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Auflistung nach Schlagwort "Automated Driving"

1 - 8 von 8
  • Workshopbeitrag
    1st Workshop on “User Experience for Sustainability in the Age of Automated Driving and Electromobility”
    (Mensch und Computer 2021 - Workshopband, 2021) Holzhammer, Uwe; Lenz, Maximilian Josef; Riener, Andreas; Schweizer, Manuel; Tutunaru, Robin
    Automation and electromobility are disruptive technologies within the automotive industry at the beginning of the second decade of the 21st century. Both technologies combined are inherent in high potential to lower fuel/energy consumption and increase overall efficiency and thus sustainability in the transportation sector. However, the acceptance of fuel-saving driving modes and of electrified drivetrains is of fundamental importance. Therefor Automotive HMIs offer the possibility to inform the passengers about the environmental impact of their driving behavior or habits of use and enable to persuade towards a more sustainable lifestyle. This workshop is designed for UX researchers, students and interested citizens that want to participate in a discourse and design process for future automotive UIs. Using brainstorming methods combined with clustering of the ideas we will find out which information provided at which time is adequate to cause a change of behaviour which then diminishes the environmental impact of driving.
  • Workshopbeitrag
    9thWorkshop Automotive HMIs: Natural and Adaptive UIs to Support Future Vehicles
    (Mensch und Computer 2021 - Workshopband, 2021) Riener, Andreas; Pfleging, Bastian; Detjen, Henrik; Braun, Michael; Peintner, Jakob
    Modern vehicles allow control by the driver with multimodal user interfaces (UIs), touch interaction on screens, speech input, and mid-air gestures. Such UIs are driver-focused and optimized for limited distraction to not compromise road safety in manual driving. Nevertheless, they are often complex and it might be difficult to find specific features. Automated driving in L3+ will disrupt the design of automotive UIs as drivers become passengers, at least for certain parts along the way. Similarly, the car is being transformed into a social space where passengers can be granted control over systems because they can devote their full attention without imposing safety risks. The complexity of advanced driver assistance, in-vehicle information and interaction systems requires explanation to the user, e.g., in which state the system is, interaction possibilities, expectations from the driver or take over timing. We expect novel technologies to allow for natural interaction and adaptivity to design valuable and future-proof interaction concepts for the changing interior of (automated) vehicles. The goal of this workshop is, thus, to discuss how natural and adaptive user interfaces can help to solve the mentioned challenges and to identify opportunities for future research and collaboration.
  • Zeitschriftenartikel
    Evaluating feedback requirements for trust calibration in automated vehicles
    (it - Information Technology: Vol. 63, No. 2, 2021) Wintersberger, Philipp; Janotta, Frederica; Peintner, Jakob; Löcken, Andreas; Riener, Andreas
    The inappropriate use of automation as a result of trust issues is a major barrier for a broad market penetration of automated vehicles. Studies so far have shown that providing information about the vehicle’s actions and intentions can be used to calibrate trust and promote user acceptance. However, how such feedback could be designed optimally is still an open question. This article presents the results of two user studies. In the first study, we investigated subjective trust and user experience of (N=21) participants driving in a fully automated vehicle, which interacts with other traffic participants in virtual reality. The analysis of questionnaires and semi-structured interviews shows that participants request feedback about the vehicle’s status and intentions and prefer visual feedback over other modalities. Consequently, we conducted a second study to derive concrete requirements for future feedback systems. We showed (N=56) participants various videos of an automated vehicle from the ego perspective and asked them to select elements in the environment they want feedback about so that they would feel safe, trust the vehicle, and understand its actions. The results confirm a correlation between subjective user trust and feedback needs and highlight essential requirements for automatic feedback generation. The results of both experiments provide a scientific basis for designing more adaptive and personalized in-vehicle interfaces for automated driving.
  • Konferenzbeitrag
    Explanation Needs in Automated Driving: Insights from German Driving Education and Vehicle Acquisition
    (Proceedings of Mensch und Computer 2024, 2024) Manger, Carina; Albrecht, Kathrin; Riener, Andreas
    As driving assistance driving systems become increasingly advanced, a correct understanding of the functionality of these systems is crucial for safe use. In this work we explored drivers’ explanation needs and current explanation methods from an important but underlooked perspective: driver training and vehicle acquisition. In a two-step approach, we conducted expert interviews with n = 7 driving instructors and vehicle salespeople in Germany and validated these results with an online survey of n = 105. Our results show that Driver Assistance Systems (DASs) and Advanced Driver Assistance Systems (ADASs), are currently covered in both driver training and vehicle acquisition but to a varying extent and in a very application-oriented manner. A drivers’ tendency for preferring comparative explanations that build upon knowledge about similar systems was found. Based on the combined results, we emphasize the need for mandatory and standardized explanation methods to ensure a safe transition to automated driving.
  • Konferenzbeitrag
    Joint Decision Making and Cooperative Driver-Vehicle Interaction during Critical Driving Situations
    (i-com: Vol. 15, No. 3, 2016) Altendorf, Eugen; Weßel, Gina; Baltzer, Marcel; Canpolat, Yigiterkut; Flemisch, Frank
    In automated driving, the human driver and an automation form a joint human-machine system. In this system, each partner has her own individual cognitive as well as perceptual processes, which enable them to perform the complex task of driving. On different layers of the driving task, both, drivers and automation systems, assess the situation and derive action decisions. Although the processes can be divided between human and machine, and are sometimes very elaborate, the outcome should be a joint one because it affects the entire driver-vehicle system. In this paper, the individual processes for decision-making are defined and a framework for joint decision-making is proposed. Joint decision-making relies on common goals and norms of the two subsystems, human and automation, and evolves with experience.
  • Konferenzbeitrag
    A Robust Drowsiness Detection Method based on Vehicle and Driver Vital Data
    (Mensch und Computer 2017 - Workshopband, 2017) Kundinger, Thomas; Riener, Andreas; Sofra, Nikoletta
    Driver drowsiness is one of the main causes of fatal traffic accidents. Current driver assistance systems often use parameters related to driving behavior for detecting drowsiness. However, the ongoing automation of the driving task diminishes the availability of driving behavior parameters, therefore reducing the scope of such detection methods. The driver’s role as the sole operator changes; the driver must supplement, supervise or serve as a fallback part of a highly assisted/automated system. Reliably monitoring the driver’s state, especially the risk factor drowsiness, becomes more and more important for future automated driver systems. Numerous approaches, utilizing vehicle-based, behavioral and physiological based metrics, exist. This paper summarizes and discusses prevailing research questions related to drowsiness modeling and detection within the automotive context. Focus is placed on the utilization of driver vital data measured by wearable and other in-car sensors.
  • Konferenzbeitrag
    A Translation Semantics for Driving Simulation Languages
    (Software Engineering 2022 Workshops, 2022) Schneider, Jörn; Schneider, Marvin
    The development of advanced driver assistance systems and automated driving functions requires the usage of driving simulation as integral part of the software engineering process. Moreover, safety standards such as SOTIF (ISO 21448) and legal regulations give driving simulation a key role for the safety validation of automated driving functions by OEMs and Tier-1s as well as independent or governmental institutions. Even as new standards for driving simulation languages come into use, this gives rise to the need for translation tools between different driving simulator languages. Two major challenges in this context for translation tools are hitherto not well addressed: 1. Adaptability to new languages or versions thereof. 2. Correctness of translation. We elaborate on some of the central challenges in this regard, present a prototype of a retargetable translator for driving simulation languages, and a suiting translation semantics, as first cornerstones of a future approach to validate or verify translations.
  • Workshopbeitrag
    Workshop on Mixed Reality Applications for In-Vehicle Experiences in Automated Driving
    (Mensch und Computer 2021 - Workshopband, 2021) Riegler, Andreas; Riener, Andreas; Holzmann, Clemens
    With the increasing development of mixed reality (MR), the number of its purposes and applications in vehicles increases. Mixed reality may help to increase road safety, allow drivers to perform nondriving related tasks (NDRTs), and enhance passenger experiences. MR can also be helpful in the transition towards automated driving. However, there are still a number of challenges with the use of MR when applied in vehicles, and also several human factors issues need to be solved. Additionally, virtual reality (VR) has the potential to simulate mixed reality applications for HCI research, such as pedestrian and passenger experiences. In a schedule tailored to fit the requirements of a hybrid presence and online event, participants will define relevant user stories and use cases and elaborate experimental designs with measurable outcomes to contribute to the research roadmap.