A vehicle control method, device and system

Abstract

The embodiment of the present application discloses a vehicle control method, device and system. First, obtain the current vehicle speed parameter value and vehicle acceleration parameter value, that is, the vehicle actual speed value and actual acceleration parameter value. Then subtract the target speed parameter value from the vehicle speed parameter value, and input the difference into the first PID controller to obtain the target acceleration parameter value. Then subtract the target acceleration parameter value from the vehicle acceleration parameter value, and input the difference value into the second PID controller to obtain the control amount for controlling the vehicle. It can be seen that in the embodiment of the present application, the execution results of the control quantities output by the second PID controller are respectively fed back to the first PID controller and the second PID controller, and the PID controller can timely discover the target value and the second PID controller through the double feedback method. The error between the actual values ​​and the reduction of the tracking error can improve the tracking accuracy, realize the matching driving strategy according to the real-time running state of the vehicle, and improve the driving experience.

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.

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