Building Trust in Autonomous System Competence – the DiTA Digital Tower Assistant for Multiple Remote Towers, an Early Concept Evaluation

A bottleneck of (future) multiple remote tower operations (MRTO) is for controllers to monitor traffic movements at two airports (or more) in real-time, at the same time. To address this, we propose an autonomous agent (digital colleague), the DiTA Digital Tower Assistant. The key issue addressed by the DiTA concept is simultaneous movements on the two airports. We present results from the first stages of concept design and evaluation of DiTA. We conducted two workshops with three fully licensed air traffic controllers. During the workshops the controllers evaluated the DiTA concept of operations through scenario walk-throughs using printed airspace maps. The outcome of the workshop series was a tentative concept of DiTA operations and key concerns for one MRTO scenario. We present and discuss the emerging picture of common concerns and views on acceptable concept of operations as the workshops progressed. We conclude that it is is vital that operators can place the right level of trust in autonomous system competence, especially when they manage safety critical movements. To achieve this, DiTA competence is a key concern. The build-up of operator trust and competence to assess DiTA comptence (re-skilling) could both rely on automation transparency and a stepwise introduction of the concept in operations.

[1]  Carl Westin,et al.  Concept of Reskilling for Automation Collaboration in Maritime Piloting , 2019 .

[2]  Todd J. Callantine CATS-based Air Traffic Controller Agents , 2013 .

[3]  Jean-Michel Hoc,et al.  Towards a cognitive approach to human-machine cooperation in dynamic situations , 2001, Int. J. Hum. Comput. Stud..

[4]  Jeffrey M. Bradshaw,et al.  Ten Challenges for Making Automation a "Team Player" in Joint Human-Agent Activity , 2004, IEEE Intell. Syst..

[5]  Wen-Chin Li,et al.  The Investigation Human-Computer Interaction on Multiple Remote Tower Operations , 2017, HCI.

[6]  Jonas Lundberg,et al.  Human-in-the-loop AI: Requirements on future (unified) air traffic management systems , 2019, 2019 IEEE/AIAA 38th Digital Avionics Systems Conference (DASC).

[7]  Jonas Lundberg,et al.  Situation awareness systems, states and processes: a holistic framework , 2015 .

[8]  Hendrikus G. Visser,et al.  Improved Trajectory Prediction for Air Traffic Management by Simulation of Guidance Logic and Inferred Aircraft Intent using Existing Data-Link Technology , 2012 .

[9]  Henry Hexmoor,et al.  Air Traffic Control Agents: Landing and Collision Avoidance , 2000 .

[10]  Robert R. Hofman,et al.  Simon's Slice: Five Fundamental Tradeoffs that Bound the Performance of Human Work Systems , 2011 .

[11]  Jonas Lundberg,et al.  Challenges for research and innovation in design of digital ATM controller environments: An episode analysis of six simulated traffic situations at Arlanda airport , 2016, 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC).

[12]  Jeffrey M. Bradshaw,et al.  The Seven Deadly Myths of "Autonomous Systems" , 2013, IEEE Intelligent Systems.

[13]  Christine M. Mitchell,et al.  GT-Cats: Tracking Operator Activities in Complex Systems , 2013 .

[14]  Björn J. E. Johansson,et al.  A framework for describing interaction between human operators and autonomous, automated, and manual control systems , 2020, Cognition, Technology & Work.

[15]  D. Woods,et al.  Automation Surprises , 2001 .