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Road centreline and lane reconstruction from pervasive GPS tracking on motorways

机译:高速公路上普遍存在GPS跟踪的道路中心线和车道重建

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A lane-based Routable Digital Map is a basis for construction of a floating-car dataset for lane-based traffic analysis. We proposed an algorithm that is capable of identifying lanes in highway segments based on GPS trajectories collected by mobile phones. The algorithm consists of three main steps. First, we identify nodes within the test site, and divide the network into segments. Second, the central line of each segment is identified based on a dissimilarity matrix computed based on Dynamic Time Warping criteria. Finally, the Gaussian Mixture Method is used to identify the lanes. This allows the width of the lanes to remain constant throughout the segment. The results have been validated by comparing the share of traffic volume in each lane based on the trajectory points in the identified lanes and the loop detectors’ data. The results show that the proposed algorithm can determine the lanes with acceptable accuracy. Estimating the traffic volume and its speed based on floating car data provides a big step in enabling data fusion from multiple sources more accurately and to estimate traffic state more precisely.
机译:基于车道的可路由数字地图是构建基于车道的流量分析的浮动车数据集的基础。我们提出了一种能够基于移动电话收集的GPS轨迹在公路段中识别车道的算法。该算法由三个主要步骤组成。首先,我们识别测试站点内的节点,并将网络划分为段。其次,基于基于动态时间扭曲标准计算的异化矩阵来识别每个段的中央线。最后,高斯混合方法用于识别车道。这允许通道的宽度在整个段中保持恒定。通过基于所识别的车道和循环检测器数据的轨迹点来比较每个车道中的交通量的份额来验证结果。结果表明,该算法可以以可接受的精度确定车道。基于浮动汽车数据估算交通量及其速度提供了大量的迈出能够更准确地从多个源融合,并更精确地估计交通状态。

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