Travel Matrix Decomposition for Understanding Spatial Long-Distance Travel Structure
Travel Matrix Decomposition for Understanding Spatial Long-Distance Travel Structure
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DOI：
10.1155/2023/1090277
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发表时间：
2023-02
期刊：
影响因子：
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通讯作者：
Hiromichi Yamaguchi;Mashu Shibata;Shoichiro Nakayama
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文献类型：
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作者：
Hiromichi Yamaguchi;Mashu Shibata;Shoichiro Nakayama
手机位置数据使我们能够获得准确且时间详细的长途旅行分布。然而，传统的长途出行分布模型无法正常处理这种详细的时间信息。本研究提出了一种处理长途旅行分布的时间详细信息的方法。考虑到这种方法，出发地-目的地矩阵分解为两个变量（指标）：目的地便利设施和旅行成本。它们可以解释为旅行目的地选择多项 Logit 模型中处理的多个变量的综合指标。由于它们仅根据起始目的地计算，因此我们可以讨论它们的详细时间变化。在这项研究中，计算了目的地便利设施的时间变化和日本县际旅行的旅行成本，以证实这种方法的价值。这些指标成功地描述了日本国内长途旅行的模式。这些量化指标有助于了解国家土地结构。它们可作为政策制定的成果衡量标准。此外，这些指标解释了目的地选择模型的时间适用性。具体而言，目的地便利设施的结果存在较大的季节性变化。这表明目的地舒适度模型的参数（即目的地变量的系数）不是季节性稳定的。因此，在处理长途旅行的目的地选择时必须考虑这一点。
Mobile phone location data enable us to obtain accurate and temporally detailed long-distance travel distribution. However, the traditional long-distance travel distribution model cannot normally handle this detailed temporal information. This study proposes an approach for handling temporally detailed information of long-distance travel distribution. Considering this approach, the origin-destination matrix decomposes into two variables (indicators): destination amenity and travel cost. They can be interpreted as composite indicators of several variables that are treated in the travel-destination choice multinomial logit model. Because they are calculated only from the origin destination, we can discuss their detailed temporal variations. In this study, time changes in destination amenities and travel costs of interprefectural travel in Japan are calculated to confirm the value of this approach. These indicators have succeeded in describing the pattern of domestic long-distance travel in Japan. These quantified indicators have facilitated the understanding of the national land structure. They are useful as outcome measures for policy-making. Moreover, these indicators explain the temporal applicability of the destination choice model. Specifically, the results of destination amenities have a large seasonal variation. This indicates that the parameters of the destination amenity model (i.e., the coefficients of the destination variables) are not seasonally stable. Therefore, this must be considered when dealing with destination choice for long-distance travel.