A Novel Loglinear Model for Freeway Travel Time Prediction

  title={A Novel Loglinear Model for Freeway Travel Time Prediction},
  author={Lili Huang and Matthew J. Barth},
  journal={2008 11th International IEEE Conference on Intelligent Transportation Systems},
As traffic congestion continues to grow worldwide, freeway travel time prediction is becoming increasingly important. During the past decade, numerous research projects have been carried out in travel time estimation. A variety of algorithms and techniques have been developed, primarily for predicting short-term travel time (less than 30 minutes ahead). However, these travel time prediction methods cannot be applied for long-term travel planning. In this paper, a loglinear travel time… CONTINUE READING


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Publications referenced by this paper.
Showing 1-10 of 17 references

Urban Travel Time Estimation by Incorporating System Recognition into K-Nearest-Neighbor Method,

  • Zhang Ke, Liu Hao
  • 86th TRB Annual Meeting,
  • 2007
1 Excerpt

Simple and Effective Method for Predicting Travel Times on Freeways,

  • John Rice, Erik Van Zwet, ”A
  • IEEE Trans. On Intelligent Transportation Systems…
  • 2004
2 Excerpts

The PeMS Algorithms for Accurate, Real-time Estimates of g-factors and Speeds from Single-loop Detectors,

  • Zhanfang Jia, Chao Chen, Ben Coifman, Pravin Varaiya
  • IEEE Intelligent Transportation Systems…
  • 2001
1 Excerpt

Combining KOHO- NEN maps with ARIMA time series models to forecast traffic flow,

  • M. Van der Voort, M. Dougherty, S. Watson
  • Transport. Res. C,
  • 1996
1 Excerpt

Traffic Flow Modeling and Control Using Artificial Neural Networks,

  • F. Ho, P. Ioannou
  • IEEE Control Syst. Mag.,
  • 1996
1 Excerpt

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