Analysis of Different Cost Functions in the Geosect Airspace Partitioning Tool

A new cost function representing air traffic controller workload is implemented in the Geosect airspace partitioning tool. Geosect currently uses a combination of aircraft count and dwell time to select optimal airspace partitions that balance controller workload. This is referred to as the aircraft count/dwell time hybrid cost function. The new cost function is based on Simplified Dynamic Density, a measure of different aspects of air traffic controller workload. Three sectorizations are compared. These are the current sectorization, Geosect's sectorization based on the aircraft count/dwell time hybrid cost function, and Geosect s sectorization based on the Simplified Dynamic Density cost function. Each sectorization is evaluated for maximum and average workload along with workload balance using the Simplified Dynamic Density as the workload measure. In addition, the Airspace Concept Evaluation System, a nationwide air traffic simulator, is used to determine the capacity and delay incurred by each sectorization. The sectorization resulting from the Simplified Dynamic Density cost function had a lower maximum workload measure than the other sectorizations, and the sectorization based on the combination of aircraft count and dwell time did a better job of balancing workload and balancing capacity. However, the current sectorization had the lowest average workload, highest sector capacity, and the least system delay

DEMAND-RESPONSIVE AIRSPACE SECTORIZATION AND AIR TRAFFIC CONTROLLER STAFFING

This dissertation optimizes the problem of designing sector boundaries and assigning air traffic controllers to sectors while considering demand variation over time. For long-term planning purposes, an optimization problem of clean-sheet sectorization is defined to generate a set of sector boundaries that accommodates traffic variation across the planning horizon while minimizing staffing. The resulting boundaries should best accommodate traffic over space and time and be the most efficient in terms of controller shifts. Two integer program formulations are proposed to address the defined problem, and their equivalency is proven. The performance of both formulations is examined with randomly generated numerical examples. Then, a real-world application confirms that the proposed model can save 10%-16% controller-hours, depending on the degree of demand variation over time, in comparison with the sectorization model with a strategy that does not take demand variation into account. Due to the size of realistic sectorization problems, a heuristic based on mathematical programming is developed for a large-scale neighborhood search and implemented in a parallel computing framework in order to obtain quality solutions within time limits. The impact of neighborhood definition and initial solution on heuristic performance has been examined. Numerical results show that the heuristic and the proposed neighborhood selection schemes can find significant improvements beyond the best solutions that are found exclusively from the Mixed Integer Program solver's global search. For operational purposes, under given sector boundaries, an optimization model is proposed to create an operational plan for dynamically combining or splitting sectors and determining controller staffing. In particular, the relation between traffic condition and the staffing decisions is no longer treated as a deterministic, step-wise function but a probabilistic, nonlinear one. Ordinal regression analysis is applied to estimate a set of sector-specific models for predicting sector staffing decisions. The statistical results are then incorporated into the proposed sector combination model. With realistic traffic and staffing data, the proposed model demonstrates the potential saving in controller staffing achievable by optimizing the combination schemes, depending on how freely sectors can combine and split. To address concerns about workload increases resulting from frequent changes of sector combinations, the proposed model is then expanded to a time-dependent one by including a minimum duration of a sector combination scheme. Numerical examples suggest there is a strong tradeoff between combination stability and controller staffing

Symbolic representation of scenarios in Bologna airport on virtual reality concept

This paper is a part of a big Project named Retina Project, which is focused in reduce the workload of an ATCO. It uses the last technological advances as Virtual Reality concept. The work has consisted in studying the different awareness situations that happens daily in Bologna Airport. It has been analysed one scenario with good visibility where the sun predominates and two other scenarios with poor visibility where the rain and the fog dominate. Due to the study of visibility in the three scenarios computed, the conclusion obtained is that the overlay must be shown with a constant dimension regardless the position of the aircraft to be readable by the ATC and also, the frame and the flight strip should be coloured in a showy colour (like red) for a better control by the ATCO

Improvements in sectorization optimizer within the dynamic airspace configuration concept

The Dynamic Airspace Configuration (DAC) concept goal is to create more flexible airspace designs and configurations as a way to improve airspace use and absorb the increasing traffic demand. This modifies the conception of an airspace comprised of fixed volumes to one using a bigger quantity of building blocks and/or flexible boundaries. This translates into an increase in the number of possible configurations, which results in the creation of a large-scale optimization problem. To tackle this problem, CRIDA developed a sectorization optimizer ¿SECTORIA¿ which ranks all the possible configurations for a defined time and airspace in terms of occupancy and selects the optimal one. The aim of this thesis is to progress the tool in order to bring it closer to an operational environment. In particular, an improvement in its capacity constraint is added in order to obtain optimal solutions in all cases. A post-processing tool is also developed to refine the optimizer results and obtain more accurate configuration plans. The validation of these improvements is then carried out in two use cases: current sectorization in Madrid ACC Route 1 and a DAC sectorization of the same airspace, considering the addition of vertical cuts. The samples of traffic used are corresponding to the dates June 22nd, July 3rd, August 3rd and February 13th, 2019. The first feature is validated comparing the results obtained with and without the improvement, whereas the post-processing tool results are compared with the configuration plan opened with the current airspace design on the days of study and with a blind test performed on a Subject Matter Expert (SME). Results from the first validation show a better handling of inevitable overload, leading SECTORIA to provide more feasible solutions. On the other hand, the post-processing tool shows promising results, showing improvements in ATC hours which can reach up to 30\%. Conclusions and future work are then described following the analysis of the results

Free Route Airspace for Efficient Air Traffic Management

Free route airspace is a new concept in airspace management that has emerged from the Single European Sky ATM Research program. The goal is to allow aircraft companies to freely plan their routes between predefined points, rather than force them to follow conventional pre-established routes. This mode of airspace management can short-en trajectories, reducing fuel consumption and environmental impact. However, intersection points in a free route airspace are “invisible” at a strategic level, which can increase traffic complexity, increase the workload on air traffic controllers under certain conditions, and indirectly affect flight safety and efficiency of air traffic management. This review examines the implementation of free route airspace and its effects on air traffic management efficiency, leading to suggestions for future research

Three Dimensional Sector Design with Optimal Number of Sectors

In the national airspace system, sectors get overloaded due to high traffic demand and inefficient airspace designs. Overloads can be eliminated in some cases by redesigning sector boundaries. This paper extends the Voronoi-based sector design method by automatically selecting the number of sectors, allowing three-dimensional partitions, and enforcing traffic pattern conformance. The method was used to design sectors at Fort-Worth and Indianapolis centers for current traffic scenarios. Results show that new designs can eliminate overloaded sectors, although not in all cases, reduce the number of necessary sectors, and conform to major traffic patterns. Overall, the new methodology produces enhanced and efficient sector designs

Methodology for Predicting Sector Capacity in Convective Weather Conditions

Convective weather conditions limit airspace capacity and increase the complexity of air traffic. Currently, air nav-igation service providers calculate sector capacity using air traffic controller workload as reference. The aim of the research is to propose a method for predicting sector capacity in convective weather using air traffic complexity model. In this proposal existing air traffic complexity model should be remodeled to enable finer resolution of com-plexity results. Also, the model should be upgraded with a new type of indicator showing aircraft-weather interactions. The adopted air traffic complexity model, in combination with the trajectory prediction model and the Weather En-semble Forecast, should be able to provide a statistical characterisation of sector capacity under impending convec-tive weather conditions