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Patterns of urban foot traffic dynamics
Computers, Environment and Urban Systems ( IF 6.454 ) Pub Date : 2021-07-07 , DOI: 10.1016/j.compenvurbsys.2021.101674
Gregory Dobler 1, 2, 3, 4 , Jordan Vani 4 , Trang Tran Linh Dam 4
Affiliation  

Using publicly available traffic camera data in New York City, we quantify time-dependent patterns in aggregate pedestrian foot traffic. These patterns exhibit repeatable diurnal behaviors that differ for weekdays and weekends but are broadly consistent across neighborhoods in the borough of Manhattan. Weekday patterns contain a characteristic 3-peak structure with increased foot traffic around 9:00 am, 12:00–1:00 pm, and 5:00 pm aligned with the “9-to-5” work day in which pedestrians are on the street during their morning commute, during lunch hour, and then during their evening commute. Weekend days do not show a peaked structure, but rather increase steadily until sunset. Our study period of June 28, 2017 to September 11, 2017 contains two American holidays, the 4th of July and Labor Day, and their foot traffic patterns are quantitatively similar to weekend days despite the fact that they fell on weekdays. Projecting all days in our study period onto the weekday/weekend phase space (by regressing against the average weekday and weekend day) we find that Friday foot traffic can be represented as a mixture of both the 3-peak weekday structure and non-peaked weekend structure. We also show that anomalies in the foot traffic patterns can be used for detection of events and network-level disruptions. Finally, we show that clustering of foot traffic time series generates associations between cameras that are spatially aligned with distributions of commercial, residential, and unbuilt space proximal to the camera locations, indicating that foot traffic dynamics encode information about the surrounding built environment.



中文翻译:

城市人流量动态模式

使用纽约市公开可用的交通摄像头数据,我们量化了行人步行总流量的时间相关模式。这些模式表现出可重复的昼夜行为,这些行为在工作日和周末有所不同,但在曼哈顿区的社区中大致一致。工作日模式包含一个典型的 3 峰结构,在上午 9:00、下午 12:00–1:00 和下午 5:00 左右增加人流量,与行人在的“朝九晚五”工作日一致他们早上上下班、午餐时间和晚上上下班时都在街上。周末的日子不会出现高峰结构,而是稳步增加,直到日落。我们2017年6月28日至2017年9月11日的学习期间包含两个美国假期,7月4日和劳动节,尽管他们在工作日下降,但他们的人流量模式在数量上与周末相似。将我们研究期间的所有天数投影到工作日/周末阶段空间(通过对平均工作日和周末日进行回归),我们发现周五的人流量可以表示为 3 个工作日高峰结构和非高峰周末的混合结构体。我们还表明,人流量模式中的异常可用于检测事件和网络级中断。最后,我们展示了步行交通时间序列的聚类在空间上与摄像机位置附近的商业、住宅和未建空间分布对齐的摄像机之间产生关联,表明步行交通动态编码了有关周围建筑环境的信息。

更新日期:2021-07-07
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