The authors are with the Industrial Computer Science Department, Instituto de Automática Industrial (CSIC), 28500 Madrid, Spain ; The goal that a car be driven autonomously is far in the future and probably unreachable, but as a first step in that direction, adaptive cruise control (ACC) and Stop&Go maneuver systems are being developed. These kind of controllers adapt the speed of a car to that of the preceding one (ACC) and get the car to stop if the lead car stops. This paper presents one such system and related experiments performed on a real road with real cars. The driving system gets its input via an RTK DGPS device and communicates its positions to one another via a wireless local area network link. It outputs signals controlling the pressure on the throttle and brake pedals. The control system is based on fuzzy logic, which is considered best to deal with processes as complex as driving. Two mass produced Citroën Berlingo electric vans have been instrumented, providing them with computer controlled actuators over the brake and the throttle to achieve human-like driving. The results of the experiments show that the behavior of the vehicles is very close to human and that they adapt to driving incidences, increasing the safety of the driving and permitting cooperation with manually driven cars. ; This work was supported in part by the Spanish Ministry of Education under Grant ISAAC CICYT DPI2002-04064-C05-02, by the Spanish Ministry of Public Works under Grant COPOS BOE 280 22/11/2002, and by the Res. 22778, Citroën España S.A. under Contract “Adquirir nuevos conocimientos sobre la introducción de las tecnologías de la información en el mundo del automóvil y para difundirlos en los ámbitos científicos, empresariales y comerciales (AUTOPIA),” and by Cybecars-2 Project UE-STREP 28062, 6th Framework Programme, 2006. ; Peer reviewed


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    Title :

    Cooperative Throttle and Brake Fuzzy Control for ACC+Stop&Go Maneuvers


    Contributors:

    Publication date :

    2007-07-01


    Remarks:

    doi:10.1109/TVT.2007.897632



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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