交通运输系统工程与信息 ›› 2015, Vol. 15 ›› Issue (3): 37-43.

• 综合交通运输体系论坛 • 上一篇    下一篇

基于精细化用地的轨道客流直接估计模型

王淑伟1,2,孙立山*1,郝思源1,荣建1   

  1. 1. 北京工业大学北京市交通工程重点实验室,北京100124;2. 国家发展和改革委员会综合运输研究所,北京100038
  • 收稿日期:2014-12-23 修回日期:2015-03-09 出版日期:2015-06-25 发布日期:2015-06-29
  • 作者简介:王淑伟(1987-),男,山东诸城人,博士生.
  • 基金资助:

    国家自然科学基金项目(51308017);高等学校博士学科点专项科研基金资助课题(20121103120025);北京市科技新星计划(Z141106001814110);北京市属高等学校人才强教资助项目.

Station Level Transit Ridership Direct Estimation Model Based on Precise Land Use

WANG Shu-wei1,2,SUN Li-shan1,HAO Si-yuan1,RONG Jian1   

  1. 1. Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China; 2. Institute of Comprehensive Transportation of National Development and Reform Commission, Beijing 100038, China
  • Received:2014-12-23 Revised:2015-03-09 Online:2015-06-25 Published:2015-06-29

摘要:

现有轨道客流直接估计模型中,对于用地的描述多基于人口、岗位分布、用地面积等概略数据,未能准确反映用地开发的多样性和复杂性,难以揭示用地混合开发对于居民出行的作用机理.本文采用北京市电子地图中的兴趣点(POI)数据表示用地信息,结合轨道站点多层次吸引范围划分,实现了轨道站点吸引范围内各类用地比例的精细化描述.通过将精细化用地信息与轨道站点乘降客流量进行回归分析,总结了用地、交通、区位因素对于轨道站点乘降客流的影响机理,建立了基于精细化用地的轨道站点客流估计模型.验证结果显示,模型对于本文所研究典型站点的预测精度达到预期,反映了用地与轨道客流之间的强相关性.

关键词: 城市交通, 轨道交通, 精细化用地, 兴趣点, 直接估计模型

Abstract:

The existing transit ridership models describe land use with indexes such as population, employment and land use area, these indexes can' t describe the diversity and complexity of land use development, thus make it difficult to reveal the influence mechanism of mixed land use on travel demand. This paper quantifies the precise land use characteristics of Beijing transit station catchment areas using POIs (points of interest) extract from an electronic map. Through the regression analysis of precise land use and transit station boarding volume, a direct ridership model is built based on the influence mechanism analysis of land use, traffic and location factors on transit ridership. Following validation shows the prediction accuracy of the proposed model meets expectation, reveals the strong correlation between land use and transit ridership.

Key words: urban traffic, rail transit, precise land use, point of interest, direct ridership model

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