Road network inference through multiple track alignment
Road network inference through multiple track alignment
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DOI：
10.1016/j.trc.2016.09.010
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发表时间：
2016-11
影响因子：
8.3
通讯作者：
Xingzhe Xie;K. Wong;H. Aghajan;P. Veelaert;W. Philips
中科院分区：
文献类型：
--
作者：
Xingzhe Xie;K. Wong;H. Aghajan;P. Veelaert;W. Philips
道路网络是路径优化和路径规划的一个重要方面。本文提出通过联合对齐各路段的轨迹，由GPS轨迹自动生成路网。首先，交叉口从道路使用者移动方向改变的转折点聚集。GPS轨迹被直接连接的交叉口划分为各个路段的小轨迹。使用基于后继分类的贪婪方法对每个路段的轨迹进行对齐。提出了一种通过联合遍历所有轨道以保持路径元素所关联的点在空间上彼此接近的方式来定位翘曲路径的前向轨道过程。这涉及对轨道上的后继点进行集群的迭代过程。在线形过程中产生的翘曲路径被用来平均轨道作为路段的几何表示，并分析沿路段的速度变化。实验结果表明，该方法在生成无伪道路边缘和更准确的几何道路表示方面优于已有的方法。
Road networks are a critical aspect of both path optimization and route planning. This paper proposes to generate the road network automatically from GPS traces through jointly aligning tracks for each road segment. First, intersections are clustered from turning points where the road users’ moving directions change. GPS traces are partitioned into small tracks for individual road segments by directly-connected intersections. The tracks for each road segment are aligned using a greedy method based on successor classification. A “forward-track” procedure is proposed to locate a warp path through jointly traversing all tracks in a way which keeps the points associated by the path element spatially close to each other. This involves an iterative procedure to cluster successor points on the tracks. The warp path produced during the alignment is used to average the tracks as the geometric representation of the road segment, and to analyze the velocity variation along the road segment. Experimental results show our method outperforms other existing methods in producing no spurious road edges and more accurate geometric road representation.