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Understanding user needs and behavior in automated vehicles (AVs) while traveling is essential for future in-vehicle interface and service design. Since AVs are not yet market-ready, current knowledge about AV use and perception is based on observations in other transportation modes, interviews, or surveys about the hypothetical situation. In this paper, we close this gap by presenting real-world insights into the attitude towards highly automated driving and non-driving-related activities (NDRAs). Using a Wizard of Oz AV, we conducted a real-world driving study (N= 12) with six rides per participant during multiple days. We provide insights into the users’ perceptions and behavior. We found that (1) the users’ trust a human driver more than a system,(2) safety is the main acceptance factor, and (3) the most popular NDRAs were being idle and the use of the smartphone.
Human emotion detection in automated vehicles helps to improve comfort and safety. Research in the automotive domain focuses a lot on sensing drivers' drowsiness and aggression. We present a new form of implicit driver-vehicle cooperation, where emotion detection is integrated into an automated vehicle's decision-making process. Constant evaluation of the driver's reaction to vehicle behavior allows us to revise decisions and helps to increase the safety of future automated vehicles.
Currently, car assistant systems mainly try to prevent accidents. Increasing built-in car technology also extends the potential applications in vehicles. Future cars might have virtual windshields that augment the traffic or individual virtual assistants interacting with the user. In this paper, we explore the potential of an assistant system that helps the car’s occupants to calm down and reduce stress when they experience an accident in front of them. We present requirements from a discussion (N= 11) and derive a system design from them. Further, we test the system design in a video-based simulator study (N= 43). Our results indicate that an accident support system increases perceived control and trust and helps to calm down the user.
Self-driving cars will relief the human from the driving task. Nevertheless, the human might want to intervene in the driving process and thus needs the possibility to control the car. Switching back to fully manual controls is uncomfortable once being passive and engaging in non-driving-related activities. A more comfortable way is controlling the car with elemental maneuvers (e.g., "turn left" or "stop"). Whereas touch interaction concepts exist, contactless interaction through voice and mid-air gestures has not yet been explored for maneuver-based car control. In this paper, we, therefore, compare the general eligibility of voice and mid-air gesture with touch interaction as the primary maneuver selection mechanism in a driving simulator study. Our results show high usability for all modalities. Contactless interaction leads to a more positive emotional perception of the interaction, yet mid-air gestures lead to higher task load. Overall, voice and touch control are preferred over mid-air gestures by most users.
How to Increase Automated Vehicles’ Acceptance through In-Vehicle Interaction Design: A Review
(2020)
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.
This Paper presents a new service-learning setting based on the collaboration of engineering students and people with disabilities. The implementation at a German university is described and first results from two years of experience are shown. The objective of this case study is to show a transferable best practice concept with impact.
Stress im Informatikstudium
(2020)
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.
Das Ziel der vorliegenden Arbeit ist es, die Eignung von MeshLab in einem Reverse-Engineering-Projekt zu überprüfen. Dazu wurden vor Beginn sechs Kriterien aufgestellt, auf die MeshLab untersucht wird. Das Ergebnis zeigt, dass MeshLab fünf von sechs Kriterien erfüllt und somit für einen Einsatz geeignet ist.
MeshLab ist ein Teil der Datenaufbereitung des Reverse Engineering. Es ist ein kostenloses Programm und somit in Kombination mit einem günstigen Scanner für einen Einsatz in Reverse-Engineering-Projekten mit einem geringen Kostenaufwand einsetzbar.
The aim of this bachelor thesis is to verify the suitability of MeshLab in a Reverse-Engineering-Project. Before the beginning six criterias were set up on which MeshLab is examined. The result shows that MeshLab fulfills five of six criterias and is therefore suitable for use.
MeshLab is a part of the data preparation from the Reverse Engineering. It is a free programm and in combination with a cheap scanner, it can be used in a Revere-Engineering-Project with a low Budget.
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.
Das Ziel der vorliegenden Bachelorarbeit ist die Konzeption eines neuen Ansatzes − die Positive Co-Creation −, der die Elemente des Positive Computing in die Co-Creation integriert. Dafür wurden in einer Literaturanalyse die bestehenden Schwachstellen der Co-Creation herausgearbeitet, um anschließend die Vorteile des Positive Computing aufzuzeigen. Nach der Entwicklung eines spezifischen Modells der Positive Co-Creation, inklusive der verwendeten Methoden und deren Auswirkungen auf die Wohlbefindensfaktoren, wurde das Modell anhand von Experteninterviews evaluiert und verbessert. Das Ergebnis dieser Arbeit ist ein theoretisches Modell der Positive Co-Creation, welches den Prozess vollständig abbildet und einen Ansatzpunkt für eine praktische Umsetzung bildet. Dieser Ansatz ist gut geeignet, um bestehende Co-Creation-Prozesse anhand von Technologien um die Aspekte des Wohlbefindens zu erweitern.
Researchers have previously utilized the advantages of a design driven by well-being and intergenerational collaboration (IGC) for successful innovation. Unfortunately, scant information exists regarding barrier dimensions and correlated design solutions in the information systems (IS) domain, which can serve as a starting point for a design oriented toward well-being in an IGC system. Therefore, in this study, we applied the positive computing approach to guide our analysis in a systematic literature review and developed a framework oriented toward well-being for a system with a multi-generational team. Our study contributes to the IS community by providing five dimensions of barriers to IGC and the corresponding well-being determinants for positive system design. In addition, we propose further research directions to close the research gap based on the review outcomes.