A neural-network automotive speed controller is presented which works at low and at high speed-levels using throttle and brake control input. It can be used for autonomous intelligent cruise control including stop-and-go traffic situations. The network itself consists of a simple multilayer feedforward perceptron network. A special training method is used, where the neural network is trained on a detailed nonlinear dynamic vehicle model. Practical road tests with the Daimler Benz experimental vehicle Oscar (MB 300 TE station wagon) show good results for both high-and low-speed control.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Neural speed control for autonomous road vehicles


    Additional title:

    Geschwindigkeitsregelung mit einem neuronalen Netz für fahrerlose Kraftfahrzeuge


    Contributors:
    Fritz, H. (author)

    Published in:

    Publication date :

    1996


    Size :

    6 Seiten, 4 Bilder, 9 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




    Model-Based Neural Distance Control for Autonomous Road Vehicles

    Fritz, H. / IEEE; Industrial Electronics Society | British Library Conference Proceedings | 1996


    Neural control of autonomous vehicles

    Mecklenburg,K. / Hrycej,T. / Franke,U. et al. | Automotive engineering | 1992


    Autonomous Vehicles and Road Safety

    Michałowska, Maria / Ogłoziński, Mariusz | British Library Conference Proceedings | 2017


    Autonomous Vehicles and Road Safety

    Michałowska, Maria / Ogłoziński, Mariusz | Springer Verlag | 2017


    Vision-based Autonomous Road Vehicles

    Graefe, Volker / Kuhnert, Klaus-Dieter | Springer Verlag | 1992