Assessment of critical delay pattern and avalanche dynamics in the ATM system

Bernardo Monechi/“La Sapienza” University of Rome

PhD Candidate and Supervisors

Bernardo Monechi, "Sapienza" University of Rome
Vito D.P. Servedio, "Sapienza" University of Rome
Vittorio Loreto, "Sapienza" University of Rome, Institute for Scientific Interchange (ISI) Turin

Overview and Background

The importance of air transport has considerably grown in time, being nowadays an essential fast mean to connect national and international locations. In recent times the competition with other means of transportation, combined with the effects of the economical crisis, reduced the amount of traffic flying over the European Airspace. Nevertheless an increase of the traffic demand has been forecast in the coming years ^[1] ^[2], driven by new emergent economies outside Europe. The current Air Traffic Management system (ATM) has a higly complex and multilayered structure, built to guarantee performances and safety standards of all the flights. Altought the increase of traffic could lead the system over its capacity limits, undermining its ability to work efficiently and safe. Hence, it is important to understand the limits and the features of the current system, seeking for new solutions aimed at improving its capacity. Complex Systems Physics has already proven to be useful to study and understand the criticality of many transportation systems. For example, the well-known Nagel-Schreckenberg model ^[3],a cellular automata model capable of reproducing many reatures of the real vehicular traffic. Such model shows a phase transition from an uncongested phase to jammed phase as the density of vehicues present in the system increases. A similar approach has been developed also for pedestrian systems ^[4] ^[5] and in relatively recent times for air traffic. Phase transitions ^[6] , percolation effects ^[7] ^[8], delay propagation ^[9] and network resilience under random failures ^[10] are features that have been modelled and studies for the ATM system, but these efforts have been devoted mainly to the airport network layer, i.e. disregarding the structure of the routes and airspaces.
The main purpose of this PhD project is to analyse and model the Air Traffic Control layer of the ATM structure, using tools and concepts coming from Complex Systems and Complex Network theory. Nowdays aircraft are suppose to fly according to flight plans built over a series of fixed geographical references, called navigation points. These navigation points form the "airways structure" of the airspace, i.e. a geographical network that the aircraft are suppsed to follow during their flight. The flight plans have to respect constraints concerning the amount of traffic per hour in "sectors", i.e. volumes in which each national airspace is divided. Although the possibility of conflicts between different trajectories and the occurrence of bad weather conditions are not taken into account. Air traffic controllers activity have to prevent these adverse situation to occur in their management while trying to assure the minimum cost in terms of fuel and fees to each flight, applying reroutings and vertical deviation to the trajectories of the aircraft. The presence of airways is an heritage from the past and less technologically advanced times, whereas nowadays controllers, by relying on sufficiently accurate instruments, can perform easily the required redirections without the need of following them.

Reasearch Done

The action of the controllers generates modification in the structure of the trajectories and thus in the structure of the network of navigation poins that can be built with the trajectories. Topological studies have been performed in order to study these differences and to provide the basis to build an ATC model. The analysis have been performed using historical traffic data coming from EUROCONTROL Demand Data Repository ^[11], providing information on both the flight plans and the real trajectories of aircraft in the European Airspace within a certain period of time.
The model has been built as a simple local search dynamics taking place over the network of navigation points. Every time a controller spot a conflict, he searches between all the available nodes in the network towards which the conflicted aircraft can be rerouted without generating other conflicts. The model shows a transition from a phase in which all the conflicts can be solved by this process to a phase in which many are not solved anymore as the traffic injected in the systems increases.
The validation of the model has been performed simulating a one day schedule of flight coming from the historical data and comparing the results from the simulations to the variations observed in the analysis. The precences of external disturbances has been found to be crucial in order to improve the agreement with the data.

References

↑ EUROCONTROL. Long-term forecast (2010). Available at www.eurocontrol.int/statfor.
↑ Joint Economic Committee of US Congress., Your flight has been delayed again: Flight delays cost passengers, airlines and the U. S. economy billions. Available online at http://www.jec.senate.gov (May 22. 2008)
↑ K. Schreckenberg, M. Schreckenberg, "A cellular automaton model for freeway traffic", Journal de Physique I 2, 2221–2229 (1992)
↑ VJ Blue, JL Alder, "Emergent fundamental pedestrian flows from cellular automata microsimulation", Transportation Research Record: Journal of the Transportation Research Board 1644, 29–36 (1998)
↑ VJ Blue, JL Alder, "Jamming transition in a cellular automaton model for traffic flow", Physical Review E 51, 4282 (1995)
↑ L Lacasa, M Cea, M Zanin, "Jamming transition in air transportation networks", Physica A 388, 3948–3954 (2009)
↑ SB Amor, TD Huy, M Bui, "A percolation based model for ATC simulation", RIVF, 17–22 (2006)
↑ SB Amor, TD Huy, M Bui, "Investigating air traffic control dynamics using random cellular automata", in Beitrag zum EUROCONTROL Innovative Research Workshop (2006)
↑ P Flerquin, JJ Ramasco, VM Eguiluz, "Systemic delay propagation in the us airport network", Scientific Reports 3, (2013)
↑ A Cardillo et al., "Modeling the multi-layer nature of the european air transport network: Re-silience and passengers re-scheduling under random failures", The European Physical Journal Special Topics 215, 23–33 (2013)
↑ https://www.eurocontrol.int/ddr

Publications and Presentations

[1] EUROCONTROL. Long-term forecast (2010). Available at www.eurocontrol.int/statfor.

[2] Joint Economic Committee of US Congress., Your flight has been delayed again: Flight delays cost passengers, airlines and the U. S. economy billions. Available online at http://www.jec.senate.gov (May 22. 2008)

[3] K. Schreckenberg, M. Schreckenberg, "A cellular automaton model for freeway traffic", Journal de Physique I 2, 2221–2229 (1992)

[4] VJ Blue, JL Alder, "Emergent fundamental pedestrian flows from cellular automata microsimulation", Transportation Research Record: Journal of the Transportation Research Board 1644, 29–36 (1998)

[5] VJ Blue, JL Alder, "Jamming transition in a cellular automaton model for traffic flow", Physical Review E 51, 4282 (1995)

[6] L Lacasa, M Cea, M Zanin, "Jamming transition in air transportation networks", Physica A 388, 3948–3954 (2009)

[7] SB Amor, TD Huy, M Bui, "A percolation based model for ATC simulation", RIVF, 17–22 (2006)

[8] SB Amor, TD Huy, M Bui, "Investigating air traffic control dynamics using random cellular automata", in Beitrag zum EUROCONTROL Innovative Research Workshop (2006)

[9] P Flerquin, JJ Ramasco, VM Eguiluz, "Systemic delay propagation in the us airport network", Scientific Reports 3, (2013)

[10] A Cardillo et al., "Modeling the multi-layer nature of the european air transport network: Re-silience and passengers re-scheduling under random failures", The European Physical Journal Special Topics 215, 23–33 (2013)

[11] ttps://www.eurocontrol.int/ddr

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

[10]

[11]