Investigating Challenges in Decision Support Systems for Energy-Efficient Ship Operation: A Transdisciplinary Design Research Approach

Abstract

This paper reflects on our endeavors employing a transdisciplinary design research approach for developing novel, human-centered AI-based tools for energy-efficient ship operations. In the context of our concurrent studies, we begin by offering a succinct overview of key findings derived from an independently published literature review concentrating on human factors within this domain. Subsequently, we delve into a research-through-design process centered around human factors, followed by an account of a formative evaluation conducted within a ship simulator. These selected forms of inquiry together resulted in a holistic understanding of the application domain, target audience, and typical tasks as well as an interactive prototype of a decision support system for energy-efficient ship navigation. By viewing these research activities through the lens of a design research model, we systematically describe and discuss the individual contributions. As a primary contribution, we reflect on our lessons learned to identify generalizable challenges for similar future projects of the maritime ergonomics community. These include (1) addressing key human factors, (2) context-sensitive integration of navigational and operational data, (3) increasing transparency in data quality and processing steps related to system-generated recommendations, which would (4) support the mitigation of biases (e.g., automation bias). As a secondary contribution, we also share our resulting designs as examples of how decision support for optimizing energy efficiency can be visually and functionally integrated into ship navigation.