Research On The Longitudinal Control Strategy Of Vehicle Adaptive Cruise Control System

Vehicle adaptive cruise control(ACC)system is an auxiliary system for vehicle driving safety.It has the function of reducing of driving burden of the driver,improving comfort of the driver and reducing traffic accident rate.The anti-lock braking system(ABS)under the ACC system can improve the response speed and stability when braking,which improve the performance of ACC system.In the paper,the ACC system and the ABS under the ACC system are studied.The ABS mathematical model,including brake model,slip rate model,tire model and vehicle dynamic model,is established.The ABS mathematical model is analyzed,and the ABS control system with road recognition system under ACC system is established by using fuzzy PID control algorithm.Simulink is used to simulate the ABS control system by the PID control algorithm and fuzzy PID control algorithm separately.The simulation results show that the fuzzy PID control algorithm improves the response speed and stability of braking of ACC system,improves the performance of ACC system when braking,which improvs the safety.By analyzing the dynamic relationship of the vehicle,the front vehicle,between the vehicle and the front vehicle,the motion relational model,including variables such as vehicle space,relative velocity,acceleration,change rate of acceleration and acceleration of the front vehicle,is obtained.Considering the safety,comfort and vehicle performance requirements,the saturation function is introduced to limit the vehicle speed,acceleration and change rate of acceleration,so the motion relational model under the limit is obtained.An inverse longitudinal dynamic model of vehicle is established by analyzing the process of vehicle driving and the engine and brake of vehicle.The motion relational model under the saturation function use the weighted square of the output variables as the objective function to coordinate the relationship among the vehicle distance,speed and acceleration,so that they can converge to the control requirements and the coordination of the vehicle multiple performance index is ensured.Using the principle of model predictive control(MPC)and the principle of extreme value control,the objective function containing multiple variables is transformed into a function containing only one variable,which effectively avoids the simultaneous appearance of multiple unknown quantities and simplifies the algorithm.Using MATLAB to compare the common MPC algorithm and the improved extreme value MPC algorithm of ACC,the simulation results show that the improved extreme value MPC algorithm of ACC has better driving safety,comfort,rapidity and coordination under various typical operating conditions.