**1. Introduction**

The increasing number of cars on the roads and the related rising accident rate have brought the concept of road safety to the forefront. The primary safety objective is to protect the health and lives of passengers and minimize the consequences of an accident. In order to achieve this goal, various security features are being applied in vehicles. They can be divided into two groups:


One of the most important active safety features includes the braking system of the vehicle, which is considered to be the most important system in the vehicle, as safe stopping or slowing down of the vehicle is one of the ways of accident prevention. Since its introduction, the braking system has undergone numerous improvements, one of them being the application of the ABS. The anti-lock braking system (ABS), which has been developed and implemented from the late 1970s, prevents the wheels from locking during braking of the vehicle, and thereby, allows the driver to maintain control over steering [1]. Although this vehicle safety system has been used for decades, it is constantly being improved using either conventional or intelligent control methods [2].

Several studies have been published that focus on optimizing the vehicle's braking system using various strategies, both for vehicles with internal combustion engines and electric vehicles. For electric vehicles, the most commonly applied method is regenerative braking control. The authors of paper [3] present regenerative braking control strategy intended to improve braking performance while maximizing braking energy recovery. Application of fuzzy logic rules enables the optimization

of regenerative braking in order to achieve better braking performance. This issue is addressed in paper [4], where the rules of fuzzy logic were used to optimize the slip parameter of a sliding mode controller and to thereby achieve a shortening of the vehicle's braking distance and an increase in the energy efficiency of regenerative braking.

As shown in several studies [5–12], the use of fuzzy logic rules in different ways of controlling the ABS has improved the braking performance of the vehicle in simulations on different road surfaces. Another possible approach to optimizing the braking performance of a vehicle is to use fuzzy logic to optimize the parameters of conventional methods of controlling ABSs. In paper [13], the authors present the achievement of optimal slip rate parameters using fuzzy logic. The presented simulation results prove the improved maneuverability and stability of the vehicle. In paper [14], the authors deal with the optimization of braking properties and shortening of vehicle braking distance using a PID-fuzzy controller with parameter adaptation.

Using fuzzy logic is not the only way to improve the vehicle ABS. The application of artificial neural networks to optimize the rules of the fuzzy controller [15], or as observers, or the implementation of neuro-controllers as such, seem to be suitable alternatives. Comparison of various strategies [16] and selection of the most appropriate method or combination of methods can result in optimization of the ABS performance, and thus, in the improvement of vehicle safety.

Mathematical modeling and simulation are powerful tools in the initial stages of research and in the verification of hypotheses, which is sometimes not possible to implement in practice, be it for safety, for physical or other reasons [17,18]. Therefore, in our design, we used a combination of two simulation tools, MATLAB/Simulink and CarSim, which allowed detailed setting of the vehicle parameters and simulation in different environments. Suitable setting and interlinking with other software, such as MATLAB/Simulink, provides the opportunity of testing vehicle performance in real time. Using the CarSim simulation software enables the verification of vehicle performance in situations where failure could have destructive consequences or even result in loss of life.
