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- W579470570 abstract "This paper presents two revised approaches for estimating time-varying Origin-Destination (O-D) flows in urban networks. Both approaches lend themselves to formulation as state-space models. An efficient parameter optimization model with the objective function to minimize the absolute deviations between measured and estimated link counts is first formulated for estimating real-time intersection turning flows, and is solved using genetic algorithm. Based on this, the first approach makes use of O-D flow deviations from historical data as state vectors, and constructs an additional set of system observation constraints with estimated intersection turning flows to improve the system observability. Since there may exist errors in DTA or simulation models, the second approach, also involves the constraints from intersection turning flows, further utilizes path flow deviations as state vectors, and accounts for the inherent errors in assignment/mapping matrix caused by DTA or traffic simulation. Intersection model is testified using field data, and both network models are evaluated using simulation experiments. The reported examples have clearly indicated that the proposed approaches are quite accurate, efficient and robust." @default.
- W579470570 created "2016-06-24" @default.
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- W579470570 date "2006-01-01" @default.
- W579470570 modified "2023-10-18" @default.
- W579470570 title "Revised Approaches for Estimation of Time-Varying Origin-Destination Flows Using Time-Series of Link Counts" @default.
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