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Hybrid Traffic Data Collection Roadmap: Objectives and Methods

Author

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  • Bayen, Alexandre
  • Sharafsaleh, Mohammad Ashkan
  • Patire, Anthony D.

Abstract

Traffic data is used to estimate current traffic conditions so that travelers and agencies can make better decisions about how to use and manage the transportation network. This research explores the fusion of probe data (vehicle speed and direction) with loop data (density, speed, and count) in the context of producing overall network speed and travel time estimates. Speed and travel time estimates are useful in many circumstances, but current system control strategies (ramp metering, for example) require density data. While it is difficult to significantly increase the quantity of loop detectors on state highways, the penetration rate of probe data is continually increasing. Multiple data sources with various characteristics were fused by running probe and loop data through the Mobile Millennium highway model, generating velocity maps and travel times. The performance of data sources both individually and when fused was evaluated. It was found that the highest quality estimates are achieved by combining probe data and loop detector data.

Suggested Citation

  • Bayen, Alexandre & Sharafsaleh, Mohammad Ashkan & Patire, Anthony D., 2013. "Hybrid Traffic Data Collection Roadmap: Objectives and Methods," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1t95h8s2, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt1t95h8s2
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    References listed on IDEAS

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    1. Daganzo, Carlos F., 1995. "The cell transmission model, part II: Network traffic," Transportation Research Part B: Methodological, Elsevier, vol. 29(2), pages 79-93, April.
    2. 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. Khan, Sakib Mahmud PhD & Fournier, Nicholas PhD & Mauch, Michael PhD & Patire, Anthony D PhD & Skabardonis, Alex PhD, 2020. "Hybrid Data Implementation: Final Report for Task Number 3643," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt32b6s0fk, Institute of Transportation Studies, UC Berkeley.
    2. Dion, Francois PhD & Yang, Mingyuan & Patire, Anthony PhD, 2023. "New Data and Methods for Estimating Regional Truck Movements," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt4cw749bp, Institute of Transportation Studies, UC Berkeley.
    3. Mauch, Michael & Skabardonis, Alex, 2016. "California’s Freeway Service Patrol Program: FSP Beat Evaluation Model; Methodology and Parameter Estimation (FY 2014-15)," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt90r29164, Institute of Transportation Studies, UC Berkeley.

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    More about this item

    Keywords

    Engineering; Automatic data collection; Algorithms; Cost effectiveness; Data fusion; Data quality; Detection; Traffic speed; Traffic density; Traffic volume;
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