Precise Vehicle Cruise Control System Based on On-Line Fuzzy Control Learning

  • Enrique Onieva
  • Jorge Godoy
  • Jorge Villagrá
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 297)


Usually, vehicle applications require the use of artificial intelligent techniques to implement control methods, due to noise provided by sensors or the impossibility of full knowledge about dynamics of the vehicle (engine state, wheel pressure or occupiers weight).

This work presents a method to on-line evolve a fuzzy controller for commanding vehicles’ pedals at low speeds; in this scenario, the slightest alteration in the vehicle or road conditions can vary controller’s behavior in a non predictable way. The proposal adapts singletons positions in real time, and trapezoids used to codify the input variables are modified according with historical data.

Experimentation in both simulated and real vehicles are provided to show how fast and precise the method is, even compared with a human driver or using different vehicles.


Intelligent Transportation Systems Autonomous Vehicles Fuzzy Control On-Line Learning Speed Control 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Enrique Onieva
    • 1
  • Jorge Godoy
    • 1
  • Jorge Villagrá
    • 1
  1. 1.AUTOPIA programCenter for Automation and Robotics (CAR)MadridSpain

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