Method for detecting disturbance state of driver by utilizing driver-side longitudinal control model

Abstract

The invention provides a method for detecting a disturbance state of a driver by utilizing a driver model. The method comprises the following steps: obtaining driving environment information of an automobile by an external sensor and judging a driving intention according to a ration between the position of the automobile and a lane boundary; when the driving intention is to keep the lane, calculating a change volume of a turning angle of a steering wheel by the driver model according to the driving environment information and the automobile state information and calculating and outputting an opening degree of an accelerator according to the present automobile speed and an expected longitudinal acceleration confirmed by a time interval between the automobile and the front automobile; when the driving intention is to change the lane, calculating the change volume of the turning angle of the steering wheel by the driver model according to the driving environment information and the state information and calculating and outputting the opening degree of the accelerator according to the present automobile speed and the expected longitudinal acceleration calculated on the basis of a lateral acceleration; comparing the turning angle of the steering wheel and the opening degree of the accelerator calculated by the driver model with a practical control data of the driver obtained by an internal sensor and judging if the driver is disturbed; and repeating the steps till stopping.

Description

technical field [0001] The invention relates to a method for detecting a driver's interference state by using a driver's side longitudinal comprehensive control model. In terms of detecting driver interference, the method uses the driver model to simulate the driver control data (steering wheel angle and throttle opening) in the current driving environment in real time, and compares the control data of the driver model with the control data of the real driver. And identify whether the driver is disturbed according to the comparison result. The method has low hardware cost and high recognition accuracy, and is especially suitable for developing an auxiliary driving system for vehicles. Background technique [0002] The interference of the driver (for example, distracted, eating, drinking water / beverage, making a phone call, chatting with passengers, and using the vehicle system, etc.) is an important cause of traffic accidents, so it is necessary to develop detection methods...

AI Technical Summary

Problems solved by technology

Although the driver's physiological representation can reflect the driver's disturbed state, it is also very deceptive. For example, when the driver is cognitively disturbed (such as thinking about problems while driving), the driver's facial expression may No change, for such interference existing methods are difficult to detect

On the contrary, the driver's control behavior on the vehicle can truly reflect the driver's state. Research shows that the driver's control data under normal conditions and the control data under disturbance are very different.

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