Improving air traffic management through agent suggestions

ABSTRACT

Providing intelligent automation to manage the continuously increasing flow of air traffic is critical to the safety and economic viability of air transportation systems. However, current automated solutions leave existing human controllers "out of the loop" rendering the potential solutions both technically dangerous (e.g., inability to react to suddenly developing conditions) and politically charged (e.g., role of air traffic controllers in a fully automated system). Instead, this paper proposes a distributed agent based solution where agents provide suggestions to human controllers. Results on traffic flow around New York show that the suggestion agents can improve system performance by up to 25% over that of human controllers alone, and that these results degrade gracefully when the number of human controllers that follow the agents' suggestions declines.

REFERENCES

• 1: Your flight has been delayed again. Joint Economic Committee, pages 1--12, May 2008.
• 2: Geert Jonker , Frank Dignum , John-Jules Meyer, Achieving cooperation among selfish agents in the air traffic management domain using signed money, Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, May 14-18, 2007, Honolulu, Hawaii [doi>10.1145/1329125.1329382]
• 3: Michal Pěchouček , David Šišlák , Dušan Pavlíček , Miroslav Uller, Autonomous agents for air-traffic deconfliction, Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, May 08-12, 2006, Hakodate, Japan [doi>10.1145/1160633.1160925]
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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence

General Terms:
Algorithms, Performance

Keywords:
air traffic control, multiagent systems, optimization