A merging algorithm is proposed for smooth and efficient merging of vehicles at intersections of an automated transportation system. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Next, a decision algorithm is designed to determine the sequence of vehicles entering a converging section. The sequencing algorithm is based on fuzzy rules, considering the relative vehicle speed, distance, and priority of the lane. The membership function of the fuzzy system is determined by the learning method using a neural net, where a cost function considering energy consumption and ride comfort is used for training of the neural net. Finally, feasibility of the algorithm is investigated and validated through a simulation. The vehicle merging algorithm can be used for a personal rapid transit system as well as for an intelligent vehicle-highway system.


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    Title :

    Vehicle merging algorithm for automated transportation systems using fuzzy logics


    Contributors:


    Publication date :

    1997


    Size :

    12 Seiten, 10 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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