on the mission to be accomplished and on the scenario of flight. The generalized development of UAS applications is still limited by the absence of systems that support the development of the actual operations. Moreover, the systematic development of UAS missions leads to many other operational risks that need to be addressed. All this elements may delay, increase the risk and cost in the implementation of a new UAS application

Domain-driven multiple-criteria decision-making for flight crew decision support tool

During the flight, the crew might consider modifying their planned trajectory, taking into account currently available information, such as an updated weather forecast report or the already accrued amount of delay. This modified planned trajectory translates into changes on expected fuel and flying time, which will impact the airline’s relevant performance indicators leading to a complex multiple-criteria decision-making problem. Pilot3, a project from the Clean Sky Joint Undertaking 2 under European Union’s Horizon 2020 research and innovation programme, aims to develop an objective optimisation engine to assist the crew on this process. This article presents a domain-driven approach for the selection of the most suitable multiple-criteria decision-making methods to be used for this optimisation framework. The most relevant performance indicators, based on airline’s objectives and policies, are identified as: meeting on-time performance, leading to a binary value in a deterministic scenario; and total cost, which can be disaggregated into sub-cost components. The optimisation process consists of two phases: first, Pareto optimal solutions are generated with a multi-objective optimisation method (lexicographic ordering); second, alternative trajectories are filtered and ranked using a combination of multi-criteria decision analysis methods (analytic hierarchy process and VIKOR). A realistic example of use shows the applicability of the process and studies the sensibility of the optimisation framework

Enhanced Demand and Capacity Balancing based on Alternative Trajectory Options and Traffic Volume Hotspot Detection

Nowadays, regulations in Europe are applied at traffic volume (TV) level consisting in a reference location, i.e. a sector or an airport, and in some traffic flows, which act as directional traffic filters. This paper presents an enhanced demand and capacity balance (EDCB) formulation based on constrained capacities at traffic volume level. In addition, this approach considers alternative trajectories in order to capture the user driven preferences under the trajectory based operations scope. In fact, these alternative trajectories are assumed to be generated by the airspace users for those flights that cross regulated traffic volumes, where the demand is above the capacity. For every regulated trajectory the network manager requests two additional alternative trajectories to the airspace users, one for avoiding the regulated traffic volumes laterally and another for avoiding it vertically. This paper considers that the network manager allows more flexibility for the new alternative trajectories by removing restrictions in the Route Availability Document (RAD). All the regulated trajectories (and their alternatives) are considered together by the EDCB model in order to perform a centralised optimisation minimising the the cost deviation with respect to the initial traffic situation, considering fuel consumption, route charges and cost of delay. The EDCB model, based on Mixed-Integer Linear Programming (MILP), manages to balance the network applying ground delay, using alternative trajectories or both. A full day scenario over the ECAC area is simulated. The regulated traffic volumes are identified using historical data (based on 28th July of 2016) and the results show that the EDCB could reduce the minutes of delay by 70%. The cost of the regulations is reduced by 11.7%, due to the reduction of the delay, but also because of the savings in terms of fuel and route charges derived from alternative trajectories

Pilot3: A crew multi-criteria decision support tool – Estimating performance indicators and uncertainty for tactical trajectory management

During a flight, when a change in the operational conditions arises (e.g., new updated weather forecast, delay at reaching a given waypoint), different alternative trajectories can be computed with dedicated optimisation or prediction systems. These systems usually produce trajectories with trade-offs between expected fuel usage and delay. The pilot, or the dispatcher, considers these expected values in order to decide how to tactically operate the aircraft. This approach has two main challenges. Firstly, it requires the translation of arrival delay into parameters which are relevant for the airlines, such as on-time performance and cost of delay. Secondly, uncertainties in the system need to be estimated, such as holding time at arrival, or taxi-in time. Both of these estimations (airlines performance indicators and uncertainty) rely on the airline staff expertise. Finally, the crew faces a multi-criteria decision process as different objectives (cost, on-time performance) and constraints need to be considered. The use of prior to the flight estimations, such as the cost index of the operational flight plan, might not be relevant at the moment of reassessing the flight, as the situation has evolved (for example, the number of passengers who can potentially miss their connections will depend on the status of the fleet of the airline). In other cases, this expected cost of delay could be estimated by the crew or the dispatchers, but generally it is difficult to internalise the dynamics of cost due to IROPS on passengers, or even to estimate the cost of a potential curfew at the end of the day. Uncertainties such as the expected holding delay, distance flown at the arrival TMA, or taxi-in time, might lead to sub-optimal decisions, such as recovering delay, using extra fuel, which does not translate into economic benefit, as larger holding than anticipated might lead to passengers still missing their connection; or shorter distances flown in the TMA means that speed-ups performed during the cruise were unnecessary. Pilot3, a Clean Sky 2 Research and Innovation action, sets out to overcome these issues by developing a multi-criteria support decision tool, which combines explicit estimation of key performance indicators and estimation of ATM operational parameters. These estimators will be developed incrementally, from simple heuristics to machine learning models. Pilot3 prototype comprises five sub-systems: * An Alternatives Generator, which will compute the different alternatives to be considered by the pilot; fed by two independent sub-systems: * Performance Indicators Estimator, which provides the Alternatives Generator with information on how to estimate the impact of each solution for the different performance indicators; * Operational ATM Estimator, which provides the Alternative Generator with information on how to estimate some operational aspects such as tactical route amendments, expected arrival procedure, holding time in terminal airspace, distance flown (or flight time spent) in terminal airspace due to arrival sequencing and merging operations, or taxi-in time; * Performance Assessment Module, which, considering the expected results for each alternative on the different KPIs, is able to filter and rank the alternatives considering airlines and pilots preferences; and * Human Machine Interface, which will present these alternatives to the pilot and allow them to interact with the system. Pilot3 is led by the University of Westminster with the Universitat Politecnica de Catalunya, Innaxis and PACE Aerospace Engineering and Information Technology as partners. The Topic Manager is Thales AVS France SAS. With support from the Advisory Board, Pilot3 has already identified the key operational performance indicators that crew should consider when tactically adjusting their trajectories (on-time performance and total cost, including fuel, IROPs and others); and a literature review and filtering process on multi-criteria decision making techniques has been conducted to select the most suitable method for the different phases of the optimisation process (trajectory generation, filtering and ranking of alternatives)

In-Flight Cost Index Optimisation Upon Weather Forecast Updates

This paper presents an optimisation framework to compute the altitude and speed profiles of a trajectory in the execution phase of the flight, such that the expected total cost (ETC) of the operation is minimised (i.e., modelling the expected cost of delay and fuel – including arrival uncertainties – at the arrival gate). This is achieved with a two-stage optimisation strategy: a trajectory optimiser that minimises a generalised direct operating cost function, for a given cost index; and an upper-level optimiser, which obtains the best cost index that minimises the ETC. Several case studies are presented for different departure delays, while considering the impact of two different weather forecast updates too: a region with relative high head-winds appearing half way across the flight; and a cold atmosphere scenario, with a tropopause altitude lower than standard conditions