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浮动车作为一种新型的交通信息采集工具已经成为智能交通领域的研究热点。基于无线定位的浮动车交通信息采集的关键问题之一就是如何确定浮动车的样本数量,分析在不同交通参数检测需求下,分别研究传统经典概率论理论方法和改进的基于满足平均行程时间估计精度的浮动车样本数量确定方法,同时在考虑定位精度和通信效率下,给出计算模型,具有重要的应用价值。
As a new traffic information collection tool, floating car has become a hot spot in the field of intelligent transportation. One of the key problems of traffic information collection for floating vehicles based on wireless location is how to determine the number of samples of floating vehicles. The paper analyzes the traditional classical theory of probability theory and the improved estimation accuracy based on satisfying the average travel time under different traffic parameter detection requirements. The method of determining the number of floating car samples is given. At the same time, the calculation model is given under the consideration of positioning accuracy and communication efficiency, which has an important application value.