Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We demonstrate our approach for strategic flight schedules in the period 2013–2018 at London Heathrow Airport. Together with the development of dedicated strategic flight schedule optimization models, our proposed approach supports an integrated strategic flight schedule assessment, where schedules are evaluated with respect to flight delays and cancellations.

[1]  Hamsa Balakrishnan,et al.  Characterization and prediction of air traffic delays , 2014 .

[2]  Banavar Sridhar,et al.  Modeling Flight Delays and Cancellations at the National, Regional and Airport Levels in the United States , 2009 .

[3]  Gano B. Chatterji,et al.  ANALYSIS OF AIRCRAFT ARRIVAL AND DEPARTURE DELAY CHARACTERISTICS , 2002 .

[4]  George Valkanas,et al.  Skyline Ranking à la IR , 2014, EDBT/ICDT Workshops.

[5]  Lewis Ntaimo,et al.  The time slot allocation problem under uncertain capacity , 2014 .

[6]  Young Jin Kim,et al.  Cost-sensitive prediction of airline delays using machine learning , 2017, 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC).

[7]  Jason Weston,et al.  Gene Selection for Cancer Classification using Support Vector Machines , 2002, Machine Learning.

[8]  C. Furlanello,et al.  Recursive feature elimination with random forest for PTR-MS analysis of agroindustrial products , 2006 .

[9]  Alexander Klein,et al.  Airport delay prediction using weather-impacted traffic index (WITI) model , 2010, 29th Digital Avionics Systems Conference.

[10]  Nicholas G. Rupp,et al.  An Investigation into the Determinants of Flight Cancellations , 2006 .

[11]  David G. Stork,et al.  Pattern Classification , 1973 .

[12]  Jing Xiong,et al.  Value of Flight Cancellation and Cancellation Decision Modeling , 2009 .

[13]  Stephen R. Marsland,et al.  Machine Learning - An Algorithmic Perspective , 2009, Chapman and Hall / CRC machine learning and pattern recognition series.

[14]  Hisashi Kashima,et al.  Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines , 2017, AAAI.

[15]  Amedeo R. Odoni,et al.  Modelling delay propagation within an airport network , 2013 .

[16]  Xin Li,et al.  Detecting periodic patterns of arrival delay , 2007 .

[17]  LORIS BELCASTRO,et al.  Using Scalable Data Mining for Predicting Flight Delays , 2016, ACM Trans. Intell. Syst. Technol..

[18]  Young Jin Kim,et al.  Prediction of weather-induced airline delays based on machine learning algorithms , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[19]  M. N. Sulaiman,et al.  A Review On Evaluation Metrics For Data Classification Evaluations , 2015 .

[20]  Young Jin Kim,et al.  A deep learning approach to flight delay prediction , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[21]  Geoffrey E. Hinton.  Connectionist Learning Procedures , 1989, Artif. Intell..

[22]  Konstantinos G. Zografos,et al.  Dealing with the efficient allocation of scarce resources at congested airports , 2012 .

[23]  Scott Lundberg,et al.  A Unified Approach to Interpreting Model Predictions , 2017, NIPS.

[24]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[25]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[26]  Daniele Micci-Barreca,et al.  A preprocessing scheme for high-cardinality categorical attributes in classification and prediction problems , 2001, SKDD.

[27]  António Pais Antunes,et al.  An optimization approach for airport slot allocation under IATA guidelines , 2018, Transportation Research Part B: Methodological.

[28]  Wolfgang Jank,et al.  Estimating Flight Departure Delay Distributions - A Statistical Approach With Long-Term Trend and Short-Term Pattern , 2008 .

[29]  Qian Wu.  A Stochastic Characterization Based Data Mining Implementation for Airport Arrival and Departure Delay Data , 2014 .

[30]  Jun Chen,et al.  Chained Predictions of Flight Delay Using Machine Learning , 2019, AIAA Scitech 2019 Forum.

[31]  David D. Cox,et al.  Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms , 2013, SciPy.

[32]  Konstantinos G. Zografos,et al.  Increasing airport capacity utilisation through optimum slot scheduling: review of current developments and identification of future needs , 2017, J. Sched..

[33]  Raffaele Pesenti,et al.  Airport slot allocation in Europe: economic efficiency and fairness , 2012 .

[34]  Raffaele Pesenti,et al.  SOSTA: An effective model for the Simultaneous Optimisation of airport SloT Allocation , 2017 .

[35]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[36]  Eduardo S. Ogasawara,et al.  A Review on Flight Delay Prediction , 2017, ArXiv.

[37]  Hugo Alonso,et al.  Predicting flight departure delay at Porto Airport: A preliminary study , 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).