中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2018, Vol. 37 ›› Issue (05): 92-96.DOI: 10.3969/j.issn.1674-0696.2018.05.16

• 交通运输工程 • 上一篇    下一篇

基于二元Logistic的公路货运超载关键影响因素识别

陈一锴1,王富超1,王凯1,郑宏富2,石琴1   

  1. (1. 合肥工业大学 汽车与交通工程学院,安徽 合肥 230009;2. 安徽省道路运输管理局,安徽 合肥 239000)
  • 收稿日期:2016-10-22 修回日期:2017-02-11 出版日期:2018-05-15 发布日期:2018-05-15
  • 作者简介:陈一锴(1984—),男, 安徽太和人, 副教授,博士,主要从事道路交通安全、汽车系统动力学等方面的研究。E-mail:yikaichen@hfut.edu.cn。 通信作者:王富超(1990—),男, 安徽宣城人,硕士生,主要从事道路交通安全、汽车系统动力学等方面的研究。E-mail:540518620@qq.com。
  • 基金资助:
    国家自然科学基金资助项目(51305117);中国博士后科学基金资助项目(2013M530230,2014T70464);高等学校博士学科点专项科研基金资助项目(20130111120031)

Identification of Key Factors Affecting Highway Freight Overloading Based on Binary Logistic Regression

CHENG Yikai1, WANG Fuchao1, WANG Kai1, ZHENG Hongfu2, SHI Qin1   

  1. (1. College of Automotive and Traffic Engineering, Hefei University of Technology, Hefei 230009, Anhui, P. R. China; 2. Road Transportation Management Bureau of Anhui Province, Hefei 239000, Anhui, P. R. China)
  • Received:2016-10-22 Revised:2017-02-11 Online:2018-05-15 Published:2018-05-15

摘要: 为了探究影响公路货车超载的关键因素,为查超、治超工作提供理论依据,基于2015年公路运输量专项调查采集的3 249辆公路货车的运营类型、线路特性、车辆特征,通过单因素分析 、共线性检验、二元Logistic回归分析,识别公路货运超载的关键影响因素,然后提出切实可行的治超措施。结果表明:运营类型、车长、运营模式、货运量及平均运距是公路货运超载关键 影响因素。

关键词: 交通运输工程, 货运, 超载, 关键因素, Logistic回归

Abstract: In order to explore the key factors influencing highway truck overloading and provide theoretical foundation to check and rule over the overloading, the key factors affecting freight vehicle overloading were identified on the basis of the collected data of the operation types, line characteristics and vehicle characteristics of 3249 highway trucks in the highway traffic volume survey conducted in 2015. The single factor analysis, collinearity test and binary Logistic regression analysis were used. And then the feasible measures to rule over the overloading were proposed. It is indicated that the operation type, vehicle length, operation mode, freight volume and average distance are the key factors to influence highway truck overloading.

Key words: traffic and transportation engineering, freight vehicle, overloading, key factor, Logistic regression

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