Carl Westin

177 T HE immediate value of this thesis is anchored to the problem definition in the context of choice: How to overcome controller acceptance issues of automated decision aids for conflict detection and resolution? This problem is set against the fragmented, increasingly crowded, and unevenly trafficked airspace worldwide. In order for ATC services to host and cope with future traffic demands, there is a need for more advanced and intelligent automation that can ease the air traffic controller’s cognitive burden in problem-solving tasks. A problem, however, is that systems de- veloped for this very purpose have been, and continue to be, rejected by controllers. This thesis proposed that the resistance towards such automated support sys- tems, in particular ATC CD&R decision aids, can be explained by machines rea- soning and solving problems differently from controllers. This difference was con- ceptualized and defined on a continuum of strategic conformance : The degree to which automation’s solution and apparent underlying operations match those of the human. As such, it is argued that strategic conformal solution advice, which matches the human’s solution, facilitates an intuitive, (sub)conscious understanding of the automation’s reasoning. Strategic conformance was introduced at the highest level of human-machine compatibility extending previous research by 1) exploring the concealed underlying strategies involved in decision-making, and 2) exploring the diversity in problem-solving by recognizing each individual’s problem-solving preferences. The goal pursued in this thesis was: Thesis goal To empirically investigate strategic conformance as a means for more personalized automation support, and develop a fundamental under- standing of how a decision aid’s strategic conformance affects the in- teraction with that aid and acceptance of its advisories. Findings in this thesis have significant implications for the understanding of how controllers’ solve conflicts and respond to resolution advisories depending on its conformance. The analysis of controllers’ manual conflict solutions showed that controllers solved conflicts consistently, but disagree. Experienced controllers were found slightly more consistent than trainees, possibly because of their more well- developed and established conflict solving preferences and strategies. An implica- tion of this is the possibility to create more personalized, conformal automation. A limitation is that consistency was limited to higher decision stages (e.g., choosing one or both aircraft, or aircraft A or B to interact with), and could not be estab- lished for more detailed decision stages (e.g., vectoring aircraft A to the right by 035 degrees). Results from three human-in-the-loop studies indicate that strategic confor- mance plays an important role for the acceptance of automated resolution advi-