Volume 8 Number 4 (Apr. 2013)
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JSW 2013 Vol.8(4): 868-877 ISSN: 1796-217X
doi: 10.4304/jsw.8.4.868-877

Seasonal Factor Assignment Based on the Similarity of Hourly Traffic Patterns and Influential Variables

Chenxi Lu1, Renfa Yang1, Shanshan Yang2, Fang Zhao2
1Ningbo University of Technology / College of Transportation and Logistics, Ningbo, China
2Florida International University / Department of Civil & Environmental Engineering, Miami, USA


AbstractAverage Annual Daily Traffic is typically estimated by applying seasonal factors (SFs) to short-term counts. SFs are obtained from continuous count sites and assigned to short-term count sites. This assignment procedure is usually empirical and subjective. Some previous studies have attempted to establish relationships between SFs and influential variables to provide an objective and data-driven alternative for SF assignment. However, in rural areas, SFs are difficult to model due to low land use intensity and, sometimes, significant through traffic. This paper presents a study of relationships between monthly SFs and hourly traffic patterns, land use, and other variables, using data from 116 continuous counters in rural areas throughout Florida. It is found that hourly traffic patterns are related to traffic seasonality and can be used to improve the modeling of influential variables that affect SF. The influential variables are then used for seasonal factor assignment and estimation. The proposed method achieved an average error of four percent, with 95 percent of the estimated monthly SFs having an error of no more than ten percent.

Index TermsHourly traffic pattern, Seasonal factors, Land use, Spatial analysis, Regression analysis

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Cite: Chenxi Lu, Renfa Yang, Shanshan Yang, Fang Zhao, "Seasonal Factor Assignment Based on the Similarity of Hourly Traffic Patterns and Influential Variables," Journal of Software vol. 8, no. 4, pp. 868-877, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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