A novel fuzzy inferencing methodology for simulated car racing

This paper describes and further extends the fuzzy inferencing system which won the simulated car racing competition that was arranged as part of FuzzlEEE 2007 conference. The details of the winning non-stationary fuzzy controller and its results are presented. A novel approach to further improve the performance of the winning controller is described and formalised. We term the new fuzzy inferencing method a dasia context-dependent fuzzy inference system psila. The concept of a dasia context-dependent fuzzy set psila that is utilised by the fuzzy system is introduced. Finally, a comparison between context-dependent fuzzy inference system and various existing techniques are carried out on the simulated car racing application. The results show a better performance for context-dependent fuzzy inference systems in stochastic circumstances.