北京市地铁客流的时空分布格局及特征——基于智能交通卡数据

doi:10.18306/dlkxjz.2018.03.010

Abstract

Abstract:

Urban railway systems can reduce environmental footprints by residents' commuting and alleviate traffic congestion in mega-cities. Investigating the characteristics of the spatiotemporal distribution of passenger flows is significant in the examination of traffic demand in public transportation systems. Moreover, the study can help decision makers in traffic demand management. Taking the metro system of Beijing as an example, this study calculated the travel time of over 4 million trips and their origin-destination (OD) matrix. In the investigation of the spatiotemporal patterns, we found that: (1) travel time distribution of all trips and trips during the morning and afternoon peaks well fit with Gamma distribution; (2) patterns of passenger flows between districts or ring roads are symmetric; and (3) spatial inequity has been captured from the evaluation of average transit trips per person per day.

Key words: urban railway system, big data, passenger flow distribution, spatiotemporal pattern, Beijing

Jie HUANG, Jiaoe WANG, Haitao JIN, Fengjun JIN. Investigating spatiotemporal patterns of passenger flows in the Beijing metro system from smart card data[J].PROGRESS IN GEOGRAPHY, 2018, 37(3): 397-406.

Figures/Tables 10

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卡号	检入线路	检入站点	刷卡时间	刷卡次序	检出线路	检出站点	检入时间	是否包含终点
00000002	13	33	2014/04/14 10:44:00	7387916344	0	0	2014/04/14 10:44:00	0
00000002	13	33	2014/04/14 11:22:27	7388858193	3	31	2014/04/14 10:44:00	1

时段	平均值(min)	标准偏差(min)
全天	38.9817	21.8475
早高峰	35.5971	17.3755
晚高峰	33.7665	18.6590

时段	形状参数	95%置信区间		比例参数	95%置信区间
时段	形状参数	下限		上限	下限	上限
全天	3.4945	3.4900	3.4990	11.1551	11.1397	11.1705
早高峰	3.6509	3.6410	3.6608	9.7629	9.7346	9.7912
晚高峰	3.0142	3.0067	3.0217	11.2505	11.2201	11.2810

Investigating spatiotemporal patterns of passenger flows in the Beijing metro system from smart card data

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