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Abstract

To maintain an internally consistent representation with actual traffic conditions, this paper presents an origin–destination (O-D) demand consistency-checking and updating model for online dynamic traffic assignment operation. Both predictive and reactive approaches are proposed to minimize the deviations between simulated states and real-world observations and O-D demand adjustment magnitude. The two objectives are combined into a weighted linear quadratic function to construct a guaranteed overdetermined optimization problem. Alternative recursive solution algorithms are presented to design an efficient feedback controller that regulates the demand input for the real-time dynamic traffic assignment simulator. The proposed model is tested with field data from the Irvine test bed network.

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Online Consistency Checking and Origin–Destination Demand Updating

Abstract

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