Impact of Airspace Reconfiguration on Controller Workload and Traffic Performance

Lee, Paul; Smith, Nancy; Prevôt, Thomas; Homola, Jeffrey; Lee, Hwa Soo; Kessell, Angela; Brasil, Connie

doi:10.1201/ebk1439834916-c54

Cited by 7 publications

(16 citation statements)

References 4 publications

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“…Voronoi was the only method to reduce delay relative to Baseline without negatively affecting traffic pattern complexity, making this the most attractive method if the reconfiguration complexity increase is manageable. Reconfiguration complexity thresholds when using DataComm-based controller tools such as those used in [15] have yet to be determined. With the right controller tools and further algorithm refinement to reduce reconfiguration complexity, achieving the higher benefits of these more aggressive methods may be feasible.…”

Section: Results Summary and Discussionmentioning

confidence: 99%

“…Homola et al [32] showed how new on-demand reconfigurations could be implemented to balance sector traffic load and minimize over-capacity time periods without compromising safety, but at the cost of increasing controller task-load and workload ratings. Lee et al [15] and Jung et al [31] identified percent airspace volume and number of aircraft transferred as the primary contributors to reconfiguration workload for the same study. Percent airspace volume transferred impacts controller situational awareness and number of aircraft transferred impacts controller task-load of handing off aircraft to their new sectors.…”

Section: Reconfiguration Complexity Metricsmentioning

confidence: 87%

“…Operational reconfigurations can be completed in roughly five minutes [15]. Therefore, the numbers of aircraft gained (n + (k 1 ,k 2 ,t)) and lost (n -(k 1 ,k 2 ,t)) between k 1 and k 2 are the numbers of unique aircraft flying in υ + (k 1 ,k 2 ) and υ -(k 1 ,k 2 ), respectively, during the five minutes preceding reconfiguration time t. Let N(k 1 ,k 2 ,t) be a weighted combined aircraft transfer complexity given by…”

Section: Reconfiguration Complexity Metricsmentioning

confidence: 99%

See 2 more Smart Citations

Comparing methods for dynamic airspace configuration

Zelinski

Lai

2011

2011 IEEE/AIAA 30th Digital Avionics Systems Conference

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This paper compares airspace design solutions for dynamically reconfiguring airspace in response to nominal daily traffic volume fluctuation. Airspace designs from seven algorithmic methods and a representation of current day operations in Kansas City Center were simulated with two times today's demand traffic. A three-configuration scenario was used to represent current day operations. Algorithms used projected unimpeded flight tracks to design initial 24-hour plans to switch between three configurations at predetermined reconfiguration times. At each reconfiguration time, algorithms used updated projected flight tracks to update the subsequent planned configurations. Compared to the baseline, most airspace design methods reduced delay and increased reconfiguration complexity, with similar traffic pattern complexity results. Design updates enabled several methods to as much as half the delay from their original designs. Freeform design methods reduced delay and increased reconfiguration complexity the most.

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Section: Results Summary and Discussionmentioning

confidence: 99%

Section: Reconfiguration Complexity Metricsmentioning

confidence: 87%

Section: Reconfiguration Complexity Metricsmentioning

confidence: 99%

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Comparing methods for dynamic airspace configuration

Zelinski

Lai

2011

2011 IEEE/AIAA 30th Digital Avionics Systems Conference

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“…A human-in-the-loop (HITL) simulation was conducted in the Airspace Operations Laboratory at the NASA Ames Research Center in 2009 to address some of the questions posed above 8,9 . Traffic scenarios with varying types and severity of boundary changes (BCs) were used to test their impact on the controllers.…”

Section: Exploring the Feasibility Of Flexible Airspace Reconfigumentioning

confidence: 99%

Sector Design and Boundary Change Considerations for Flexible Airspace Management

Lee

Prevôt

Homola

et al. 2010

10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference

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In Next Generation Air Transportation System (NextGen) operations, we expect that the demand-capacity balance can be achieved by selectively managing the airspace capacity in conjunction with managing the traffic demand. In Flexible Airspace Management (FAM), the airspace complexity can be assessed a few hours ahead in order to identify sectors that could exceed their defined traffic threshold as well as sectors that are under-utilized. Using various airspace optimization algorithms, airspace can be reconfigured to manage the existing traffic demand without moving aircraft away from their original user-preferred routes. A human-in-the-loop simulation study was conducted in 2009 to assess the impact of airspace reconfiguration on the controllers. The results from the objective data found that the acceptability of the boundary change and the associated workload were mainly affected by airspace volume change and aircraft that changed ownership. However, observations and subjective feedback have suggested that other cognitively-driven factors, such as spatial relationships between upstream/downstream sectors, may also play a role, especially in traffic situations where the airspace has only a few aircraft that change ownership but still has a high degree of airspace complexity associated with the reconfiguration. In this paper, we identify these factors and discuss the human factors issues that should be considered in designing the airspace and airspace transitions.

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“…A human-in-the-loop study conducted at NASA Ames tested the feasibility of reconfiguring by moving an airspace boundary on-demand rather than combining and splitting functional airspace blocks [15]. The study found that the reconfiguration operation itself was feasible.…”

Section: Introductionmentioning

confidence: 99%