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Kriging Geostatistical Methods for Travel Mode Choice: A Spatial Data Analysis to Travel Demand Forecasting

机译:用于出行方式选择的Kriging地统计方法:用于出行需求预测的空间数据分析

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This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at S?o Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.
机译:本文旨在比较两种Kriging技术(普通Kriging和指标Kriging)的结果,这两种技术分别用于在相关非抽样值的多个地理坐标中估算私人机动(PM)出行方式的使用(汽车或摩托车)变量。使用的数据来自始发地/目的地和公共交通意见调查,该调查于2007/2008年在S?o Carlos(巴西SP)进行。该技术已在具有110个采样点(家庭)的区域中应用。最初,决策树用于估计被调查家庭选择模式的可能性,从而确定用于普通克里金法的数值变量。对于指标克里金法的应用,以离散方式使用了变量“主行驶模式”,其中“ 1”表示使用PM行驶模式,“ 0”表示其他行驶模式。通过两种空间估计技术获得的结果相似(克里格图和交叉验证程序)。但是,指标克里金(KI)的命中率最高。此外,借助KI,可以以其原始形式使用变量,从而避免错误传播。最后,得出的结论是,空间统计正在旅行需求预测问题中蓬勃发展,这两种克里格方法都以确认的方式引起了旅行模式选择面的出现。

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