A passive brain–computer interface application for the mental workload assessment on professional air traffic controllers during realistic air traffic control tasks

2016 ◽  
pp. 295-328 ◽  
Author(s):  
P. Aricò ◽  
G. Borghini ◽  
G. Di Flumeri ◽  
A. Colosimo ◽  
S. Pozzi ◽  
...  
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Mental Workload ◽  
Brain Computer Interface ◽  
Air Traffic ◽  
Computer Interface ◽  
Air Traffic Controllers

Artificial Intelligence for Evaluating the Mental Workload of Air Traffic Controllers

2020 ◽  
pp. 184-212
Author(s):  
Tetiana Shmelova ◽  
Yuliya Sikirda
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Expert System ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Mental Workload ◽  
Air Traffic ◽  
Control Center ◽  
Air Traffic Controllers ◽  
And Control

In this chapter, the authors propose the application of artificial intelligence (namely expert system and neural network) for estimating the mental workload of air traffic controllers while working at different control centers (sectors): terminal control center, approach control center, area control center. At each air traffic control center, air traffic controllers will perform the following procedures: coordination between units, aircraft transit, climbing, and descending. So with the help of the artificial intelligence (AI) and its branches expert system and neural network, it is possible to estimate the mental workload of dispatchers for a different number of aircraft, compare the workload intensity of the air traffic control sectors, and optimize the workload between sectors and control centers. The differentiating factor of an AI system from a standard software system is the characteristic ability to learn, improve, and predict. Real dispatchers, students, graduate students, and teachers of the National Aviation University took part in these researches.

Exploring the Peak-End Effects in Air Traffic Controllers’ Mental Workload Ratings

2021 ◽  
pp. 001872082199435
Author(s):  
Han Qiao ◽  
Jingyu Zhang ◽  
Liang Zhang ◽  
Yazhe Li ◽  
Shayne Loft
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Mental Workload ◽  
Peak Effect ◽  
Air Traffic ◽  
High Peak ◽  
End Effects ◽  
Air Traffic Controllers ◽  
Cognitive Awareness ◽  
Potential Impact

Objective This study examined whether professional air traffic controllers (ATCos) were subject to peak-end effects in reporting their mental workload after performing an air traffic control task, and in predicting their mental workload in future scenarios. Background In affective experience studies, people’s evaluation of a period of experience is strongly influenced by the most intense (peak) point and the endpoint. However, whether the effects exist in mental workload evaluations made by professional operators is still not known. Method In Study 1, 20 ATCos performed air traffic control scenarios on high-fidelity radar simulators and reported their mental workload. We used a 2 (high peak, low peak) × 2 (high end, low end) within-subject design. In Study 2, another group of 43 ATCos completed a survey asking them to predict their mental workload given the same air traffic control scenarios. Results In Study 1, ATCos reported higher mental workload after completing the high-peak and the high-end scenarios. In contrast, in Study 2, ATCos predicted the peak workload effect but not the end workload effect when asked to predict their experience in dealing with the same scenarios. Conclusion Peak and end effects exist in subjective mental workload evaluation, but experts only had meta-cognitive awareness of the peak effect, and not the end effect. Application Researchers and practitioners that use subjective workload estimates for work design decisions need to be aware of the potential impact of peak and end task demand effects on subjective mental workload ratings provided by expert operators.

scholarly journals Visual Search and Conflict Mitigation Strategies Used by Expert en Route Air Traffic Controllers

Aerospace ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 170
Author(s):  
Ricardo Palma Fraga ◽  
Ziho Kang ◽  
Jerry M. Crutchfield ◽  
Saptarshi Mandal
Keyword(s):  
Visual Search ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Relevant Information ◽  
Air Traffic ◽  
Mitigation Strategies ◽  
Air Traffic Controllers ◽  
Search Patterns ◽  
Potential Applications ◽  
Conflict Mitigation

The role of the en route air traffic control specialist (ATCS) is vital to maintaining safety and efficiency within the National Airspace System (NAS). ATCSs must vigilantly scan the airspace under their control and adjacent airspaces using an En Route Automation Modernization (ERAM) radar display. The intent of this research is to provide an understanding of the expert controller visual search and aircraft conflict mitigation strategies that could be used as scaffolding methods during ATCS training. Interviews and experiments were conducted to elicit visual scanning and conflict mitigation strategies from the retired controllers who were employed as air traffic control instructors. The interview results were characterized and classified using various heuristics. In particular, representative visual scanpaths were identified, which accord with the interview results of the visual search strategies. The highlights of our findings include: (1) participants used systematic search patterns, such as circular, spiral, linear or quadrant-based, to extract operation-relevant information; (2) participants applied an information hierarchy when aircraft information was cognitively processed (altitude -> direction -> speed); (3) altitude or direction changes were generally preferred over speed changes when imminent potential conflicts were mitigated. Potential applications exist in the implementation of the findings into the training curriculum of candidates.

Real-Time Assessment of Operator State in Air Traffic Controllers Using Ocular Metrics

2017 ◽  
Vol 61 (1) ◽  
pp. 257-261
Author(s):  
Jonny Kuo ◽  
Michael G. Lenné ◽  
Rama Myers ◽  
Anna Collard-Scruby ◽  
Courtney Jaeger ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Pupil Diameter ◽  
Negative Relationship ◽  
Continuous Operator ◽  
Air Traffic ◽  
State Monitoring ◽  
Air Traffic Controllers ◽  
Operator Fatigue

This study examined the utility of continuous operator state monitoring in predicting air traffic control officer (ATCO) workload and fatigue. Participants (N=8) were observed in live operational air traffic control environments for 60-minute periods. ATCO state was assessed using a real-time, computer vision-based system which tracked operator gaze and pupil diameter. Workload and fatigue were also assessed via the adapted Bedford Workload Scale and Samn-Perelli Fatigue Scale, respectively. Standard deviation of gaze was a significant predictor of both max and mean workload, showing a strong negative relationship with both subjective measures. Pupil diameter showed a significant positive relationship with operator fatigue. Our findings demonstrate the utility of continuous ocular metrics of workload and fatigue in operational environments.

Sign in / Sign up

Export Citation Format

Share Document