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Aircraft Sequencing Problem Near Terminal Area

Aircraft Sequencing Problem Near Terminal Area Final Term Project Presentation Sepehr Sarmadi Dec. 10 th 2002 System definition System users & objectives Terminal area: A cylindrical-shaped region with varying radius and altitude centered around an airport. Airlines and passengers

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Aircraft Sequencing Problem Near Terminal Area

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  1. Aircraft Sequencing Problem Near Terminal Area Final Term Project Presentation Sepehr Sarmadi Dec. 10th 2002

  2. System definition System users & objectives Terminal area: A cylindrical-shaped region with varying radius and altitude centered around an airport. Airlines and passengers Delay • Passenger delays • Crew costs • Aircraft utilization • Fuel costs 50 nm • Air Traffic Controllers • Safety (time and space separations) • Workload 10,000 ft Size is determined by the range of the airport’s radar and communication coverage. • Pilots • Predictable ATC instructions • Being treated fairly Final approach An area where aircraft begins its landing maneuver Airport managers Throughput maximization Runway(s)

  3. Decision making strategies to compute • FCFSSE (First Come First Served System Entrance) • FCFSRW (First Come First Served Runway entrance) • LLT (minimizing the Last landing Time) • TPD (minimizing Total Passenger -or flight- Delay) Aircraft Sequencing Problem (ASP) Definition The problem of sequencing aircraft near the terminal area to satisfy some of the “system objectives” stated before Aircraft Sequencing Aircraft category &

  4. ASP components • Finding the static solution to the scheduling problem at any given time • Updating the static solution to take into account the arrival of new aircraft Main challenge: Both components must be completed in a few seconds as the nature of the real time ASP demands

  5. 4 2 2 4 3 1 3 1 2 5 4 6 3 1 5 6 5 6 ASP, DP approaches (1) ASP is a special case of the famous Traveling Salesman Problem TSP in a complete directed graph Hamilton problem Equivalent to LLT version of ASP

  6. But still DP approaches (or any other combinatorial approach) are computationally prohibitive in practice • “n” is usually larger than 3 (10-15 velocity classes is normal) • For every new entrance, the algorithm should be solved again = 0.002 ASP, DP approaches (2) DP algorithm solution time for TSP (non-polynomial) A time saving technique classifying arriving aircraft into a few categories (n) generally based on landing velocity and weight Solution time For m1=m2=m3=5, n=3, N=15:

  7. Dynamic updating for a simple example* *Source: Dear, Roger, PhD thesis, MIT, 1976

  8. Min delay and Max throughput strategies fail in practice • Large solution times, huge number of legitimate permutations to check • Difficulty in actual determination of the “optimal” solution • Global shifting of aircraft positions that cannot practically be implemented • Certain aircraft types might continuously be shifted backwards, causing intolerable delays making no sense to the pilot and to the passengers (note the treatment of aircraft #1 in minimum delay case and aircraft #3 in minimum blockage case)

  9. CPS methodology The only practical solution to ASP must involve a compromise. “Constrained Position Shifting” methodology is a very successful compromise. CPS Limits the maximum number of position shifts (forwards or backwards) with respect to FCFS • Is computationally practicable, omits many of the previously legitimate permutations • Avoids “wholesale” updating • Treats individual aircraft and velocity classes equitably • Decreases total and average delay • Increases runway throughput

  10. CPS in practice (1) Almost all major airports around the world still implement the FCFS strategy to avoid additional controller’s workload The “CTAS” system in Denver and Dallas/Ft. Worth and the “COMPAS” system in Frankfurt include algorithms for assisting controllers do CPS with a maximum position shift of 1 or 2. CTAS was conceived and is being prototyped at the NASA Ames Research Center. In 1991 it was chosen by the FAA as the future automation system for the terminal area COMPAS was developed in the early 1980’s in Germany. One of the project goals was to plan an optimal sequence of the arriving aircraft from different arrival routes to make best use of the existing runway capacity

  11. Interesting results in the first two weeks of operation: • Controller acceptance of the runway advisories was 96.9% • Controllers reported the first week of operations “very positive.” • Rush periods seemed to last shorter • An increase in surface traffic was reported CPS in practice (2)* On February 15, 1999, the Passive Final Approach Spacing Tool (pFAST) began sixteen hour per day operational use (covering over 80% of the arrival rushes) at the Dallas/Fort Worth (D/FW) TRACON. *Source: NASA website

  12. Thank You !

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