期刊名称: |
IEEE Internet of Things Journal |
全部作者: |
ZHOU Baoding,ZHENG Tianjing,HUANG Jincai**,ZHANG Yunfei,TU Wei,LI Qingquan,DENG Min |
出版年份: |
2020 |
卷 号: |
0 |
期 号: |
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页 码: |
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查看全本: |
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With the promotion of low-carbon travel, pedestrian network plays an important role in many location-based applications, such as bicycle routing, pedestrian navigation and refined traffic management. Due to the lack of systematic data acquisition mechanics, the accuracies and detail levels of pedestrian network data are hardly capable of satisfying the demands of such transportation applications. Presently, various mobile phone apps recorded and stored users’ movement trajectories, which provide a valuable data source for pedestrian network construction. Hence, this paper proposes a crowdsourcing-based system for generating pedestrian network that encompasses three key components of crowdsourced walking trajectory data filtering, pedestrian network construction and evaluation of pedestrian network. Self-collected data and open platform data were used to evaluate the proposed system. Experimental results demonstrate that the proposed method can accurately and completely extract pedestrian network. Moreover, the pedestrian network can be updated in a timely manner by the proposed method. The data collection application and the collected data are available to the public.