This paper describes a method for recognizing voice command based on a fuzzy logic system capable of perceiving fuzzy commands, i.e. commands containing fuzzy terms, for example, ‘close’, ‘closer’, ‘close to’, ‘closer than’, ‘further’ and ‘very far’. The developed approach has the ability to be trained for a specific user. The developed fuzzy logic system is used to recognize linguistically inaccurate commands in order to increase the expressiveness of the language for control of a moving robot.

This article analyzes the traffic situation, and also discusses the methods of collecting data and how they are applied on the road. In addition, the advantages and disadvantages of the methods studied in the work are given. There is a separate talk about the Floating Car Data (FCD) method, what is the essence of the method, its advantages and disadvantages. In turn, the paper presents a difference in the approaches to using data collection methods, namely the Floating Car Data method on the use of the Global Positioning System in cars and the method based on telephone devices with a Global Positioning System signal. The average annual daily traffic is considered as one of the most important traffic data. Describes a way to implement the Floating Car Data method, the advantage in using and improving this method and the prospects of the method in the future.