MODEL OF UNMANNED WHEELED VEHICLE MOTION IN COMPLEX ROAD TRANSPORT CONDITIONS

This article presents the development of an algorithm for modeling the motion of unmanned vehicles in complex road conditions. The key stages of the model development, the system architecture, approaches to the implementation of modules for processing map data, constructing trajectories and managing obstacles are described. The methods of computer vision (road segmentation in HSV space, skeletonization according to Zhang- Suen) and mathematical modeling (cubic splines, BFS graph algorithms) are used. A system of adaptive behavior of a car when avoiding obstacles and driving on roads with slippery surfaces with state control (Normal, Avoiding Stone, On Ice) is implemented. The results include visualization of road networks, trajectories and obstacle processing, confirming the operability of the approach and the model as a whole.