Genetic fuzzy-based steering wheel controller using a mass-produced car

  • E. Onieva
  • , V. Milanés
  • , J. Pérez
  • , T. de Pedro

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle to reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

Original languageEnglish
Pages (from-to)3477-3494
Number of pages18
JournalInternational Journal of Innovative Computing, Information and Control
Volume8
Issue number5 B
Publication statusPublished - May 2012
Externally publishedYes

Keywords

  • Autonomous vehicles
  • Fuzzy control
  • Fuzzy logic
  • Genetic algorithms
  • Intelligent transportation systems (ITS)
  • Intelligent vehicles
  • Lateral control

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