Vehicle control method, device and system

Abstract

The embodiments of the invention disclose a vehicle control method, device and system. The vehicle control method includes the steps that firstly, a current vehicle speed parameter value and a vehicleacceleration parameter value are obtained, and that is, a vehicle actual speed value and an actual acceleration parameter value; then a target speed parameter value is subtracted from the vehicle speed parameter value, and a difference value is input into a first PID controller to obtain a target acceleration parameter value; and then the target acceleration parameter value is subtracted from thevehicle acceleration parameter value, a difference value is input into a second PID controller to obtain the control quantity of a control vehicle. Thus, according to the embodiments, execution results of the control quantity output by the second PID controller are fed back to the first PID controller and the second PID controller correspondingly, through a double-feedback mode, the PID controllers can find errors between a target value and an actual value in time and reduce tracking errors, thus the tracking accuracy is improved, a matched driving strategy is obtained according to the real-time running state of the vehicle, and the driving experience is improved.

Description

technical field [0001] The present application relates to the technical field of automatic control, in particular to a vehicle control method, device and system. Background technique [0002] With the continuous development of automobile technology, autonomous driving technology has received a lot of attention. Self-driving cars rely on artificial intelligence, visual computing, radar, and positioning systems to allow computers to automatically and safely operate motor vehicles without any active human intervention. [0003] In practical applications, the vehicle obtains a driving strategy that matches the current operating state by collecting information about the surrounding environment and its own operating state, and through a proportional-integral-derivative (Proportion Integration Differentiation, PID) controller. However, due to the complexity of the current traffic environment, there are many interference factors, which will affect the tracking error of the PID cont...

AI Technical Summary

Problems solved by technology

However, due to the complexity of the current traffic environment, there are many interference factors, which will affect the tracking error of the PID controller, and then affect the tracking accuracy and stability of the PID controller, and the control target of the vehicle needs to be changed frequently during driving. The dynamic performance of the controller puts forward higher requirements

However, the traditional algorithm cannot fully meet the control requirements in this application scenario, resulting in the failure of the vehicle to obtain the optimal driving strategy.

Images