Man-machine co-driving control system based on driver model and handling inverse dynamics and switching mode of man-machine co-driving control system

Abstract

The invention discloses a man-machine co-driving control system based on a driver model and handling inverse dynamics and a switching mode of the man-machine co-driving control system. The man-machineco-driving control system comprises a sensor system, a driving intention recognition model, a man-machine co-driving model, a right switching control system and an executive system. The method comprises the following steps: monitoring driving environment information, vehicle state information and driver state information by the sensor system, wherein a driver state signal is transferred to the driving intention recognition model; establishing a man-machine co-driving model based on the handling inverse dynamics and the driver model, and calculating expected control input and control input ofthe driver; performing necessary correction by the system on the basis of understanding the driving intention of the driver based on the established man-machine co-driving switching law, and performing full authority control by the other party when the driver temporarily loses control ability or the auxiliary system temporarily loses auxiliary operational capability to avoid unnecessary man-machine interference. According to the man-machine co-driving control system disclosed by the invention, the operating burden of the driver is reduced, and man-machine alternative disharmony is avoided.

Description

Technical field [0001] The invention belongs to the technical field of automobile safety, and particularly relates to a man-machine co-driving control system based on a driver model and manipulation inverse dynamics and a switching mode thereof. Background technique [0002] The popularization of driverless cars can greatly reduce driver accidents caused by human factors such as fatigue driving and improper operation. According to SAE's classification standards, the development of automobile intelligence can be divided into five levels: full human driving, driving assistance, partial automatic driving, conditional automatic driving, highly automatic driving and fully automatic driving. Although driverless technology has received long-term attention, and its research has achieved great development, from the perspective of actual promotion and mass application, driverless cars will face legal restrictions if they want to become human vehicles. , Insurance, technical difficulty, ac...

AI Technical Summary

Problems solved by technology

Although unmanned driving technology has received long-term attention, and its research has made great progress, but from the perspective of practical promotion and mass application, unmanned vehicles will face legal constraints if they want to become a means of transportation for human beings. , insurance, technical difficulty, accident liability, driving pleasure and other issues, the complex road traffic environment also determines that unmanned driving is impossible to achieve in the short term. The Situation of Joint Control of Human-Machine

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