This study focuses on the development of entry capacity models for roundabouts by using Genetic Algorithm (GA), Multi-variate Adaptive Regression spline (MARS) and Random Forest Regression (RFR) technique under heterogeneous traffic conditions. Required data were collected from 27 selected roundabouts of India by using high-definition video (HD) camera. Influence area for gap acceptance (INAGA) method is employed to find out the critical gap and follow up time. It is found from sensitivity analysis that variable like Entry width (Ew) contributes the most while the follow-up time (Tf) variable has less contribution in the proposed model.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Comparison of Artificial Intelligence Based Roundabout Entry Capacity Models


    Additional title:

    Int. J. ITS Res.


    Contributors:


    Publication date :

    2020-05-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Models of Roundabout Lane Capacity

    Yap, Yok Hoe / M. Gibson, Helen / J. Waterson, Ben | ASCE | 2015


    Models of Roundabout Lane Capacity

    M. Gibson, Helen | Online Contents | 2015


    Models of Roundabout Lane Capacity

    Yap, Yok Hoe / Gibson, Helen M. / Waterson, Ben J. | British Library Online Contents | 2015


    Models of Roundabout Lane Capacity

    Yok Hoe Yap | Online Contents | 2015


    The effect of Pelican crossings on roundabout entry capacity

    Hunt, J. / Jabbar, J. A. | British Library Online Contents | 1995