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Accurate estimation of travel times from single-loop detectors

Author

Listed:
  • Petty, Karl F.
  • Bickel, Peter
  • Ostland, Michael
  • Rice, John
  • Schoenberg, Frederic
  • Jiang, Jiming
  • Ritov, Ya'acov

Abstract

As advanced traveler information systems become increasingly prevalent the importance of accurately estimating link travel times grows. Unfortunately, the predominant source of highway traffic information comes from single-loop loop detectors which do not directly measure vehicle speed. The conventional method of estimating speed, and hence travel time, from the single-loop data is to make a common vehicle length assumption and to use a resulting identity relating density, flow, and speed. Hall and Persaud (Transportation Research Record 1232, 9-16, 1989) and Pushkar et al. (Transportation Research Record 1457, 149-157, 1994) show that these speed estimates are flawed. In this paper we present a methodology to estimate link travl times directly from the single-loop loop detector flow and occupancy data without heavy reliance on the flawed speed calculations. Our methods arise naturally from an intuitive stochastic model of traffic flow. We demonstrate by example on data collected on I-880 data (Skabardonis et al. Technical Report UCB-ITS-PRR-95-S, Institute of Transportation Studies, University of California, 1994) that when the loop detector data has a fine resolution (about one second), the single-loop based estimates of travel time can accurately track the true travel time through many degrees of congestion. Probe vehicle data and double-loop based travel time estimates corroborate the accuracy of our methods in our examples.

Suggested Citation

  • Petty, Karl F. & Bickel, Peter & Ostland, Michael & Rice, John & Schoenberg, Frederic & Jiang, Jiming & Ritov, Ya'acov, 1998. "Accurate estimation of travel times from single-loop detectors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(1), pages 1-17, January.
  • Handle: RePEc:eee:transa:v:32:y:1998:i:1:p:1-17
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    References listed on IDEAS

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    1. Dailey, D. J., 1993. "Travel-time estimation using cross-correlation techniques," Transportation Research Part B: Methodological, Elsevier, vol. 27(2), pages 97-107, April.
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    Cited by:

    1. Zhang, Xiaoyan & Rice, John & Bickel, Peter, 1999. "Empirical Comparison of Travel Time Estimation Methods," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6kt6082p, Institute of Transportation Studies, UC Berkeley.
    2. Kai Liu & Meng-Ying Cui & Peng Cao & Jiang-Bo Wang, 2016. "Iterative Bayesian Estimation of Travel Times on Urban Arterials: Fusing Loop Detector and Probe Vehicle Data," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-12, June.
    3. Coifman, Benjamin A. & Mallika, Ramachandran, 2007. "Distributed surveillance on freeways emphasizing incident detection and verification," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(8), pages 750-767, October.
    4. Sun, Lu & Yang, Jun & Mahmassani, Hani, 2008. "Travel time estimation based on piecewise truncated quadratic speed trajectory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(1), pages 173-186, January.
    5. Guo, Jianhua & Kong, Ye & Li, Zongzhi & Huang, Wei & Cao, Jinde & Wei, Yun, 2019. "A model and genetic algorithm for area-wide intersection signal optimization under user equilibrium traffic," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 92-104.
    6. Agafonov, Evgeny & Bargiela, Andrzej & Burke, Edmund & Peytchev, Evtim, 2009. "Mathematical justification of a heuristic for statistical correlation of real-life time series," European Journal of Operational Research, Elsevier, vol. 198(1), pages 275-286, October.
    7. Zhang, Xiaoyan & Rice, John, 1999. "Visualizing Loop Detector Data," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt37j8b3ff, Institute of Transportation Studies, UC Berkeley.

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