Research On Active Steering Avoidance Control Based On Model Forecast And Path Planning

The vehicle active collision avoidance control is a hotspot research of automobile safety.When there is an obstacle in front of the travel path,the vehicle can avoid collision accident by means of autonomous braking or steering,which can remarkably improve the safety of the vehicle.Aiming at the problem of lateral active collision avoidance of intelligent vehicle,this paper establishes the 14-DOF vehicle model and the two-degree-of-freedom nonlinear prediction model using Newtonian analysis mechanics method.And then This paper proposes a hierarchical steering collision avoidance control strategy based on the model predictive control principle,and studies the collision avoidance problem of autonomous path planning and path tracking.The hierarchical collision avoidance control perform better when solving the problem of multiple collision avoidance tasks.The upper controller can keep routing path according to the obstacle,while the lower controller realizes the effective path tracking of collision avoidance problem..The main contents of the paper are as follows:Vehicle system modeling,,including the alleged vehicle model and forecasting model.In order to solve the contradiction between the prediction model accuracy and the complexity of the control algorithm in the model predictive control,the vehicle model is established based on the Newtonian mechanics method,and to meet the vehicle motion prediction accuracy requirements,the vehicle model is decoupled and simplified as two degrees of freedom Nonlinear prediction model.Design of collision avoidance path tracking controller based on Model Predictive Control.Aiming at the collision avoidance path tracking problem proposed in this paper,a collision avoidance path tracking control method based on model predictive control is proposed.The nonlinear system is transformed into a linear time-varying system and the model predictive control algorithm for collision avoidance path tracking is deduced.Online optimization is used to reduce path deviation and steering angle to meet avoid collision control needs at different speed and different road conditions.The research on different control parameters.In order to further improve the performance of the tracking path controller,a variable sampling period and a variable prediction time domain are proposed according to a variable sampling period.The path tracking error is reduced on the basis of ensuring smooth control.Layered collision avoidance control system provides the basis for the underlying control.The experimental results show that the improved path tracking accuracy is better.To achieve the goal of "autonomous collision avoidance path planning + path tracking",a hierarchical steering collision avoidance controller based on path planning is designed.On the basis of the obstacle avoidance path tracker,the obstacle avoidance function is introduced,and the upper path planning controller based on model prediction is designed.Considering the actual obstacle avoidance stage requirements,an improved obstacle avoidance function is proposed to improve the performance of path planning and control system.