Abstract To reduce inaccuracies due to insufficient spatial resolution of models, it has been suggested to use smaller raster cells instead of larger zones. Increasing the number of zones, however, increases the size of a matrix to store travel times, called skim tables in transport modeling. Those become difficult to create, to store and to read, while most of the origin-destination pairs are calculated and stored but never used. At the same time, such approaches do not solve inaccuracies due to lack of temporal resolution. This paper analyzes the use of personalized travel times at the finest spatial resolution possible (at x/y coordinates) and a detailed temporal resolution for synthetic agents. The approach is tested in the context of an existing integrated land use/transport model (ILUT) where travel times affect, among others, household relocation decisions. In this paper, person-level individual travel times are compared to traditional skim-based travel times to identify the extent of errors caused by spatial and temporal aggregation and how they affect relocation decisions in the model. It was shown that skim-based travel times fail to capture the spatial and temporal variations of travel times available at a microscopic scale of an agent-based ILUT model. Skims may provide acceptable averages for car travel times if a dense network and small zones are used. Transit travel times, however, suffer from temporal and spatial aggregation of skims. When analyzing travel-time-dependent relocation decisions in the land use model, transit captive households tend to react more sensitively to the transit level of service when individual travel times are used. The findings add to the existing literature a quantification of spatial biases in ILUT models and present a novel approach to overcome them. The presented methodology eliminates the impact of the chosen zone system on model results, and thereby, avoids biases caused by the modifiable spatial unit problem.

中文翻译：

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旅行时间矩阵的终点：综合土地利用/运输模型中的个人旅行时间

摘要 为了减少由于模型空间分辨率不足而导致的不准确性，建议使用较小的栅格单元而不是较大的区域。然而，增加区域的数量会增加用于存储旅行时间的矩阵的大小，在交通建模中称为撇脂表。那些变得难以创建、存储和读取，而大多数源-目的地对被计算和存储但从未使用。同时，由于缺乏时间分辨率，此类方法无法解决不准确问题。本文分析了在可能的最佳空间分辨率（在 x/y 坐标处）以及合成代理的详细时间分辨率下个性化旅行时间的使用。该方法在现有综合土地利用/运输模型 (ILUT) 的背景下进行了测试，其中旅行时间会影响，除其他外，家庭搬迁决定。在本文中，人员级别的个人旅行时间与传统的基于撇脂的旅行时间进行了比较，以确定由空间和时间聚合引起的错误程度以及它们如何影响模型中的搬迁决策。结果表明，基于浏览的旅行时间无法捕捉在基于代理的 ILUT 模型的微观尺度上可用的旅行时间的空间和时间变化。如果使用密集的网络和小区域，撇去可以提供可接受的汽车行驶时间平均值。然而，过境旅行时间受到撇去时间和空间聚合的影响。在土地利用模型中分析与出行时间相关的搬迁决策时，当使用个人出行时间时，过境俘虏家庭往往对过境服务水平做出更敏感的反应。这些发现为现有文献增加了 ILUT 模型中空间偏差的量化，并提出了一种克服它们的新方法。所提出的方法消除了所选区域系统对模型结果的影响，从而避免了由可修改空间单元问题引起的偏差。