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From simply ringing a bell to preparing a five-course menu, human behavior commonly causes changes in the environment. Such episodes where an agent acts, thereby causing changes in their environment constitute the sense of agency. In this thesis four series of experi-ments elucidate how the sense of agency is represented in complex action-event sequences, thereby bridging a gap between basic cognitive research and real-life practice. It builds upon extensive research on the sense of agency in unequivocal sequences consisting of single ac-tions and distinct, predominantly auditory, outcomes. Employing implicit as well as explicit measures, the scope is opened up to multi-step sequences.
The experiments show that it is worthwhile devoting more research to complex action-event sequences. With a newly introduced auditory measure (Chapter II), common phenomena such as temporal binding and a decrease in agency ratings following distorted feedback were replicated in multi-step sequences. However, diverging results between traditional implicit and explicit measures call for further inspection. Multisensory integration appears to gain more weight when multiple actions have to be performed to attain a goal leading to more accurate representations of the own actions (Chapter III). Additionally, freedom of choice (Chapter III) as well as early spatial ambiguity altered the perceived timing of outcomes, while late spatial ambi-guity (Chapter IV) and the outcome’s self-relevance did not (Chapter V). The data suggests that the cognitive system is capable of representing multi-step action-event sequences implicitly and explicitly. Actions and sensory events show a temporal attraction stemming from a bias in the perception of outcomes. Explicit knowledge about causing an event-sequence facilitates neither feelings of control nor taking authorship. The results corroborate current theorizing on the un-derpinnings of temporal binding and the divergence between traditional implicit and explicit measures of the sense of agency. Promising avenues for further research include structured analyses of how much inferred causality contributes to implicit and explicit measures of agency as well as finding alternative measures to capture conceptual as well as non-conceptual facets of the agency experience with one method.
The rise of automated driving will fundamentally change our mobility in the near future. This thesis specifically considers the stage of so called highly automated driving (Level 3, SAE International, 2014). At this level, a system carries out vehicle guidance in specific application areas, e.g. on highway roads. The driver can temporarily suspend from monitoring the driving task and might use the time by engaging in so called non-driving related tasks (NDR-tasks). However, the driver is still in charge to resume vehicle control when prompted by the system. This new role of the driver has to be critically examined from a human factors perspective.
The main aim of this thesis was to systematically investigate the impact of different NDR-tasks on driver behavior and take-over performance. Wickens’ (2008) architecture of multiple resource theory was chosen as theoretical framework, with the building blocks of multiplicity (task interference due to resource overlap), mental workload (task demands), and aspects of executive control or self-regulation. Specific adaptations and extensions of the theory were discussed to account for the context of NDR-task interactions in highly automated driving.
Overall four driving simulator studies were carried out to investigate the role of these theoretical components. Study 1 showed that drivers focused NDR-task engagement on sections of highly automated compared to manual driving. In addition, drivers avoided task engagement prior to predictable take-over situations. These results indicate that self-regulatory behavior, as reported for manual driving, also takes place in the context of highly automated driving. Study 2 specifically addressed the impact of NDR-tasks’ stimulus and response modalities on take-over performance. Results showed that particularly visual-manual tasks with high motoric load (including the need to get rid of a handheld object) had detrimental effects. However, drivers seemed to be aware of task specific distraction in take-over situations and strictly canceled visual-manual tasks compared to a low impairing auditory-vocal task. Study 3 revealed that also the mental demand of NDR-tasks should be considered for drivers’ take-over performance. Finally, different human-machine-interfaces were developed and evaluated in Simulator Study 4. Concepts including an explicit pre-alert (“notification”) clearly supported drivers’ self-regulation and achieved high usability and acceptance ratings.
Overall, this thesis indicates that the architecture of multiple resource theory provides a useful framework for research in this field. Practical implications arise regarding the potential legal regulation of NDR-tasks as well as the design of elaborated human-machine-interfaces.
Are there emotional reactions towards social robots? Could you love a robot? Or, put the other way round: Could you mistreat a robot, tear it apart and sell it? Media reports people honoring military robots with funerals, mourning the “death” of a robotic dog, and granting the humanoid robot Sophia citizenship. But how profound are these reactions? Three experiments take a closer look on emotional reactions towards social robots by investigating the subjective experience of people as well as the motor expressive level. Contexts of varying degrees of Human-Robot Interaction (HRI) sketch a nuanced picture of emotions towards social robots that encompass conscious as well as unconscious reactions. The findings advance the understanding of affective experiences in HRI. It also turns the initial question into: Can emotional reactions towards social robots even be avoided?