This study examines the variations in travel time and travel time reliability on an urban arterial route in Chennai, India, by using Wi-Fi detections. The travel time data was collected over a seven-week period using three Wi-Fi sensors. The study used Generalized Extreme Value (GEV) distribution to analyze travel time variations and found it to be the best fit for the data. It was found that the time of day (TOD), day of the week (DOW), and direction of travel (DOT) have a significant impact on travel time variations. The consistency of these variations is better measured through travel time reliability (TTR) measures. Disaggregate level comparisons of selected TTR measures were carried out to analyze TTR by TOD, DOW and DOT. For a given TOD, weekends are more reliable compared to weekdays. Similarly off-peak hours for a given a DOW were reliable than peak and off-peak hours. Additionally, TTR measures also revealed significant distinctions between segments, which can be attributed to varying traffic flow conditions.


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    Titel :

    Estimation of Travel Time Reliability Using Wi-Fi Detections on an Urban Arterial Road


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Rao, K. Ramachandra (Herausgeber:in) / Seyfried , Armin  (Herausgeber:in) / Schadschneider, Andreas (Herausgeber:in) / Singh, Vikram (Autor:in) / Gore, Ninad (Autor:in) / Arkatkar, Shriniwas (Autor:in)

    Kongress:

    International Conference on Traffic and Granular Flow ; 2022 ; Delhi, India October 08, 2022 - October 10, 2022


    Erschienen in:

    Traffic and Granular Flow '22 ; Kapitel : 55 ; 447-454


    Erscheinungsdatum :

    2024-05-26


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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