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ItemAssessment of the cooperation between driver and vehicle automation: A framework(Elsevier, 2023)As long as the human driver is responsible for part(s) of the driving task during automated driving, the driver and automated driving system are sharing the driving task. Such a shared task is characterized by shared control, in which cooperation between the driver and vehicle automation is essential. However, means to holistically assess the quality of this cooperation are currently lacking. This work addresses how cooperation between driver and vehicle automation can be operationalized and assessed to gain insight into the quality of the shared driving task. Quality indicators and measurement methods are identified across seven dimensions reflective of the quality of cooperation between driver and automation. Based on previous empirical and theoretical studies a total of 34 quality indicators are identified. The methods to measure these quality indicators fall into four categories: 1) Subjective (such as questionnaires); 2) behavioral (such as reaction times, steering response); 3) neurophysiological (such as heart rate and pupil size); and 4) heuristic evaluation. The result is a first step in the development of a framework for the quantitative assessment of cooperation in the shared driving task. Yet, important knowledge gaps remain. For instance, the exact contribution of each quality indicator and their exact interrelationship are currently unclear. Moreover, all quality indicators reflect a requirement that should be met. Further research is needed to define exactly when each requirement is met. Additionally, it should be established to what degree each measurement method can validly and reliably provide insight into their quality indicator. Therefore, to ultimately ensure valid and reliable application of the framework in practice, the framework should continue to be developed and improved upon in future work.
ItemLearning Analytics voor de luchtvaart : white paper(Netherlands Aerospace Centre NLR, 2023)
ItemImpact of aircraft noise on health(Springer, 2022)Aircraft noise exposure is an environmental stressor and has been linked to various adverse health outcomes, such as annoyance, sleep disturbance, and cardiovascular diseases. Aircraft noise can trigger both psychological (annoyance and disturbance) and physiological stress responses (e.g. activation of the cardiovascular system and release of stress hormones). People are usually able to deal with this kind of stressor. However, a constant exposure to aircraft noise can cause a continuous state of stress. This in turn can constrain a person’s ability to regenerate and restore its resources to cope with the noise situation. As a consequence, the risk for certain negative health outcomes can be increased. Within the ANIMA project, literature reviews on the effects of aircraft noise on health outcomes have been performed. This chapter gives an overview of the relevant health outcomes affected by aircraft noise and summarises the results of different reviews and studies on these outcomes. Additionally, the underlying mechanisms of how noise impacts health are explained for daytime as well as night-time aircraft noise exposure (i.e. while sleeping). Further, the relevance of considering not only the general population, but vulnerable groups as well (such as children and elderly people) is described. Lastly, open questions for further studies are presented and discussed.
ItemDesign of a Tiltrotor Semi-Span Wind Tunnel Model for Whirl Flutter Investigations(Netherlands Aerospace Centre NLR, 2023)
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