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

城市轨道交通是居民绿色出行、缓解大城市交通拥堵的重要交通方式。研究大城市地铁客流时间和空间的分布特征,有利于深入了解大城市公共交通的需求,进而制定合理的交通需求管理政策。本文以北京市地铁为例,计算了431万条智能交通卡数据的出行时间和OD矩阵(Origin-Destination Matrix),研究其客流的时间和空间分布特征。研究发现：①全天、早高峰和晚高峰的出行时间分布符合Gamma分布,总体上离城市中心越远,平均出行时间越长;②从市辖区尺度和环路尺度分析,乘客流向和流量均呈现对称性;③从街道尺度来看,居民地铁出行强度的空间不均等性很强。

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

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.