@phdthesis{,
    author = {Mund, Dennis},
    title = {Bewertung psychophysiologischer Mess-Sensoriken als Basis für nutzeradaptive Automation},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2022},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {Adaptive Automation, Workload, Mental State Estimation, Activity Determination},
    abstract = {This dissertation addresses the enabling of automated support that adapts to the workload experienced by pilots of future manned- unmanned aircraft teams. The basic prerequisite for this is a real-time determination of the workload to identify situations with an increased need for support. For this purpose, different methods of operationalizing workload were investigated experimentally and then evaluated for their suitability for adaptive automation. Past studies of adaptive automation often separate the analysis of workload or other mental state descriptions from the selection of an adequate support strategy. In contrast, this work will consider the extent to which even the determination of strain can provide clues as to the appearance of an adaptation of automation. An additional core component of the work is the development of a functional prototype, which represents a realistic simulation of a complex real task spectrum. Only in such simulations can the interactions of adaptive automation with humans be investigated in closed-loop experiments. Within the functional prototype, different types of workload determination are experimentally investigated and the findings about the methods are summarized based on evaluation criteria. Finally, based on the previous evaluation, a concept for the use of adaptive automation for the leader of a manned-unmanned team is presented, which combines the advantages of the respective measurement method.},
    note = {},
    
    school = {Universität der Bundeswehr München},
    
}