TRB Special Report 301: Traffic Controller Staffing in the En Route Domain A Review of the Federal Aviation Administration's Task Load Model (2010) / Chapter Skim
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3 Task Load Model
3 Task Load Model
Pages 26-45
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From page 26... ...
of its efforts to evaluate and validate the traffic simulations, key model parameters such as task times, and the task load output from the model. The chapter concludes with the committee's assessment of each modeling element, including evaluation and validation efforts.
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From page 27... ...
: (based on consultations with – Low – Shortcut operational experts) – Medium – Reroute – High – Hold – Diversion 4 R-Side Task Load Computation – Sums times spent on R-side tasks during 15-minute period (assumes task times are fixed and no multitasking)
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Three types of hand-offs are distinguished in the model: those involv ing aircraft entering from international airspace, from a sector con trolled by a different en route center, and from a sector controlled by the same center. Hand-offs are differentiated in this way in order to associate different task times with each.
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The committee was told that they represent about 90 percent of the R-side tasks performed based on CAASD's review of the literature and consultations with controller personnel and other subject matter experts. TRAFFIC SIMULATIONS AND TASK TRIGGERS Data Sources The two sources of flight data used to simulate traffic and trigger tasks are the National Offload Program (NOP)
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. Because FAA does not currently maintain an operations data set that contains information to trigger separation and delay tasks, CAASD uses its own analytic model to develop this information.
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Consistency in results led CAASD to conclude that CAPER would generate accurate separation event data for the task load model. Further analyses were performed to calibrate the parameters used by CAPER in detecting separation events.
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TASK TIMES AND SCHEDULES Derivation of Task Times The time assigned to each triggered task is a critical element of the task load model, since the task load output is a time summation. In briefings to the committee, CAASD maintained that it encountered difficulty establishing task times from the literature.
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The consultations with subject matter experts also led CAASD to conclude that the longer task times were needed for certain types of traffic, particularly flights involving propeller and military aircraft. For this particular traffic, assigned task times are increased by 25 percent for entry, exit, and nonradar arrivals and departures, under the assumption that additional communication and coordination are required.
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None 3 s/min in holding Monitoring None Variable s = seconds; min = minutes. NOTE: When aircraft is military or propeller, all task times for entry, exit, and nonradar arrivals and departures increase 25 percent.
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At first, the model assumed that a fixed amount of controller time is spent monitoring each aircraft transiting the sector. However, because some of the task times already presumed a certain amount of monitoring -- especially in the case of the time-consuming delay tasks -- CAASD was concerned that such a fixed time would lead to double counting and an overestimation of total monitoring task time for some flights.
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The time for nonradar arrivals and departures is uniformly distributed on the basis of the entry time identified by the trigger. Evaluation of Task Times CAASD selected GOMS to model task times because it was viewed as providing efficiency and flexibility, since the time estimate can be calculated with relatively little effort if the operators and methods are known and accurate operator time data are available.
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According to CAASD, these GOMS error rates are comparable with GOMS error rates generally, as observed from the literature cited in Box 3-1. However, because the FAA HITL experiments were not conducted for the specific purpose of developing model times, they could only be used to assess some of the task times.
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1995. GLEAN: A Computer Based Tool for Rapid GOMS Model Usability Evaluation of User Interface Designs.
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* GOMS Modeling for the MITRE En Route Workload Model, a briefing presented by MITRE to the TRB Committee for a Review of the En Route Air Traffic Control Com plexity and Workload Model, March 2010.
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TASK LOAD COMPUTATION Rollup to Task Load As previously discussed, the task times are scheduled in 1-minute intervals. The model processes the 1-minute intervals with the output rolled up to a larger time interval, typically 15 minutes.
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COMMITTEE ASSESSMENT FAA asked the committee to examine the input data and processes used for modeling traffic activity, the tasks and methods used to assign task times, and the means for validating model assumptions, parameters, and output. An assessment of each is offered next.
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CAASD leveraged the results from those dynamic density experiments in a 2004 analysis of the task load model, comparing the scores provided in that study with the values generated by running the model with scenario data obtained from the dynamic density HITL experiments. The results of the study indicated that as estimated task load increased, the controller-perceived complexity rating tended to increase as well.
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It is assumed further that a certain (but undefined) amount of monitoring is already included in other task times, particularly in the time-consuming delay tasks.
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The committee questions the extensive use of GOMS for task time derivation and the complete absence of task times developed through field observation or HITL experiments. GOMS modeling is typically used where there is limited opportunity to observe and analyze task performance in operational or experimental settings.
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Computation of Task Load The addition of task times to calculate R-side task load may be the simplest approach to computing task load while still being reasonable. However, adding task times does not account for the possibility -- and real-world probability -- that some tasks are performed concurrently and that the time it takes to performs tasks can change depending on the total task load or the number of controllers working the sector.
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