An intelligent vehicle horizontal and vertical comprehensive control system and control method

Abstract

The invention discloses an intelligent vehicle transverse and longitudinal integrated control system and control method. The intelligent vehicle transverse and longitudinal integrated control system comprises a decision module, a control module and an executing module; the decision module plans a vehicle future trajectory and generates a planning trajectory, a planning position, a planning speed, a planning accelerated speed, a restriction condition and a depth threshold; the control module calculates each parameter according to a trajectory to be tracked and guarantees that a vehicle runs according to the planning trajectory by repeatedly correcting a steering wheel angle and an accelerator brake change which act upon the executing vehicle; and the executing module feeds back an actual position and an actual speed to the control module. The intelligent vehicle transverse and longitudinal integrated control system can be used for vehicles running under various working conditions, can guarantee the planning path tracking accuracy and running stability of the vehicle at minimum calculation cost and can greatly reduce requirements on the performance of a vehicle-mounted processor.

Description

technical field [0001] The invention belongs to the technical field of vehicle dynamics control, and in particular relates to an intelligent vehicle horizontal and vertical comprehensive control system and control method. Background technique [0002] For many years, the problem of motion control of intelligent vehicles has been the subject of many researchers' attention. The control algorithm based on the vehicle mathematical model is a widely used control method. However, intelligent vehicles not only have strong nonlinearity, but also have uncertainties. characteristics such as time-varying and time-varying characteristics, which make it more difficult to obtain the precise mathematical model of the vehicle. Even if the precise mathematical model is obtained and can be applied to the design of the control algorithm, it will increase the computational burden and the real-time performance is difficult to guarantee; at the same time, Many researchers have proposed to apply M...

AI Technical Summary

Problems solved by technology

[0002] For many years, the problem of motion control of intelligent vehicles has been the subject of many researchers' attention. The control algorithm based on the vehicle mathematical model is a widely used control method. However, intelligent vehicles not only have strong nonlinearity, but also have uncertainties. characteristics such as time-varying and time-varying characteristics, which make it more difficult to obtain the precise mathematical model of the vehicle. Even if the precise mathematical model is obtained and can be applied to the design of the control algorithm, it will increase the computational burden and the real-time performance is difficult to guarantee; at the same time, Many researchers have proposed to apply Model Predictive Control (MPC) to the motion control of intelligent vehicles. Although the requirement for the precise mathematical model of the vehicle is eliminated, the MPC constrained optimization problem is solved online, which involves a large The computing time and computing resources have high performance requirements for the hardware required for computing, making it difficult for MPC to be practically applied to intelligent vehicle control with fast dynamics and limited computing resources.

Images