Extracting Campus’ Road Network from Walking GPS Trajectories

Extracting Campus’ Road Network from Walking GPS Trajectories
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从步行 GPS 轨迹中提取 Campus™ 道路网络

DOI:
10.32604/jcs.2020.010625
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发表时间:
2020
期刊:
Journal of Cyber Security
影响因子:
--
通讯作者:
Hong Ouyang
Hong Ouyang
中科院分区:
其他
文献类型:
--
作者:
Yizhi Liu;Rutian Qing;Jianxun Liu;Zhuhua Liao;Yijiang Zhao;Hong Ouyang

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道路网络提取对于车辆导航和道路规划都是至关重要的。现有的方法主要集中在从浮动车的GPS轨迹中挖掘城市主干道。然而,路径提取在抗震救灾和乡村旅游中起着重要的作用,却一直被忽视。针对这一问题,我们提出了一种从行走的GPS轨迹中提取校园道路网的新方法。它由数据预处理和道路中心线生成两部分组成。以湖南科技大学采集的巡逻GPS轨迹为实验数据。实验评估结果表明,该方法能够有效、准确地提取校园主干道和路径。该方法的覆盖率为96.21%,错误率为3.26%。
Road network extraction is vital to both vehicle navigation and road planning. Existing approaches focus on mining urban trunk roads from GPS trajectories of floating cars. However, path extraction, which plays an important role in earthquake relief and village tour, is always ignored. Addressing this issue, we propose a novel approach of extracting campus’ road network from walking GPS trajectories. It consists of data preprocessing and road centerline generation. The patrolling GPS trajectories, collected at Hunan University of Science and Technology, were used as the experimental data. The experimental evaluation results show that our approach is able to effectively and accurately extract both campus’ trunk roads and paths. The coverage rate is 96.21% while the error rate is 3.26%.
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