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This article presents a model for the economic value of extra capacity at an airport. The model is based on a series of functional relationships linking the benefits of extra capacity and the associated costs. It takes into account the cost of delay for airlines and its indirect consequences on the airport, through the loss or gain of aeronautical and non-aeronautical revenues. The model is highly data-driven and to this end a number of data sources have been used. In particular, special care has been used to take into account the full distribution of delay at the airports rather than its average only. The results with the simple version of the model show the existence of a unique maximum for the operating profit of the airport in terms of capacity. The position of this maximum is clearly dependent on the airport and also has an interesting behaviour with the average number of passenger per aircraft at the airport and the predictability of the flight departure times. In addition, we also show that there exists an important trade-off between an increased predictability and the punctuality at the airport. Finally, it is shown that a more complex behavioural model for passengers can introduce several local maxima in the airport profit and thus drive the airport towards suboptimal decisions. [ABSTRACT FROM AUTHOR]

Air Traffic Flow Management (ATFM) measures are often used to alleviate capacity demand imbalances. Usually, these measures impose a departure delay on flights crossing the airspace in question, where delay is assigned on a "First Planned First Served" (FPFS) base, which minimises total delay. Since delays typically have a different impact on individual flights in terms of cost, a procedure based on cost minimisation could reduce delay-related costs. User-Driven Prioritisation Process (UDPP) is developing a set of solutions aimed at allowing airlines to rearrange their flights within their own slots assigned by the FPFS rule. Inter-airline cost reducing approaches are still missing, but several works have been launched in this direction, using either central optimisations or market-based mechanisms. We analyse the impact of cost approximations procedures, integral part of certain inter-airline mechanisms, overall likely to be used by airlines or the Network Manager (that manages ATFM measures). Using cost models and simulations to collect the true cost of delay profiles, we show that the impact of cost approximations have been severely underestimated, leaving little room for new mechanisms to improve over UDPP. Moreover, we show that the errors made by the airlines on their own costs, expected at least for some airlines, further deteriorate the situation, including UDPP. However, we find that approximation procedures create a strong resilience to these errors, showing how both UDPP and inter-airline procedures may benefit from not having the airlines communicate their detailed costs. Thus, we find that any design of new mechanisms could include a cost approximation procedure in order to increase its resilience. • Air traffic flow management regulations impose delays and consequent flight costs. • Slot allocation based on delay cost minimisation might be beneficial for stakeholders. • Exploring approximation and errors of the cost of delay for flights in regulations. • Cost approximation reduces efficiency of inter-airline slot exchange mechanisms. • However, cost approximation is resilient to internal errors in the cost calculations. [ABSTRACT FROM AUTHOR]

This paper presents results from the SESAR ER3 Domino project. Three mechanisms are assessed at the ECAC-wide level: 4D trajectory adjustments (a combination of actively waiting for connecting passengers and dynamic cost indexing), flight prioritisation (enabling ATFM slot swapping at arrival regulations), and flight arrival coordination (where flights are sequenced in extended arrival managers based on an advanced cost-driven optimisation). Classical and new metrics, designed to capture network effects, are used to analyse the results of a micro-level agent-based model. A scenario with congestion at three hubs is used to assess the 4D trajectory adjustment and the flight prioritisation mechanisms. Two different scopes for the extended arrival manager are modelled to analyse the impact of the flight arrival coordination mechanism. Results show that the 4D trajectory adjustments mechanism succeeds in reducing costs and delays for connecting passengers. A trade-off between the interests of the airlines in reducing costs and those of non-connecting passengers emerges, although passengers benefit overall from the mechanism. Flight prioritisation is found to have no significant effects at the network level, as it is applied to a small number of flights. Advanced flight arrival coordination, as implemented, increases delays and costs in the system. The arrival manager optimises the arrival sequence of all flights within its scope but does not consider flight uncertainties, thus leading to sub-optimal actions. • Micro-level agent-based model capture interactions at ECAC-wide level. • Use of new metrics to capture network effects. • 4D trajectory adjustment reduces costs, and delays for connecting passengers • Flight prioritisation found not to have significant effect at network level. • Advanced flight arrival coordination, as implemented, increase delays and costs. [ABSTRACT FROM AUTHOR]

This article highlights the importance of uncertainty in day-to-day operations, and the need to take it into account to properly assess the cost of delay for airspace users. It defines a cost of uncertainty and estimates it using real data. It provides some easily computable models based on the average and standard deviation of delay to estimate the cost of delay in general. The article shows that uncertainty is also important in the formulation of buffers for airlines and provides a simple model to estimate the optimal assignment, further using real data to compute the optimal value at different airports. [ABSTRACT FROM AUTHOR]

This article presents a new, holistic model for the air traffic management system, built during the Vista project. The model is an agent-driven simulator, featuring various stakeholders such as the Network Manager and airlines. It is a microscopic model based on individual passenger itineraries in Europe during one day of operations. The article focuses on the technical description of the model, including data and calibration issues, and presents selected key results for 2035 and 2050. In particular, we show clear trends regarding emissions, delay reduction, uncertainty, and increasing airline schedule buffers. [ABSTRACT FROM AUTHOR]

In ATM systems, the massive number of interacting entities makes it difficult to identify critical elements and paths of disturbance propagation, as well as to predict the system-wide effects that innovations might have. To this end, suitable metrics are required to assess the role of the interconnections between the elements and complex network science provides several network metrics to evaluate the network functioning. Here we focus on centrality and causality metrics measuring, respectively, the importance of a node and the propagation of disturbances along links. By investigating a dataset of US flights, we show that existing centrality and causality metrics are not suited to characterise the effect of delays in the system. We then propose generalisations of such metrics that we prove suited to ATM applications. Specifically, the new centrality is able to account for the temporal and multi-layer structure of ATM network, while the new causality metric focuses on the propagation of extreme events along the system. • Need of network tools to characterise systemic effects of innovations in ATM networks. • Existing centrality and causality metrics are not suitable, we introduce new ones. • New centrality metric accounts for temporal multiplex structure of ATM networks. • New causality metric individuates channels of propagation of extreme disturbances. [ABSTRACT FROM AUTHOR]