An Introduction to Probability Theory and its Applications, Volume I

Increasing air traffic has resulted in the development of strategies such as continuous descent approaches (CDA). Using a computational environment called computational red teaming, complex traffic patterns are explored with the aim to identify underlying relationships in patterns leading to bottlenecks in the system. Ground events are considered in the evaluation of CDA. Co-evolutionary algorithms can identify distributions of arriving flights that lead to higher delays. In addition, the co-evolutionary search identified vulnerabilities in the CDA.

Discovering Delay Patterns in Arrival Traffic with Dynamic Continuous Descent Approaches Using Co-Evolutionary Red Teaming

at a specific node of the Air Traffic Management (ATM) network, but it does not allow controlling the distribution of delay assignment and it does not take into account traffic conditions elsewhere in the network. Optimization and prioritization add value compared to FCFS. The ATFM toolset applies optimization aiming for efficient regulations and, at the same time, controlling the distribution and assignment of pre-departure imposed delays. This is accomplished by optimizing towards a weighted minimum of average delay and spread of delay per network node. Delay assignment per flight is accomplished by selecting the most penalized node of a flight along its flightpath. Prioritization is added as a relative weight factor during optimization. Prioritization may serve several objectives each with the purpose to add weight to a flight representing its specific condition regarding either network throughput or economic value. An example of prioritizing network throughput is to prioritize all flights to and from a disrupted airport with the aim to avoid penalizing an airport already struggling with capacity problems, and an example of priority by economic value is allowing Airline Operators to prioritise specific flights at a specific cost. They will receive priority but balanced against the performance of the ATM network. The tool to process imposed delays is ready as a prototype and is used for a number of validation exercises all running basically on one scenario. The applicable scenario is a European enlarged Core Area scenario of around 25.000 flights in 24 hours. The tool turns out to be robust under varying operational conditions and varying levels of disruption. To evaluate operational benefits, the ATFM results have to be processed on simulated operations, simulating the scenario in fast-time, and evaluating the impact of regulations on queuing and workload. This article describes the present status of research, mainly focused on the prototype of the ATFM tool, and future work, focused on fast-time simulation and validation. Also some early results of validated operational benefits are presented.

Optimizing and Prioritizing Air Traffic Flow Management in a European Scenario

The stochastic nature of air traffic management arises mainly from uncertain operational events This uncertainty may jeopardize the central flow management unit (CFMU) planning leading to safety problems and sub optimally used capacity An absorption area is defined as one or several free slots in the planning so that the management of uncertainty is easier Its aim is to compensate the aircraft uncertainty The issue is to use the free slots in order to absorb uncertainty, and so not modify the initial planning Finding the best configuration of the absorption areas corresponds to balancing optimally their size with the available capacity in order to absorb uncertainty and minimize "load loss" (unused capacity) This paper presents the initial results of slot allocation problem incorporating absorption areas: Under some elementary assumptions, the simulations show that, for whatever the rate of uncertainty is, the debit of traffic with absorption areas in slot allocation is always higher than without the absorption areas A theoretical model is attempted to bring the proof to these empirical results

/pdf/using-absorption-areas-to-improve-atfm-adyofm6z6y.pdf

Using absorption areas to improve ATFM

The Asia-Pacific (APAC) region is witnessing a surge in the demand for air traffic. Despite this growth, the absence of centralized Air Traffic Flow Management (ATFM) units presents a significant obstacle in executing tasks such as slot allocation to ensure demand and capacity balancing. This paper proposes a hierarchical multi-agent framework for automated demand and capacity balancing, resulting in slot allocation within the ATFM operations. Aligned with the multi-nodal ATFM (vATFM) concept, our proposal offers a coordinated approach to decision-making, aiming to streamline flight scheduling procedures. A heuristic algorithm is implemented based on the proposed frame-work to solve the demand-capacity balancing problem, using independent parallel decision-making to facilitate fairness among agents. Compared to a conventional peer-to-peer multi-agent design, the hierarchical approach results up to 100% better in a typical traffic scenario of APAC region and up to 400% better in a doubled traffic scenario. Our findings demonstrate the superiority of the hierarchical multi-agent framework over traditional frameworks, offer a promising approach to address the strategic slot allocation challenges in the ATFM operations.

A Hierarchical Multi-Agent Coordinated Decision-Making for Strategic Slot Allocation

Air traffic flow management (ATFM) is a service established with the objective of contributing to safe, orderly, and expeditious flow of air traffic. The ATFM is divided into three phases. (1) The strategic phase takes place between 18 month and seven days prior to the day of operation and includes research, planning and coordination activities. The output of this phase is the capacity plan for the following year. (2) The pre-tactical phase is applied during 6 days prior to the days of operation and consists of planning and coordination activities. The output is the ATFM daily plan. (3) The tactical phase is applied on the day of the operation. This phase updates the daily plan according to the actual traffic and capacity. The management of the traffic is achieved through slot allocation.

/pdf/a-new-slot-allocation-for-atfm-d4f1hr4k6a.pdf

A new slot allocation for ATFM

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A new slot allocation for ATFM

Using absorption areas to improve ATFM