Integrated Heteroscedasticity Test for Vehicular Traffic Condition Series

AbstractBecause 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,...

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