Watching vehicle speed using GPS by using data mining approach

Seror Manea Bahloo
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Abstract

The suggested effort is an endeavor to regulate the speed of the car using computer software that allows the owner to obtain information about the driver’s position, speed, and activities. To do this, the system must be able to send data in real time. The widespread accessibility of GPS-enabled instruments, as well as the enormous quantities of data collected from them, allows us to get a perfect understanding of the condition of traffic and the road network. The current study was prompted through a sample of “T-Drive GPS” trajectory data made public by Microsoft Research in 2010. The final objective was to estimate the average speeds of the road sections using the supplied trajectory data and therefore obtain a speed overview of the road network. The corrected sensor data are used by Driving Sense to detect three types of hazardous behaviors: uncontrolled speed, driving irregularly and shifting the directions. We test the efficacy of our system in real-world scenarios. Driving Sense can identify the convert of directions through driving and anomalous speed control with 93.95 percent accuracy and 90.54 percent recall, correspondingly, according to the findings. Furthermore, the speed estimate mistake is within an acceptable range of less than 2.1 m/s.
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采用数据挖掘的方法,利用GPS监测车辆速度
建议的努力是使用计算机软件来调节汽车的速度,使车主能够获得有关驾驶员的位置、速度和活动的信息。要做到这一点,系统必须能够实时发送数据。具有gps功能的仪器的广泛使用,以及从中收集的大量数据,使我们能够完美地了解交通状况和道路网络。目前的研究是通过2010年微软研究院公开的“T-Drive GPS”轨迹数据样本进行的。最后的目标是使用提供的轨迹数据估计路段的平均速度,从而获得路网的速度概览。Driving Sense使用校正后的传感器数据来检测三种危险行为:超速失控、不规则驾驶和改变方向。我们在现实世界的场景中测试我们的系统的有效性。结果表明,驾驶感知能够识别通过驾驶和异常速度控制进行的方向转换,正确率为93.95%,召回率为90.54%。此外,速度估计误差在小于2.1 m/s的可接受范围内。
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