his article is devoted to the study of the possibility of implementing computer vision technology in the framework of using a mobile device camera to determine the type of neoplasm on the skin. The study involved a dataset of 70,000 photographs of various geometric parameters, color, shades, and symmetry. A comparative analysis of the use of a neural network as part of its training by a database of images and computer vision technology is given. The results on the use of mobile device resources when using two technologies are presented.

Currently, various companies are developing unmanned vehicles in the cargo transportation industry. According to the results of the analysis of domestic and foreign sources, it has been revealed that algorithms based on graph theory are often used to construct the trajectory of motion, but only a few studies articulated vehicles and algorithms applicable to them, considering their features and the features of a dynamically changing environment. In this case, the maneuver of constructing a trajectory of movement in reverse for an articulated large-sized vehicle was studied, namely, the problems of using such algorithms on road trains to ensure the execution of the corresponding maneuver. A solution is proposed based on the method of finding a path from the final position using sensors and a signal processing unit installed on the vehicle.

This article is devoted to the study of the problem of performing a reverse maneuver for large-sized vehicles, namely, the path-finding algorithms used to plot the trajectory of movement depending on the type of terrain surrounding static or moving objects using sensors and means of displaying the information received from them. When analyzing the data, it was found that the most suitable option is a graphically modified algorithm A* derived from Dijkstra’s algorithm due to the speed of operation, optimization and the possibility of using realistic turns with smoothing, which is a critical factor when considering an articulated vehicle. Some problems when using the algorithm in real conditions are also considered.

Today, the creation of new vehicles is impossible without computer modeling. Modern vehicles have numerous electronic systems that increase its traffic safety, comfort, and route planning management. Reliable operation of all systems is achieved by using an accurate dynamic model of the vehicle to assess safety and the possibility of movement along specified trajectories. Creating an accurate dynamic vehicle model requires correct initial parameters. When modeling the curvilinear movement of motor vehicles, such parameters as the coefficients of resistance to lateral sliding of tires and the angles of sliding of axles, which are mainly determined on test benches in laboratory conditions, are important to obtain the adequacy of the object under study. However, quite often it is impossible to obtain reliable information from tire manufacturers or testing laboratories, which ultimately affects the adequacy of modeling the parameters of vehicle movement. A method is proposed for determining the design parameters of tires using primary information sensors, which are sensors of angular and linear velocities, linear accelerations, rotation angles of controlled wheels and an on-board information processing device. The advantages of this method are that it allows real-time measurement of the angles of the axles and the coefficients of resistance to the lateral withdrawal of the axles when the vehicle is moving at an arbitrary speed along a trajectory of variable curvature. This method can be used to create an accurate dynamic model in the study of the controllability and stability of the vehicle, as well as an integral part of the vehicle dynamics control system.