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Airspace Architecture Study proposed the future Single European Airspace System, based on modern technologies that could divide the air traffic service provision from local infrastructure for data provision, enabling the decoupling of geographical location from the service provision. This decoupling would enable virtualisation where service providers could use data from the common data services, opening doors to different organisation of air traffic service provision, namely more advanced capacity sharing. Virtualisation concept is still under development and several recent studies evaluated some aspects of virtualisation in ATM, but did not yet address in detail the impacts of different Virtual Centre implementation scenarios. In this paper, we propose a linear optimisation model to evaluate the impact of virtualisation and capacity sharing in terms of delay reduction. We show that taking into account the current airspace design and air traffic management resources, even the air navigation service providers that accumulate the highest capacity-caused delays could decrease those in the range of 25-50% up to about 80% through internal collaboration. Furthermore, the decrease of over 50% of the total capacity- caused delays could be obtained if FABEC1 were to form a Virtual Centre, and the decrease of about 90% of the total European delay if the Single European Sky (SES) area would form a Virtual Centre. The analysed capacity sharing collaborations indicate the possibility of significant delay reductions, but would not be sufficient, on their own, to eliminate capacity-caused issues in Europe.

This paper extends the use of peak-load pricing (PLP) to the context of the European Air Traffic Management system, as EU regulation No 391/2013 allows the modulation of en-route charges to avoid network capacity-demand imbalance in a specific area or on a specific route at specific times. In particular, we propose a centralised approach to PLP (CPLP) where a Central Planner (CP) is responsible for setting en-route charges on the network and Airspace Users (AUs) assess the routing of each flight. Set en-route charges should guarantee that air navigation service providers (ANSPs) are able to recover their operational costs, and that AUs perform their flights avoiding imbalances between demand and available airspace capacity. Like in the current charging system, in CPLP AUs react to en-route charges (which are imposed by CP instead of ANSPs) by choosing alternative and cheaper routes. Hence, we model this relationship between the CP and the AUs as a Stackelberg game where a leader (CP) makes his/her decision first, with complete knowledge on how the follower(s) (AUs) would react to it. The Stackelberg equilibrium is obtained by means of an optimisation problem formulated as a bilevel mixed-integer linear programming model, where the CP sets, for each ANSP, one peak and one off-peak en-route charge and the AUs make their routing choice. Preliminary results on real data instances on a regional scale are presented., European Journal of Transport and Infrastructure Research, Vol 17 No 1 (2017)

TSL 2017 - Transportation Science and Logistics, Chicago, ETATS-UNIS, 26-/07/2017 - 29/07/2017; In this work, we introduce SOSTA for the Simultaneous Optimization of the SloT Allocation for a network of airports. Currently, twice a year, each main airport allocates its slots and then, at a IATA conference, negotiations and slot exchanges alleviate the possible mismatch between requests and allocations. By reproducing the current regulations and best practice, SOSTA allows the slot allocation for an entire network of airports. Using real data, our experimental analysis shows that SOSTA can deal with all the European airports within a good computational time. Moreover, it can be used as a scenario analysis tool to assess the impact of difference policies, as for example the elimination of grandfather rights.

Introduction to the Special Issue on Long Term and Innovative Research based on papers selected from the fourth SESAR Innovation Days conference hosted by Universidad Politecnica de Madrid, Spain, from 25th to 27th November 2014.

Peak-load pricing (PLP), a two-tariff pricing scheme commonly used in public transport and utilities, is tested on the European Air Traffic Management (ATM) system as a means for reducing airspace congestion. In particular, a centralised approach to PLP (CPLP) where a Central Planner (CP) sets en-route charges on the network is presented. CPLP consists of two phases: in the first phase congested airspace sectors and their peak and off-peak hours are identified; in the second phase the CP assesses and sets en-route charges in order to reduce the overall shift on the network, where shift is intended as the difference between the actual and the scheduled flight departure times. Such charges should guarantee that Air Navigation Service Providers (ANSPs) are able to recover their operational costs while inducing the Airspace Users (AUs) to route their traffic in such way that the network is able to sustain it. The interaction between CP and AUs is modelled as a Stackelberg game and formulated by means of bilevel linear programming. A Genetic Algorithm is used to solve the CPLP model based on a dataset obtained from historical data for an entire day of traffic on the entire European airspace (approximately 30,000 flights). GAs are very popular stochastic optimization methods and are particularly suitable for solving multi-objective problems and finding reasonably good trade-off solutions. Results show that significant improvements in traffic distribution in terms of both shift and sector load can be achieved through this simple en-route charges modulation scheme. We model the relationship between the CP and the AUs as a Stackelberg game where the leader (CP) has a comprehensive knowledge on the entire system and makes his decision first, to which the follower(s) (AUs) must react. The Stackelberg equilibrium is obtained by means of an optimisation problem formulated as a bilevel linear programming model where the CP sets one peak and one off-peak en-route charge and the AUs choose the route among the available alternatives.

ACCESS (www.access-sesar.eu) is a SESAR WPE research project that addresses the study of market-based mechanisms for airport slot allocation from the perspective of agent-based computational economics. In this paper, we present the airport slot allocation simulation model developed by ACCESS and we apply it to the evaluation of primary slot auctioning in a multi-airport scenario. We show how combinatorial price-setting auctions can be used to balance capacity and demand in a decentralized manner, without the need for airlines to disclose sensitive information, so that the available capacity is used by those airlines able to make best economic use of it. The end prices of the auction reveal the economic value of each slot.

The present work lays down the roadmap for a Ph.D. research on methods for redistributing traffic demand through pricing policies in European airspace. First, the authors introduce a classification framework for pricing schemes in network industries. The framework is then applied for identifying relevant characteristics that a pricing scheme for European airspace should have. Finally, some guidelines are drawn on which pricing approaches in other industries may be suitable for each of the delineated configurations.

Current strategic decisions involving air traffic flows are limited to the allocation of airport slots. In this work, a first strategic market-based mechanism for the allocation of en route resources, i.e., sector capacity, is proposed. Identifying en route capacity shortages at this phase can lead to strategic actions to reduce flight delays on the day of operations. Tradable mobility permits previously developed for roadway transportation are analyzed and adapted to the air transport case. A trading mechanism for the strategic alleviation of air traffic congestion that uses time-place specific permits is proposed, providing alternative implementations. We call this new approach Tradable Flight Permit System (TFPS). An example of its use is illustrated, showing how it can lead to cost reductions for the airlines competing for a single sector access permit. We also highlight the improvements it can provide compared to current practice and a variety of alternative methods.

We present a software tool (yet under development) for short and long-term civil aviation management in case of explosive volcanic eruptions. The tool covers the needs of stakeholders involved in civil aviation management and interested in taking decisions based on a range of possible tephra dispersal scenarios and/or ash dispersal forecasts. The GIS-based tool allows to display hazard and vulnerability information, overlap maps to and estimate expected impacts (airports disrupted, routes cancelled, etc.). We present the structure of the tool underlining the scientific background and technical aspects of each element. Hazard and vulnerability data are stored in a spatial database specifically designed to store deterministic and probabilistic data sources. The database has a central role for the risk management process, acting as a repository of maps to be used by the stakeholders for different purposes. To our knowledge, this is the first “ad hoc” database proposed to store information about tephra dispersal hazard and vulnerability. The tool allows to overlap hazard and vulnerability data and estimate expected impacts through spatially-based rules. Vulnerability and impact assessments are implemented by means of plug-ins embedded in the GIS friendly interface. The analysis has been automated for the European air traffic management during explosive eruptions. Results are relevant for the long-term risk assessment in the European area. Regarding short-term, we present an example of application during an explosive eruption at an active Icelandic volcano. This GIS-based tool improves civil aviation management by automating short and long-term analyses and making them faster and repeatable. Although this is only a prototype and still needs further development, the up-to-date work can be a relevant contribution to the scientific community.

Aircraft operators need some flexibility when executing flight operations such as taking off, landing or entering into a sector, because the exact time of these operations is often affected by uncertainty. We express this flexibility in terms of time windows which are periods of time assigned to flights under the agreement that when a flight performs all its operations within the corresponding time windows no downstream delay is caused to any other actor of the air traffic system. If some last minute inconveniences make a flight unable to meet its time windows, some delay may also be caused to other flights. Relying on simulated and real air traffic data of the European airspace, this paper shows that this additional delay can be significantly reduced if there is the opportunity to reallocate unused airport or sector capacity, especially when airlines collaborate by updating and disclosing their expected times of departure, arrival and entry into sectors.

The difficulty in synchronizing the activities of different actors and the existence of external constraints, e.g., weather conditions, usually produce some uncertainty on the exact time at which a flight operation can be executed. To cope with this uncertainty, aircraft operators need some flexibility when performing their flight operations, i.e., departing, arriving and flying through air sectors. We express this flexibility in terms of time windows, i.e, periods of time within which flight operations can be executed. The more flexible a flight is, the wider its time windows are. Time windows are centrally calculated and assigned to flights under the agreement that when a flight performs all its operations within the corresponding time windows, no downstream delay is caused to any other actor of the air traffic system. When a flight is unable to respect its time windows, some delay may also be caused to other flights. This paper investigates the effects on the system in terms of additional delay of the nonfulfillment of time windows at flight departures. It considers both airline collaboration and non-collaboration cases and proposes an algorithm that reduces this additional delay. This is achieved through the reassignment of capacity released by flights that are either delayed or have departed. We simulate a set of realistic instances where delays at departure are randomly assigned to flights after time windows have been determined. Our results show that the amount of additional delay generated by departure delays is limited, thus demonstrating the practical viability of the proposed approach.

This paper presents an ant colony optimization algorithm for allocating airport slots to flights. Slot allocation at origin and destination airports of each flight are not independent, and they must be coherent with flight durations. The algorithm is able to deal effectively with large instances: in very short CPU time, it allows to fulfil almost all flight requests for slots. Conversely, an exact approach already proposed in the literature only solves small and medium size instances, and with longer CPU times. Our results suggest that ant colony optimization may be preferred to exact optimization when large instances are to be solved, or when only a short CPU time is available for the solution process.

In Europe, all Air Navigation Service Providers (ANSPs) finance their activities by charging airlines using their airspace. These ‘en route charges’ usually account for a significant part of the cost of a flight, and they can therefore influence the route choice: airlines may decide to fly longer routes to avoid countries with higher charges. If ANSPs want to maximize their revenues, they must choose the optimal charge to impose on their airspace. We show that this optimal charge can be identified through a Network Pricing Problem (NPP) formulation in the form of Bilevel Programming where the leader (i.e. the ANSP) owns a set of arcs (the airways in its national airspace) and charges the commodities (i.e. the flights) passing through them. As the en route charges are proportional to a Unit Rate value fixed by the ANSP, we are able to apply a similar methodology as in the case of a single toll arc for the NPP. By exploiting the structure of the problem, we propose an exact algorithm to compute the optimal Unit Rate and apply it to a case study relying on real air traffic data and realistic flight cost figures., disponible à l'adresse suivante :http://www.icrat.org/downloads/bookofabstract.pdf, info:eu-repo/semantics/published

This paper develops a methodology to compare the economic suitability of different Air Traffic Management (ATM) scenarios using Fast-Time Simulations (FTS), from an airline perspective. So far, FTS was mainly used for preliminary assessment of the capacity- and safety-related effects of novel ATM concepts, with hardly any application concerning the economic implications of those concepts. As a novelty, we put forward a method to assess costs to airlines’ of a new ATM scenario, based on FTS outputs. We first discuss the relevant ATM-related airlines’ economic interests, and consequently identify the associated indicators. To provide consistency with the Single European Sky II requirements and specifications, we show that our approach is clearly aligned with the performance-based framework proposed by the Single European Sky ATM Research Programme (SESAR).Then we demonstrate the capabilities of the FTS to address economic aspects of an ATM scenario. We illustrate the methodology through a case study of different sectorisations of the Greek airspace. The results indicate that FTS allows for a detection of statistically significant airline cost differentials between alternative ATM scenarios.

This paper defines a set of temporal intervals, called time windows, which are defined prior to flight departure and constitute milestones to be met during the flight execution. The size of the time windows is variable as it reflects all known constraints, such as punctuality at destination, runway capacities or congested en-route areas that the flight will cross. Once a time window is defined, all the air traffic actors are committed to guarantee that flight operations, e.g. enter an airspace sector, depart from or arrive at an airport, are executed within the time window. We propose a two-step approach based on a mixed integer programming formulation. The first step determines a set of time windows such that the overall cost of delay is minimized. Then in the second step we choose the set of optimal time windows which also maximizes the overall time window size. In such a way, we provide to all air traffic stakeholders the largest degree of flexibility to perform their operations under the constraint that the minimum achievable delay is kept constant. We also gain information on the critical flights of the system: if the optimal width of a time window is equal to its minimum available value, any disruption that may cause the flight not to meet it may produce undesired downstream effects. Our preliminary computational experience based on small-scale random instances confirms that the flexibility granted to flights increases with the capacity while the system delay simultaneously decreases. We also show that when there is no congestion a non negligible share of small size time windows may exist, thus indicating the existence of bottlenecks and critical flights.