TY - JOUR
T1 - A constraint programming model with time uncertainty for cooperative flight departures
AU - Schefers, Nina
AU - Ramos González, Juan José
AU - Folch, Pau
AU - Munoz-Gamarra, José Luis
PY - 2018/11/1
Y1 - 2018/11/1
N2 - © 2018 Elsevier Ltd The lack of a proper integration of strategic Air Traffic Management decision support tools with tactical Air Traffic Control interventions usually generates a negative impact on the Reference Business Trajectory adherence, and in consequence affects the potential of the Trajectory-Based Operations framework. In this paper, a new mechanism relaying on Reference Business Trajectories as a source of data to reduce the amount of Air Traffic Controller interventions at the tactical level while preserving Air Traffic Flow Management planned operations is presented. Artificial Intelligence can enable Constraint Programming as it is a powerful paradigm for solving complex, combinatorial search problems. The proposed methodology takes advantage of Constraint Programming and fosters adherence of Airspace User's trajectory preferences by identifying tight interdependencies between trajectories and introducing a new mechanism to improve the aircraft separation at concurrence events considering time uncertainty. The underlying philosophy is to capitalize present degrees of freedom between layered Air Traffic Management planning tools, when sequencing departures at the airports by considering the benefits of small time stamp changes in the assigned Calculated Take-Off Time departures and to enhance Trajectory-Based Operations concepts.
AB - © 2018 Elsevier Ltd The lack of a proper integration of strategic Air Traffic Management decision support tools with tactical Air Traffic Control interventions usually generates a negative impact on the Reference Business Trajectory adherence, and in consequence affects the potential of the Trajectory-Based Operations framework. In this paper, a new mechanism relaying on Reference Business Trajectories as a source of data to reduce the amount of Air Traffic Controller interventions at the tactical level while preserving Air Traffic Flow Management planned operations is presented. Artificial Intelligence can enable Constraint Programming as it is a powerful paradigm for solving complex, combinatorial search problems. The proposed methodology takes advantage of Constraint Programming and fosters adherence of Airspace User's trajectory preferences by identifying tight interdependencies between trajectories and introducing a new mechanism to improve the aircraft separation at concurrence events considering time uncertainty. The underlying philosophy is to capitalize present degrees of freedom between layered Air Traffic Management planning tools, when sequencing departures at the airports by considering the benefits of small time stamp changes in the assigned Calculated Take-Off Time departures and to enhance Trajectory-Based Operations concepts.
KW - Air Traffic Management
KW - Air Transportation Planning
KW - Artificial Intelligence
KW - Conflict Detection and Resolution
KW - Constraint Programming
KW - Data Analysis
KW - Decision Support Tool
KW - Predictive Analysis
KW - Reference Business Trajectories
KW - System-level Simulation
KW - Trajectory Based Operations
KW - Trajectory Prediction
KW - Uncertainties
U2 - 10.1016/j.trc.2018.09.013
DO - 10.1016/j.trc.2018.09.013
M3 - Article
SN - 0968-090X
VL - 96
SP - 170
EP - 191
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
ER -