Research On Model Prediction-based Trajectory Planning And Tracking Control Of Intelligent Vehicle Lane Change

The regularity of lane shifts has significantly increased recently due to the fast growth in car ownership and the rising number of vehicles on the road,presenting a serious threat to road effectiveness and safety.Traffic mishaps involving lane changes are on the rise,and the majority of them are the result of careless or exhausted drivers.Therefore,research into intelligent vehicle lane change trajectory planning and tracking control has the potential to not only free up drivers’ hands,lower the likelihood of human error-related traffic accidents,and increase the efficiency of road traffic,but also advance the development of intelligent transportation systems.In order to carry out simulation experiments on the trajectory planning and tracking control of lane change in various working conditions,this paper optimizes the trajectory planning scheme,designs a variable time domain linear model predictive controller for different vehicle speeds and different adhesion coefficients,and builds a joint simulation platform of Car Sim and MATLAB/Simulink.The controller developed in this article has significant resilience,as demonstrated by verification,modeling,and testing findings;particular material includes:The vehicle is first set up in this paper to move in translational motion along the x and y axes as well as in a transverse pendulum motion around the z axis.Next,a three-degree-of-freedom dynamics model for the vehicle is established,and the Magic Formula tyre model is selected because it has a good fitting accuracy and is widely used.The tyre force was discovered to be linear over a narrow angular range by modeling its properties.The car model is further reduced based on the linear tyre model and the small angle assumption,which lays the groundwork for the design of the trajectory tracking controller.This reduces the complexity of the model computation.By keeping a safe distance between the self-vehicle and the surrounding vehicles,it ensures that no risky behavior,such as a collision,occurs during the lane changing process.Secondly,based on the planning problem of the intelligent vehicle trajectory,this paper analyzes the intelligent vehicle lane changing behavior and the performance indicators in the process.This paper compares and analyzes several common lane-changing trajectories,including equal velocity offset,circular arc,trapezoidal acceleration,sine,and polynomial.Five polynomial functions are then chosen for planning lane-changing trajectories,and the lane-changing trajectory function is established.This paper then develops a variable time domain linear model prediction controller based on the lane change trajectory function and the model prediction control principle;linearises and discretizes the vehicle dynamics model to obtain the prediction model needed for the controller;specifies the various constraints in the vehicle lane change process;chooses the objective function for optimally solving the control quantity;and transforms the objective function into It is discovered through simulation that the same set of controller parameters is not suitable for all driving speed conditions.To achieve the best tracking control of lane change trajectories at various vehicle speeds,the optimal control parameters within a given speed range are determined through extensive simulation experiments.In the final phase,a joint Car Sim/MATLAB simulation platform is created to conduct lane change simulation experiments under simplified scenarios.A variable time domain linear model predictive controller is then used to verify the tracking control of the lane change trajectory of the intelligent vehicle under various operating conditions,such as various speeds and road adhesion coefficients.The results of the simulation show that the intelligent vehicle can change lanes safely and smoothly,and the variable time-domain linear time-varying model predictive controller developed in this paper has better accuracy and robustness under various operating conditions and can smoothly control the vehicle along the planned trajectory.And the performance of the controller was verified through actual vehicle tests,and the results showed that the parameter information was within the constraint range.The controller’s lane change tracking effect was good,the driving process was stable,and the comfort of passengers was met.