A method to estimate air traffic controller mental workload based on traffic clearances

Workload estimation is a complex domain which has been investigated extensively over the years. Past estimation techniques have focused on measuring workload directly from the air traffic controllers (ATCOs) or inferring it from traffic factors. The limitations of these techniques are interfering into the ATCO job and not being able to capture the differences amongst individual ATCOs respectively. This paper presents a novel technique overcoming these limitations, able to accurately estimate the workload experienced by the ATCO based exclusively on the clearances provided to air traffic. The technique, which was calibrated for the EUROCONTROL Maastricht Upper Area Control (MUAC) Centre, thereby has the potential to more accurately estimate actual airspace capacity. It is independent of the level of system automation and therefore applicable not only with the current ATM system, but also in the anticipated future highly automated environments as well as during the transition period. The paper discusses potential applications such as real time monitoring of operational workload and post-operations identification of sector workload imbalances. Both can contribute towards enhancing the performance of the ATM system.

[1]  W. Ochieng,et al.  Estimation of European Airspace Capacity from a Model of Controller Workload , 2002, Journal of Navigation.

[2]  R. H. Mogford,et al.  The Complexity Construct in Air Traffic Control: A Review and Synthesis of the Literature. , 1995 .

[3]  S. Kauppinen,et al.  European medium-term conflict detection field trials [ATC] , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[4]  Mark D. Rodgers,et al.  THE RELATIONSHIP OF SECTOR CHARACTERISTICS TO OPERATIONAL ERRORS. , 1997 .

[5]  Christopher D. Wickens,et al.  Workload Assessment and Prediction , 1990 .

[6]  David Gianazza,et al.  An efficient airspace configuration forecast , 2009 .

[7]  Mica R. Endsley,et al.  Automation and situation awareness. , 1996 .

[8]  Erik Hollnagel,et al.  Time and time again , 2002 .

[9]  Hartmut Fricke,et al.  Air traffic control complexity as workload driver , 2010 .

[10]  A J Tattersall,et al.  An experimental evaluation of instantaneous self-assessment as a measure of workload. , 1996, Ergonomics.

[11]  William S. Pawlak,et al.  A FRAMEWORK FOR THE EVALUATION OF AIR TRAFFIC CONTROL COMPLEXITY , 1996 .

[12]  R. Christien,et al.  Air traffic complexity indicators & ATC sectors classification , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[13]  G. R. J. Hockey Compensatory control in the regulation of human performance under stress and high workload: A cognitive-energetical framework , 1997, Biological Psychology.

[14]  Erik Hollnagel,et al.  Cognitive reliability and error analysis method : CREAM , 1998 .

[15]  Glenn F. Wilson,et al.  An Analysis of Mental Workload in Pilots During Flight Using Multiple Psychophysiological Measures , 2002 .

[16]  A Bisseret Analysis of mental processes involved in air traffic control. , 1971, Ergonomics.

[17]  Brian Hilburn,et al.  COGNITIVE COMPLEXITY IN AIR TRAFFIC CONTROL: A LITERATURE REVIEW , 2004 .

[18]  George E. Cooper,et al.  Handling qualities and pilot evaluation , 1986 .

[19]  Joan M. Ryder,et al.  Cognitive Task Analysis of Expertise in Air Traffic Control , 1993 .

[20]  Jonathan Histon The impact of structure on cognitive complexity in air traffic control , 2002 .

[21]  Anthony J. Masalonis,et al.  DYNAMIC DENSITY AND COMPLEXITY METRICS FOR REALTIME TRAFFIC FLOW MANAGEMENT , 2003 .

[22]  Parimal Kopardekar,et al.  Analysis of Current Sectors Based on Traffic and Geometry , 2008 .

[23]  Elizabeth D. Murphy,et al.  Using Knowledge Exploration Tools to Study Airspace Complexity in Air Traffic Control , 1994 .

[24]  John W. Polak,et al.  Estimating Capacity of Europe’s Airspace Using a Simulation Model of Air Traffic Controller Workload , 2001 .

[25]  Marsha C. Lovett,et al.  Modeling Individual Difference Factors in a Complex Task Environment , 2003 .

[26]  Keumjin Lee,et al.  Air Traffic Complexity: An Input-Output Approach , 2007, 2007 American Control Conference.

[27]  Richard I. Thackray,et al.  Age-Related Differences in complex Monitoring Performance , 1981 .

[28]  Glenn F. Wilson,et al.  Psychophysiological responses to changes in workload during simulated air traffic control , 1996, Biological Psychology.

[29]  Colin G. Drury,et al.  Air Traffic Controllers' Performance in Advance Air Traffic Management System: Part I—Performance Results , 2011 .

[30]  Carol A. Manning,et al.  Relationship of Sector Activity and Sector Complexity to Air Traffic Controller Taskload , 2006 .

[31]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[32]  J. Sperandio The regulation of working methods as a function of work-load among air traffic controllers. , 1978, Ergonomics.

[33]  Shayne Loft,et al.  Modeling and Predicting Mental Workload in En Route Air Traffic Control: Critical Review and Broader Implications , 2007, Hum. Factors.

[34]  Kang Li,et al.  Understanding Perceived Complexity in Human Supervisory Control , 2000, Cognition, Technology & Work.

[35]  Paul U. Lee,et al.  Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments , 2012 .

[36]  Arnab Majumdar,et al.  En-Route Sector Capacity Estimation Methodologies: An International Survey , 2005 .

[37]  P. Averty,et al.  Evaluating a new index of mental workload in real ATC situation using psychophysiological measures , 2002, Proceedings. The 21st Digital Avionics Systems Conference.

[38]  Lisanne Bainbridge,et al.  Ironies of automation , 1982, Autom..

[39]  Paul A. Falzon Discourse segmentation and the management of multiple tasks in single episodes of air traffic controller-pilot spoken radio communication , 2009 .