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Systematic Traffic Peak Period Identification Using Bottom-Up Segmentation and Wavelet Transformation

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Abstract

This paper develops a framework to test Bottom-up segmentation and Wavelet transform capability to distinguish on-peak from off-peak periods given the time series of the travel time. The proposed techniques are tested on the times series of travel time obtained from 15 working days of Bluetooth data on Brisbane’s busiest urban corridor. This study shows that the peak period can be systematically determined from either Bottom-up segmentation or WT on the time series of travel times. The Bottom-up segmentation technique estimated a mean peak period over the 15 working days of 106 min, compared to 99 min with Wavelet transformation. Further investigation is warranted should a recommendation be made as to which technique can more reliably estimate peak period.

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Acknowledgements

The authors would like to thank the Brisbane City Council for providing the Bluetooth data used for this research.

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Authors and Affiliations

  1. School of Civil Engineering & Built Environment, Queensland University of Technology (QUT), QLD, Brisbane, 4001, Australia

    Patrick Connors, Sara Respati & Ashish Bhaskar

  2. School of Civil Engineering, The University of Queensland, QLD, St. Lucia, 4072, Australia

    Anshuman Sharma

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  1. Patrick Connors
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  2. Sara Respati
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  3. Anshuman Sharma
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  4. Ashish Bhaskar
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Correspondence to Ashish Bhaskar.

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Connors, P., Respati, S., Sharma, A. et al. Systematic Traffic Peak Period Identification Using Bottom-Up Segmentation and Wavelet Transformation. Int. J. ITS Res. 18, 256–266 (2020). https://doi.org/10.1007/s13177-019-00196-z

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