[1]马 飞,刘 飞,孙启鹏,等.复杂通勤出行链脆弱性感知结构模型[J].长安大学学报(自然科学版),2017,37(06):99-104.
　MA Fei,LIU Fei,SUN Qi-peng,et al.Perceptual structural model of vulnerability of complex commuter travel chain[J].Journal of Chang’an University (Natural Science Edition),2017,37(06):99-104.
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复杂通勤出行链脆弱性感知结构模型()
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长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
第37卷
期数:
2017年06期
页码:
99-104
栏目:
交通工程
出版日期:
2017-11-20

文章信息/Info

Title:
Perceptual structural model of vulnerability of complex commuter travel chain
文章编号:
1671-8879(2017)06-0099-06
作者:
马 飞; 刘 飞; 孙启鹏; 蒋晓兰; 王文琳; 李晓丹
1. 长安大学 经济与管理学院，陕西 西安 710064；2. 长安大学 综合运输经济管理研究中心，陕西 西安 710064；3. 中国西安卫星测控中心，陕西 西安 710043
Author(s):
MA Fei;  LIU Fei;  SUN Qi-peng;  JIANG Xiao-lan;  WANG Wen-lin;  LI Xiao-dan
1. School of Economic and Management, Chang’an University, Xi’an 710064, Shaanxi, China; 2. Center of Comprehensive Transportation Economic Management, Chang’an University, Xi’an 710064, Shaanxi, China; 3. China Xi’an Satellite Control Center, Xi’an 710043, Shaanxi, China
关键词:
交通工程; 城市交通; 感知结构模型; 通勤出行链; 脆弱性
Keywords:
traffic engineering;  urban traffic;  perceptual structural model;  commuter travel chain;  vulnerability
分类号:
U491
文献标志码:
A
摘要:
为测度城市居民复杂通勤出行链的脆弱性，保证城市交通平稳、高效和可持续发展，引入复杂通勤出行链脆弱性概念，给出典型复杂通勤出行链的系统模型。在此基础上，分析复杂通勤出行链脆弱性的影响因素，采用预抽样数据和主成分分析法对主要影响因素进行识别，提取交通网络拥堵、公共交通衔接不畅、机动车停车困难、交通诱导信息误差和主观因素等5个公因子，据此设计了复杂通勤出行链脆弱性感知的测度指标体系；运用探索性因子分析方法得出各影响因素之间的关系，并基于西安市居民出行调查数据，结合结构方程模型对分析结果进行进一步验证。研究结果表明：交通网络拥堵和公共交通衔接不畅对复杂通勤出行链脆弱性感知水平的贡献度最大，分别为0.278和0.274，是影响出行链可靠性的最主要因素；机动车停车困难的影响程度处于较高水平（0.222），表明停车难是制约复杂通勤出行链稳健运行的重要因素；交通诱导信息误差的影响程度虽然较低（0.144），但其会导致复杂通勤出行链的脆弱性加剧；而主观因素的影响程度最低（0.083），说明由出行者主观因素造成的复杂通勤出行链的脆弱程度并不明显。
Abstract:
In order to measure the vulnerability of complex commuter travel chain of residents and ensure the smooth, efficient and sustainable development of urban traffic, this paper introduced the concept of vulnerability for complex commuter travel chain, and gave a model of typical complex commuter travel chain system. On this basis, the influence factors of vulnerability of complex commuter travel chain were analyzed, and pre-sampling data and principal component analysis method were used to identify the main factors. Five common factors were extracted from the influence factors, namely, traffic network congestion, poor connection of public transport, difficulties of vehicle parking, information errors of traffic guidance and subjective factors. Accordingly, the measurement index system of vulnerability perception of complex commuter traffic chain was designed, and the relationship among influence factors was obtained by exploratory factor analysis. The analysis results were further verified by using the travel survey data of Xi’an residents and structural equation model. The results show that traffic network congestion and poor connection of public transport make the largest contribution to the vulnerability perception level of complex commuter travel chain (0.278 and 0.274), which are the main factors to influence the reliability of traffic chains. The influence degree of parking difficulty is at a high level (0.222), which indicates that parking difficulties are important factors restricting the robust operation of complex commuter travel chain. The influence degree of information errors of traffic guidance is low (0.144), but it can exacerbate the vulnerability of complex commuter travel chains. The influence degree of subjective factors is the lowest (0.083), which indicates that the vulnerability degree of complex commuter travel chain caused by subjective factors is not obvious.

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备注/Memo

备注/Memo:
收稿日期：2017-05-17 基金项目：国家社会科学基金项目（17BJY139）；教育部人文社会科学基金项目（17YJCZH125）；陕西省社会科学基金项目（2016R026）；西安市社会科学规划基金项目（17J176）作者简介：马 飞（1979-），男，陕西泾阳人，副教授，工学博士，E-mail:mafeixa@163.com。
更新日期/Last Update: 2017-12-18