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Evaluation of Bluetooth Detectors in Travel Time Estimation

Author

Listed:
  • Krit Jedwanna

    (Department of Civil Engineering, Faculty of Engineering, Rajamangala University of Technology Phra Nakhon, Bangkok 10300, Thailand)

  • Saroch Boonsiripant

    (Department of Civil Engineering, Faculty of Engineering, Kasetsart University, Bangkok 10900, Thailand)

Abstract

With the current popularity of mobile devices with Bluetooth technology, numerous studies have developed methods to analyze the data from such devices to estimate a variety of traffic information, such as travel time, link speed, and origin–destination estimations. However, few studies have comprehensively determined the impact of the penetration rate on the estimated travel time derived from Bluetooth detectors. The objectives of this paper were threefold: (1) to develop a data-processing method to estimate the travel time based on Bluetooth transactional data; (2) to determine the impact of vehicle speeds on Bluetooth detection performance; and (3) to analyze how the Bluetooth penetration rate affected deviations in the estimated travel time. A 28 km toll section in Bangkok, Thailand, was chosen for the study. A number of Bluetooth detectors and microwave radar devices were installed to collect traffic data in October 2020. Five data-processing steps were developed to estimate the travel time. Based on the results, the penetration rate during the day (50 to 90 percent) was higher than during the night (20 to 50 percent). In addition, we found that speed had adverse effects on the MAC address detection capability of the Bluetooth detectors; for speeds greater than 80 km/h, the number of MAC addresses detected decreased. The minimum Bluetooth penetration rate should be at least 1 percent (or 37 vehicles/h) during peak periods and at least 5 percent (or 49 vehicles/h) during the off-peak period.

Suggested Citation

  • Krit Jedwanna & Saroch Boonsiripant, 2022. "Evaluation of Bluetooth Detectors in Travel Time Estimation," Sustainability, MDPI, vol. 14(8), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4591-:d:791936
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    References listed on IDEAS

    as
    1. Mariem Fekih & Tom Bellemans & Zbigniew Smoreda & Patrick Bonnel & Angelo Furno & Stéphane Galland, 0. "A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)," Transportation, Springer, vol. 0, pages 1-32.
    2. Mariem Fekih & Tom Bellemans & Zbigniew Smoreda & Patrick Bonnel & Angelo Furno & Stéphane Galland, 2021. "A data-driven approach for origin–destination matrix construction from cellular network signalling data: a case study of Lyon region (France)," Transportation, Springer, vol. 48(4), pages 1671-1702, August.
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    Cited by:

    1. Krit Jedwanna & Chuthathip Athan & Saroch Boonsiripant, 2023. "Estimating Toll Road Travel Times Using Segment-Based Data Imputation," Sustainability, MDPI, vol. 15(17), pages 1-22, August.

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