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首页> 外文期刊>International Journal of Innovative Computing Information and Control >TRAFFIC INFORMATION ESTIMATION USING PERIODIC LOCATION UPDATE EVENTS
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TRAFFIC INFORMATION ESTIMATION USING PERIODIC LOCATION UPDATE EVENTS

机译：使用定期位置更新事件估算交通信息

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摘要

In recent years considerable concerns have arisen over building intelligent transportation system (ITS) which focuses on efficiently managing the road network. Before this goal can be achieved, it is vital to obtain correct and real-time traffic information, so that traffic information services can be provided in a timely and effective manner. Using mobile stations (MS) as probes to track the vehicle movement is a low cost and immediate solution to obtain the real-time traffic information. In this paper, we propose an estimation method to analyze the relation between the amount of Periodic Location Update (PLU) events and traffic density. By numerical analysis and estimating real-time traffic information with level of service (LOS), the results show that the average accuracy of traffic density is 76.33% and the average traffic condition hit rate (TCHR) is 85%. Therefore, the proposed estimation method is feasible to estimate the traffic density and traffic congestion with lower cost and higher efficiency solution for ITS improvement.
机译：近年来，人们对建立专注于有效管理道路网络的智能交通系统（ITS）产生了很大的关注。在实现这一目标之前，至关重要的是获取正确的实时交通信息，以便及时有效地提供交通信息服务。使用移动站（MS）作为探针来跟踪车辆的运动是一种获取即时交通信息的低成本且即时的解决方案。在本文中，我们提出了一种估计方法来分析周期性位置更新（PLU）事件的数量与流量密度之间的关系。通过数值分析并以服务水平（LOS）估算实时交通信息，结果表明，交通密度的平均准确度为76.33％，平均交通状况命中率（TCHR）为85％。因此，所提出的估计方法是可行的，以较低的成本和较高的效率解决方案来估计ITS的交通密度和交通拥堵。

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