Journal of the Korean Society for Aviation and Aeronautics (한국항공운항학회지)

The Korean Society for Aviation and Aeronautics (한국항공운항학회)
권호 표지
DOI QR코드

DOI QR Code

En-route Trajectory Prediction via Weighted Linear Regression

가중선형회귀를 통한 순항항공기의 궤적예측

  • 김소윤 (한국항공대학교 대학원 항공교통물류학과) ;
  • 이금진 (한국항공대학교 항공교통물류학과)
  • Published : 2016.12.30
Download PDF
⟨ Previous Next ⟩

Abstract

The departure flow management is the planning tool to optimize the schedule of the departure aircraft and allows them to join smoothly into the overhead traffic flow. To that end, the arrival time prediction to the merge point for the cruising aircraft is necessary to determined. This paper proposes a trajectory prediction model for the cruising aircraft based on the machine learning approach. The proposed method includes the trajectory vectored from the procedural route and is applied to the historical data to evaluate the prediction performances.

Keywords

Acknowledgement

Grant : 항공기 출발 및 도착 통합관리기술연구

Supported by : 국토교통과학기술진흥원

References

  1. Sridhart, C.C.B. and Bilimoria, K.D., "En-route Flight Trajectory Prediction for Conflict Avoidance and Traffic Management". AIAA Cuidance Navigation, and Control Conference, San Diego, CA, July 29-31, 1996.
  2. Lymperopoulos, I. and Lygeros, J., "Sequential Monte Carlo Methods for Multi-Aircraft Trajectory Prediction in Air Traffic Management", International Journal of Adaptive Control and Signal Processing, vol. 24, 10, 2010, pp. 830-849. https://doi.org/10.1002/acs.1174
  3. Lymperopoulos, I. and Lygeros, J., "Model Based Aircraft Trajectory Prediction during Takeoff", Guidance, Navigation and Control Conference and Exhibit, Colorado, Keystone, August 21-24, 2006.
  4. Roy, K., Levy, B. and Tomlin, CJ., "Target Tracking and Estimated Time of Arrival (ETA) Prediction for Arrival Aircraft", AIAA Guidance, Navigation, and Control Conference and Exhibit, Colorado, Keystone, August 21-24, 2006.
  5. Yepes, J.L., Hwang, I. and Rotea, M., "New Algorithms for Aircraft Intent Inference and Trajectory Prediction", Jounal of Guidance, Control, and Dynamics, Vol. 30, No. 2, 2007, pp. 370-382. https://doi.org/10.2514/1.26750
  6. Schleicher, D.R., Jones, E., Dow, D. and Coppenbarger, R. A., "Improved Lateral Trajectory Prediction through En Route Air-Ground Data Exchange," AIAA Aircraft Technology, Integration, and Operations, Los Angeles, California, October 1-3, 2002.
  7. Liu, Y. and Li, X.R., "Intent Based Trajectory Prediction by Multiple Model Prediction and Smoothing", AIAA Guidance, Navigation, and Control Conference, Kissmmee, Florida, January 5-9, 2015
  8. Liu, W. and Hwang, I., "Probabilistic Trajectory Prediction and Conflict Detection for Air Traffic Control", Journal of Guidance, Control, and Dynamics, Vol. 34, No. 6, 2011, pp. 1779-1789. https://doi.org/10.2514/1.53645
  9. Schultι C.A., Thipphavog, D. and Erzberger, H., "Adaptive Trajectory Prediction Algorithm for Climbing Flights", AIAA Guidance, Navigation, and Control Conference, Minneapolis, Minnesota, August 13-16, 2012.
  10. Park, Y. and Thipphavong, D.P., "Performance of an Adaptive Trajectory Prediction Algorithm for Climbing Aircraft, AlAA Aviation, Los Angeles, CA, August 12-14, 2013.
  11. Tastambekov, K., Puechmorel, S., Delahaye, D and Rabut, C., "Aircraft Trajectory Forecasting Using Local Functional Regression in Sobolev Space", Journal of Transportation Research, Part C, Vol. 39, No. 1, 2014, pp. 1-22. https://doi.org/10.1016/j.trc.2013.11.013
  12. Kun, W. and Wei, P., "A 4-D Trajectory Prediction Model Based on Radar Data", proceedings of the Twenty-seventh Chinese Control Conference, Kunming, Yunnan, China, July 16-18, 2008, pp. 591-594.
  13. Hamed, M.G., Gianazza, D., Serrurier, M, and Durand, N., "Statistical Prediction of Aircraft Trajectory: Regression Method vs Point-Mass Model", 10th US/Europe Air Traffic Management Research and Development Seminar, Chicago, 2013.
  14. Roundtree, B., "Airline Flight Departure and Arrival Prediction Based upon Historical and Real-Time Data", U.S. Patent Application 09/783,215, 2001.
  15. Fablec, Y.L. and Aliot, J.M., "Using Neural Networks to Predict Aircraft Trajectories", proceedings of the International Conference on Artificial Intelligence Vol. 2, CSREA Press, Las Vegas, 1999, pp. 524-529.
  16. De Leege, A.M.P., van Paassen, M.M. and Mulder, M., "A Machine Learning Approach to Trajectory Prediction", AIAA Guidance, Navigation, and Control Conferences, Boston, MA, August 19-22, 2013.
  17. Hong, S. and Lee, K., "Aircraft Arrival Time Prediction via Modeling Vectored Area Navigation Arrivals", Journal of Korean Society for Aviation and Aeronautics, Vol. 22, No. 2, 2014, pp. 1-7. https://doi.org/10.12985/ksaa.2014.22.2.001
  18. Strottmann Kern, C., de Medeiros, I. P. and Yoneyama, T., "Data-Driven Aircraft Estimated Time of Arrival Prediction", Systems Conference, ninth Annual IEEE International, 2015, pp. 727-733.
  19. Kim, S., and Lee, K., "En-route Trajectory Prediction via Weighted Linear Regression", APISAT, Cairns, Australia, 2015.
  20. Engelland, Shawn A., et al. "Precision Departure Release Capability (PDRC) Final Report", NASA, 2013.
  21. Palopo, K., Chatterji, G.B. and Lee, H.T, "Benefit Assessment of the Precision Departure Release Capability Concept", 11th AIAA Aviation Technology, Integration, and Operations Conference, Virginia Beach, VA, September 20-22, 2011.
  22. Capps, A. and Engelland, S.A., "Characterization of Tactical Departure Scheduling in the National Airspace System", 11th A1AA Aviation Technology Integration and Operations Conference, Virginia Beach, VA, September 20-22, 2011.
  23. Cleveland, W.S. and Devlin, S.J., "Locally Weighted Regression: An Approach to Regression Analysis by local Fitting", Journal of the American Statistical Association, Col. 83, No. 403, 1988, pp. 596-610. https://doi.org/10.1080/01621459.1988.10478639
  24. Ruppert, D. and Wand, M.P., "Multivariate Locally Weighted Least Squares Regression", The Annals of Statistics, Vol. 22, No. 3, 1994, pp. 1346-1370. https://doi.org/10.1214/aos/1176325632
  25. Fan, J., Cijbels, I., Hu, T.C. and Huang, L.S., "A Study of Variable Bandwidth Selection for Local Polynomial Regression", Statistics Sinica, 1996, pp. 113-127.
  26. Ruppert, D., "Empirical-Bias Bandwidth for Local Polynomial Nonparametric Regression and Density Estimation", Journal of the American Statistical Association, 92.439, 1997, pp. 1049-1062. https://doi.org/10.1080/01621459.1997.10474061
  27. Fan, J. and Gijbels, I., "Variable Bandwidth and Local Linear Regression Smoothers", The Annals of Statistics, Vol. 20, No. 4, 1992, pp. 2008-2036. https://doi.org/10.1214/aos/1176348900

Cited by

  1. 생성 모형을 사용한 순항 항공기 향후 속도 예측 및 추론 vol.27, pp.4, 2016, https://doi.org/10.12985/ksaa.2019.27.4.027