UAS integration in congested terminal airspace: challenges posed to pilots

2020 ◽  
Vol 8 (2) ◽  
pp. 79-88
Author(s):  
Julie Diiulio ◽  
Laura G. Militello ◽  
Devorah E. Klein
Keyword(s):  
Traffic Control ◽  
Task Analysis ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Analysis Method ◽  
Aircraft Systems ◽  
Increasing Demand ◽  
Cognitive Challenges

There is increasing demand to operate unmanned aircraft systems (UAS) in congested terminal environments, such as busy commercial airports. With this demand comes challenges to pilots. To identify these challenges, we conducted critical decision method (CDM) interviews with pilots. CDM is a cognitive task analysis method aimed at uncovering tacit cognitive challenges. Eight pilots from the U.S. were interviewed including four UAS pilots and four commercial pilots. Interviews were analyzed using thematic analysis, resulting in the identification of four categories of cognitive challenges: (i) noticing anomalies, (ii) diagnosing automation behavior, (iii) understanding when and how to intervene, and (iv) coordinating with air traffic control. In this paper, we describe each challenge, highlight real-world examples from our interviews, and provide some recommendations for addressing the implications of integrating UAS in congested terminal airspace.

scholarly journals Providing a foundation for interpretable autonomous agents through elicitation and modeling of criminal investigation pathways

2020 ◽  
Vol 64 (1) ◽  
pp. 239-243
Author(s):  
Sam Hepenstal ◽  
Leishi Zhang ◽  
Neesha Kodogoda ◽  
B.L. William Wong
Keyword(s):  
Artificial Intelligence ◽  
Task Analysis ◽  
Autonomous Agents ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Criminal Investigation ◽  
Event Tree ◽  
Analysis Method ◽  
Ethical Concerns ◽  
Criminal Intelligence

Criminal investigations are guided by repetitive and time-consuming information retrieval tasks, often with high risk and high consequence. If Artificial intelligence (AI) systems can automate lines of inquiry, it could reduce the burden on analysts and allow them to focus their efforts on analysis. However, there is a critical need for algorithmic transparency to address ethical concerns. In this paper, we use data gathered from Cognitive Task Analysis (CTA) interviews of criminal intelligence analysts and perform a novel analysis method to elicit question networks. We show how these networks form an event tree, where events are consolidated by capturing analyst intentions. The event tree is simplified with a Dynamic Chain Event Graph (DCEG) that provides a foundation for transparent autonomous investigations.

Expertise in Air Traffic Control (ATC): What is it, and how Can we Train for It?

1992 ◽  
Vol 36 (17) ◽  
pp. 1326-1330 ◽  
Author(s):  
Richard E. Redding ◽  
John R. Cannon ◽  
Thomas L. Seamster
Keyword(s):  
Traffic Control ◽  
Task Analysis ◽  
Cognitive Task ◽  
Federal Aviation Administration ◽  
Cognitive Task Analysis ◽  
Air Traffic ◽  
Curriculum Redesign ◽  
Air Traffic Controllers ◽  
Data Collection And Analysis ◽  
Training Efficiency

The Federal Aviation Administration has embarked on a major curriculum redesign effort to improve the training efficiency of en route air traffic controllers. Included in this effort was a comprehensive cognitive task analysis conducted in several phases, spanning several years. Eight different types of data collection and analysis procedures were used, resulting in an integrated model of controller expertise. This paper provides a description of controller expertise, and describes the training program under development. This is one of the first examples of cognitive task analysis being applied to study expertise in complex cognitive tasks performed in time-constrained, multi-tasking environments.

Cognitive Task Analysis of Expertise in Air Traffic Control

1993 ◽  
Vol 3 (4) ◽  
pp. 257-283 ◽  
Author(s):  
Thomas L. Seamster ◽  
Richard E. Redding ◽  
John R. Cannon ◽  
Joan M. Ryder ◽  
Janine A. Purcell
Keyword(s):  
Traffic Control ◽  
Air Traffic Control ◽  
Task Analysis ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Air Traffic

scholarly journals Introducing Unmanned Aircraft Systems into a High Reliability ATC System

2013 ◽  
Vol 66 (5) ◽  
pp. 719-735 ◽  
Author(s):  
Peter Brooker
Keyword(s):  
Traffic Control ◽  
High Reliability ◽  
Policy Decision ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems ◽  
Efficient Integration ◽  
Effective Use ◽  
Technological Improvements ◽  
Real Time Simulations

Civil and military unmanned aircraft systems (UAS) operations are currently subject to restrictions that put major limits on their use of airspace. There is considerable debate about how to develop the safe, secure and efficient integration of UAS into non-segregated airspace and aerodromes. This paper examines a necessary safety aspect. Airlines and their passengers would obviously ask, “Is it still safe with all these unmanned aircraft around?” The spotlight must be on Air Traffic Control Systems as High Reliability Organizations (HRO). That status comes from industry characteristics: focus on safety, effective use of technological improvements, learning from feedback from accidents/incidents, and an underpinning safety culture. The safety of ATC Systems has improved dramatically: accidents are now the product of rare and complex ‘messes’ of multiple failures. It is therefore a major challenge to preserve the HRO status by ensuring at least current safety performance. The analysis sketches feasible processes of policy decision-making and safety analyses. Key factors are policies on UAS equipage and airspace usage, implementation of a Traffic Alert and Collision Avoidance System (TCAS)-variant appropriate for UAS, use of an ‘Equivalent Level of Safety’ philosophy, small datalink latencies, proven HRO safety and learning cultures, and stress testing of system resilience by real-time simulations.

Cognitive Task Analysis of Future Air Traffic Control Concepts: The TCAS Downlink Scenario

2007 ◽  
Vol 51 (2) ◽  
pp. 98-101 ◽  
Author(s):  
Brian Hilburn
Keyword(s):  
Situation Awareness ◽  
Traffic Control ◽  
Air Traffic Control ◽  
Task Analysis ◽  
Cognitive Task ◽  
Cognitive Task Analysis ◽  
Air Traffic ◽  
Joint Decision ◽  
Potential Benefits ◽  
The Impact

Traffic Collision Avoidance System (TCAS) is a flightdeck-based technology aimed at helping aircraft avoid proximate traffic. TCAS information has traditionally not been presented to the air traffic controller. A 2002 German midair collision was triggered, in part, by incompatible air traffic control (ATC) and TCAS clearances. Largely in response to this accident, attention has focused in recent years on the potential benefits of “downlinking” to the controller TCAS Resolution Advisories (RAs) in near real time. Such presentations, it is thought, could benefit situation awareness and joint decision making between controller and pilot. A cognitive task analysis (CTA) was recently conducted into the present-day and future RA Downlink (RAD) operational concepts. On the basis of functional task description and cognitive walkthroughs, CTA assessed the impact of various specific non-nominal events (e.g. pilot reports RA, but does not initiate an evasive maneuver). Finally, a set of cognitive elements and potential error mechanisms was identified.

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