Intelligent Vehicle Path Planning And Tracking In Ice And Snow Environment Considering The Motion Characteristics Of Obstacles

With the rapid development of the automobile industry,vehicles have become the daily means of transportation for the public,which has facilitated people’s life and improved their comfort while traveling.But at the same time,the increase of vehicle ownership makes traffic accidents occur frequently.In order to ensure the safety of people’s travel,intelligent driving technology has become a hot spot for many scholars to study.Path planning and path tracking are important components of intelligent driving,which are of great significance to improve the driving efficiency of intelligent vehicles and guarantee the safe and stable driving of vehicles.Although the research on path planning and path tracking of intelligent vehicles has achieved certain results,the coverage of working conditions for path planning and path tracking in complex environments is limited.In addition,China is located in the northern hemisphere,the winter snowfall time is long and the snowfall range is wide,inevitably need to consider the problem of intelligent vehicle driving safety in the snow and ice environment.Due to the complex roads and many types of obstacles in the snow and ice environment,how to efficiently plan a feasible path for intelligent vehicles to drive safely in the snow and ice environment under the consideration of the movement characteristics of obstacles is a difficult research point.In addition,due to the low adhesion coefficient of the road surface in the snow and ice environment,the tire force of the vehicle is easy to saturate when the intelligent vehicle is tracking and driving,and the phenomenon of side-slip will occur during the driving process,which affects the path tracking effect of the intelligent vehicle,and how to guarantee the intelligent vehicle to complete the tracking and driving safely and stably in the snow and ice environment is another difficult point of the research.In view of the above path planning and path tracking technical difficulties,this paper develops a study on intelligent vehicle path planning and tracking in snow and ice environment considering obstacle motion characteristics.Firstly,a path planning method combining artificial potential field and model predictive control is proposed for the complex roads in snow and ice environment with ice static obstacles,conventional static obstacles and dynamic obstacle vehicles.The artificial potential field method is used to establish the driving environment model in the ice and snow environment,and dynamic obstacle vehicles,static obstacles,desired target points and lane lines are considered as the main factors affecting the intelligent vehicle driving.For static obstacles,according to the road conditions of snow and ice environment,they are divided into crossable obstacles such as snow,icy road surface,snow puddles and uncrossable obstacles such as road blocks and large stones.A kinetic prediction model with longitudinal acceleration and front wheel turning angle as control quantities is established,and the path planning optimization problem is mathematically described according to the established prediction model and the driving environment model to realize intelligent vehicle path planning considering dynamic and static obstacles.The simulation results show that the intelligent vehicle can plan a smoother path without colliding with dynamic obstacle vehicles,without crossing conventional static obstacles,and avoiding crossing icy static obstacles as much as possible when driving on snow and ice,and the control volume of the vehicle changes smoothly.Secondly,for the problem that there is competition between this vehicle driving and the surrounding vehicle driving when the target of this vehicle and the surrounding vehicle are in conflict in snow and ice environment,this paper describes the competition between this vehicle driving and the surrounding vehicle driving as a game to solve this problem.A path planning method that effectively integrates model predictive control and Nash equilibrium is proposed.The path planning model of this vehicle and the driver model of the surrounding vehicle are established separately and integrated into a V2 V model,which is used as the vehicle game model for prediction.Based on the established prediction model and the driving environment model,and combined with the game planning objectives that both this vehicle and the surrounding vehicle can affect each other’s vehicle,the path planning optimization problem of this vehicle and the surrounding vehicle game is mathematically described.The game performed when the two vehicles are driving is described as the case of a nonlinear Nash equilibrium game,and in order to solve the game planning optimization problem,a Nash equilibrium point solving method based on multi-start optimization is proposed.The simulation results show that when driving in the ice and snow environment,this vehicle and the surrounding vehicle can plan a smooth path efficiently without colliding with the surrounding vehicle and obstacles after the game planning,and drive as soon as possible according to its own desired goal with a smoothly changing state amount.Finally,the intelligent vehicle path tracking method based on feedback linearization with linear quadratic regulator is proposed for the problem of tire force saturation of intelligent vehicles driving on icy and snowy roads with low road adhesion coefficients in icy and snowy environments.Considering the characteristics that the vehicle tire force is easy to saturate and then present nonlinearity,a nonlinear tire model is used to establish a vehicle dynamics model,and the affine nonlinear form of the vehicle system model is constructed by combining the established vehicle kinematic model.Since the nonlinear characteristics of the vehicle will affect the path tracking effect,this paper adopts the feedback linearization method to linearize the nonlinear model.Based on the linear model obtained from the processing,a linear quadratic regulator method is used to design the path tracking controller to realize the path tracking of intelligent vehicles in snow and ice environment.Simulation experiments are conducted under the working conditions of low-speed ice and snow road and high-speed ice and snow road,respectively.The simulation results show that the path tracking method using the combination of feedback linearization and linear quadratic regulator can track the upper reference path under different working conditions,and the error is small,and the intelligent vehicle can track better under the ice and snow environment.Therefore,the intelligent vehicle can drive safely and stably in the snow and ice environment.