The Bus Rapid Transit System (BRT) is a public transport system that uses exclusive lanes for its circulation. However, this does not prevent interaction with other vehicles at intersections, which use fixed-cycle traffic lights whose phasing configuration does not consider changes in traffic volumes. This limits the continuous flow of BRT, making its timing less reliable or predictable as in a subway system. The fixed-cycle traffic light often generates an increase in queue lengths in the BRT exclusive lanes. Often, this occurs while other approaches to the intersection are in the green phase, by with little or no vehicular flow. This article performs an operational analysis of adaptive traffic light with the help of detection sensors, which predict the arrival time of the BRT at the intersection to grant crossing priority. As a case study, the intersection of Avenida Habich and Tupac Amaru in Lima, Peru was evaluated. This area was chosen because one of the busiest BRT stations of the northern section is found nearby. By a microsimulation model in VISSIM 9.0, BRT control delays at the intersection were evaluated. In addition, the VisVAP programme was used to simulate the adaptive traffic light control and evaluate the logical sequence with detection sensors. By means of this, crossing priority was given to BRT. For the validation of the proposal, two scenarios were analysed. The first one corresponds to the current situation of the intersection. The second is the improved situation using adaptive traffic signalisation. The results indicate a reduction in traffic light delay between 31 and 42%. While travel times improved by 23-33%.


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    Titel :

    Reduction of BRT delays at highway intersections through adaptive traffic lights control


    Beteiligte:
    Brena, Andy (Autor:in) / Vasquez, Junior (Autor:in) / Silvera, Manuel (Autor:in) / Campos, Fernando (Autor:in)


    Erscheinungsdatum :

    05.10.2022


    Format / Umfang :

    2123430 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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