Airports Metrics: A Big Data Application For Computing Flights' Performance Indexes Based On Flown Trajectories

A research line of the AIRPORTS Project, a partnership between Boeing Research and Technology-Europe (BR&TE) and several Spanish institutions, is focused on the measurement and assessment of performance indicators involved in ATM systems from surveillance data. As primary source of information we have different ADS-B (Automatic Dependent Surveillance - Broadcast) providers and, possibly, other sources that can enrich the raw data with other flight-related information. Previous work has already proposed and described a Big Data-based architecture, referred to as AIRPORTS DL, to manage in a scalable way the huge available collection of data. The conceptual data model is built around a sequence of ADS-B messages to reconstruct flight trajectories and, if possible, relates each trajectory with the departure and arrival airports, the aircraft being used, the corresponding airline or its flight-plan. In this paper, we describe a first attempt to develop an end-user application under the AIRPORTS DL framework. The application computes different metrics or performance indexes that depend only on the flown trajectory (e.g., traffic density, peak load or number of conflicts). Details about the proposed workflow for computing in advance these metrics are given and then, some examples of computed metrics for reference volumes (ATC sectors, FIR regions or ASMA circles around major airports) of the Spanish airspace during the year 2016 are used to illustrate novel visualization components in the AIRPORTS dashboard.