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Elaine M. Pfleiderer

Bio: Elaine M. Pfleiderer is an academic researcher from Civil Aerospace Medical Institute. The author has contributed to research in topics: Workload & Logistic regression. The author has an hindex of 5, co-authored 13 publications receiving 103 citations.

Papers
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01 Apr 2002
TL;DR: In this article, a study was conducted to determine whether air traffic control (ATC) communication events would predict subjective estimates of controller workload as well as measures of controller taskload.
Abstract: : A study was conducted to determine whether air traffic control (ATC) communication events would predict subjective estimates of controller workload as well as measures of controller taskload We compared different regression models' predictions of subjective workload estimates made by 16 subject matter experts on 5 occasions during 8 samples of air traffic activity The predictors were different combinations of four taskload principal components computed from routinely recorded ATC data, two principal components representing the number and duration of voice communication events, and two principal components representing the content of voice communications Several regression model comparisons were computed to identify 'reduced' regression models containing fewer predictors that would predict the workload ratings as well as a full model containing all predictors Several reduced models predicted ATWIT (Air Traffic Workload Input Technique) ratings as well as the full model but all of these contained the Activity component These reduced models were a model containing only the Activity component, a model containing the Activity and Instructional Clearances components, and a model containing the Activity, Instructional Clearances, and All Communications Number and Duration components The results suggest that routinely recorded ATC data provide a good estimate of subjective workload However, if recordings of voice communications are available and researchers want to invest the time required to analyze the transcripts, they may be able to improve slightly their estimate of subjective workload The researcher must consider whether the information gained is worth the additional time investment required for analysis

38 citations

Journal ArticleDOI
TL;DR: In this paper, a study was conducted to determine whether air traffic control (ATC) communication events (number and duration of controller/ pilot communications) would predict subjective estimates of controller workload as well as taskload measures based on aircraft and controller activities.
Abstract: A study was conducted to determine whether air traffic control (ATC) communication events (number and duration of controller/ pilot communications) would predict subjective estimates of controller workload as well as taskload measures based on aircraft and controller activities. Analyses were conducted that compared different regression models’ predictions of subjective workload estimates made by 16 subject matter experts for 8 samples of air traffic activity. The predictors in the regression models were different combinations of five taskload principal components computed from routinely recorded ATC data and two measures of pilot/controller voice communications. A series of model comparisons was conducted to determine whether a “reduced” regression model containing fewer variables would predict the workload ratings as well as the full model containing all predictors. Several reduced models predicted ATWIT ratings as well as the full model, but a reduced model containing only the communications variables was not as effective. The results suggest that certain voice communications measures add nothing to the prediction of subjective workload, over and above that of taskload.

30 citations

01 Feb 2002
TL;DR: Two computer programs, the National Airspace System (NAS) Data Management System (NDMS) and the Performance and Objective Workload Evaluation Research (POWER) program, have been developed to provide a platform for quantifying en route air traffic controller activity and taskload.
Abstract: : Two computer programs, the National Airspace System (NAS) Data Management System (NDMS) and the Performance and Objective Workload Evaluation Research (POWER) program, have been developed to provide a platform for quantifying en route air traffic controller activity and taskload. The NDMS program extracts data produced by en route mainframe computers and encodes the information into database files that provide efficient storage and access. The POWER program calculates specific measures using aircraft positions and controller data entries. The development and use of such measures is important for establishing baseline activity measures and for evaluating modifications to ATC systems. NAS System Analysis Recording (SAR) data were collected from the Jacksonville en route air traffic control center between 8:30-10:30 a.m. and between 12:00-2:00 p.m. (local time) for each of four consecutive days. POWER measures were computed in 30-minute intervals for all active sectors. A Principal Components Analysis (PCA) was conducted to evaluate the current set of POWER variables and provide guidelines for the addition of new measures or the modification of existing ones. PCA with Varimax rotation converged in seven iterations and produced five components with eigenvalues> 1. Cumulatively, the four components accounted for 68.18% of the variability in the data set: Component 1 (Activity) accounted for 26%, Component 2 (Flight Path Variability) accounted for nearly 13%, Component 3 (Objective Workload) accounted for 11%, Component 4 (D-side Activity) accounted for 9%, and Component 5 (Overload) accounted for approximately 8%. Variables comprising the five extracted components provided valuable information about the underlying dimensions of the NAS data set. Additions or modifications that might improve the ability of POWER to describe ATC activity and taskload were identified.

17 citations

01 Dec 2006
TL;DR: In this paper, the authors compared the relative effectiveness of two constructs, sector activity and sector complexity, in predicting air traffic controller taskload, and found that sector activity predicted controller task load better than sector complexity.
Abstract: This study compared the relative effectiveness of two constructs, sector activity and sector complexity, in predicting air traffic controller taskload. Sector activity was defined as the activity associated with aircraft moving through the sector and was measured by counting the number of aircraft under the control of the sector during a traffic sample. Sector complexity describes a set of factors presumed to affect the difficulty experienced by a controller when controlling traffic. Sector complexity was measured in two ways. The first measure of complexity was a subjective rating made by supervisors and controllers to describe the complexity associated with specific traffic samples. The second was a composite variable that included measures reflecting several of the complexity variables found in the literature. Taskload was defined as controller activity and was measured by counting the number of data entries made by a controller during a traffic sample. The results appear to suggest that the authors' hypothesis, that sector activity predicted controller taskload better than sector complexity, was incorrect. However, interpretation of these results depended on consideration of what each of the variables measured. The Complexity Rating predicted controller activity better than the number of aircraft alone, but the Complexity Value (based on a set of variables identified through previous research) did not contribute at all to that prediction. Additional analyses suggested that the Complexity Rating measured something very different than the Complexity Value. The authors believe that the Complexity Ratings estimated the workload that observers believed the controller at the sector experienced instead of the complexity of the situation. On the other hand, the complexity measures used here did not appear to be not good measures of the construct. This may have occurred because the measures used in this study had limited variability or because they were not very good measures of the construct even though they were derived from factors identified in the literature as contributing to sector complexity. While the authors expected that the number of aircraft alone might be sufficient to predict controller activity/taskload, the results suggested that measuring both controller activity and extracting measures from other routinely recorded data might be necessary to develop more objective staffing standards used to determine how many controllers are needed to provide ATC services to individual facilities.

9 citations

01 May 2007
TL;DR: In this paper, the authors examined the extent to which objective static sector characteristics and controller ratings of static and dynamic sector complexity factors contributed to the occurrence of operational errors (OEs) at the Indianapolis air route traffic control center (ZID).
Abstract: : This study is an examination of the extent to which objective static sector characteristics and controller ratings of static and dynamic sector complexity factors contributed to the occurrence of operational errors (OEs) at the Indianapolis air route traffic control center (ZID). A multiple regression model of the relationship between a combination of static sector characteristics (sector altitude strata and sector size) resulted in a modest prediction of the variance in OE incidence (R = .70, R2 = .49). Sector size was negatively related to OEs, indicating that smaller sectors were associated with more OEs. Sector strata were positively related to OEs, indicating that higher altitude sectors were associated with more OEs. Principal Components Analysis (PCA) of the complexity ratings produced four components with eigenvalues >1.00, accounting for 62% of the variance in the data. Components were used as predictors in a multiple regression analysis of the number of OEs in the ZID sectors. Only Component 1 (climbing and descending aircraft in the vicinity of major airports) and Component 2 (services provided to non-towered airports) contributed significantly to the total proportion of variance explained by the model (R = .78, R2 = .61). Component 2 shared an inverse relationship with the number of OEs, indicating that the complexity related to providing services to non-towered airports is associated with fewer OEs. These results will be used to guide the choice of objective measures for further analysis of the influence of static and dynamic sector characteristics in the occurrence of OEs.

6 citations


Cited by
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Journal ArticleDOI
TL;DR: A critical review of research on mental workload in en route air traffic control (ATC) is performed and a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems is presented.
Abstract: Objective: We perform a critical review of research on mental workload in en route air traffic control (ATC). We present a model of operator strategic behavior and workload management through which workload can be predicted within ATC and other complex work systems. Background: Air traffic volume is increasing worldwide. If air traffic management organizations are to meet future demand safely, better models of controller workload are needed. Method: We present the theoretical model and then review investigations of how effectively traffic factors, airspace factors, and operational constraints predict controller workload. Results: Although task demand has a strong relationship with workload, evidence suggests that the relationship depends on the capacity of the controllers to select priorities, manage their cognitive resources, and regulate their own performance. We review research on strategies employed by controllers to minimize the control activity and information-processing requirements of control tasks. Conclusion: Controller workload will not be effectively modeled until controllers' strategies for regulating the cognitive impact of task demand have been modeled. Application: Actual and potential applications of our conclusions include a reorientation of workload modeling in complex work systems to capture the dynamic and adaptive nature of the operator's work. Models based around workload regulation may be more useful in helping management organizations adapt to future control regimens in complex work systems.

292 citations

Journal Article
TL;DR: In this paper, the authors consider problems related to the management of air traffic and airline operations for the purpose of minimizing the impact and cost of disruptions, and provide background that is essential to understand the fundamental issues and motivating the subsequent material.
Abstract: This chapter considers problems related to the management of air traffic and airline operations for the purpose of minimizing the impact and cost of disruptions The considerable system complexity outlined makes these problems challenging and has motivated a vibrant and innovative body of research Section 2 provides background that is essential to understanding the fundamental issues and motivating the subsequent material The authors review the “physics’ and characteristics of airspace system elements and airspace operations in order to explain why capacity constraints are so unpredictable and variable from day to day Of critical importance are the arrival and departure capacities of airports, which depend on weather, winds, and the number of active runways and their configurations

162 citations

01 Jan 2003
TL;DR: This study’s goal was to model airspace Dynamic Density and complexity (and hence controller workload) using traffic characteristic metrics, with a focus on metrics that could eventually enable Traffic Flow Management personnel to strategically prevent overloads using triggers other than predicted sector traffic count.
Abstract: This study’s goal was to model airspace Dynamic Density and complexity (and hence controller workload) using traffic characteristic metrics. The focus was on metrics that could eventually enable Traffic Flow Management (TFM) personnel to strategically prevent overloads using triggers other than predicted sector traffic count. Potential metrics from past studies were assessed in terms of how well they could be predicted at time horizons required for TFM decision support (up to 120 minutes), and their face validity. Also, proportional odds logistic regression determined the metrics’ usefulness for predicting subjective complexity ratings collected in an FAA-NASA study. Based on these analyses, a subset of 12 metrics was chosen (from the original 41). Further multiple regression analyses were conducted with this reduced model, to determine which metrics provided unique contributions to the prediction of subjective complexity, and to see the extent to which the same complexity factors related to subjective workload in different airspaces.

134 citations

Journal ArticleDOI
TL;DR: A critical analysis of the existing approaches for modeling and predicting air traffic complexity, examining their portability to autonomous ATM systems is presented.
Abstract: The characterization of complex air traffic situations is an important issue in air traffic management (ATM) Within the current ground-based ATM system, complexity metrics have been introduced with the goal of evaluating the difficulty experienced by air traffic controllers in guaranteeing the appropriate aircraft separation in a sector The rapid increase in air travel demand calls for new generation ATM systems that can safely and efficiently handle higher levels of traffic To this purpose, part of the responsibility for separation maintenance will be delegated to the aircraft, and trajectory management functions will be further automated and distributed The evolution toward an autonomous aircraft framework envisages new tasks where assessing complexity may be valuable and requires a whole new perspective in the definition of suitable complexity metrics This paper presents a critical analysis of the existing approaches for modeling and predicting air traffic complexity, examining their portability to autonomous ATM systems Possible applications and related requirements will be discussed

117 citations

Journal Article
TL;DR: In this article, the results of a dynamic density (DD) human-in-the-loop simulation and model development activity that was designed to examine the complexity measures were presented at the US/Europe ATM 2003 Seminar were used.
Abstract: This paper describes results of a dynamic density (DD) human-in-the-loop simulation and DD model development activity that was designed to examine the complexity measures. DD measures that were presented at the US/Europe ATM 2003 Seminar were used in the analysis. This study differed from the previous one in three aspects: first, the simulation included Reduced Vertical Separation Minima procedures, second, the study focused on the Cleveland Air Route Traffic Control Center’s airspace where previous study results showed the weakest correlation, and third, the traffic was actively controlled during the simulation, whereas in the previous study, audio/video replays were shown. The results indicated that the DD metric performed better than aircraft count, which is the basis of the presently used complexity gauge, and that the new DD model performed better than the previous model for Cleveland Center.

110 citations