个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职:Director of International Office Dean of School of Transportation and Logistics
其他任职:交通运输学院名誉院长
性别:男
毕业院校:日本东京大学
学位:博士
所在单位:交通运输系
学科:交通运输规划与管理. 交通系统工程. 市政工程. 行政管理
联系方式:0411-84708224
电子邮箱:szhao@dlut.edu.cn
Induced Traffic in China: Elasticity Models with Panel Data
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论文类型:期刊论文
发表时间:2015-12-01
发表刊物:JOURNAL OF URBAN PLANNING AND DEVELOPMENT
收录刊物:SCIE、SSCI、Scopus
卷号:141
期号:4
ISSN号:0733-9488
关键字:Urban transportation planning; Induced traffic; Elasticity model; Panel data
摘要:The induced traffic model is an essential component of travel demand analysis, which has been primarily researched with elasticity models in the United States and U.K. This paper aims to find the most suitable elasticity model based on the set of panel data regarding annual observations of 30 cities and provinces across China (except Chongqing city) for the years 1990 to 2010. To derive the ideal elasticity model, several basic elasticity models are included; among them are the elasticity-based model, distributed lag model, growth model, and fixed-effect model. Advanced elasticity models, such as the three stages of least squares (3SLS) are also discussed. According to relative researches and data collection, any increase of passenger kilometers of transport (PKT) with the growth of lane kilometers is considered induced traffic and is routinely used as such in this paper. Lane kilometers in China are found to have a statistically significant relationship with PKT measurements of approximately 0.026-0.274 in the short term and 0.367-0.773 in the long term. Population and gross regional product (GRP) numbers are also considered in basic elasticity models. Based on the detailed analysis of empirical results, the 3SLS is judged as the best suitable model for China. It can reflect the time effect, consider endogenous variables (including congestion and vehicle stock), and eliminate the simultaneity bias. (C) 2014 American Society of Civil Engineers.