Integrated Heteroscedasticity Test for Vehicular Traffic Condition Series
Publication: Journal of Transportation Engineering
Volume 138, Issue 9
Abstract
Because of the growing awareness of the importance of the traffic condition uncertainty-related studies, traffic condition uncertainty modeling is gaining increasing attention from the transportation research community. In this field, traffic condition uncertainty, gauged mainly by the conditional variance of traffic characteristics, has been investigated primarily with two major approaches, generalized autoregressive conditional heteroscedasticity approach and stochastic volatility approach; however, both lack a thorough and sound test on the applicability of these approaches. To complete this modeling gap and hence lay the theoretical basis for traffic uncertainty-related studies, an integrated heteroscedasticity test, including an optimal transformation search and four statistical tests, is proposed in this study. By using real world data collected from 36 stations across four regions in both the United Kingdom and the United States and aggregated at 15-min interval as a typical representative, the proposed integrated heteroscedasticity test is demonstrated, validating the heteroscedastic nature of the traffic conditional series. In addition, the effects of transformations are illustrated together with an online short-term traffic condition forecasting algorithm as an additional validation of this heteroscedastic nature. On firmly establishing the heteroscedastic nature of the traffic conditions, future studies are recommended to further the modeling of traffic condition uncertainties over a spectrum of time intervals and apply the uncertainty models in various applications such as travel time reliability or the proactive traffic control systems.
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Acknowledgments
The authors thank the Minnesota Department of Transportation, the Washington State Department of Transportation, and the Maryland Department of Transportation, and the United Kingdom Highways Agency for providing the traffic data used in this research. The authors hold all the responsibility on the analyses and views presented in this work. This work is supported in part by the National Science Foundation of China under the Grant No.71101025.
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Information & Authors
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Published In
Journal of Transportation Engineering
Volume 138 • Issue 9 • September 2012
Pages: 1161 - 1170
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Jul 28, 2011
Accepted: Feb 22, 2012
Published online: Feb 23, 2012
Published in print: Sep 1, 2012
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