En Route Traffic Optimization to Reduce Environmental Impact
En route airspace throughput (the number of aircraft than can safely fly though a given location over a given time) can be increased by optimizing aircraft cruise altitude and speed based on the distance between their origin and destination. The increase in throughput, and the corresponding reductions in fuel burn and emissions, result when aircraft can fly closer to the optimum altitude for their performance characteristics, and from a reduction in situations where one aircraft gets “stuck” behind another with a lower optimal cruise speed.
Project 5 investigated and quantified the benefits of an optimization tool that air traffic controllers could use to assign aircraft to cruise altitude. There were five objectives to the research:
- extend the algorithm to multiple flight levels
- ensure that all aircraft exit the sector as originally planned
- ensure reasonable controller workload
- develop an interface and concept of operations to test the algorithm
- evaluate the algorithm with a human in the loop evaluation.
The first three objectives were achieved through the optimization algorithm design. In current conflict avoidance maneuver practice, aircraft may change their paths laterally, vertically, or both. First, resolution maneuvers are temporally spaced no closer than 20 seconds. Second, resolution maneuvers are scheduled to occur long enough after maneuvers are presented to controllers so they have sufficient time to comprehend them and take appropriate action. Third, each aircraft may only be maneuvered once in each volume of airspace.
Three versions of the algorithm were created and tested:
- cooperative version: all the aircraft involved in a potential conflict are allowed to maneuver to resolve the conflict
- non-cooperative version: one aircraft involved in a potential conflict is allowed to maneuver to resolve the conflict
- no-speed-change version: potential conflicts are resolved without aircraft speed changes, (i.e., heading and altitude changes only)
The algorithm was evaluated in two phases. In the first phase, an algorithm-level evaluation was conducted within the scope of the algorithm process, where the results from the algorithm were checked by a conflict detection routine. In the second phase, a scenario-level evaluation was conducted on the output (specifically the time history of the output) of the algorithm. This latter phase of testing was needed because of the greater-than-expected stochasticity in real-world radar data when the FAA’s traffic simulation application was employed.
The evaluation yielded the following key observations:
- the algorithm’s optimal solution is often cooperative, maneuvering both conflicting aircraft
- a non-cooperative solution can be enforced at the cost of a higher fuel burn (on an average about 3 percent)
- when speed changes are disallowed, more altitude changes are observed, but fewer of solutions are cooperative
- restricting speed changes results in recommendations with a higher fuel burn than those provided by the primary (general) version of the algorithm that allows for speed changes
Researchers recommended that the next steps could include further, more detailed scenarios/simulations, including humans in the loop testing with controllers, conducted to validate and verify the results. There might also be additional parameters included, such as weather impacts, and, if successful, preparation for actual flight-testing.
Georgia Institute of Technology
Massachusetts Institute of Technology
John-Paul Clarke, Associate Professor, School of Aerospace Engineering; Director, Air Transportation Laboratory; Georgia Institute of Technology, email@example.com
László Windhoffer, firstname.lastname@example.org
- Final Findings on the Development and Evaluation of an En-Route Fuel Optimal Conflict Resolution Algorithm to Support Strategic Decision-Making. John-Paul Clarke, Karen Feigh, Atr Dutta, Brian Lee, Sarah Milway, Clayton Tino. Report No. PARTNER-COE-2012001. The PARTNER Project 5, En Route Traffic Optimization to Reduce Environmental Impact, final report. January 2012. Download (pdf 1.7M)
- En Route Traffic Optimization to Reduce Environmental Impact: PARTNER Project 5 Report. John-Paul Clarke, Marcus Lowther, Liling Ren, William Singhose, Senay Solak, Adan Vela, Lawrence Wong. Report no. PARTNER-COE-2008-005. Download (pdf 2.7M)