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Updating and transferring Random Effect models: The case of operating speed percentile estimation

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  • Tremblay, Jean-Michel
  • Cirillo, Cinzia
  • Bassani, Marco

Abstract

Random Effect (RE) models are used for analyzing data that are non-independent or when data are characterized by a hierarchical structure. In traffic and highway engineering, RE models have been successfully employed to estimate free-flow speed distributions from data containing observations that are naturally nested according to different levels (i.e. direction, sections, roads). Empirical studies conducted on both urban arterials and rural two-lane highways have shown that RE models, by properly accounting for the survey design, are superior to traditional Fixed Effect (FE) models. However, RE models are non-transferable because of the unknown RE value for roads or road sections belonging to a different network or road of the same network that were not originally used to develop the model.

Suggested Citation

  • Tremblay, Jean-Michel & Cirillo, Cinzia & Bassani, Marco, 2021. "Updating and transferring Random Effect models: The case of operating speed percentile estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 286-304.
    • Handle: RePEc:eee:transa:v:148:y:2021:i:c:p:286-304
    DOI: 10.1016/j.tra.2021.01.008
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    References listed on IDEAS

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    1. Shankar, Venkataraman & Mannering, Fred, 1998. "Modeling the endogeneity of lane-mean speeds and lane-speed deviations: a structural equations approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(5), pages 311-322, September.
    2. Park, Young-Jin & Saccomanno, Frank F., 2006. "Evaluating speed consistency between successive elements of a two-lane rural highway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(5), pages 375-385, June.
    3. Himes, Scott C. & Donnell, Eric T. & Porter, Richard J., 2013. "Posted speed limit: To include or not to include in operating speed models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 52(C), pages 23-33.
    4. Cheng, Wen & Gill, Gurdiljot Singh & Sakrani, Taha & Ralls, Dennis & Jia, Xudong, 2018. "Modeling the endogeneity of lane-mean speeds and lane-speed deviations using a Bayesian structural equations approach with spatial correlation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 220-231.
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