| Based on sensor communication,cooperative adaptive cruise control uses wireless communication technology to obtain the driving information of the preceding vehicle for vehicle control,which can improve the communication delay and lag of the vehicle controller.Combined with the feedforward control based on vehicle-vehicle communication,it can effectively shorten the control delay time,thereby shortening the distance between vehicles,reducing vehicle air resistance,and achieving the purpose of saving energy and reducing consumption and improving road capacity.In order to improve the control accuracy and tracking performance of the cooperative adaptive cruise control algorithm,this paper designs a model predictive controller under the condition of satisfying the control objectives and constraints,and builds a joint simulation platform to analyze and evaluate the practicability and effectiveness of the algorithm.Firstly,the overall architecture of the cooperative adaptive cruise system is designed according to the existing research technologies and achievements,in which the controllers are divided into upper and lower controllers.Based on the analysis of the vehicle longitudinal dynamics model,the lower-level controller is built,and the vehicle inverse dynamics model is established,including the throttle valve,the brake and the switching logic algorithm of the two.The lower controller introduces the PID control strategy,separates the integral control,and establishes the lower controller of the cooperative adaptive cruise system by controlling the difference between the actual acceleration and the expected acceleration according to the working conditions.The lower controller is simulated and verified by setting a step acceleration signal,which solves the problem of acceleration jitter when the throttle valve and the brake are switched.Aiming at the nonlinear dynamic characteristics of the vehicle during driving,based on the fixed headway algorithm,a safety distance model considering the longitudinal motion of the vehicle is built,which lays the foundation for the design of the upper-level controller.Then,based on the model predictive control algorithm,the upper controller of the cooperative adaptive cruise system is designed,and a discrete linear state space model is built.The required objective function,and the constrained state-space model prediction problem is transformed into a standard quadratic programming problem.By applying the feedback linearization control algorithm,the speed tracking curve and the distance error result graph of the model predictive control algorithm are compared and analyzed,which proves the stability and effectiveness of the model predictive control algorithm.In order to solve the problem that a feasible solution cannot be obtained due to strict upper and lower bounds,a multiplication factor is introduced into the objective function as a slack variable to improve the model predictive control algorithm,and the weight coefficient is set to determine the softening degree of the slack variable to each variable in the system.Convert it into a quadratic optimization function that can be solved,and use Lyapunov’s second method to analyze the stability of the improved model predictive control algorithm.Finally,through the Simulink/Truck Sim co-simulation platform,the result graphs of the two algorithms before and after the improvement in smooth following and emergency braking are analyzed,and it is verified that the improved control algorithm can effectively reduce the fluctuation of vehicle speed in the queue and shorten the time.The response time of the following vehicle,thereby improving traffic safety. |
