kl.
10.00
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15.00
Vestfold, Rom A1-36, campus Vestfold og Zoom
Mehdi Poornikoo skal forsvare avhandlingen sin for graden philosophiae doctor (ph.d.) ved Universitetet i Sørøst-Norge. 
Han har fulgt doktorgradsprogrammet nautiske operasjoner ved Fakultet for teknologi, naturvitenskap og maritime fag.
Alle interesserte ønskes velkommen til prøveforelesning og disputas. Denne vil også strømmes digitalt via Zoom: Direktelenke til Zoom.
Sammendrag
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.