WheelShare: Crowd-Sensed Surface Classification for Accessible Routing

Janick Edinger, A. Hofmann, Anton Wachner, C. Becker, V. Raychoudhury, Christian Krupitzer
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引用次数: 11

Abstract

Accessible path routing for wheeled mobility is an important problem given the permanent and temporary obstacles in the built environment. Existing research works have focused on identifying several obstacles as well as facilities such as crosswalks with traffic signals using smartphone based sensing or crowd-sourcing and used those knowledge to generate accessible routes. In this work, we propose WheelShare which generates an accessible route through the best possible surface depending on user and wheelchair requirements. It is 1) scalable, as it uses crowd-sensing to collect voluminous data, 2) dynamic, as the data gets constantly updated, and 3) objective, as it uses an empirical and data-centric approach.
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WheelShare:无障碍路由的人群感知表面分类
考虑到建筑环境中存在的永久性和暂时性障碍物,轮式移动的无障碍路径选择是一个重要的问题。现有的研究工作主要集中在识别几个障碍以及设施,如使用基于智能手机的传感或众包的交通信号人行横道,并利用这些知识来生成可访问的路线。在这项工作中,我们提出了WheelShare,它根据用户和轮椅的要求,在尽可能好的表面上生成一条可达的路线。它是1)可扩展的,因为它使用人群感知来收集大量数据;2)动态的,因为数据不断更新;3)客观的,因为它使用经验和以数据为中心的方法。
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