Vehicle auxiliary driving control method, system, equipment and medium

Abstract

The invention relates to the technical field of intelligent automobiles, in particular to a vehicle auxiliary driving control method, system and device and a medium, and the method comprises the steps that the fatigue response time of a driver is obtained through the eye closing characteristic and the mouth opening characteristic; the expected speed of the host vehicle is obtained through the fatigue response time and the optimization prediction model; obtaining a control error of the nonsingular terminal sliding mode controller according to the expected speed and the actual speed of the host vehicle; determining a control law of a nonsingular terminal sliding mode controller according to the control error and the selected sliding mode approaching rate; and according to the control law, the expected torque and the expected brake pressure of the engine are obtained so as to perform brake control on the host vehicle. According to the method, vehicle aided driving work is achieved based on the driver fatigue degree and nonlinear model optimal prediction control, the problem that an existing vehicle aided driving control method lacks monitoring on the driver fatigue degree and adaptability is solved, and the adaptability of a system to different driver states is effectively improved.

Description

technical field [0001] The present invention relates to the technical field of smart cars, in particular to a vehicle auxiliary driving control method, system, equipment and medium. Background technique [0002] With the development of environmental perception and intelligent autonomous driving technology, the degree of automation of intelligent networked vehicles is increasing day by day. Among them, the development of intelligent vehicles is divided into four stages: autonomous driving assistance, networked assistance, human-machine co-driving, and highly automatic However, due to the consideration of environmental constraints, traffic safety, policy control and many other factors, the current ICV mainly uses the form of man-machine co-driving to complete the driving task, for example: in some specific scenarios, the driver Assistance systems control the vehicle jointly with the driver. The existing driving assistance systems mainly include: automatic parking system (APS)...

AI Technical Summary

Problems solved by technology

[0004] However, the existing driving assistance systems usually only consider the early warning during vehicle driving and exist independently of the vehicle's control system. Their functions cannot achieve the expected effect of intelligent control. The existing driving assistance systems have the following problems:

[0005] (1) When calculating important parameters such as time to collision (TTC), the influence of driver fatigue on its reaction time is not considered, the function is relatively single, and the timing of activation is not accurate enough

[0006] (2) Without considering the driver's handling comfort and other issues, the brakes are often only performed at the maximum braking deceleration, which makes it difficult to dynamically optimize the vehicle control system

[0007] (3) It is difficult to adjust the critical safety distance in the driving assistance system according to different driving environments, and the practicability is poor

[0008] (4) The differences in driving habits of different drivers are not considered, and it is difficult to produce strong adaptability to a large number of driver groups

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