摘要
居民出行特征分析是研究交通需求和探寻交通拥堵症结的基础手段。为研究居民出行特征,基于企事业单位人群出行特征调研数据,改进经典DBSCAN聚类算法,识别出居民出行停留点,进而结合关联规则提取出居民出行轨迹数据;根据出行轨迹数据的时空特征,分别从时空角度和功能区划分角度,挖掘出企事业人群出行时空分布规律,以及不同功能区企事业人群的出行特征。最后,以北京市亦庄区为例进行分析,得到以下结果:居民出行群体以中低收入的中青年通勤族为主,出行潮汐现象明显,工作日居民出行起讫点分布有明显规律,而休息日居民出行时间灵活,出行起终点分布较分散;商务区、居住区内居民出行量较大,起终点时间分布主要集中在早晚高峰时期,而混合区居民出行起终点分布呈现双高峰规律,休闲区居民出行规律不显著。
The analysis of residents'travel characteristics is the basic means to study traffic demand and explore the crux of traffic congestion.In order to study the travel characteristics of residents,based on the survey data of the travel characteristics of enterprises and business crowd,the classical DBSCAN clustering algorithm was used to identify the stop points of residents'travel,then the travel trajectory data of residents was extracted by combining association rules.According to the spatial-temporal characteristics of travel trajectory data,the spatial-temporal distribution rules of residents'travel were dug out from the perspectives of spatial-temporal and functional area division respectively.Finally,the Yizhuang district of Beijing was taken as an example to explore the characteristics of passenger travel.The results show that the travel group of residents is mainly young or middle-aged commuter group with middle and low-income.The starting and ending point distribution of residents travel on weekday has obvious regularity,which the travel tide phenomenon is obvious.But residents travel time on non-weekday is flexible,and the distribution of travel starting and ending point is scattered.In the business district and the residential district,the travel volume is large,and the start and end time distribution is mainly concentrated in the morning and evening peak periods,while in the mixed district,the start and end time distribution presents a double peak pattern and the travel pattern of the leisure district is not significant.
作者
晋泽倩
陈艳艳
李臣
JIN Ze-qian;CHEN Yan-yan;LI Chen(Department of Urban Construction, Beijing University of Technology, Beijing 100124, China)
出处
《科学技术与工程》
北大核心
2022年第6期2531-2538,共8页
Science Technology and Engineering
基金
国家科技重大专项(2018YFB1601300)
北京市国家科技重大专项(2018YFB1601300)。
关键词
城市交通
企事业人群
出行链提取
出行特征
停留点识别
urban traffic
enterprises and business crowd
travel chain extraction
travel characteristics
stop point identification
作者简介
第一作者:晋泽倩(1995—),女,汉族,陕西韩城人,硕士研究生,研究方向:交通规划与行为分析,E-mail:1374787596@qq.com;通信作者:陈艳艳(1970—),女,汉族,河南郑州人,博士,教授,研究方向:交通规划、交通大数据与智能交通,E-mail:cdyan@bjut.edu.cn。
