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A motion simulation model for road network based crowdsourced map datum

机译:基于道路网络的众包地图数据的运动仿真模型

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Using the Semi-Markov decision model, we start with the real road map datum with a constructed logic network and construct the complex road network with random moving characteristics. First we translate the crowdsoured map datum into the vectorgraph in road network by the ArcGIS with the conversion of longitudinal and Latitude Coordinates to planar coordinates. In the motion simulation model all objects are sorted by the time of state change, and the moving object with the closest state change time to the current time are set at the front of the queue. And then, the moving object motion model based crowdsourced map datum is simulated. The experimental results for fitting and analysing the distribution rules of in-degree and out-degree show that the designed model can satisfy the Poission Distribution Rule on the cross node of Road Network based Uniform Distribution of moving object random motion, which conform to the characteristics of Distance Space and small-world network.
机译:使用半马尔可夫决策模型,我们从具有构造逻辑网络的真实路线图数据开始,并用随机移动特性构建复杂的道路网络。 首先,通过ArcGIS将众群地图数据转化为在道路网络中的矢量图,随着纵向和纬度坐标转换为平面坐标。 在运动仿真模型中,所有对象都是由状态改变的时间进行排序,并且在队列的前面设置具有最接近状态的变化时间的移动对象。 然后,模拟了基于移动的基于移动对象运动模型的众包数据。 拟合和分析程度分布规则的实验结果表明,所设计的模型可以满足基于行程的道路网络跨节节点的拓展分配规则符合其特征 距离空间与小世界网络。

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