Fitting and Characteristics Analysis of Travel-Time Fluctuations on an Urban Road Network

被引：2

作者：

Li, Junxian ^{[1
]}

Wu, Zhizhou ^{[1
]}

Shen, Zhoubiao ^{[2
]}

机构：

[1] Tongji Univ, Key Lab Rd & Traff Engn, Minist Educ, 4800 Caoan Rd, Shanghai 201804, Peoples R China

[2] Urban Construct Design & Res Inst Grp Co Ltd, 3447 Dongfang Rd, Shanghai 200127, Peoples R China

来源：

JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS | 2021年 / 147卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Travel time reliability (TTR); Travel time volatility (TTV); Urban road network; Iterative cumulative sums of squares (ICSS); Autoregressive conditional heteroskedasticity (ARCH) family models; RELIABILITY-MEASURES; VOLATILITY; MODELS;

D O I：

10.1061/JTEPBS.0000582

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Detailed knowledge about the times at which links in a network suffer travel time instability is of great significance for route decision making and traffic management. With a data set of 1,170 links in a large-scale urban road network, this paper introduces advanced algorithms to fit the travel time volatility (TTV) and analyze its characteristics. TTV is prone to clustering, and its distribution exhibits leptokurtosis and a heavy tail. These characteristics suggest iterative cumulative sums of squares (ICSS) and the autoregressive conditional heteroskedasticity family models (ARCHs) are applicable to analyze TTV. ICSS finds the structural change points to locate the time and determine the intensity of the travel time variances fluctuate. ARCHs are employed to fit the TTV series, and the best model is determined by comparison. ICSS and ARCHs are combined to improve the fitting model. With TTV, TTR is analyzed from a dynamic and temporal perspective at intervalwise and linkwise levels.

引用

页数：10

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