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Nonparametric Approach to Analyze the Effects of Heterogeneity on Travel Duration

机译:非参数方法分析异质性对旅行持续时间的影响

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Activity-based travel demand forecasting has got great concern in the past decade. In this paper, a nonparametric regression method is presented which can model travel durations by identifying heterogeneity patters that may undermine duration modeling if not detected. The technique utilizes a kernel estimate of the probability density function (PDF) of daily travel durations to compare different activity pattern. The advantage of this method is that it's free of any distributional assumption. The results show that the more complex activity pattern, time spent in travel is more. And it is also found that the distribution of travel duration for the standard-working group and the long-term maintenance group cannot be modeled by a linear or a linearized function. It is indicated that the approach is effective in evaluating covariate effects.
机译:在过去十年中,基于活动的旅行需求预测备受关注。在本文中,提出了一种非参数回归方法,该方法可以通过识别可能会破坏持续时间建模(如果未检测到)的异质性模式,对出行持续时间进行建模。该技术利用每日旅行持续时间的概率密度函数(PDF)的核估计来比较不同的活动模式。这种方法的优点是它没有任何分布假设。结果表明,活动模式越复杂,花在旅行上的时间就越多。而且还发现,标准工作组和长期维护组的旅行持续时间分布无法通过线性或线性化函数建模。结果表明,该方法在评估协变量效应方面是有效的。

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