Trajectory Option Set Planning Optimization under Uncertainty in CTOP

Abstract

The goal of the Collaborative Trajectory Options Program (CTOP) is to improve the Air Traffic Management (ATM) and by considering National Airspace System (NAS). The business goals of the NAS' users flight and airspace restrictions, thereby operations more flexible and financially stable for those involved. During a CTOP, airlines can share their route preferences with Federal Aviation Administration (FAA), combining delay and reroute. Considering that trajectory preferences will impact in the final sort to be assigned, how an airline could reduce its global delay achieving a better position to be assigned. Current solutions for this problem are based on Greedy methods. However, when a CTOP demand is initiated each airline might decide its TOS strategy without knowledge about other airline's flights. A Game Theory approach for single games (SG-CTOP) was proposed to improve the decision-making process. It was developed as an intelligence solution regarding the TOS strategy under involved uncertainty about airline competitors. A case study was conducted using real data from two airlines and 100 different CTOP demands called as SG-CTOP cycle. It was performed 100 SG-CTOP cycles to verify the SG-CTOP behavior by the time. The result analysis identified that when it was used the same strategy for every flight, after 100 SG-CTOP cycles the best strategy was to send two trajectories option for each FCA plus a NOSLOT option to fly around, regarding a maximum assigned delay to fly through the FCA. This strategy achieved a global delay of 53% less than NOSLOT strategy for every flight. When this strategy was compared with the proposed SG-CTOP model, Airline A would achieve a global delay less than, or equal, in 97% of CTOP negotiations representing a delay reduction of 537 hours for the airline.