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Using of behavioral information for enhancing Conditional Random Field-based map matching

机译:使用行为信息增强基于条件随机场的地图匹配

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In this paper we propose an enhancement to our previous Conditional Random Field (CRF) based map matching algorithm in order to make the map matched trajectory smoother and more feasible. The existing algorithm uses one feature, which is the distance with the input coordinate, and has the problem of non-smooth output trajectory. In this work we propose adding a new semantic layer to the map model that depends on the behavioral areas of walking, and to use that information in the map matching algorithm to enhance the smoothness of the output trajectory. The common walking lines of pedestrians will be determined and this behavioral information will be added as a feature to the CRF algorithm. A test version of the new algorithm is applied on a few examples and the results show smoother and more accurate map matched trajectories.
机译:在本文中,我们提出了对先前基于条件随机场(CRF)的地图匹配算法的增强,以使地图匹配的轨迹更平滑,更可行。现有算法使用一个特征,即与输入坐标的距离,并且具有输出轨迹不平滑的问题。在这项工作中,我们建议在地图模型中添加一个新的语义层,该语义层取决于步行的行为区域,并在地图匹配算法中使用该信息来增强输出轨迹的平滑性。将确定行人的共同步行路线,并将此行为信息作为功能添加到CRF算法中。在一些示例上应用了新算法的测试版本,结果表明,地图匹配的轨迹更平滑,更准确。

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