CLRIC: Collecting Lane-Based Road Information Via Crowdsourcing
CLRIC: Collecting Lane-Based Road Information Via Crowdsourcing
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CLRIC：通过众包收集基于车道的道路信息
DOI：
10.1109/tits.2016.2521482
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发表时间：
2016-09-01
影响因子：
8.5
通讯作者：
Li, Qingquan
中科院分区：
文献类型：
--
作者：
Tang, Luliang;Yang, Xue;Li, Qingquan
基于车道的路网信息，如道路上的车道数量和位置，在智能交通系统中发挥着重要的作用。本文提出了一种基于车道众包的道路信息收集方法(CLRIC)，该方法利用车辆采集的众包数据自动提取道路的详细车道结构。首先，CLRIC利用先验知识，基于区域生长聚类，从原始轨迹中过滤出高精度的GPS数据。其次，CLRIC通过优化的约束高斯混合模型挖掘车道的数量和位置。以武汉、中国的出租车GPS轨迹进行了实验，结果表明，CLRIC是量化的，并将车道的数量和位置与卫星图像和人为解释的情况进行比较，显示详细的道路网络。
Lane-based road network information, such as the number and locations of traffic lanes on a road, has played an important role in intelligent transportation systems. In this paper, we propose a Collecting Lane-based Road Information via Crowdsourcing (CLRIC) method, which can automatically extract detailed lane structure of roads by using crowdsourcing data collected by vehicles. First, CLRIC filters the high-precision GPS data from the raw trajectories based on region growing clustering with prior knowledge. Second, CLRIC mines the number and locations of traffic lanes through optimized constrained Gaussian mixture model. Experiments are conducted with taxi GPS trajectories in Wuhan, China, and the results show that CLRIC is quantified and displays detailed road networks with the number and locations of traffic lanes comparing with the satellite image and human-interpreted situation.