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Automation, Trust and Workload

Principal Investigator

Andreas Duenser, Senior Research Scientist (email)

Team Members

Martin Lochner, Postdoctoral Fellow

Andrew Heathcote, Professor of Cognitive Psychology, UTAS (collaborator)

Timothy Gale, Senior Lecturer Engineering, UTAS (collaborator)

Benjamin Brooks, Associate Professor Seafaring, AMC / UTAS (collaborator)

Margareta Lutzhoft, Professor of Nautical Studies, Deputy Director NCPS, AMC / UTAS (collaborator)

Kristy de Salas, Senior Lecturer in Computing and Info Systems, UTAS (collaborator)

Christopher Lueg, Professor of Computing, UTAS (collaborator)

Mark Billinghurst, Professor of Human Computer Interaction School of Information Technology and Mathematical Sciences, UNISA (collaborator)

Lifetime

2016 – ongoing

Project Description

This is a Collaborative Research Project with collaboration partners form the University of Tasmania and the University of South Australia and applications in transportation, health and FinTech

Automation and autonomous systems are playing an increasing role in every-day life. Whereas the previous generation of autonomous technology had its impact largely in industrial spaces, (e.g. automotive factory robots), current advances are bringing such systems into the homes, workplaces, and automobiles of today’s citizens. A key factor here is the increased proximity to human operators and bystanders. This project aims to develop a useful model for making predictive analyses based on the three factors of: Automation; Trust; and Workload.

Our framework includes physical automation (e.g. self-driving cars, autonomous robotics) as well as automation within a user-experience framework, considering automated online information systems. Recent research on human interactions with autonomous and decision support systems indicates that the level of trust in the system affects the success of the interaction on a number of levels, and should therefore be taken into account as a major factor in the design process. Therefore the relation between trust, autonomy, and workload is intrinsic to the human-machine system, and the development of a model surrounding these influences will inform the successful future development of such systems.

Example projects

Managing Vessels in Port Waters

This project is a collaboration with Australian Maritime College (UTAS) and the CSIRO CI team to design a system to aid the navigation of large vessels as they enter or leave a port.

AMC_6104

The overall objective of the project is to identify mechanisms for managing vessels in port waters that will improve productivity, occupational health and safety (OHS), and operations from a safety point of view.

 

AMC custom ‘full mission’ maritime simulator main bridge, in Launceston, Australia
Figures 1 and 2:   AMC custom ‘full mission’ maritime simulator main bridge, in Launceston, Australia

 

Our focus in this project is:

  • Developing and testing new measurement tools of team workload in real-world and simulated environments (including psycho-physiological measurements).
  • Developing human performance testing protocols and performing system evaluations

Given the safety-critical nature of operations on a large ocean going vessel, and considering the need to understand operator workload for individuals in the distributed maritime operations team (including Captain, Pilot, Tug Master(s), and Vessel Traffic Service), we have begun investigating the remote collection of Electro-Dermal Activity (also known as Galvanic Skin Response) as a correlate of mental workload.  Electrophysiological signals are collected via personal radio transmitters for each team member, and these measures are combined with more traditional methodology (Instantaneous Situation Awareness measure; Subjective Workload Assessment Technique; Communications Analysis) in order to develop an understanding of the mental state of each team member during both standard operation conditions, and during critical emergency events such as engine failure, steering failure, and communications failure.

Some example data from our latest full scale-simulation run with specialists from an Australian port authority in the AMC sim follow.

comms sendercomms destination

Figure 3:  Full list of communications within the maritime operations team, listed by Sender (left) and by Destination (right). FWD Deck (forward deck) controls the ship’s anchor. Communications that were not specifically for the Captain or Pilot were labeled ‘Bridge’. If the pilot had an order for both tugs, this was labelled ‘Both Tugs’, as opposed to individual tug orders (Keera, Marysvale).

Synchronous GSR signals from Tug and Pilot, during a steering failure event
Figure 4:  Synchronous GSR signals from Tug and Pilot, during a steering failure event

 

Mine Informatics project

The CSIRO Mine Informatics project is working with the Mining Industry to address productivity improvements by the application of intelligent informatics methods. The main activities are:

  • mapping and characterising major voids in underground mines using remotely operated flying vehicles; and
  • virtual modelling of mining and mineral processing operations, enabling automation of the discovery of opportunities for improving efficiency through the application of machine learning techniques.

Cognitive Informatics team members help address the second of these challenges, helping to develop interfaces and visualisations to make intelligent optimisation comprehensible to a wide range of users within mines, such as mine managers and supervisors, planners, maintenance controllers and procurers.

mine_informatics
Figure 1: Operations centre.