基于上海轨道交通刷卡数据的乘客出行模式研究

乘客出行模式研究是深入认识城市交通的基础性工作,也是交通规划的重要技术支撑。基于上海轨道交通刷卡数据分析网络客流特征,以轨道交通出行全过程出行链视角对进出站客流量、站间客流量、乘距等出行要素的空间模式开展研究,发现上海轨道交通进站和出站客流量分布均呈现对数正态分布特征,乘客乘距服从负二项分布特征。研究同时发现,相比于幂律分布,上海站间客流量分布更加适合采用对数正态分布拟合。此外,工作日客流和周末客流在空间分布总体形态上较为接近,工作日客流分布更为集聚,周末客流分布则更为离散。

Understanding Spatial Patterns of Urban Human Mobility Using Shanghai Rail Transit Smart Card Records

Spatial patterns of urban human mobility is a fundamental area of urban and transportation research, and an important technology support for transportation planning. In this paper, I establish a whole process analysis framework which includes station inflow and outflow, station-to-station flow, and distance, based on the smart card data of Shanghai rail transit system. The results show that the distribution of inflow and outflow exhibits log-normal distribution characteristics. The travel distance also follows a negative binomial distribution. Moreover, individual travel patterns at station level in Shanghai follow a log-normal distribution in comparison with the power distribution. Finally, the spatial patterns of weekday and weekend data are similar. However, the weekday pattern is more dispersed while weekend pattern is more centralized.