Neural networks’ (NNs) capability of mapping the nonlinear functions of variables describing the behaviour of objects and the simplicity of designing their configuration favours their applications in transport. This paper presents representative examples in the scope of prediction of road traffic parameters, road traffic control, measurement of road traffic parameters, driver behaviour and autonomous vehicles, and transport policy and economics. The features of the solutions are examined. The review shows that feedforward multilayer neural networks are the most often utilised configurations in transportation research. No systematic approach is reported on the optimisation of the NN configurations to achieve a set level of performance in solving modelling tasks


    Access

    Download


    Export, share and cite



    Title :

    NEURAL NETWORKS IN TRANSPORTATION RESEARCH – RECENT APPLICATIONS


    Contributors:


    Publication date :

    2016



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Recent research in maritime transportation

    Engineering Index Backfile | 1958



    Recent Advances in Fuel Cells for Transportation Applications

    Dircks, Ken | SAE Technical Papers | 1999


    Recent advances in fuel cells for transportation applications

    Dircks,K. / Ballard Automotive,US | Automotive engineering | 1999