Efficient Management of Aircraft Taxiing Phase by Adjusting Speed Through Conflict-Free Routes
Abstract
Air traffific congestion is considered to be the main problem in air traffific management. It represents a real handicap in the current rising air traffific flflows without a corresponding enhancement in airport infrastructure. This issue leads to more workloads for air traffific controllers, air stakeholders and other airport operations. The following paper aims to minimize the departure aircraft taxiing time in the movement area. This duration can be affected by several factors such as routing, taxiing speed, holding while taxiing ... etc. In this work, we are going to solve the previous problem by using a tactical planning tool: it consists on assigning effificient and nonstop routes to the scheduled traffific on departure. This tool, using a real-time algorithm, will detect in advance routing conflflicts and solve them before aircraft leave stands and approach the hotspots in taxing network. Furthermore, the proposed method will optimize the use of the available ground network by acting on the taxiing speed in order to reduce departures’ delays, fuel consumption and gas emissions.References
eurocontrol, “traffic growth 2018,” eurocontrol, 2019, https://www.eurocontrol.int.
iata, “transportation growth,” iata, 2019, https://www.iata.org/en/pressroom/pr/2017-10-24-01/.
T. Zhang, M. Ding, B. Wang, and Q. Chen, “Conflict-free time-based trajectory planning for aircraft taxi automation with refined taxiway modeling,” Journal of Advanced Transportation, vol. 50, no. 3, pp. 326–347, 2016.
H. Khadilkar and H. Balakrishnan, “Network congestion control of airport surface operations,” Journal of Guidance, Control, and Dynamics, vol. 37, no. 3, pp. 933–940, 2014.
L. Yang, S. Yin, K. Han, J. Haddad, and M. Hu, “Fundamental diagrams of airport surface traffic: Models and applications,” Transportation research part B: Methodological, vol. 106, pp. 29–51, 2017.
J. Ma, D. Delahaye, M. Sbihi, and M. Mongeau, “Integrated optimization of terminal manoeuvring area and airport,” 6th SESAR Innovation Days, 2016.
C. Yu, D. Zhang, and H. H. Lau, “A heuristic approach for solving an integrated gate reassignment and taxi scheduling problem,” Journal of Air Transport Management, vol. 62, pp. 189–196, 2017.
O. E. Guclu and C. Cetek, “Analysis of aircraft ground traffic flow and gate utilisation using a hybrid dynamic gate and taxiway assignment algorithm,” The Aeronautical Journal, vol. 121, no. 1240, pp. 721–745, 2017.
J.-B. Gotteland, N. Durand, J.-M. Alliot, and E. Page, “Aircraft ground traffic optimization,” in ATM 2001, 4th USA/Europe Air Traffic Management Research and Development Seminar, 2001, pp. pp–xxxx.
J.-B. Gotteland and N. Durand, “Genetic algorithms applied to airport ground traffic optimization,” in The 2003 Congress on Evolutionary Computation, 2003. CEC’03., vol. 1. IEEE, 2003, pp. 544–551.
C. Stergianos, J. Atkin, P. Schittekat, T. E. Nordlander, C. Gerada, and H. Morvan, “The importance of considering pushback time and arrivals when routing departures on the ground at airports,” in 8th international conference on applied operational research (ICAOR 2016), Rotterdam, The Netherlands, 2016, pp. 41–46.
S. Ravizza, J. A. Atkin, and E. K. Burke, “A more realistic approach for airport ground movement optimisation with stand holding,” Journal of Scheduling, vol. 17, no. 5, pp. 507–520, 2014.
K. Yin, C. Tian, B. X. Wang, and L. Quadrifoglio, “Analysis of taxiway aircraft traffic at george bush intercontinental airport, houston, texas,” Transportation research record, vol. 2266, no. 1, pp. 85–94, 2012.
G. Clare and A. G. Richards, “Optimization of taxiway routing and runway scheduling,” IEEE Transactions on Intelligent
Transportation Systems, vol. 12, no. 4, pp. 1000–1013, 2011.
J. Gu´epet, O. Briant, J.-P. Gayon, and R. Acuna-Agost, “The aircraft ground routing problem: Analysis of industry punctuality indicators in a sustainable perspective,” European Journal of Operational Research, vol. 248, no. 3, pp. 827–839, 2016.
C. Evertse and H. Visser, “Real-time airport surface movement planning: Minimizing aircraft emissions,” Transportation Research Part C: Emerging Technologies, vol. 79, pp. 224–241, 2017.
S. Ravizza, J. Chen, J. A. Atkin, P. Stewart, and E. K. Burke, “Aircraft taxi time prediction: comparisons and insights,” Applied Soft Computing, vol. 14, pp. 397–406, 2014.
H. Khadilkar and H. Balakrishnan, “Integrated control of airport and terminal airspace operations,” IEEE Transactions on Control Systems Technology, vol. 24, no. 1, pp. 216–225, 2015.
T. V. Truong, “The distribution function of airport taxi-out times and selected applications,” in Journal of the Transportation Research Forum, vol. 50, no. 2, 2012.
I. Simaiakis and H. Balakrishnan, “A queuing model of the airport departure process,” Transportation Science, vol. 50, no. 1, pp. 94–109, 2016.
O. Lordan, J. M. Sallan, and M. Valenzuela-Arroyo, “Forecasting of taxi times: The case of barcelona-el prat airport,” Journal of Air Transport Management, vol. 56, pp. 118–122, 2016.
J. Koeners and R. Rademaker, “Creating a simulation environment to analyze benefits of real-time taxi flow optimization using actual data,” in AIAA Modeling and Simulation Technologies Conference, 2011, p. 6372.
Y. Liu, M. Hansen, G. Gupta, W. Malik, and Y. Jung, “Predictability impacts of airport surface automation,” Transportation Research Part C: Emerging Technologies, vol. 44, pp. 128–145, 2014.
H. Lee and H. Balakrishnan, “Fast-time simulations of detroit airport operations for evaluating performance in the presence of uncertainties,” in 2012 IEEE/AIAA 31st Digital Avionics Systems Conference (DASC). IEEE, 2012, pp. 4E2–1.
T. K. Simi´c and O. Babi´c, “Airport traffic complexity and environment efficiency metrics for evaluation of atm measures,” Journal of Air Transport Management, vol. 42, pp. 260–271, 2015.
D. Rappaport, P. Yu, K. Griffin, and C. Daviau, “Quantitative analysis of uncertainty in airport surface operations,” in 9th AIAA Aviation Technology, Integration, and Operations Conference (ATIO) and Aircraft Noise and Emissions Reduction Symposium (ANERS), 2009, p. 6987.
A. E. Brownlee, M. Weiszer, J. Chen, S. Ravizza, J. R. Woodward, and E. K. Burke, “A fuzzy approach to addressing uncertainty in airport ground movement optimisation,” Transportation Research Part C: Emerging Technologies, vol. 92, pp. 150–175, 2018.
C. Lesire, “Iterative planning of airport ground movements,” in Proceedings of the 4th international conference on research in air transportation (ICRAT 2010), Budapest, Hungary, 2010, pp. 147–154.
J. Chen, S. Ravizza, J. A. Atkin, and P. Stewart, “On the utilisation of fuzzy rule-based systems for taxi time estimations at airports,” in 11th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems. Schloss Dagstuhl-LeibnizZentrum fuer Informatik, 2011.
M. Weiszer, J. Chen, S. Ravizza, J. Atkin, and P. Stewart, “A heuristic approach to greener airport ground movement,” in 2014 IEEE congress on evolutionary computation (CEC). IEEE, 2014, pp. 3280–3286.
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