Carol A. Manning

Bio: Carol A. Manning is an academic researcher from Civil Aerospace Medical Institute. The author has contributed to research in topics: Air traffic control & Aviation. The author has an hindex of 7, co-authored 20 publications receiving 164 citations.

Using air traffic control taskload measures and communication events to predict subjective workload

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

The Relationship Between Air Traffic Control Communication Events and Measures of Controller Taskload and Workload

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.

Operational Use of the Air Traffic Selection and Training Battery

Abstract: : The Federal Aviation Administration (FAA) is commencing a massive hiring of air traffic control specialists using a new selection procedure, the Air Traffic Selection and Training (AT-SAT) computerized test battery. Before AT-SAT could be used for hiring purposes, however, the issue of its potential for adverse impact (potential unfair discrimination) had to be addressed. A previous project (Wise, Tsacoumis, Waugh, Putka, & Hom, 2001) reweighted the subtests and adjusted the overall constant to mitigate potential group differences that could result in adverse impact, without unduly compromising validity. A subsequent study (Dattel & King, 2006) used research participants and found that this effort appeared to have achieved its goal of mitigating group differences that could result in adverse impact. The present study endeavors to: 1) describe how AT-SAT functions as an operational selection method with respect to the several applicant pools, and 2) determine how the reweighting effort fares with actual applicants in the goal of reducing/eliminating group differences that could result in adverse impact. Of the 854 applicants who have taken AT-SAT as part of a job application process (rather than as according to a research protocol), 219 applicants (25.64%) voluntarily disclosed their race; gender was known for 253 (29.63%). The results suggest that the reweighting effort is paying dividends as group differences that could result in adverse impact are not in evidence. While the initial numbers reported here are relatively small, the issue of group differences that could result in adverse impact will be continually monitored. Longitudinal validation, comparing AT-SAT results to training and on-the-job performance, is a research priority due to concerns about the overall passing rate of 93.33%, which is higher than the expected passing rate of 67%.

Power: objective activity and taskload assessment in en route air traffic control

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.

Spinning paper into glass: transforming flight progress strips

Abstract: The aims of this paper are to describe how flight progress strips are currently used in U.S. en route air traffic control (ATC), and to discuss the Federal Aviation Administration's objective of eliminating them. The paper begins by briefly describing the U.S. ATC system, in particular, the en route environment, and then details how flight strips are used. Issues surrounding the replacement of flight strips are discussed, along with the role of various methods of inquiry in answering questions about appropriate strip replacements.

Modeling and Predicting Mental Workload in En Route Air Traffic Control: Critical Review and Broader Implications

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.

Air Transportation: Irregular Operations and Control

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

Dynamic density and complexity metrics for realtime traffic flow management

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.

Haptic Interaction Design for Everyday Interfaces

Abstract: This chapter sets about to provide the background and orientation needed to set a novice designer on his or her way to bringing haptics successfully into an interactive product. To define appropria...