Vehicle Collision Avoidance Path Planning And Tracking Control Based On Multi-constraint MPC

In today's complex traffic environment,driver error is one of the main causes of frequent accidents.Therefore,active research on intelligent vehicle driving assistance systems is of great significance for improving driving safety,vehicle stability and improving traffic efficiency.Firstly,based on the model predictive control algorithm,a Multi-Constraints Model Predictive Control(MMPC)with dynamic constraints is designed.Using the two-degree-of-freedom vehicle dynamics model as the predictive model,the predicted values of the state quantity and output of the system are obtained.By constraining the centroid side yaw angle and the yaw rate to a stationary state of the steering stability state,the minimum value of the objective function is solved.Get the best front wheel angle needed to track the target path.Then,the collision avoidance penalty function is introduced.By designing the objective function,the local trajectory planning is realized.The curve parameters of the local reference trajectory are output to the path tracking controller by the fifth-order polynomial fitting algorithm,and the path tracking and collision avoidance control are realized.Next,this paper studies the Collaborative Adaptive Cruise Control in the longitudinal control of intelligently driven vehicles.In order to combine the CACC control system and the Collision Avoidance system and solve the problem of the influence of the longitudinal acceleration of the controlled vehicle on the comfort of the occupants,in the design process of the CACC control system,the two-car following model is established.Based on the model predictive control theory,the system output is hardly constrained and the system control quantity is adaptively constrained.A multi-channel variable structure MPC upper-layer controller considering collision avoidance is designed to realize the control.Switching between three functional modes of CACC,CACC+CA,and CCA,and in the third control mode CCA,in order to avoid dangerous conditions in which the rear vehicle is in extreme deceleration,a collision avoidance collision between two vehicles is proposed.Acceleration allocation strategy.The designed controller was verified by different operating conditions.Finally,in order to study the intelligent vehicle control system with two kinds of assisted driving functions,that is,the L2 level automatic driving level,we have studied the problem of CACC two-car system synchronous lane change,and established the CACC two-car synchronous lane change control system.The frame structure is based on the fifth-order polynomial design of the lane change trajectory planner.In order to combine the MMPC path tracking controller and the CACC controller,a vertical-horizontal integrated control system with two control modes is designed.The effectiveness of the designed control system is verified by simulation experiments.