Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction

Tao Ma, Zhou Zhou and Baher Abdulhai

Transportation Research Part B: Methodological, 2015, vol. 76, issue C, 27-47

Abstract: We propose Time–Space Threshold Vector Error Correction (TS-TVEC) model for short term (hourly) traffic state prediction. The theory and method of cointegration with error correction mechanism is employed in the general design of the new statistical model TS-TVEC. An inherent connection between mathematical form of error correction model and traffic flow theory is revealed through the transformation of the well-known Fundamental Traffic Diagrams. A threshold regime switching framework is implemented to overcome any unknown structural changes in traffic time series. Spatial cross correlated information is incorporated with a piecewise linear vector error correction model. A Neural Network model is also constructed in parallel to comparatively test the effectiveness and robustness of the new statistical model. Our empirical study shows that the TS-TVEC model is an effective tool that is capable of modeling the complexity of stochastic traffic flow processes and potentially applicable to real time traffic state prediction.

Keywords: Cointegration; Vector error correction; Threshold regime switching; Short term traffic state prediction; Neural Network (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.trb.2015.02.008

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