High performance computing simulator for the performance assessment of trajectory based operations

High performance computing (HPC), both at hardware and software level, has demonstrated significant improve- ments in processing large datasets in a timely manner. However, HPC in the field of air traffic management (ATM) can be much more than only a time reducing tool. It could also be used to build an ATM simulator in which distributed scenarios where decentralized elements (airspace users) interact through a centralized manager in order to generate a trajectory-optimized conflict-free scenario. In this work, we introduce an early prototype of an ATM simulator, focusing on air traffic flow management at strategic, pre-tactical and tactical levels, which allows the calculation of safety and efficiency indicators for optimized trajectories, both at individual and network level. The software architecture of the simulator, relying on a HPC cluster of computers, has been preliminary tested with a set of flights whose trajectory vertical profiles have been optimized according to two different concepts of operations: conventional cruise operations (i.e. flying at constant altitudes and according to the flight levels scheme rules) and continuous climb cruise operations (i.e., optimizing the trajectories with no vertical constraints). The novel ATM simulator has been tested to show preliminary benchmarking results between these two concepts of operations. The simulator here presented can contribute as a testbed to evaluate the potential benefits of future Trajectory Based Operations and to understand the complex relationships among the different ATM key performance areasPeer ReviewedPostprint (published version

Formulating the cognitive design problem of air traffic management

Evolutionary approaches to cognitive design in the air traffic management (ATM) system can be attributed with a history of delayed developments. This issue is well illustrated in the case of the flight progress strip where attempts to design a computer-based system to replace the paper strip have consistently been met with rejection. An alternative approach to cognitive design of air traffic management is needed and this paper proposes an approach centred on the formulation of cognitive design problems. The paper gives an account of how a cognitive design problem was formulated for a simulated ATM task performed by controller subjects in the laboratory. The problem is formulated in terms of two complimentary models. First, a model of the ATM domain describes the cognitive task environment of managing the simulated air traffic. Second, a model of the ATM worksystem describes the abstracted cognitive behaviours of the controllers and their tools in performing the traffic management task. Taken together, the models provide a statement of worksystem performance, and express the cognitive design problem for the simulated system. The use of the problem formulation in supporting cognitive design, including the design of computer-based flight strips, is discussed

Increasing resilience of ATM networks using traffic monitoring and automated anomaly analysis

Systematic network monitoring can be the cornerstone for the dependable operation of safety-critical distributed systems. In this paper, we present our vision for informed anomaly detection through network monitoring and resilience measurements to increase the operators' visibility of ATM communication networks. We raise the question of how to determine the optimal level of automation in this safety-critical context, and we present a novel passive network monitoring system that can reveal network utilisation trends and traffic patterns in diverse timescales. Using network measurements, we derive resilience metrics and visualisations to enhance the operators' knowledge of the network and traffic behaviour, and allow for network planning and provisioning based on informed what-if analysis

Promoting Public Health and Safety: A Predictive Modeling Software Analysis on Perceived Road Fatality Contributory Factors

Extensive literature search was conducted to computationally analyze the relationship between key perceived road fatality factors and public health impacts, in terms of mortality and morbidity. Heterogeneous sources of data on road fatality 1970-2005 and that based on interview questionnaire on European road drivers’ perception were sourced. Computational analysis was performed on these data using the Multilayer Perceptron model within the dtreg predictive modeling software. Driver factors had the highest relative significance. Drivers played significant role as causative agents of road accidents. A good degree of correlation was also observed when compared with results obtained by previous researchers. Sweden, UK, Finland, Denmark, Germany, France, Netherlands, and Austria, where road safety targets were set and EU targets adopted, experienced a faster and sharper reduction of road fatalities. However, Belgium, Ireland, Italy, Greece and Portugal experienced slow, but little reduction in cases of road fatalities. Spain experienced an increase in road fatalities possibly due to road fatalities enhancing factors. Estonia, Slovenia, Cyprus, Hungry, Czech Republic, Slovakia and Poland experienced a fluctuating but decreasing trend. Enforcement of road safety principles and regulations are needed to decrease the incidences of fatal accidents. Adoption of the EU target of -50% reductions of fatalities in all countries will help promote public health and safety

Noise load management at Amsterdam Airport Schiphol

Amsterdam Airport Schiphol is one of the five primary hub-airports in Europe. All flight movements are controlled by Air Traffic Control the Netherlands (LVNL), whose main objective is to guarantee safety, efficiency, and protection of the environment, that includes noise load. To this end, a number of enforcement points is located in the vicinity of Schiphol. Each aircraft movement contributes to the noise load at these points. If the cumulative load in an aviation year at an enforcement point exceeds its maximum, the civil aviation authority may impose severe sanctions, such as fines, or a reduction in the number of aircraft movements. The latter is a typical restriction for Schiphol.\ud Runway selection is carried out via the preference list, an ordered set of runway combinations such that the higher on the list a runway combination, the better this combination is for maintaining the noise load limit. The highest safe runway combination in the list will actually be used. This paper has formulated the preference list selection process in the mathematical framework of Stochastic Dynamic Programming that enables determining an optimal strategy for preference list selection taking into account future and unpredictable weather conditions, as well as safety and efficiency restrictions

Multiobjective Tactical Planning under Uncertainty for Air Traffic Flow and Capacity Management

We investigate a method to deal with congestion of sectors and delays in the tactical phase of air traffic flow and capacity management. It relies on temporal objectives given for every point of the flight plans and shared among the controllers in order to create a collaborative environment. This would enhance the transition from the network view of the flow management to the local view of air traffic control. Uncertainty is modeled at the trajectory level with temporal information on the boundary points of the crossed sectors and then, we infer the probabilistic occupancy count. Therefore, we can model the accuracy of the trajectory prediction in the optimization process in order to fix some safety margins. On the one hand, more accurate is our prediction; more efficient will be the proposed solutions, because of the tighter safety margins. On the other hand, when uncertainty is not negligible, the proposed solutions will be more robust to disruptions. Furthermore, a multiobjective algorithm is used to find the tradeoff between the delays and congestion, which are antagonist in airspace with high traffic density. The flow management position can choose manually, or automatically with a preference-based algorithm, the adequate solution. This method is tested against two instances, one with 10 flights and 5 sectors and one with 300 flights and 16 sectors.Comment: IEEE Congress on Evolutionary Computation (2013). arXiv admin note: substantial text overlap with arXiv:1309.391