This study provides an analysis of the prospects and priorities for the development of autonomous vehicles in the electronic age and their potential impact on solving the problems associated with road traffic injuries. The work highlights the need for priority development of unmanned vehicles as an essential element of modern society. The presented modified learning-capable fuzzy control module demonstrates its promise in solving the car parking problem by using the mean value binding function and the backpropagation algorithm to correct the network weights. The module’s adaptability to different parking scenarios and its optimization based on supervised learning highlight its flexibility and accuracy in solving specific problems. Simulation of the module’s operation for various initial vehicle positions confirms its ability to function correctly, which makes it a promising tool for automating the parking process, improving traffic safety and ensuring optimal vehicle control.
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