Investigation of Changes in Passenger Behavior Using Longitudinal Smart Card Data
Investigation of Changes in Passenger Behavior Using Longitudinal Smart Card Data
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DOI：
10.1007/s13177-020-00232-3
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发表时间：
2020-10
影响因子：
2.1
通讯作者：
Rattanaporn Kaewkluengklom;F. Kurauchi;Takenori Iwamoto
中科院分区：
文献类型：
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作者：
Rattanaporn Kaewkluengklom;F. Kurauchi;Takenori Iwamoto
为了更好地了解人类流动的长期模式，本研究探讨在个人层面上的旅行行为的变化，每年的活动配置文件使用3年的纵向智能卡数据收集在日本静冈。我们首先通过k-均值聚类来表征铁路使用的时空模式，然后研究聚类成员随时间的变化。对于那些仍然活跃的乘客，定期通勤者在研究期间有类似的旅行模式，而不经常旅行者显着增加了他们对铁路系统的使用。分析和讨论了簇分配算法的演化过程。
To better understand long-term patterns of human mobility, this study examines changes in travel behavior at the individual level based on yearly activity profiles using 3 years of longitudinal smart card data collected in Shizuoka, Japan. We first characterize spatiotemporal patterns of railway usage by k-means clustering, and then investigate variation in cluster membership with time. For among passengers who remained active, regular commuters had similar travel patterns over the study period, whereas infrequent travelers significantly increased their use of the railway system. The evolution of cluster assignment is analyzed and discussed.