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Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data

Author

Listed:
  • Xiyang Zhou
  • Zhaosheng Yang
  • Wei Zhang
  • Xiujuan Tian
  • Qichun Bing

Abstract

To improve the accuracy and robustness of urban link travel time estimation with limited resources, this research developed a methodology to estimate the urban link travel time using low frequency GPS probe vehicle data. First, focusing on the case without reporting points for the GPS probe vehicle on the target link in the current estimation time window, a virtual report point creation model based on the K‐Nearest Neighbour Rule was proposed. Then an improved back propagation neural network model was used to estimate the link travel time. The proposed method was applied to a case study based on an arterial road in Changchun, China: comparisons with the traditional artificial neural network method and the spatiotemporal moving average method revealed that the proposed method offered a higher estimation accuracy and better robustness.

Suggested Citation

  • Xiyang Zhou & Zhaosheng Yang & Wei Zhang & Xiujuan Tian & Qichun Bing, 2016. "Urban Link Travel Time Estimation Based on Low Frequency Probe Vehicle Data," Discrete Dynamics in Nature and Society, John Wiley & Sons, vol. 2016(1).
    • Handle: RePEc:wly:jnddns:v:2016:y:2016:i:1:n:7348705
    DOI: 10.1155/2016/7348705
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    References listed on IDEAS

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    1. Jenelius, Erik & Koutsopoulos, Haris N., 2013. "Travel time estimation for urban road networks using low frequency probe vehicle data," Transportation Research Part B: Methodological, Elsevier, vol. 53(C), pages 64-81.
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