Implementation of cognitive perception functions in fuzzy situational control model

Abstract

In autonomous transport systems, it is useful to be able to continue interrupted traffic after removing the obstacle that caused deviations from the route. This article describes a control model in which cognitive functions, such as context and attention are embedded. The fuzzy situational control model of an autonomously moving machine along a route with obstacles is expanded by tracking context and switching attention mechanisms. Additionally, it describes a knowledge representation about the route, the surrounding space and how to avoid collisions with obstacles.