The cost of delays was estimated as $ 33 billion only in 2019 for the US National Airspace System (NAS), a peak value following a growth trend in past years. Aiming to address this huge inefficiency, we designed and developed a novel Data Analytics (DA) and Machine Learning (ML) system, which aims at reducing delays by proactively supporting re-routing decisions.Given a time interval up to a few days in the future, the system predicts if a reroute advisory for a certain Air Route Traffic Control Center (ARTCC) or for a certain advisory identifier will be issued, which may impact the pertinent routes. To deliver such predictions, the system uses historical reroute data, collected from the System Wide Information Management (SWIM) data services provided by the FAA, and weather data, provided by the US National Centers for Environmental Prediction (NCEP), part of the National Oceanic and Atmospheric Administration (NOAA). The data is huge in volume, and has many items streamed at high velocity, uncorrelated and noisy. The system continuously processes the incoming raw data and makes it available for the next step where an interim data store is created and adaptively maintained for efficient query processing. The resulting data is fed into an array of ML algorithms, which compete for higher accuracy. The best performing algorithm is used in the final prediction, generating the final results. Mean accuracy values higher than 90% were obtained in our experiments with this system.Our algorithm divides the area of interest in units of aggregation and uses temporal series of the aggregate measures of weather forecast parameters in each geographical unit, in order to detect correlations with reroutes and where they will most likely occur. Aiming at practical application, the system is formed by a number of microservices, which are deployed in the cloud, making the system distributed, scalable and highly available. We implemented a web-based prototype client application that is integrated with Boeing’s world-wide popular flight planning tool, ForeFlight®Due to its unique features, this system provides increased situational awareness and operational insights to airline managers and Air Navigation Service Providers (ANSPs). With this system, airline managers can perform more accurate strategic and tactical operations planning and decision making, which result in time and fuel savings for airlines. The ANSPs are likewise able to plan and re-plan more accurately the flight routes, leading to more efficient utilization of airspace and airport capacities.


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    Titel :

    Reroute Prediction Service


    Beteiligte:


    Erscheinungsdatum :

    01.10.2023


    Format / Umfang :

    1777431 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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