A research work was carried out at the Centre for Computational Intelligence at NTU to develop novel technologies for the routing, navigation, and control of intelligent cars. One objective is to endow the cars with the ability to autonomously drive on various types of roads and realize manoeuvres such as reverse and parallel parking, three-point turns, etc. The approach is to design a self-training system that makes use of human expertise to automatically derive a working car control system. A new neuro-fuzzy architecture known as the GenSoYager Fuzzy Neural Network has been realized and integrated with a car-driving simulator for training and testing purposes. The GenSoYagerFNN has proven so far superior to other trained networks in detecting parking slots and accomplishing reverse parking manoeuvres. The approach described has also been validated using a microprocessor controlled model car.


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    Title :

    Self-trained automated parking system


    Additional title:

    Ein selbstlernendes, automatisches Parksystem


    Contributors:


    Publication date :

    2004


    Size :

    6 Seiten, 11 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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