摘要
以北京市西城区广安门外地区违章停车记录数据为基础,利用时空分析方法和社会认知理论,总结停车供给、道路交通管理、驾驶人差异作为外生潜变量,提炼出停车需求、违章停车行为作为内生潜变量,并建立结构方程模型,揭示违章停车行为产生路径及各因素间的作用机理。研究结果表明:道路交通管理潜变量对违章停车行为影响最大,停车费率、寻泊时长、停车时长这些观测变量对违章停车行为影响显著,效用值分别为0.83、0.70、0.70。基于此,应落实违停治理精细化、停车资源共享化、驾驶员素质教育常态化的停车管理政策,切实有效改善路内违章停车现状,为更好管理城市违章停车实现高水平停车治理提供决策依据。
This paper investigates the management strategy for illegal parking behavior using the illegal parking data in Guanganmenwai Street in Xicheng District of Beijing,China.The spatial-temporal analysis method and social cognitive theory are used to summarize parking supply.The road traffic management and driver difference are used as exogenous latent variables.Then the parking demand and illegal parking behavior are extracted as endogenous latent variables.The structural equation model is developed to reveal the path of illegal parking behavior and the mechanism of each factor.The results show that the latent variable of road traffic management has the greatest impact on illegal parking behavior.The observed variables such as parking rate,seeking time and parking time have significant impact on illegal parking behavior,and the utility values are respectively 0.83,0.70 and 0.70.Improving road traffic management measures,activating parking resources,and improving the utilization rate of parking resources can effectively improve the current situation of illegal parking on roads,and provide a decision-making basis for the illegal parking management in cities.
作者
林建新
刘依妮
朱雪超
刘博
LIN Jian-xin;LIU Yi-ni;ZHU Xue-chao;LIU Bo(School of Civil and Transportation Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;Xicheng Transportation Detachment,Beijing Traffic Management Bureau,Beijing 100037,China;Beijing City Interface Technology Co.Ltd,Beijing 100045,China)
出处
《交通运输系统工程与信息》
EI
CSCD
北大核心
2023年第6期133-140,共8页
Journal of Transportation Systems Engineering and Information Technology
基金
北京市社会科学基金(21GLB034)。
关键词
交通工程
停车管理
结构方程
违章停车
时空分析
traffic engineering
parking management
structural equation
illegal parking
spatial-temporal analysis
