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Analysis of time- and space-domain sampling for probe vehicle-based traffic information system

机译:基于探测车辆的交通信息系统的时空采样分析

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摘要

Using vehicles as probes is a flexible and low-cost way to obtain real-time traffic information. A key problem of using probe vehicles is to determine vehicle's sampling period and probe sample size. This paper addresses the sampling issue of using probe vehicles for detecting traffic information. An extended Nyquist sampling theorem based on signal processing theory is proposed to derive bounds on the sampling period and probe sample size. We also develop a Traffic & Information-collecting Simulation Platform (TISP), to simulate the traffic flows in a road network and generate probe vehicle data for analysis. We demonstrate through simulations that the traffic situations can be reconstructed from the samples without distortion according to the designed sampling period and sample size. The methods proposed in this paper can be a valuable tool for designers on planning parameters in the probe vehicle-based traffic information system.
机译:使用车辆作为探测是一种获取实时交通信息的灵活且低成本的方法。使用探测车的一个关键问题是确定车辆的采样时间和探测样本的大小。本文解决了使用探测车检测交通信息的抽样问题。提出了一种基于信号处理理论的扩展奈奎斯特采样定理,以推导采样周期和探针样本大小的界限。我们还开发了交通和信息收集模拟平台(TISP),以模拟道路网络中的交通流量并生成探测车辆数据以进行分析。我们通过仿真证明,根据设计的采样周期和样本大小,可以从样本中重建交通状况而不会产生失真。本文提出的方法可以为设计人员在基于探测车辆的交通信息系统中规划参数提供有价值的工具。

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