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Vehicle platoon matching and prediction of travel time using a quantified vehicle characteristic

机译:车辆排匹配和使用量化的车辆特征预测行驶时间

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摘要

Travel time is one of the most important pieces of traffic information, and various methods for measuring this parameter have been studied so far. There are some typical method, for example, the Automatic Vehicle Identification (AVI) system which measures travel time directly by reading number plates at multiple locations and a method that predicts travel time indirectly from speeds and traffic volume measured by vehicle detectors. However, both of these methods have disadvantages in installation cost and measurement precision. Therefore, the authors studied an algorithm for measuring travel time with little measurement delay and high precision by establishing a vehicle platoon correspondence using a quantified vehicle characteristic which can be measured using commonly used vehicle detectors. The evaluation results indicated an extremely good matching accuracy of 72% and RMS error in the travel time of about 2% even when vehicle height was used as the quantified characteristic. We also found that precision could be further improved by using vehicle length or combining vehicle height and vehicle length. Finally, we also propose an algorithm for improving precision by using images.
机译:出行时间是最重要的交通信息之一,到目前为止,已经研究了各种测量此参数的方法。有一些典型的方法,例如,自动车辆识别(AVI)系统通过读取多个位置的车牌直接测量行驶时间,以及一种根据车辆检测器测得的速度和交通量间接预测行驶时间的方法。但是,这两种方法在安装成本和测量精度上均具有缺点。因此,作者研究了一种算法,该算法通过使用量化的车辆特性建立车辆排对应关系,从而以较低的测量延迟和较高的精度测量行驶时间,该量化的车辆特性可以使用常用的车辆检测器进行测量。评估结果表明,即使将车高用作量化特征,其匹配度也非常好,达到72%,RMS误差约为2%。我们还发现,通过使用车辆长度或结合车辆高度和车辆长度可以进一步提高精度。最后,我们还提出了一种通过使用图像提高精度的算法。

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