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首页> 外文期刊>Journal of Intelligent Transportation Systems >An Investigation of the Application of Stratified Sampling in Probe-Based Traffic-Monitoring Systems
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An Investigation of the Application of Stratified Sampling in Probe-Based Traffic-Monitoring Systems

机译:分层采样在基于探针的交通监控系统中的应用研究

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摘要

Probe vehicles represent samples in a traffic stream, and hence, probe-based traffic monitoring relies on effective sampling of vehicles. Current research views sampling from a networkwide perspective, and a single sample size is specified for the entire network. Using this method, research has indicated that the smaller routes in a network, such as minor and other arterials, are not adequately monitored. Increasing the sample size is not always a feasible option because of the restrictions of cost for use of the wireless network bandwidth and the availability of required number of probe vehicles. In this article, the authors describe a research effort that identified and extended stratified sampling as a method for increasing the efficacy of probe-based traffic monitoring. A methodology for application of stratified sampling for probe-based traffic monitoring is developed and implemented using a heavily traveled suburban traffic network simulation as a case study. Also, the authors discuss results of the implementation and the future direction of research.
机译:探测车辆代表交通流中的样本,因此,基于探测器的交通监控依赖于车辆的有效采样。当前的研究从网络范围的角度看待抽样,并且为整个网络指定了一个样本大小。使用这种方法,研究表明,网络中较小的路由(例如小动脉和其他动脉)没有得到充分监控。由于限制了无线网络带宽的使用成本和所需探测车数量的可用性,因此增加样本大小并不总是可行的选择。在本文中,作者描述了一项研究工作,该工作确定并扩展了分层采样作为增加基于探针的流量监控效率的方法。开发和应用分层抽样的方法,以基于探测的交通监控为例,并以大量旅行的郊区交通网络模拟为例进行了研究。此外,作者还讨论了实施的结果和未来的研究方向。

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