阅读说明：本技术 驾驶行为分析方法、装置、设备及计算机可读存储介质 (driving behavior analysis method, device, equipment and computer readable storage medium ) 是由 曾伟 蒋鑫龙 李亚 潘志文 张辉 于 2019-09-17 设计创作，主要内容包括：本发明公开了一种驾驶行为分析方法、装置、设备及计算机可读存储介质,该方法包括以下步骤：采集待分析用户的头部姿态数据；从所述头部姿态数据中提取头部姿态数据特征；根据预设驾驶行为分析模型和所述头部姿态数据特征,确定所述待分析用户的驾驶行为类型；若所述待分析用户的驾驶行为类型为注意力分散型,则采取驾驶行为校正措施的过程。本发明不涉及侵犯用户的隐私,也不会影响用户正常驾驶,不容易引起用户的反感,通过头部姿态数据特征和模型的输出确定驾驶行为类型,通用性较高,能够在保证准确性的同时,大大降低驾驶行为分析的运算量,进而提升驾驶行为分析效率,从而能够更及时的对用户的不当行为进行校正。(the invention discloses a driving behavior analysis method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: collecting head posture data of a user to be analyzed; extracting head pose data features from the head pose data; determining the driving behavior type of the user to be analyzed according to a preset driving behavior analysis model and the head posture data characteristics; and if the driving behavior type of the user to be analyzed is a distraction type, taking a driving behavior correcting measure process. The method does not involve invasion of privacy of the user, does not influence normal driving of the user, is not easy to cause the user to feel upset, determines the driving behavior type through the head posture data characteristics and the output of the model, has high universality, can ensure accuracy, greatly reduces the calculation amount of driving behavior analysis, further improves the driving behavior analysis efficiency, and can correct the improper behavior of the user in time.)

1. a driving behavior analysis method, characterized by comprising the steps of:

collecting head posture data of a user to be analyzed;

extracting head pose data features from the head pose data;

Determining the driving behavior type of the user to be analyzed according to a preset driving behavior analysis model and the head posture data characteristics;

and if the driving behavior type of the user to be analyzed is a distraction type, taking a driving behavior correction measure.

2. the driving behavior analysis method according to claim 1, wherein the step of determining the driving behavior type of the user to be analyzed based on a preset driving behavior analysis model and the head posture data characteristics is preceded by:

acquiring sample head posture data of which the driving behavior types of sample users are a distraction type and an attention concentration type;

extracting sample head pose data features from the sample head pose data;

and training to obtain a preset driving behavior analysis model based on the driving behavior type and the sample head posture data characteristics corresponding to the driving behavior type.

3. the driving behavior analysis method according to claim 1, wherein the step of collecting head pose data of the user to be analyzed comprises:

acquiring acceleration data of the head of a user to be analyzed through an accelerometer;

acquiring angular velocity data of the head of a user to be analyzed through a gyroscope;

Obtaining a quaternion based on the acceleration data and the angular velocity data;

and taking the acceleration data, the angular velocity data and the quaternion as head posture data.

4. The driving behavior analysis method according to claim 3, wherein the step of extracting head pose data features from the head pose data is preceded by:

Denoising the head posture data;

performing sliding window segmentation on the head attitude data subjected to denoising processing to obtain current window data;

the step of extracting head pose data features from the head pose data comprises:

Extracting head pose data features from the current window data.

5. the driving behavior analysis method according to claim 4, wherein the step of extracting the head pose data feature from the current window data comprises:

Extracting time domain characteristics and frequency domain characteristics of acceleration data, time domain characteristics and frequency domain characteristics of angular velocity data and time domain characteristics of quaternion in the current window data;

and constructing the head posture data characteristic of the current window data based on the time domain characteristic and the frequency domain characteristic of the acceleration data, the time domain characteristic and the frequency domain characteristic of the angular velocity data and the time domain characteristic of the quaternion in the current window data.

6. The driving behavior analysis method according to claim 5, wherein the time-domain characteristics of the acceleration data include a maximum value, a minimum value, an average value, a standard deviation, and an over-average line number of the acceleration data in the current window data;

the frequency domain characteristics of the acceleration data comprise a direct current component, an amplitude mean value, an amplitude standard deviation, an amplitude slope and an amplitude kurtosis of the acceleration data in the current window data;

The time domain characteristics of the angular velocity data comprise the maximum value, the minimum value, the average value, the standard deviation and the number of lines of the over-average value of the angular velocity data in the current window data;

the frequency domain characteristics of the angular velocity data comprise a direct current component, an amplitude mean, an amplitude standard deviation, an amplitude slope and an amplitude kurtosis of the angular velocity data in the current window data;

the time domain features of the quaternion include a maximum value, a minimum value, an average value, a standard deviation and an over-average line number of the quaternion in the current window data.

7. the driving behavior analysis method according to claim 2, wherein after the step of determining the driving behavior type of the user to be analyzed according to a preset driving behavior analysis model and the head posture data characteristics, further comprising:

if the driving behavior type of the user to be analyzed is attention-concentrated type, continuously executing the following steps: head pose data of a user to be analyzed is collected.

8. A driving behavior analysis device characterized by comprising:

the acquisition module is used for acquiring head posture data of a user to be analyzed;

The extraction module is used for extracting head posture data characteristics from the head posture data;

The determining module is used for determining the driving behavior type of the user to be analyzed according to a preset driving behavior analysis model and the head posture data characteristics;

and the correction module is used for taking driving behavior correction measures if the type of the driving behavior of the user to be analyzed is a distraction type.

9. A driving behavior analysis apparatus characterized by comprising a memory, a processor, and a driving behavior analysis program stored on the memory and executable on the processor, the driving behavior analysis program, when executed by the processor, implementing the steps of the driving behavior analysis method according to any one of claims 1 to 7.

10. a computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a driving behavior analysis program which, when executed by a processor, implements the steps of the driving behavior analysis method according to any one of claims 1 to 7.