United States Department of Transportation
i
Estimation of Traffic Variables Using Point Processing Techniques
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1978-05-01
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[PDF-2.64 MB]
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NTL Classification:NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow;NTL-OPERATIONS AND TRAFFIC CONTROLS-OPERATIONS AND TRAFFIC CONTROLS;NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION;
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Abstract:An alternative approach to estimating aggregate traffic variables on freeways--spatial mean velocity and density--is presented. Vehicle arrival times at a given location on a roadway, typically a presence detector, are regarded as a point or counting Poisson process whose rate is a function of the state of the traffic at every instant of time. Moreover, the traffic state is modeled as a finite-state Markov chain. A sequential point process filter, optimum in the mean-squared error sense, is designed to estimate the state from observations of the vehicle arrival-time sequence. Different possibilities for incorporating potential additional information such as speed and headway are explored. Parameter values for the underlying Markov chain are obtained via a maximum likelihood estimator. Qualitative behavior of the proposed algorithms is studied with simulated traffic flow data from both macroscopic and microscopic models.
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