یک الگوریتم تکاملی چند هدفه برای تنظیم پایگاه های قوانین فازی برای تقاطع ناهماهنگ در رانندگی خودکار

In this paper, a MOEA is proposed to obtain a more compact and efficient FRBS. The proposal is based on the well-known Strength Pareto Evolutionary Algorithm 2 (SPEA2) technique, but uses different mechanisms for guiding the search towards the desired Pareto zone. The MOEA uses specific operators to deal with the problem, to inherit fitness values from one generation to the next, thus arranging that it is only necessary to execute one scenario per generation to obtain an FRBS that works fine in many situations. In addition, the most important rules are identified in each FRBS, with the aim of realizing balanced crossovers.