交通运输系统工程与信息 ›› 2020, Vol. 20 ›› Issue (5): 163-168.

• 系统工程理论与方法 • 上一篇    下一篇

基于Panel Data的山地城市立交基本段通行能力影响因素研究

周约珥1, 2,龚华凤*1, 2,赵聪霄1, 2,徐小童1, 2,黄博亚1, 2   

  1. 1. 林同棪国际工程咨询(中国)有限公司,重庆 401121; 2. 重庆市山地城市可持续交通工程技术研究中心,重庆 401121
  • 收稿日期:2020-05-08 修回日期:2020-08-18 出版日期:2020-10-25 发布日期:2020-10-26
  • 作者简介:周约珥(1993-),男,湖南浏阳人,工程师.
  • 基金资助:

    重庆市建设科技计划/Construction Plan Project of Science and Technology of Chongqing(城科字2019第1-5-3).

Interchange Basic Segment Capacity Impact Factor Analysis Based on Panel Data

ZHOU Yue-er1, 2, GONG Hua-feng1, 2, ZHAO Cong-xiao1, 2, XU Xiao-tong1, 2, HUANG Bo-ya1, 2   

  1. 1. T. Y. Lin International Engineering Consulting(China)Co., Ltd, Chongqing 401121, China; 2. Sustainable Transportation Engineering & Technology Research Center for Mountain Cities, Chongqing 401121, China
  • Received:2020-05-08 Revised:2020-08-18 Online:2020-10-25 Published:2020-10-26

摘要:

通过统计学分析,基于重庆市主城区不同立交基本段采集的交通流与道路线型等数据,建立Panel Data(面板数据)模型,研究山地城市立交基本段通行能力的主要影响因素,确定通行能力与主要影响因素间的数学关系,对主要影响因素的敏感度排序.结果表明:竖曲线半径、设计速度、圆曲线半径、大车比例是影响山地城市立交基本段通行能力的主要因素,其 中,竖曲线半径对通行能力的影响最大,敏感度最高,为20.66%;道路坡度由于影响权重较小,被大车比例取代.

关键词: 城市交通, 通行能力影响因素, panel data, 立交通行能力, 山地城市

Abstract:

This study aims to identify the capacity impact factors (CIFs) of basic interchange segments in mountainous cities and examine the co- relation of the major CIFs with the capacity. Using the traffic data and roadway geometric data collected from basic interchange segments located in multiple districts in Chongqing, China, the study conducted statistical analysis and developed a panel data model to describe the relationship of capacity and CIFs. The sensitivity of the CIFs to the capacity of basic interchange segments was analyzed and ranked. The results indicate the major CIFs include radius of vertical curve, design speed, radius of horizontal curve, and heavy vehicle percentage. Among these factors, radius of vertical curve is the most significant CIF, and the sensitivity is up to 20.66%. The roadway grade doesn't appear as a major CIF due to the small impact weight. The heavy vehicle percentage is identified as a major impact factor.

Key words: urban traffic, capacity impact factor (CIF), panel data, interchange capacity, mountainous cities

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