Browsing by Author "Drew, Daniel"

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    Hand Images in Virtual Spatial Collaboration for Traffic Incident and Disaster Management
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-03) Drew, Daniel; Hayes, Caroline C.; Nguyen, Mai-Anh; Cheng, Xuan
    To develop demonstration technology that can overlay hand videos on spatial images such as traffic maps, and assess the impact of this technology on virtual collaboration. This work explores to what degree gestures impact collaboration effectiveness in the task of traffic incident management, with the goal of informing design of tools to support virtual collaboration in this domain. Methods: Eighteen participants worked in pairs to solve three traffic incident scenarios using three different interaction approaches: 1) face-to-face: participants worked together by marking up an electronic map projected on the table in front of them; 2) separated: participants were separated by a soft wall while they worked together on the electronic map with electronic drawing tools; or 3) hand images: same as 2 with the addition of the partner’s hand images projected on the map. Participants were video recorded. The questionnaires were given to participants after each trial to evaluate workload, positive interactions, team behaviors, connection to teammate, and frustration. Results: Participants spent more time on the task and perceived a higher level of time pressure when using hand images than when working face-to-face. When working face-to-face, participants felt more like their teammate was at the same table and felt less disconnected from their teammate than when working separately or using hand images. Conclusions: The results indicate that adding hand videos to a virtual drawing tool for the task of traffic incident management can increase team behaviors and change the way in which team members communicate information.
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    In-Vehicle Decision Support to Reduce Crashes at Rural Thru-Stop Intersections
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2011-08) Hayes, Caroline C.; Drew, Daniel
    Purpose: Within the context of thru-stop intersections, investigate the feasibility and future promise of warning systems inside the vehicle, where interfaces are best placed, and what modalities are most effective (visual versus haptic). Methods: A driving simulator study was conducted to compare three decision support systems (DSSs): a dynamic traffic sign, a set of displays on the vehicle side mirrors, and a vibrating seat. Dependent variables included measurements of safe driving behavior, and a usability questionnaire. A follow-up focus group study was conducted to gain further feedback on the in-vehicle systems and on ideas for how to improve the systems. Results: The vibrating seat yielded significantly higher results than the dynamic traffic sign on two safety variables. No system clearly outperformed the others in terms of promoting safer driving behavior, nor did any improve driving performance compared to the control condition. The questionnaire and usability data showed that the dynamic traffic sign was most preferred, while the in-vehicle displays were most comprehended. Comments during the simulator studies suggested that participants wanted stronger advisory messages from the systems, and the Focus Group Study confirms this. Conclusions: In-vehicle DSSs appear to be feasible for the purposes of assisting drivers with navigating rural thru-stop intersections. No results of this study indicate that in-vehicle systems are an inherently poor means of presenting traffic gap information to the driver. Results indicate that a visual display would be easier to comprehend than a vibrotactile display when no training or explanation is provided.