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Investigating Travel Flow Differences between Peak Hours with Spatial Model with Endogenous Weight Matrix Using Automatic Vehicle Identification Data

Authors :
Zhou, Yiwei
He, Zhaocheng
Chen, Jin-Yong
Ni, Linglin
Dong, Jieshuang
Source :
Journal of Advanced Transportation. December 28, 2022, Vol. 2022
Publication Year :
2022

Abstract

The rapid urbanization has brought great challenges to the transportation network. However, travel flow at peak hours is not always the same. It is important to investigate how travel flow differs between peak hours to capture travel flow patterns and influential factors to facilitate traffic management and urban planning. This paper establishes a spatial model with endogenous weight matrix (SARBP-EWM) to investigate the travel flow differences between morning and evening peaks on both weekday and weekend based on automatic vehicle identification (AVI) data and point of interest (POI) data in Xuancheng, China. The results confirm strong spatial effects and endogeneity issue. Besides, facility variables such as number of offices and number of clinics reveal strong negative impacts on travel flow differences on both weekday and weekend, while the number of middle school shows significantly positive relation with travel flow differences. In addition, the endogenous weight matrix on both weekday and weekend is successfully estimated and compared. It is found that TAZ pairs tend to be clustered with lower spatial weights on weekday, while they are more randomly distributed with higher spatial weights at weekend. Based on the results above, the policies proposed from Xuancheng 14[sup.th] Five-Year Plan are evaluated and discussed. The above empirical analysis quantifies impacts from key factors on urban travel flow differences between peak hours and provides important references for urban planning and policy making.<br />Author(s): Yiwei Zhou [1,2]; Zhaocheng He [3]; Jin-Yong Chen (corresponding author) [4]; Linglin Ni [5]; Jieshuang Dong [1] 1. Introduction The rapid urbanization process in China has brought much challenges [...]

Details

Language :
English
ISSN :
01976729
Volume :
2022
Database :
Gale General OneFile
Journal :
Journal of Advanced Transportation
Publication Type :
Academic Journal
Accession number :
edsgcl.732627656
Full Text :
https://doi.org/10.1155/2022/7729068