The proposed concept

The overall objective of CADENZA (Advanced Capacity and Demand Management for European Network Performance Optimization) is to develop and validate a trajectory broker concept with different options for advanced capacity-demand balancing, aiming at a step-change improvement in network performance. Within the concept, we are acting simultaneously on three levers: capacity provision, temporal, and spatial distribution of demand, i.e., departure slots and flight paths, respectively. Compared to today’s situation, the CADENZA concept would reduce capacity requirements as well as ATFM delays with marginal negative impact on flight-efficiency and the environment. CADENZA builds upon the findings of previous SESAR exploratory research projects, especially COCTA and APACHE.

There are several ways to act on the three levers mentioned above. CADENZA will explore a range of options and compare their respective merits and drawbacks. In one of the options, CADENZA puts forward a paradigm shift in network management: the Network Manager acts as a (trajectory) broker between Airspace Users (AUs) and capacity providers to match air traffic demand and capacities in the network. This innovative trajectory broker concept is based on organisational and regulatory changes to support novel capacity and demand (network) management options. The trajectory broker balances capacity and demand through collaborative trajectory management (including a novel trajectory charging scheme) and a coordinated capacity provision process, which starts at the strategic level (up to one year in advance of the day of operation) and spans over the pre-tactical (several days before the day of operation) and the tactical level (day of operation). In the CADENZA network management, demand side and capacity side decisions are highly interlinked. To improve readability, in the following paragraphs the capacity management and the demand management elements of the concept are described separately.

On the capacity management side, the trajectory broker coordinates capacity provision in line with the expected temporal and spatial distribution of flights in the network. For the sake of illustration, we here sketch one possible option for the capacity management process from strategic to tactical level. At strategic level, the trajectory broker has reliable information on scheduled flights (approximately 80% of total demand) and a forecast on non-scheduled flights. This serves as a basis for the trajectory broker to assess the expected network performance and ask for capacity profiles to be provided from each air navigation service provider (ANSP) to accommodate anticipated traffic flows in the network. As the day of operations approaches, the trajectory broker adjusts the capacity requirements in line with updated information on demand and/or capacity. These capacity adjustments will depend on ANSPs' flexibility to adjust capacity at strategic, pre-tactical and tactical phases; after a certain point in time, further adjustments will not be possible for some ANSPs and the trajectory broker has to make its final capacity decision before that. On the other hand, depending on ANSP flexibility to provide services locally or cross-border (in neighbouring countries, at a larger regional level or in the entire network), the trajectory broker would have different options to call and/or allocate capacities where needed.

On the demand management side, the collaboration between the trajectory broker and the airspace users starts with an indication of flight intents, which may be as early as in the strategic phase, where only airport pair and schedule information are available. At this point, there is no precise and reliable information for (detailed) flight planning; nevertheless, indicating an early intent enables the trajectory broker to plan and coordinate capacity provision. At pre-tactical level flight planning with a low level of granularity becomes possible, and if the trajectory broker anticipates potential capacity shortages in the network, it can already incentivise airspace users to plan their flights in a way that avoids hotspots and uses other available capacities. There are different demand management options to incentivise demand earlier in the flight planning process to utilise available capacity, e.g. charges discounts to reward predictability for an early hotspot-avoiding-route commitment. At tactical level, airspace users have sufficient information to start their trajectory planning and the trajectory broker has better awareness of the network situation.

As one element of this collaborative trajectory management process, we foresee the introduction of a new trajectory charging scheme. Herein the trajectory broker uses a set of economic incentives to steer demand towards a more efficient use of available capacities in the network, as early as practical in the flight planning process. With updated information on available capacity (which may be affected by e.g. military zones activation or adverse weather), the trajectory broker incentivises airspace users to fine-tune their final trajectories in order to establish a “system-optimum” solution (network perspective). It should be noted that there are also different options to define the charging scheme, such as static, pre-defined charges for airport-pairs independent from planned/flown route or with incentives to use shortest routes. On the other end of the spectrum there is a fully dynamic trajectory-charging scheme with incentives set to influence airspace users' choices in such manner to maximise the desired impact on network performance.

In addition to the interactions outlined above, the trajectory broker fully takes into account airport capacities, creating additional information flows and coordination requirements. Consequently, the CADENZA concept is a comprehensive approach, covering all stakeholders involved in the provision of air transport services. In this sense, CADENZA has four major interrelated research blocks with feedback loops and stakeholder involvement in each block:

  1. Conceptual models: Selected TB concept and ADCB options from a range of variants;

  2. Mathematical models: Network Optimisation, AU and ANSP models and parameters;

  3. Baseline model for comparison: R-NEST baseline and benchmarking against CADENZA models;

  4. Assessment and feedback: Results comparison, stakeholder and SJU feedback.

Based on selected conceptual models (1), we proceed with CADENZA mathematical modelling (2), model testing and benchmarking against baseline for selected case studies (3) and conclude with results assessment and feedback (4). These steps include feedback loops: mathematical model development may require fine- tuning of conceptual models, benchmarking could reveal the need to update the mathematical model or some parameters, while results assessment may point out that case studies require modifications. Internal (CADENZA Consortium and Expert Panel) and external (Stakeholders and the SJU) thorough assessment of initial results (4) concludes the first research loop. Based on model testing and result comparison, conclusions and feedback, we start the final loop with the same research step and improved concept and models.