Public Defence: Mehdi Poornikoo

Mehdi Poornikoo will defend his PhD degree. The thesis explores how simulation models can improve the interaction between human operators and maritime autonomous systems.

05 Sep

Practical information

  • Date: 5 September 2024
  • Time: 10.00 - 15.00
  • Location: Vestfold, Room A1-36, campus Vestfold and Zoom
  • Download calendar file

    • Zoom link for digital participation.

    Program 

    10.15 Trial lecture: “What are the typical Human-Automation Interaction (HAI) challenges across various industries? How do they differ in the context of autonomous shipping operations?”

    12.15 Public defence: Modeling Perspective on Human-Automation Interaction (HAI): Levels and Trust in Automation.

    Evaluation committee

    • First opponent: Birgit Kopainsky, professor, Bergen University, Norway
    • Second opponent: Johannes Kraus, assistant professor, Johannes Gutenberg-Universität Mainz, Germany
    • Administrator: Ziaul Haque Munim, associate professor, Universitety of Southeastern Norway 

    Supervisors

    • Main supervisor: Kjell Ivar Øvergård, professor, Universitety of Southeastern Norway 
    • Co supervisor: Frøy Birte Bjørneseth, associate professor, NTNU
Any questions?

Mehdi Poornikoo is defending his dissertation for the degree philosophiae doctor (PhD) at the University of South-Eastern Norway.

The doctoral work has been carried out at the Faculty of Technology, Natural Sciences and Maritime Sciences in the program nautical operations. 

Link to full dissertation. portrett av doktorgradstipendiat Mehdi Poornikoo

You are invited to follow the trial lecture and the public defence.
The event will also be available to attend digitally: Link to Zoom.

Summary

The development of Maritime Autonomous Surface Ships (MASS) is on the verge of opening a new era in the shipping industry. This can result in a new paradigm shift with regard to efficiency, safety, security, and environmental impact. Such novel development imposes a complex interaction between human operators and autonomous systems, particularly within Shore Control Centers (SCCs), where remote operators are expected to supervise one or many vessel operations.

To fully harness the potential of MASS, it is essential to create robust scientific models of Human-Automation Interaction (HAI) that cater to the specific demands of maritime environments and the roles of remote operators.

This doctoral study focuses on the importance of models and modeling within HAI, with particular emphasis on Trust in Automation (TiA) and Levels of Automation (LOA) as central themes. It embarks by exploring the significance of scientific modeling and developing scientific criteria to assess the credibility of the existing  models. Models of TiA are evaluated against these criteria to demonstrate their applicability and to understand prevailing TiA modeling efforts.

Additionally, this PhD project examines epistemological accounts of modeling efforts to determine the suitability of different approaches for HAI modeling. The findings suggest simulation modelling as a viable and flexible approach for addressing the complexities of trust and levels of automation in the context of supervisory control of MASS. The PhD project further offers two distinct simulation models using fuzzy logic and system dynamics methods. 
Through understanding the cognitive, behavioral, and social factors that impact remote operators' trust, the proposed models can inform the design of more intuitive and effective interfaces and decision-support systems.

Effective HAI models can also guide the development of tailored training programs, emphasizing critical skills such as situational awareness, decision-making under uncertainty, and efficient communication with autonomous systems. Lastly, these models can help identify potential sources of error, cognitive overload, and enhance operators' decision-making processes, thereby reducing the likelihood of accidents.