Browsing by Author "Lee, Seul Chan"

Now showing 1 - 7 of 7
  • The 4th Workshop on Localization vs. Internationalization: Creating an International Survey on Automotive User Interfaces
    Stojmenova, Kristina; Lee, Seul Chan; De Oliveira Faria, Nayara; Schroeter, Ronald; Jeon, Myounghoon (ACM, 2022-09-17)
    International surveys tend to collect data on attitudes, values and behaviors towards a specific topic from users from multiple countries, providing an insight on the differences and similarities across nations, cultures or geo-political structures. Consequently, international surveys provide important information about the diversity of the user's needs, values and preferences, which have to be taken into consideration when creating products and services as widely used as the personal automobile. The workshop will focus on the design and development of an international survey on automotive user interfaces on a global scale. It will try to identify the most important aspects related to automotive user interfaces, which should be addressed in the survey. It will also prepare a strategy for its international distribution and create a plan for comprehensive data collection. Lastly, it will try to outline venues and communication channels for the survey dissemination, with the goal of achieving wide visibility.
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    Exploring User Needs and Design Requirements in Fully Automated Vehicles
    Lee, Seul Chan; Nadri, Chihab; Sanghavi, Harsh; Jeon, Myounghoon (ACM, 2020)
    An automated driving system is expected to pave the way for a new area of user experience in a vehicle. However, few studies have been conducted on the understanding what people want to do and how the vehicle can support user needs, specifically, in level 5, fully automated vehicles (FAVs). Therefore, the present study aimed at exploring user needs and design requirements for potential activities in FAVs. We conducted expert interviews and focus group interviews to collect data, and the qualitative analysis was applied to elicit user needs and design requirements. Twelve user needs and general design considerations in four categories were found. The findings will contribute to enhancing user experience in future FAVs by considering user needs and design requirements we elicited.
  • HCI for Future Mobility
    Lee, Seul Chan; Jeon, Myounghoon; Stojmenova, Kristina; Fakhrhosseini, Maryam; Ji, Yong Gu (Taylor & Francis, 2023-07-14)
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    How to Ensure Diversity and Inclusion at Conferences? A Workshop for General Chairs, Program Committee Members, Reviewers and Authors
    Stojmenova Pečečnik, Kristina; Lee, Seul Chan; Hong, Sara; Schuß, Martina; Şahin Ippoliti, Hatice; Patel, Ankit; Löcken, Andreas; Dey, Debargha; Riener, Andreas; Mirnig, Alexander; Jeon, Myounghoon (ACM, 2023-09-18)
    Being the premier forum for automotive user interface research and other vehicular technologies, AutomotiveUI concerns professionals, academics, researchers, and industry representatives from all around the world interested in innovation, research, and application of automotive user interface topics, embodying diversity at its core. This diversity is however not always reflected in the conference’s main program. In order expand the topic foci of the conference in the future, this workshop aims to identify the key factors that influence the main program creation, and create strategies that can help increase its diversity and accessibility, culturally and geographically. We aim to exchange ideas, experiences and start conversations that raise awareness about this topic, in order to inspire longer-term follow-up activities which will eventually result in increased diversity and accessibility not only at AutomotiveUI, but at international conferences in general.
  • Pairing in-vehicle intelligent agents with different levels of automation: implications from driver attitudes, cognition, and behaviors in automated vehicles
    Wang, Manhua; Lee, Seul Chan; Jeon, Myounghoon (Taylor & Francis, 2024-01-01)
    In-vehicle intelligent agents (IVIAs) have been developed to improve user experience in autonomous vehicles. Yet, the impact of the automation system on driver behavior and perception toward IVIAs is unclear. In this study, we conducted three experiments with 73 participants in a driving simulator to examine how automation system parameters (the level of automation system and IVIA features) influence driver attitudes, cognition, and behaviors when driving or riding in a simulated vehicle. We focused on subjective evaluations of driver-agent interaction and driver trust toward IVIAs to assess driver attitudes, driver situation awareness, and visual distraction to capture their cognition, and their driving performance to understand their behaviors. Our results show that the level of automation system affects drivers’ attitudes toward agent capabilities (e.g. perceived intelligence). Embodiment benefits are more pronounced with Level 5 systems, while speech style, in general, is more influential in determining affective aspects of user attitudes (e.g. Warmth, Likability). As the level of automation increases, drivers engage in more visual distractions. In addition, conversational speech style in general encouraged safer driving behaviors indicated by more stable lateral control under lower levels of automation. Our findings uncover the path of how system parameters affect driver behaviors through system evaluation and trust in agents. These findings have important implications for the development of cohesive user experiences in future transportation systems.
  • "Slow down. Rail crossing ahead. Look left and right at the crossing": In-vehicle auditory alerts improve driver behavior at rail crossings
    Nadri, Chihab; Kekal, Siddhant; Li, Yinjia; Li, Xuan; Lee, Seul Chan; Nelson, David; Lautala, Pasi; Jeon, Myounghoon (Elsevier, 2022-09-27)
    Even though the rail industry has made great strides in reducing accidents at crossings, train-vehicle collisions at Highway-Rail Grade Crossings (HRGCs) continue to be a major issue in the US and across the world. In this research, we conducted a driving simulator study (N = 35) to evaluate a hybrid in-vehicle auditory alert (IVAA), composed of both speech and non-speech components, that was selected after two rounds of subjective evaluation studies. Participants drove through a simulated scenario and reacted to HRGCs with and without the IVAA present and through different music conditions and crossing devices. Driver simulator testing results showed that the inclusion of the hybrid IVAA significantly improved driving behavior near HRGCs in terms of gaze behavior, braking reaction, and approach speed to the crossing. The driving simulator study also showed the effects of background music and warning device types on driving performance. The study contributes to the large-scale implementation of IVAAs at HRGCs, as well as the development of guidelines toward a more standardized approach for IVAAs at HRGCs.
  • What Do You Want for In-Vehicle Agents? One Fits All vs. Multiple Specialized Agents
    Park, Se Hyeon; Lee, Seul Chan; Wang, Manhua; Hock, Philipp; Baumann, Martin; Jeon, Myounghoon (ACM, 2022-09-17)
    It is expected that in-vehicle intelligent agents (IVIAs) become an important user interface in automated driving, and much research on how to design IVIAs considering user needs and scenarios has been conducted. The question arising here is whether people want to have one almighty agent connecting to all user's data sources and dealing with all situations, including driving contexts. Another plausible form is multiple specialized agents that play the role only in each task context. As a first step in answering the question, we developed two plausible scenarios of interacting with IVIAs and presented the video. In both scenarios, a user of IVIAs experiences embarrassing situations because of the connectivity of IVIAs. We expect that this effort can be a starting point to understand users' needs and requirements to develop and design IVIAs in terms of connectivity.