Travel times are an important measure for quantifying travel quality across different modes. However, collecting travel time data is a non-trivial and expensive task. Current practice involves using separate data collection methods for each mode. This paper presents a cost-effective and simple way to collect travel time data across multiple modes using media access control (MAC) matching detected by the mobile unit for sensing traffic (MUST) sensor. This technology detects personal electronic devices to determine people’s movement instead of traditional methods which detect singular modes, such as induction loops. This paper proposes a new travel-time calculation method for pedestrian, bicycle, and automobile travelers. A linear model distributes the travel time between different modes by weighting the travel time based on highest, lowest, and most likely speeds. Comparing estimated results for the modal distribution, an accuracy of approximately 83% is achieved, which is acceptable for most applications in transportation engineering.


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    Titel :

    Calculating Travel Time across Different Travel Modes Using Bluetooth and WiFi Sensing Data


    Beteiligte:
    Ricord, Samuel (Autor:in) / Ash, John E. (Autor:in) / Wang, Yinhai (Autor:in)

    Kongress:

    International Conference on Transportation and Development 2020 ; 2020 ; Seattle, Washington (Conference Cancelled)



    Erscheinungsdatum :

    31.08.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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