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Estimating vehicle miles traveled (VMT) in urban areas using regression kriging

机译:使用回归克里格法估算市区的车辆行驶里程(VMT)

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摘要

The recent increase in demand for performance-driven and outcome-based transportation planning makes accurate and reliable performance measures essential. Vehicle miles traveled (VMT), the total miles traveled by all vehicles on roadways, has been utilized widely as a proxy for traffic impact assessment, vehicle emissions, gasoline consumption, and crashes. Accordingly, a number of studies estimate VMT using diverse data sources. This study estimates VMT in the urban area of Bucheon, South Korea, by predicting the annual average daily traffic for unmeasured locations using spatial interpolation techniques (i.e., regression kriging and linear regression). The predictive performance of this method is compared with that of the existing Highway Performance Monitoring System (HPMS) method. The results show that regression kriging could provide more accurate VMT estimates than the HPMS method and linear regression, especially with a small sample size. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:最近对以绩效为导向和基于结果的运输计划的需求不断增长,因此,准确,可靠的绩效指标至关重要。车辆行驶里程(VMT)是道路上所有车辆行驶的总里程,已被广泛用作交通影响评估,车辆排放,汽油消耗和碰撞的替代指标。因此,许多研究使用不同的数据源来估计VMT。这项研究通过使用空间插值技术(即回归克里金法和线性回归)预测未测位置的年平均每日交通量,从而估算了韩国富川市的VMT。将该方法的预测性能与现有的高速公路性能监控系统(HPMS)方法进行了比较。结果表明,与HPMS方法和线性回归相比,回归克里金法可以提供更准确的VMT估计值,尤其是在样本量较小的情况下。版权所有(C)2016 John Wiley&Sons,Ltd.

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