Integrated use of spatial and semantic relationships for extracting road networks from floating car data
Integrated use of spatial and semantic relationships for extracting road networks from floating car data
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DOI：
10.1016/j.jag.2012.05.013
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发表时间：
2012-10-01
影响因子：
7.5
通讯作者：
Zhao, Yue
中科院分区：
文献类型：
--
作者：
Li, Jun;Qin, Qiming;Zhao, Yue
数字道路地图的更新频率影响道路相关服务的质量。然而，通过探测车测量或从遥感图像提取的数字道路地图仍然具有较长的更新周期和成本仍然很高。随着GPS技术和无线通信技术的成熟和成本的降低，浮动车技术被应用于交通监控和管理中，浮动汽车的动态定位数据成为更新道路地图的新数据源。针对我国商用车监控平台的浮动车数据更新数字道路地图的问题，提出了一种适用于平台GPS数据采样频率低、覆盖面积大的增量式道路网提取方法。该方法根据轨迹点与道路之间的空间和语义关系，对轨迹点进行分类，然后根据轨迹点的类型进行添加或修改，将轨迹点合并到候选道路网络中。道路网络逐渐更新，直到所有轨迹都已处理。最后，将该方法应用于华北地区主要道路的更新过程中，实验结果表明，该方法能够准确地获取不同场景下道路的几何信息。本文提出了一种高效、低成本的数字道路地图更新方法。(c)2012 Elsevier B.V.保留所有权利。
The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps. (c) 2012 Elsevier B.V. All rights reserved.