Real-time traffic estimation using data expansion
This paper presents a method for estimating missing real-time traffic volumes on a road network using both historical and real-time traffic data. The method was developed to address urban transportation networks where a non-negligible subset of the network links do not have real-time link volumes, and where that data is needed to populate other real-time traffic analytics. Computation is split between an offline calibration and a real-time estimation phase. The offline phase determines link-to-link splitting probabilities for traffic flow propagation that are subsequently used in real-time estimation. The real-time procedure uses current traffic data and is efficient enough to scale to full city-wide deployments. Simulation results on a medium-sized test network demonstrate the accuracy of the method and its robustness to missing data and variability in the data that is available. For traffic demands with a coefficient of variation as high as 40%, and a real-time feed in which as much as 60% of links lack data, we find the percentage root mean square error of link volume estimates ranges from 3.9% to 18.6%. We observe that the use of real-time data can reduce this error by as much as 20%.
Year of publication: |
2011
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Authors: | Lederman, Roger ; Wynter, Laura |
Published in: |
Transportation Research Part B: Methodological. - Elsevier, ISSN 0191-2615. - Vol. 45.2011, 7, p. 1062-1079
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Publisher: |
Elsevier |
Keywords: | Traffic equilibrium Real-time traffic analytics Bilevel programming OD matrix estimation |
Saved in:
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