Performance evaluation of the approaches and algorithms using Hamburg Airport operations

The German Aerospace Center (DLR) and the National Aeronautics and Space Administration (NASA) have been independently developing and testing their own concepts and tools for airport surface traffic management. Although these concepts and tools have been tested individually for European and US airports, they have never been compared or analyzed side-by-side. This paper presents the collaborative research devoted to the evaluation and analysis of two different surface management concepts. Hamburg Airport was used as a common test bed airport for the study. First, two independent simulations using the same traffic scenario were conducted: one by the DLR team using the Controller Assistance for Departure Optimization (CADEO) and the Taxi Routing for Aircraft: Creation and Controlling (TRACC) in a real-time simulation environment, and one by the NASA team based on the Spot and Runway Departure Advisor (SARDA) in a fast-time simulation environment. A set of common performance metrics was defined. The simulation results showed that both approaches produced operational benefits in efficiency, such as reducing taxi times, while maintaining runway throughput. Both approaches generated the gate pushback schedule to meet the runway schedule, such that the runway utilization was maximized. The conflict-free taxi guidance by TRACC helped avoid taxi conflicts and reduced taxiing stops, but the taxi benefit needed be assessed together with runway throughput to analyze the overall performance objective.

[1]  Meilin Schaper,et al.  Management of Time Based Taxi Trajectories coupling Departure and Surface Management Systems , 2015 .

[2]  Yoon C. Jung,et al.  Usability Evaluation of Spot and Runway Departure Advisor (SARDA) Concept in Dallas/Fort Worth Airport Tower Simulation , 2013 .

[3]  Yoon C. Jung,et al.  Spot Release Planner: Efficient Solution for Detailed Airport Surface Traffic Optimization , 2012 .

[4]  Yoon C. Jung,et al.  Evaluation of Pushback Decision-Support Tool Concept for Charlotte Douglas International Airport Ramp Operations , 2015 .

[5]  Yoon C. Jung,et al.  A Concept of Operations for Trajectory-based Taxi Operations , 2016 .

[6]  Annette Temme,et al.  Taxi routing for aircraft: Creation and ControllingGround movements with time constraints , 2012 .

[7]  Hanbong Lee,et al.  Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques , 2015 .

[8]  W. Malik,et al.  Performance Evaluation of a Surface Traffic Management Tool for Dallas / Fort Worth International Airport , 2011 .

[9]  Hamsa Balakrishnan,et al.  Impact of Congestion on Taxi Times, Fuel Burn, and Emissions at Major Airports , 2010 .

[10]  Harshad Khadilkar,et al.  DEMONSTRATION OF REDUCED AIRPORT CONGESTION THROUGH PUSHBACK RATE CONTROL , 2014 .

[11]  Robert Horonjeff,et al.  Planning and design of airports , 1950 .

[12]  Meilin Schaper OPERATIONAL IMPROVEMENTS IN THE CONTEXT OF DMAN,A-SMGCS AND A-CDM , 2009 .

[13]  Yoon C. Jung,et al.  An Integrated Collaborative Decision Making and Tactical Advisory Concept for Airport Surface Operations Management , 2012 .

[14]  Zhifan Zhu,et al.  Validation of Simulations of Airport Surface Traffic with the Surface Operations Simulator and Scheduler , 2013 .

[15]  Meilin Schaper,et al.  Trajectory based ground movements and their coordination with departure management , 2013, 2013 IEEE/AIAA 32nd Digital Avionics Systems Conference (DASC).

[16]  Rapport DU Capscaafrica,et al.  INTERNATIONAL CIVIL AVIATION ORGANIZATION , 1947, International Organization.

[17]  Shawn A. Engelland,et al.  Microscopic Analysis of Airport Surface Sequencing , 2008 .

[18]  Shawn A. Engelland,et al.  Microscopic Analysis of Airport Surface Sequencing (ALTERNATE PAPER) , 2008 .

[19]  Moffett Field,et al.  A Simulator for Modeling Aircraft Surface Operations at Airports , 2009 .

[20]  Robert Hoffman,et al.  Air Traffic Management , 2011 .

[21]  Meilin Schaper,et al.  Improved Departure Management through Integration of DMAN and A-SMGCS , 2008 .

[22]  J. M. ten Have The development of the NLR ATC Research Simulator (Narsim): Design philosophy and potential for ATM research , 1993, Simul. Pract. Theory.