• Project ID START
  • Project duration 2020-05-01 > 2022-10-31
  • Cost
    • Total EUR 1,999,411.25
    • EU Contr. EUR 1,999,411.25
  • Status Ongoing


Stable and resilient ATM by integrating Robust airline operations into the network

One of the key enablers of Trajectory Based Operations (TBO) is the automated updating of trajectories in reaction to developing uncertainties. However, a high frequency of updates and modifications leads to degraded system stability. The overall goal of START (a Stable and resilienT ATM by integrAting Robust airline operations into the neTwork) is to develop, implement, and validate optimisation algorithms for robust airline operations that result in stable and resilient ATM performance even in disturbed scenarios. 

START’s goal shall be reached by a suitable combination of methods from applied mathematics, i.e.: mathematical optimisation, optimisation under uncertainty, Artificial Intelligence (AI) and data science, as well as algorithm design. Furthermore, insight into the uncertainties relevant in TBO systems will be gained through simulations. The main focus of the project is the optimization of conventional traffic situations while considering disruptive weather events such as thunderstorms.  Specific goals include:

  1. To model uncertainties at the micro (trajectory) level, assimilate observations (via ADSB/Radar) every 15 min and propagate trajectory uncertainties using assimilated models and a stochastic trajectory predictor. 
  2. To model uncertainties at the macro (ATM network) level, assimilate observations (satellite data for storm, and network status) every 15 min., and propagate ATM network uncertainties using the assimilated models. 
  3. To develop an Artificial Intelligence (AI) algorithm capable of generating a set of pan-European (i.e., considering the whole traffic over Europe) robust trajectories that make the European ATM system resilient when facing these relevant validate ties. 
  4. To implement those algorithms as an advanced fight dispatching demo functionality for airspace users to obtain robust trajectories.
  5. To validate these concepts through system-wide simulation procedures in order to evaluate their stability.


Artificial Intelligence to increase air safety in the face of storms


Universidad Carlos III de Madrid (Coordinator)

Universitat Politècnica de Catalunya

İstanbul Teknik Üniversitesi

École nationale de l'aviation civile


Deutsches Zentrum für Luft- und Raumfahrt e.V

Boeing Deutschland GmbH

This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 893204

European Union