Have a personal or library account? Click to login

Structural Modelling and Deceleration Algorithm for a Follow Aircraft on Performance-Based Navigation Airway Based on Multi-Agent Technique

Open Access
|Dec 2015

References

  1. 1. ICAO. Performance-Based Navigation (PBN) Manual (Doc9613), ICAO. 999 University Street, Montréal, Quebec, Canada H3C 5H7, 2008.
  2. 2. CAAC. CAAC 2009 Implementation Roadmap of Performance-Based Navigation. Beijing, China Civil Aviation Press, 2009. 10 p.
  3. 3. Tandale, M. D., P. Sengupta, P. K. Menon et al. Queuing Network Models of the National Airspace System. – In: Proc. of 26th Congress of International Council of the Aeronautical Sciences. Reston: AIAA, 2008, pp. 1-14.
  4. 4. Hansen, M. Micro-Level Analysis of Airport Delay Externalities Using Deterministic Queuing Models: A Case Study. – Journal of Air Transport Management, Vol. 8, 2002, No 2, pp. 73-87.10.1016/S0969-6997(01)00045-X
  5. 5. Hansen, M., A. Odoni, D. Lovell et al. Advanced Stochastic Network Queuing Models of the Impact of 4d Trajectory Precision. – NEXTOR Research Symposium. Washington, DC, FAA Headquarters, 2008, pp. 1-25.
  6. 6. Menon, P. K., M. D. Tandale, J. Kim et al. A Framework for Stochastic Air Traffic Flow Modeling and Analysis. – In: Proc. of AIAA Guidance, Navigation, and Control Conference. Reston, AIAA, 2010, pp. 1-28.
  7. 7. Bayen, A. M., R. L. Raffard, C. J. Tomlin. Adjoint-Based Control of a New Eulerian Network Model of Air Traffic Flow. – IEEE Transactions on Control Systems Technology, Vol. 14, 2006, No 5, pp. 804-818.10.1109/TCST.2006.876904
  8. 8. Robelin, C. A., D. Sun, D. Wu et al. MILP Control of Aggregate Eulerian Network Airspace Models. – In: Proc. of 2006 American Control Conference. Piscataway, NJ, IEEE, 2006, pp. 5257-5262.10.1109/ACC.2006.1657558
  9. 9. Lighthill, M. J., G. B. Whitham. On Kinematic Waves. II. A Theory of Traffic Flow on Long Crowded Roads. – In: Proceedings of the Royal Society of London. Mathematical and Physical Sciences Series A, Vol. 229, 1955, No 1178, pp. 317-345.10.1098/rspa.1955.0089
  10. 10. Daganzo, C. F. The Cell Transmission Model, Part II: Network Traffic. – Transportation Research, Part B, Vol. 29, 1995, No 2, pp. 79-93.10.1016/0191-2615(94)00022-R
  11. 11. Menon, P. K., G. D. Sweriduk, K. Bilimoria. New Approach for Modeling, Analysis and Control of Air Traffic Flow. – AIAA Journal of Guidance, Control and Dynamics, Vol. 27, 2004, No 5, pp. 737-744.10.2514/1.2556
  12. 12. Zhang, Z. N., M. Cai, L. L. Wang et al. Research of Longitudinal Safety Separation Based on Nagel-Schreckenberg Traffic Flow Model. – Physics Procedia, Vol. 33, 2012, No 1, pp. 573-579.10.1016/j.phpro.2012.05.106
  13. 13. Zhang, H. The Key Technologies of Collaborative Flow Management in Airport Terminal Area. Nanjing, Nanjing University of Aeronautics and Astronautics, 2009.
  14. 14. Li, X. H., Z. N. Zhang. Research of the Structure of Air Traffic Flow Management System Based on the Agent. – Journal of Transportation Engineering and Information, Vol. 5, 2007, No 1, pp. 56-61.
  15. 15. Wang, W. L. Application of Multi-Agent System in Flight Conflict Detection and Resolution. – Journal of Transport Information and Safety, Vol. 27, 2009, No 3, pp. 9-15.
  16. 16. Dai, L., X. Z. Xia. Application of Multi-Agent in Flight Conflict Resolution. – Ship Electronic Engineering, Vol. 28, 2009, No 3, pp. 62-64, 89.
  17. 17. Wang, C., X. H. Xu. Researching on Air Traffic System Using Agent-Based Modeling and Simulation. – Computer Engineering and Applications, Vol. 44, 2008, No 31, pp. 12-14.
  18. 18. Wang, F., X. H. Xu, J. Zhang. Air Traffic Flow Collaborate Management Based on Multi-Agent. – Journal of Guangxi Normal University: Natural Science Edition, Vol. 26, 2008, No 1, pp. 125-128.
  19. 19. Zhang, J. X., M. H. Hu. Design of the Air Traffic Intelligent Simulation System for the Airport with Multi-Terminal Areas Based on Multi-Agents. – Journal of Transportation Engineering and Information, Vol. 7, 2009, No 2, pp. 90-98.
  20. 20. Hexmoor, H., T. Heng. Air Traffic Control Agents: Landing and Collision Avoidance. – International Conference in Artificial Intelligence. Las Vegas, AIAA, 2000, pp. 21-35.10.1145/336595.337458
  21. 21. Nitschke, G. Cooperating Air Traffic Control Agents. – Applied Artificial Intelligence, Vol. 15, 2001, No 2, pp. 209-235.10.1080/088395101750065778
  22. 22. Callantine, T. J. CATS-Based Air Traffic Controller Agents. Sacramento: NASA Ames Research Center, 2002.10.1145/860575.860741
  23. 23. Nguyen, M., J. Briot, A. Drogoul. An Application of Multi-Agent Coordination Techniques in Air Traffic Management. – In: Proc. of 2003 IEEE/WIC International Conference in Intelligent Agent Technology. Halifax, IEEE, 2003, pp. 622-625.
  24. 24. Hill, J., J. Archibald, W. Stirling et al. A Multi-Agent System Architecture for Distributed Air Traffic Control. – In: Proc. of 2005 AIAA Guidance, Navigation and Control Conference, San Francisco, AIAA, 2005, pp. 1005-1049.10.2514/6.2005-6049
  25. 25. Agogino, A., K. Tumer. Learning Indirect Actions in Complex Domains: Action Suggestions for Air Traffic Control. – Advances in Complex Systems, Vol. 12, 2009, No 4, pp. 493-512.10.1142/S0219525909002283
DOI: https://doi.org/10.1515/cait-2015-0066 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 46 - 56
Published on: Dec 30, 2015
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Ming Zhaohui, Zhang Ming, Tang Xinmin, Han Song-Chen, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.