摘要
随着上海市轨道交通客流量日益增长,部分车站在运营过程中逐渐暴露出高峰集散能力不足等问题。基于运营超过5年的238座车站的刷卡数据,从车站高峰小时时段分布、高峰小时系数取值范围、超高峰系数取值范围三个方面分析车站客流高峰小时特征。得到以下主要结论。1)车站进站客流高峰呈现集聚于早高峰的单峰分布特征,出站高峰客流则呈现向早晚高峰集聚的双峰分布特征。2)进站客流高峰小时系数取值普遍高于出站客流高峰小时系数,进出站客流高峰小时系数主要与车站周边用地特征、车站区位密切相关;城市外围高强度单一居住功能为主的车站或周边高强度单一办公密集型车站存在较高高峰小时系数的可能。3)大部分车站超高峰系数位于规范推荐值范围内;对于位于线路末梢同时承担周边一定范围内交通接驳功能的车站,在客流预测中超高峰系数建议选用规范推荐范围中较高值。
Along with the increasing passenger flow of Shanghai urban rail transit,many stations shows inadequate in passenger distribution during peak hours.Based on the smart card data of 238 stations which have been in operation for more than 5 years,this paper analyzes the characteristics of peak hour distribution,peak hour factors and extra peak hour factors.Firstly,arrival passenger volume peak hour tends to occur in the morning peak,while departure passenger volume peak hour clusters in both the morning and evening.Secondly,peak hour factor of arrival passenger volume is higher than that of departure passenger volume.The peak hour factor is closely related to both the characteristics of land use around stations and station location.Stations with single and high intensity of residence or office land use may bring high peak hour factors.Thirdly,extra peak hour factors of most station are within the recommended range of specifications.However,for those stations located at the end of lines and functioned as terminals,a higher value of extra peak hour factors are recommended.
作者
金昱
Jin Yu(Shanghai Urban Planning and Design Institute,Shanghai 200040,China)
出处
《城市交通》
2019年第4期50-57,共8页
Urban Transport of China
关键词
轨道交通
车站客流
高峰小时系数
超高峰系数
大数据
上海市
rail transit
passenger flow at stations
peak hour factor
extra peak hour factor
big data
Shanghai