Generating Road Networks for Old Downtown Areas Based on Crowd-Sourced Vehicle Trajectories.
Generating Road Networks for Old Downtown Areas Based on Crowd-Sourced Vehicle Trajectories.
复制标题
基于众包车辆轨迹生成老城区道路网络
DOI：
10.3390/s21010235
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发表时间：
2021-01-01
期刊：
影响因子：
--
通讯作者：
Li S
中科院分区：
文献类型：
--
作者：
Zhang C;Li Y;Xiang L;Jiao F;Wu C;Li S
随着便携式定位设备的普及，众包轨迹数据引起了广泛关注，并带动了道路网提取领域的许多研究突破。然而，从高噪声、低频率、不均匀的分布轨迹来检测具有复杂网络布局的老城区的道路网络仍然是一项具有挑战性的任务。因此，本文以老城区为研究对象，提出了一种基于低质量众包车辆轨迹的交叉口优先生成道路网络的新方法。在交叉口检测方面，提出了一种基于距离约束的虚拟代表点检测方法，并引入了基于密度峰快速搜索的聚类算法(CFDP)，克服了轨迹的低频特征，提高了交叉口的定位精度。在道路提取方面，提出了一种基于Delaunay三角剖分网络的识别策略，以快速滤除大规模交叉口之间的虚假道路。为了缓解数据稀疏和分布不均匀的问题，进一步设计了一种考虑特征差异的自适应链路拟合方案，以求取链路中心线。实验结果表明，本文提出的方法在旧城区的交叉口检测和路网生成方面都有明显的改善。
With the popularity of portable positioning devices, crowd-sourced trajectory data have attracted widespread attention, and led to many research breakthroughs in the field of road network extraction. However, it is still a challenging task to detect the road networks of old downtown areas with complex network layouts from high noise, low frequency, and uneven distribution trajectories. Therefore, this paper focuses on the old downtown area and provides a novel intersection-first approach to generate road networks based on low quality, crowd-sourced vehicle trajectories. For intersection detection, virtual representative points with distance constraints are detected, and the clustering by fast search and find of density peaks (CFDP) algorithm is introduced to overcome low frequency features of trajectories, and improve the positioning accuracy of intersections. For link extraction, an identification strategy based on the Delaunay triangulation network is developed to quickly filter out false links between large-scale intersections. In order to alleviate the curse of sparse and uneven data distribution, an adaptive link-fitting scheme, considering feature differences, is further designed to derive link centerlines. The experiment results show that the method proposed in this paper preforms remarkably better in both intersection detection and road network generation for old downtown areas.
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