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Traffic flow reconstruction using mobile sensors and loop detector data

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  • Herrera, Juan C
  • Bayen, Alexandre M

Abstract

In order to develop efficient control strategies to improve traffic conditions on freeways, it is necessary to know the state of the freeway at any point in time and space. Using data collected from stationary detectors –such as loop detector stations– the density field can be currently reconstructed to a certain accuracy. Unfortunately, deploying this type of infrastructure is expensive, and its reliability varies. This article proposes and investigates new algorithms that make use of data provided by mobile sensors, in addition to that collected by stationary detectors, to reconstruct traffic flow. Two approaches are proposed and evaluated with traffic data. The first approach is based on data assimilation methods (so-called nudging method) and the second is based on Kalman filtering. These approaches are evaluated using traffic data. Results show that the proposed algorithms appropriately incorporate the new data, improving significantly the accuracy of the estimates that consider loop detector data only.

Suggested Citation

  • Herrera, Juan C & Bayen, Alexandre M, 2007. "Traffic flow reconstruction using mobile sensors and loop detector data," University of California Transportation Center, Working Papers qt6v40f0bs, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt6v40f0bs
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    1. Ygnace, Jean-Luc & Drane, Chris & Yim, Y. B. & de Lacvivier, Renaud, 2000. "Travel Time Estimation on the San Francisco Bay Area Network Using Cellular Phones as Probes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8xn8m01v, Institute of Transportation Studies, UC Berkeley.
    2. Sanwal, Kumud K. & Walrand, Jean, 1995. "Vehicles As Probes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3gh0890x, Institute of Transportation Studies, UC Berkeley.
    3. Westerman, Marcel & Litjens, Remco & Linnartz, Jean-paul, 1996. "Integration Of Probe Vehicle And Induction Loop Data: Estimation Of Travel Times And Automatic Incident Detection," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt8mh629c3, Institute of Transportation Studies, UC Berkeley.
    4. Denos C. Gazis & Charles H. Knapp, 1971. "On-Line Estimation of Traffic Densities from Time-Series of Flow and Speed Data," Transportation Science, INFORMS, vol. 5(3), pages 283-301, August.
    5. Daganzo, Carlos F., 1994. "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transportation Research Part B: Methodological, Elsevier, vol. 28(4), pages 269-287, August.
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    Cited by:

    1. Xiaomeng Wang & Ling Peng & Tianhe Chi & Mengzhu Li & Xiaojing Yao & Jing Shao, 2015. "A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-20, December.
    2. Shang, Wen-Long & Zhang, Mengxiao & Wu, Guoyuan & Yang, Lan & Fang, Shan & Ochieng, Washington, 2023. "Estimation of traffic energy consumption based on macro-micro modelling with sparse data from Connected and Automated Vehicles," Applied Energy, Elsevier, vol. 351(C).

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