Ohn-Bar Eshed, Guerreiro João, Kitani Kris, Asakawa Chieko
Carnegie Mellon University, 5000 Forbes Ave. Pittsburgh, PA, 15213, USA.
Carnegie Mellon University and IBM Research, 5000 Forbes Ave. Pittsburgh, PA, 15213, USA.
Proc ACM Interact Mob Wearable Ubiquitous Technol. 2018 Sep;2(3). doi: 10.1145/3264941.
'Turn slightly to the left' the navigational system announces, with the aim of directing a blind user to merge into a corridor. Yet, due to long reaction time, the user turns too late and proceeds into the wrong hallway. Observations of such user behavior in real-world navigation settings motivate us to study the manner in which blind users react to the instructional feedback of a turn-by-turn guidance system. We found little previous work analyzing the extent of the variability among blind users in reaction to different instructional guidance during assisted navigation. To gain insight into how navigational interfaces can be better designed to accommodate the information needs of different users, we conduct a data-driven analysis of reaction variability as defined by motion and timing measures. Based on continuously tracked user motion during real-world navigation with a deployed system, we find significant variability between users in their reaction characteristics. Specifically, the statistical analysis reveals significant variability during the crucial elements of the navigation (, turning and encountering obstacles). With the end-user experience in mind, we identify the need to not only adjust interface timing and content to each user's personal walking pace, but also their individual navigation skill and style. The design implications of our study inform the development of assistive systems which consider such user-specific behavior to ensure successful navigation.
“稍微向左转。”导航系统发出指令，目的是引导一位盲人用户进入一条走廊。然而，由于反应时间过长，用户转向过晚，走进了错误的走廊。在现实世界导航场景中对这种用户行为的观察促使我们研究盲人用户对逐向导航系统的指令反馈做出反应的方式。我们发现之前很少有工作分析盲人用户在辅助导航过程中对不同指令引导做出反应时的变化程度。为了深入了解如何更好地设计导航界面以满足不同用户的信息需求，我们对由运动和时间测量定义的反应变异性进行了数据驱动的分析。基于在实际导航过程中使用已部署系统对用户运动的持续跟踪，我们发现不同用户在反应特征方面存在显著差异。具体而言，统计分析表明在导航的关键环节（转弯和遇到障碍物）存在显著变异性。考虑到最终用户体验，我们认识到不仅需要根据每个用户的个人步行速度调整界面时间和内容，还需要根据他们各自的导航技能和风格进行调整。我们研究的设计启示为辅助系统的开发提供了参考，这类系统会考虑此类用户特定行为以确保导航成功。
