Method and system for detecting hand separation of steering wheel based on artificial intelligence learning

A technology of artificial intelligence and detection methods, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of single detection results, out-of-hand warning output results, inaccurate detection, etc., to improve the fault tolerance rate and work efficiency , improve the accuracy and avoid the effect of misjudgment

Pending Publication Date: 2022-07-08
CHONGQING UNIV OF TECH
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Problems solved by technology

[0005] The purpose of the present invention is to provide a hand-off detection method and system based on artificial intelligence learning, which is used to solve the problem that the existing hand-off detection system is inaccurate and the detection result and the hand-off warning output result are single

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  • Method and system for detecting hand separation of steering wheel based on artificial intelligence learning
  • Method and system for detecting hand separation of steering wheel based on artificial intelligence learning
  • Method and system for detecting hand separation of steering wheel based on artificial intelligence learning

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Embodiment Construction

[0070] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

[0071] figure 1 It is the overall frame diagram of a steering wheel off-hand detection system based on artificial intelligence learning of the present invention. The system mainly includes a data acquisition module, including an array film pressure sensor module; a signal processing module, a data acquisition module, a driving condition acquisition module, HOD ( Hands-off detection) warning module and ADAS (advanced driver assistance system) control module.

[0072] In this example, the array thin film pressure sensor module mainly measures the pressure generated by the driver's hand on t...

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Abstract

The invention relates to the technical field of automobile auxiliary driving and driving safety, in particular to a steering wheel hand-leaving detection method and system based on artificial intelligence learning. Comprising the following steps: acquiring pressure data, filtering and amplifying the pressure data, and converting the pressure data into digital signals; extracting the pressure data; carrying out pre-judgment on the data characteristics; and carrying out holding posture recognition on the data features. According to the method, the holding posture features are extracted and detected through an artificial intelligence algorithm, the holding posture of a driver can be effectively recognized, and misjudgment is effectively avoided; according to the method, through a layered detection model of pre-judgment and holding posture recognition, the accuracy of hand-leaving detection is effectively improved, and the error-tolerant rate and the working efficiency of a detection system are improved; by means of the HOD warning module, various warning effects of the warning lamp and the vibration exciter can be achieved, automatic braking can be achieved through the ADAS control module, and the safety of the vehicle in the hand leaving state is guaranteed.

Description

technical field [0001] The invention relates to the technical field of assisted driving and driving safety of automobiles, in particular to a method and system for detecting hand-off of a steering wheel based on artificial intelligence learning. Background technique [0002] In the existing hands-off detection technology, in order to realize the function of hands-off detection, most of the sensors used are cameras, torque sensors, capacitive sensors, etc., and most of the detection results of the existing steering-wheel off-hand detection systems have only two results (the driver leaves the hands) state and the driver's holding state), and there is no further detection of the holding posture, which can easily lead to misjudgment of the results. For example, when the torque sensor is driving on a rough road, the measurement result of the torque sensor is inaccurate due to the moment that the ground faces the steering rocker arm; for the capacitive sensor, it is easily affecte...

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Application Information

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IPC IPC(8): B60W40/09B60W30/09B60W50/14B60W50/16G06N3/04G06N3/08
CPCB60W40/09B60W30/09B60W50/14B60W50/16G06N3/08B60W2050/143G06N3/045
Inventor 郭栋黎洪林李波
Owner CHONGQING UNIV OF TECH
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