交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (5): 51-55.

• 智能交通系统与信息技术 • 上一篇    下一篇

基于信令数据的出行强度影响因素分析模型

雷方舒*   

  1. 北京交通发展研究院 城市交通运行仿真与决策支持北京市重点实验室城市交通北京市国际科技合作基地,北京 100073
  • 收稿日期:2020-06-26 修回日期:2020-07-16 出版日期:2020-10-25 发布日期:2020-10-26
  • 作者简介:雷方舒(1990-),女,内蒙古赤峰人,工程师.
  • 基金资助:

    国家重点研发计划/ National Key Research and Development Program of China(2018YFB1600700).

Travel Intensity Influencing Factors Analysis Model Based on Signaling Data

LEI Fang-shu   

  1. Beijing International Science and Technology Cooperation Base of Urban Transport, Beijing Key Laboratory of Urban Transport Simulation and Decision Making Support, Beijing Transport Institute, Beijing 100073, China
  • Received:2020-06-26 Revised:2020-07-16 Online:2020-10-25 Published:2020-10-26

摘要:

为探究城市交通出行强度影响因素及不同因素的影响程度,本文从土地利用与交通基础设施建设两方面出发,分析包括土地利用混合指数,职住混合率熵指数,公共交通站点 500 m覆盖率,路网可达性等17个指标与出行强度的相关关系;基于相关系数和拟合优度分析,提取7个与出行强度强相关指标,基于所识别指标构建北京市中心城区出行强度多元回归模型.模型结果表明,职住混合率熵指数对出行强度的影响最为显著,公共交通站点覆盖率对出行强度的影响比道路网密度和可达性更为明显.此外,给出单一土地利用/交通基础设施指标对出行强度拟合结果的离群特征分析方法,用于评估不同区域基础设施供给与交通出行需求之间的平衡关系.

关键词: 智能交通, 影响因素, 多元回归模型, 出行强度, 土地利用, 交通基础设施

Abstract:

This paper investigates the impact factors of urban travel intensity and the corresponding degree of impact. The land use and transportation infrastructure construction factors are considered in the analysis the 17 indicators involved in the analysis include land use mixing index, job-residential mixed ratio entropy index, public transportation stops 500-meter coverage, road network accessibility, so and so forth. Seven indicators with strong correlation with travel intensity were extracted based on correlation coefficients and goodness- of- fit analysis. A travel intensity multiple regression model in the central city of Beijing was developed based on the extracted indicators. Model results show that the work-resident ratio entropy index has the most significant impact on travel intensity. The impact of public transportation stop coverage rate on travel intensity is more obvious than road network density and accessibility. In addition, this paper also proposes a method of the outlier character analyze based on single land use or transportation infrastructure construction index fitting result, which is used to evaluate the balance between infrastructure supply and travel demand for different regions.

Key words: intelligent transportation, influence factor, multiple regression model, travel intensity, land use, transportation infrastructure

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