In this study, we investigate the method to increase the accuracy of traffic estimation based on multiple GPS data from GPS-equipped vehicles in Bangkok area, Thailand. We propose an algorithm to predict an average speed of a road segment by combining hourly speed profiles of the road with real-time GPS velocity data. The algorithm utilizes incremental weighted update of average travel velocity from both sources. The velocity of data from GPS is used for update every time the data comes in, whereas the speed profiles are used for update when there is no data for a period of five minutes. The outputs are compared with a speed obtained with the position-based method. In this algorithm provides the low average speed error results around 8 km/h approximately.
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机译：在这项研究中，我们研究了基于泰国曼谷地区配备GPS的车辆的多个GPS数据来提高交通量估算准确性的方法。我们提出了一种算法，可通过将道路的每小时速度剖面与实时GPS速度数据相结合来预测路段的平均速度。该算法利用来自两个来源的平均行驶速度的增量加权更新。每次输入数据时，都会使用来自GPS的数据速度进行更新，而如果五分钟内没有数据，则使用速度配置文件进行更新。将输出与通过基于位置的方法获得的速度进行比较。在该算法中，平均速度误差较低，大约为8 km / h。
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