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ETS FUZZY DRIVER MODEL FOR SIMULTANEOUS LONGITUDINAL AND LATERAL VEHICLE CONTROL
S. AKCA,S. ERTUGRUL 한국자동차공학회 2014 International journal of automotive technology Vol.15 No.5
In this paper, evolving Takagi-Sugeno (eTS) fuzzy driver model is proposed for simultaneous lateral andlongitudinal control of a vehicle in a test track closed to traffic. The developed eTS fuzzy driver model can capture humanoperator’s driving expertise for generating desired steering angle, throttle angle and brake pedal command values byprocessing only information which can be supplied by the vehicle’s on-board control systems in real time. Apart from otherfuzzy rule based (FRB) models requiring human expert knowledge or off-line clustering, the developed eTS driver model canadapt itself automatically, even ‘from scratch’, by an on-line learning process using eTS algorithm while human driver issupervising the vehicle. Proposed eTS fuzzy driver model’s on-line human driver identification capability and autonomousvehicle driving performance were evaluated on real road profiles created by digitizing two different intercity express ways ofTurkey in IPG© CarMaker® software. The training and validation simulation results demonstrated that eTS fuzzy drivermodel can be used in product development phase to speed up different tests via realistic simulations. Furthermore eTS fuzzydriver model has an application potential in the field of autonomous driving.