Automated vehicles (AVs) are on the edge of being available on the mass market. Research often focuses on technical aspects of automation, such as computer vision, sensing, or artificial intelligence. Nevertheless, researchers also identified several challenges from a human perspective that need to be considered for a successful introduction of these technologies. In this paper, we first analyze human needs and system acceptance in the context of AVs. Then, based on a literature review, we provide a summary of current research on in-car driver-vehicle interaction and related human factor issues. This work helps researchers, designers, and practitioners to get an overview of the current state of the art.

Einführung Ziel der vorliegenden Thesis ist es, die Eu- und Disstressoren der Infomatikstudierenden an der Hochschule Ruhr West zu untersuchen. Hierzu sollen nach den Wünschen der neuen Beratungsstelle für den Studienstress die Studierenden befragt werden. Nachfolgend werden in der Thesis die bekannten Problematiken im Informatikstudium eingebunden. Zusätzlich sollen die Informatikstudierenden auf den Stress mit einem Cartoon-Video aufmerksam gemacht werden. Mithilfe des Videos sollen die zukünftigen Eu- und Disstressoren rechtzeitig erkannt und Hilfe an der Hochschule Ruhr West abgeholt werden. Methode Die Untersuchung der Stressoren wird mit einem Fokusgruppeninterview (N = 4) und mit einer Online-Fragebogenerhebung (N = 120) durchgeführt. Die Signifikanzprüfungen sind varianzanalytisch und die Abweichungen der Gruppen werden mit t-Tests und einfaktorieller ANOVA berechnet. Ergebnisse Die Ergebnisse zeigen Unterschiede zwischen den Stressoren in unterschiedlichen Gruppen. Vor allem in den Gruppen mit davor erworbenen Vorkenntnissen und mit verschieden bewerteten Fachkompetenzen. Insbesondere ist der Stresslevel zwischen den Geschlechtern und bei den Informatikstudierenden, die mehrmals im Studium erkrankt waren, unterschiedlich. Schlussfolgerung Die Ergebnisse sind für die aktuellen Stresssituationen im Informatikstudium und für die nächsten Studien relevant. Außerdem wird mit dieser Studie auch auf die Problematiken in der Informatik, wie z. B. dem Frauenmangel in der Informatik, die den Informatikstudierenden den Stress verursachen könnten, aufmerksam gemacht.

The present bachelor theses discusses the creation process of a framework for the sys-tematic analysis of twitter posts regarding their sentiment. The result is an application, which links and uses the covered theoretical approaches for text classification.

The task of object detection in the automotive sector can be performed by evaluating various sensor data. The evaluation of LiDAR data for the detection of objects is a special challenge for which systems with neural networks can be used. These neural networks are trained by means of a data set. If you want to use the net with your own recordings or another data set, it is important to know how well these systems work in combination with data from another sensor. This allows the results to be estimated in advance and compared with the results of previous experiments. In this work the sensor dependence of a LiDAR based object recognition with neural networks will be analysed. The detector used in this work is PointRCNN [1], which was designed for the KITTI dataset [2]. To check the sensor dependency, the ’AEV Autonomous Driving Dataset’ (A2D2) dataset [3] was selected as a further dataset. After an introduction to PointRCNN and its functionality, the data of both datasets are analysed. Then the data of the second dataset will be ported into the format of the KITTI dataset so that they can be used with PointRCNN. Through experiments with varying combinations of training and validation data it shall be investigated to what extent trained models can be transferred to other sensor data or datasets. Therefore, it shall be investigated how strong the dependence of the detector (PointRCNN) on the used sensors is. The results show that PointRCNN can be evaluated with a different dataset than the training dataset while still being able to detect objects. The point density of the datasets plays a decisive role for the quality of the detection. Therefore it can be said that PointRCNN has a sensor dependency that varies with the nature of the point cloud and its density. Keywords: LiDAR data, 3D object recognition, laser scanner, sensor dependency, PointRCNN, PointNet++, PointNet, KITTI Dataset, AEV Autonomous Driving Dataset, A2D2 Dataset

Learning the German language is one of the most critical challenges for refugee children in Germany. It is a prerequisite to allow communication and integration into the educational system. To solve the underlying problem, we conceptualized a set of principles for the design of language learning systems to support collaboration between teachers and refugee children, using a Design Science Research approach. The proposed design principles offer functional and non-functional requirements of systems, including the integration of open educational resources, different media types to develop visual and audio narratives that can be linked to the cultural and social background. This study also illustrates the use of the proposed design principles by providing a working prototype of a learning system. In this, refugee children can learn the language collaboratively and with freely accessible learning resources. Furthermore, we discuss the proposed design principles with various socio-technical aspects of the well-being determinants to promote a positive system design for different cultural and generational settings. Overall, despite some limitations, the implemented design principles can optimize the potential of open educational resources for the research context and derive further recommendations for further research.

IEEE Workshop 2019 - Industrial and Medical Measurement and Sensor Technology, Vehicle Sensor Technology

Vortragsreihe der Hochschule Ruhr West Kurzfassung der Beiträge zum IEEE Workshop 2014 Industrielle Messtechnik & Kraftfahrzeugsensorik 28. März 2014, Band 3

The process automation extends over every manufacturing step of a product in the steel-mill to increase the quality, quantity and energy efficiency. The product dimensions are an important part of the quality control; these must maintain the specified tolerances. Additional to the cross-sectional-area, the measured data contains much more information about the manufacturing process, e.g. eccentricity, condition of the rolls and defects of the rod. For analyzing the measured data and to gather more information about the manufacturing process it is necessary to increase the speed of the data acquisition by performing some modifications of the VNA, e.g. faster analog to digital converter and microcontroller, improved firmware and optimized values of the passive electrical components for faster time constants and transient responses.

Quality and dimensional accuracy of hot rolled steel rods depend on several process parameters. In fact many of these crucial parameters are not be sufficiently determined yet. By improving automation and process control costs and scrap of production can be decreased. As part of the research project PIREF, one of these parameters – the roll gap – is under investigation beside other topics. Before starting rolling, the roll gap is typically set to a fixed value according to the planed dimensions of the product, but the forces during the rolling of the rod cause an enlargement of the roll gap. In which way the rolls change their position and form shall be examined in our research project. Therefore a first experimental setup has been built up to determine the change in position of the rolls under applied force. This is realized by a pot core coil as sensor using impedance analysis. The first results are presented in this work as a proof-of-principle.