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Im Zentrum dieses Workshops stehen Erkenntnisse zur Mensch-Computer-Interaktion in sicherheitskritischen Anwendungsgebieten. Da in solchen Feldern – etwa Katastrophenmanagement, Verkehr, Produktion oder Medizin – immer häufiger MCI stattfindet, sind viele wissenschaftliche Gebiete, unter anderem die Informatik, zunehmend gefragt. Die Herausforderung besteht darin, bestehende Ansätze und Methoden zu diskutieren, anzupassen und innovative Lösungsansätze zu entwickeln.
Die breite Einführung autonomer Fahrzeuge, ob für den Individualverkehr oder auch den öffentlichen Nahverkehr, ist nur noch eine Frage der Zeit. Dies bedeutet unweigerlich, dass in absehbarer Zeit alle Verkehrsteilnehmer*innen mit dieser Art von Fahrzeugen in Berührung kommen werden. In diesem Artikel soll diskutiert werden, wie Ansätze des Positive Computing helfen können, die Ausgestaltung der automatisierten Fahrzeuge so vorzunehmen, dass sie zum Wohlbefinden der Menschen in Verkehrssituationen beitragen.
The way we communicate with autonomous cars will fundamentally change as soon as manual input is no longer required as back-up for the autonomous system. Maneuver-based driving is a potential way to allow still the user to intervene with the autonomous car to communicate requests such as stopping at the next parking lot. In this work, we highlight different research questions that still need to be explored to gain insights into how such control can be realized in the future.
For highly automated vehicles (AVs), new interaction concepts need to be developed. Even in AVs, the driver might want to intervene and override the automation from time to time. To create the possibility of control, we explore vehicle control through maneuver-based interventions (MBI). Thereby, we focus on explicit, contact-less interaction, which could be beneficial in future AV designs, where the driver is not necessarily bound to classical controls. We propose a set of freehand gestures and keywords for voice control derived in a user-centered design process. Further, we discuss properties, applicability and user impressions of both interaction modalities. Voice control seems to be an efficient way to select a maneuver and free-hand gestures could be used, if voice channel is blocked, e.g., through conversation with passengers.
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.
Even though many aspects of automated driving have not yet become reality, many human factors issues have already been investigated. However, recent discussions revealed common misconceptions in both research and society about vehicle automation and the levels of automation levels. This might be due to the fact that automated driving functions are misnamed (cf. Autopilot) and that vehicles integrate functions at different automation levels (L1 lane keeping assistant, L2/L3 traffic jam assist, L4 valet parking). The user interface is one of the most critical issues in the interaction between humans and vehicles--and diverging mental models might be a major challenge here. Today's (manual) vehicles are ill-suited for appropriate HMI testing for automated vehicles. Instead, virtual or mixed reality might be a much better playground to test new interaction concepts in an automated driving setting.
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.
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.