Browsing by Author "Bao, S."

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    The 2nd workshop on localization vs. Internationalization: Impact of covid-19 pandemic on automotiveui activities from the view of diversity and inclusion
    Lee, S. C.; Stojmenova, K.; Prabhakar, G.; Bao, S.; Sodnik, J.; Jeon, Myounghoon (ACM, 2020-09-21)
    A worldwide pandemic has brought many challenges in numerous areas of everyone's life. The AutomotiveUI 2020 has also been moved to a virtual conference. Although the situation seems to be improving in some parts of the world, the impacts that the pandemic has brought to the research and academia may last long even after the pandemic is over. In the AutomotiveUI community, there is more than one aspect that should be taken into consideration. Ironically, the situation brought about both risks and opportunities including research methods, collaboration, interaction manners, and diversity and inclusion. With this background, the goal of this workshop is to discuss the impact of the COVID19 pandemic on the AutomotiveUI community from the perspective of the diversity and inclusion and to discuss the direction of collaborative activities of our community with researchers from various groups. We will organize three virtual workshop sessions accomodating different time zones.
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    Auto-UI
    Janssen, C. P.; Schroeter, R.; Bidwell, N. J.; Ji, Y. G.; Alvarez, I.; Bao, S.; Jeon, Myounghoon; Boyle, L. N.; Donker, S. F.; Chuang, L. L.; Ju, W.; Kun, A. L. (ACM, 2020-11-02)
    ACM SIGCHI Auto-UI (https://www.autoui.org/) is a growing community, but one in which some continents were less involved than expected and hoped for. For the 2019 conference in Utrecht, the Netherlands, we made various targeted attempts to grow and diversify our international community, with support from the ACM SIGCHI Development Fund (https://sigchi.org/resources/sigchi-development-fund/).
  • Computational Modeling of Driving Behaviors: Challenges and Approaches
    Jeon, Myounghoon; Zhang, Y.; Jeong, H.; Janssen, C.; Bao, S. (ACM, 2021-09-09)
    Computational modeling has great advantages in human behavior research, such as abstracting the problem space, simulating the situation by varying critical variables, and predicting future outcomes. Although much research has been conducted on driver behavior modeling, relatively little modeling research has appeared at the Auto-UI Conferences. If any, most work has focused on qualitative models about manual driving. In this workshop, we will first describe why computational driver behavior modeling is crucial for automotive research and then, introduce recent driver modeling research to researchers, practitioners, and students. By identifying research gaps and exploring solutions together, we expect to form the basis of a new modeling special interest group combining the Auto-UI community and the computational modeling community. The workshop will be closed with suggestions on the directions for future transdisciplinary work.