摘要
公共交通是解决城市交通拥堵问题的有效措施.通勤群体作为城市公共交通的主要参与者,其行为模式一直以来是学界的研究重点与难点.本研究以全样本出行数据为基础,采用人类行为动力学方法,通过分析通勤乘客的出行时间间隔分布特征,从群体层面实证了人类行为"幂律呈现"的普适性,但同时也在部分个体样本上观察到了"幂律消散"现象.深入研究发现,这些偏离幂律拟合特征的个体,一般具有更为规则的出行规律.进一步提出了基于曲线拟合参数及出行间隔谱函数的通勤乘客聚类方法,直观、有效地解决了通勤乘客的细分问题.珠海市的案例显示,对于深入研究城市公共交通出行规律具有很强的实用价值.
Public transportation is an effective measure to solve urban traffic congestion problems.As a major participant in urban public transportation,commuting groups and their behavioral patterns have long been the focus of academic research.The study constructed the passenger bus travel time interval distribution with behavior dynamics method based on the whole sample travel data.It demonstrates the universality of "power law representation" of human behavior from the group level.But at the same time,the phenomenon of "power law dissipation" has been observed in some individual samples.In-depth study finds that the individuals deviating from power law fitting characteristics have more regular travel rules generally.Further,the clustering methods of commuter passengers was proposed based on curve fitting parameters and travel interval spectral function.The methods can solve the subdivision problem of commuter passengers intuitively and effectively.The case of Zhuhai shows that the research has a strong practical value for in-depth study of urban public transport travel rules.
作者
姚树申
翁小雄
李飞羽
YAO Shushen;WENG Xiaoxiong;LI Feiyu(School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China)
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2019年第9期53-60,共8页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(51308227)~~
关键词
公共交通
通勤
大数据
行为动力学
public transportation
commuting
big data
behavior dynamics
