STUDY OF METHODS OF AUTOMATIC ADJUSTMENT OF VEHICLE MOVEMENT TRAJECTORY

Abstract

The article discusses the methods of automatic adjustment of the trajectory of vehicles, which is one of the key components of modern intelligent transport systems. The topicality of the topic is due to the growing requirements for the safety, efficiency and energy efficiency of the movement of vehicles in difficult traffic conditions. The paper developed mathematical models that describe the movement of a vehicle on a plane using classical dynamics equations, where the position is given as a function of time, and the direction of movement is described by an angular function. The research is based on the problem of trajectory optimization, which consists in the minimization of the objective function, which takes into account energy consumption, control effort and other parameters affecting the efficiency of movement. To solve this problem, the Lagrange method is applied, which allows obtaining a system of Euler–Lagrange equations, thanks to which the optimal parameters of the vehicle movement are determined in real time.The article analyzes the influence of key parameters, such as speed, direction angle and other variables, on the quality and safety of traffic. The results of mathematical modeling are confirmed by the construction of graphic dependencies, in particular histograms and 3D surface graphs, which demonstrate the relationship between model parameters, in particular the influence of speed and direction angle on the specific consumption of electricity and the value of the objective function. The obtained results indicate the possibility of applying optimization algorithms for the correction of the movement trajectory in order to minimize energy costs and ensure maximum stability of vehicle control.The practical significance of the research lies in the development of a methodology that can be integrated into modern systems of automatic control of vehicles. This will allow them to adapt their movement to changing traffic conditions, reducing the risk of accidents and improving operational performance. Also, the results of the research will help reduce fuel costs and minimize the impact of vehicles on the environment.