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Research on Evaluation and Prediction Method of Link Travel Time Based on Floating Car Data by Simulation

机译:基于浮动车数据的路段行驶时间评估与预测方法的仿真研究

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Using the floating car data obtained by simulation to carry out theoretical research on link travel time evaluation and prediction, it has the advantage of conveniently setting different situations and providing reference for practical applications. In this paper, we have acquired the floating car data based on microscopic simulation, and then the complex trapezoidal quadrature formula is used to obtain link travel time of a single vehicle. When setting different ratios of floating cars, the average link travel time is obtained by the mean-median method. The results show that the effect is better than the arithmetic average method, and the higher the ratio of floating cars, the higher the accuracy of evaluation. The markov model has been used to correct the gray prediction model, with that we establish travel time prediction model based on the grey markov chain. The experimental results show that the prediction accuracy is high.
机译:利用仿真得到的浮车数据对路段行程时间进行评价和预测的理论研究,具有方便设置不同情况并为实际应用提供参考的优点。在本文中,我们基于微观仿真获得了浮动车数据,然后使用复杂的梯形正交公式来获得单个车辆的行驶时间。设定不同比例的浮动车时,平均连杆行程时间是通过均值中位数法获得的。结果表明,该方法的效果优于算术平均法,浮动车比例越高,评估的准确性越高。使用马尔可夫模型来校正灰色预测模型,从而基于灰色马尔可夫链建立旅行时间预测模型。实验结果表明,该方法的预测精度较高。

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