高级出行需求模型的增强人口仿真研究  

Enhanced Population Simulation for Advanced Travel Demand Modeling

作　　者：张天然 朱春节 陈先龙 叶昕[3] 王波 ZHANG Tianran;ZHU Chunjie;CHEN Xianlong;YE Xin;WANG Bo(Shanghai Urban Planning&Design Research Institute,Shanghai 200040,China;Guangzhou Transport Planning Research Institute Co.,Ltd.,Guangzhou Guangdong 510030,China;Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China)

机构地区：[1]上海市城市规划设计研究院,上海200040 [2]广州市交通规划研究院有限公司,广东广州510030 [3]同济大学道路与交通工程教育部重点实验室,上海201804

出　　处：《城市交通》2023年第5期113-124,共12页Urban Transport of China

摘　　要：人口仿真的结果既可以作为传统四阶段模型的基本输入,又是基于出行链的模型、基于活动的模型和混合模型的必备数据条件。总结人口仿真的发展历程,详述了迭代比例拟合(IPF)算法、迭代比例更新(IPU)算法、增强迭代比例更新算法等人口仿真算法的技术原理和应用局限性。以第七次全国人口普查数据为边界约束、以居民出行调查数据为种子,利用增强IPU算法在交通小区层面对上海市全市域开展人口仿真实践。基于单一和多属性交叉等维度的边界约束数据对仿真结果进行校核,结果显示增强IPU算法拟合效果相对IPF算法更为理想。同时,讨论了交通大区划分以及不同地理空间分层约束对仿真结果的影响。研究表明,使用增强IPU算法能为高级出行需求模型提供较好的仿真人口。The results of population simulation can serve as basic inputs for the conventional four-step model;they also reflect data conditions for advanced travel chain-based,activity-based,and mixed travel demand models.This paper summarizes the evolution of population simulation and discusses the technical principles and application limitations associated with population simulation algorithms,such as the Itera-tive Proportional Fitting(IPF)algorithm,the Iterative Proportional Updating(IPU)algorithm,and the en-hanced IPU algorithm.Leveraging China's seventh national population census data as a boundary con-straint and residential travel survey data as foundational inputs,an enhanced IPU algorithm is implemented to perform population simulation at the Traffic Analysis Zone(TAZ)level in the Shanghai metropolitan ar-ea.Subsequently,the simulation results are validated against boundary constraint data,encompassing both single and multi-attribute dimensions.The findings demonstrate that the enhanced IPU algorithm outper-forms the IPF algorithm in terms of the goodness of fit.The paper also presents the impact of dividing TAZ districts and employing different geospatial hierarchical constraints on simulation outcomes.The research suggests that using the enhanced IPU algorithm can provide more robust simulated population for ad-vanced travel demand models.

关 键 词：交通模型 人口仿真/人口合成 出行需求模型 迭代比例更新 人口普查 居民出行调查 地理空间分层约束 

分 类 号：U491.12[交通运输工程—交通运输规划与管理]