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Auflistung nach Schlagwort "Driving Simulator"

1 - 3 von 3
  • Konferenzbeitrag
    Autonomous Driving - Analysing the Impact of Resilience Engineering Features in Smart Car Interfaces
    (Mensch und Computer 2022 - Tagungsband, 2022) Pasnicu, Otilia; Zmmermann, Verena; Gerber, Nina; Cardoso, Sarah
    The communication between driver and vehicle plays an important role in the development of car automation. Being able to perform non-driving related tasks in uncritical situations is one of the biggest advantages of autonomous driving in smart cars. Yet, critical situations often require the driver to take over control again, thereby making the design of takeover maneuvers a highly relevant task. Our study thus investigated the impact of basic vs. enhanced HMIs considering the principles of resilience engineering on supporting drivers in taking control over the vehicle. We investigated driving on the highway in two critical scenarios: a roadworks and a potential collision scenario. In a VR study in a driving simulator 45 participants tested three HMIs: basic, visual, and visual + speech-based. Even though the results indicate high usability scores and a positive user experience for all HMIs, no significant differences regarding takeover time could be measured between the HMIs. Reasons include the visual differences in the interface design with regards to resilience engineering being minor and the sample size being too small to detect small effects. Implications for future research and the design of takeover maneuvers are discussed.
  • Workshopbeitrag
    Investigating Car Futures from Different Angles
    (Mensch und Computer 2019 - Workshopband, 2019) Stevens, Gunnar; Meurer, Johanna; Pakusch, Christina; Bossauer, Paul
    The design of self-driving cars is one of the most exciting and ambitious challenges of our days and every day, new research work is published. In order to give an orientation, this article will present an overview of various methods used to study the human side of autonomous driving. Simplifying roughly, you can distinguish between design science-oriented methods (such as Research through Design, Wizard of Oz or driving simulator ) and behavioral science methods (such as survey, interview, and observation). We show how these methods are adopted in the context of autonomous driving research and dis-cuss their strengths and weaknesses. Due to the complexity of the topic, we will show that mixed method approaches will be suitable to explore the impact of autonomous driving on different levels: the individual, the social interaction and society.
  • Konferenzbeitrag
    Non-Contact In-Car Monitoring of Heart Rate: Evaluating the Eulerian Video Magnification Algorithm in a Driving Simulator Study
    (Proceedings of Mensch und Computer 2024, 2024) Renner, Philipp; Gleichauf, Johanna; Winkelmann, Sven
    Monitoring drivers’ health is crucial for saving lives in emergencies and enabling in-car health applications. The state of the art in pulse monitoring is contact-based sensors which impair the driving experience and have to be applied manually before driving. This paper focuses on automated hyper parameter optimizing the Eulerian Video Magnification (EVM) algorithm, which detects heart rates through non-contact facial camera images, for use in driving scenarios. We conducted a user study where 21 participants performed a driving simulation while their heart rates were recorded by a wearable fitness tracker (serving as ground truth) and facial images with an RGB camera. Our findings indicate that, despite using the optuna library for hyper parameter tuning, the Eulerian Video Magnification algorithm is insufficient for accurate pulse detection in a driving simulator environment.