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Driver physiological data-based driving suitability evaluation method and system

A technology of physiological data and evaluation methods, applied in data processing applications, vehicle testing, machine/structural component testing, etc., can solve the problems of objectivity and low reliability, reduce bad driving behaviors, and improve safety Effect

Active Publication Date: 2020-05-15
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of low objectivity and reliability in the existing evaluation of driving suitability, the present invention provides a method and system for evaluating driving suitability based on driver's physiological data

Method used

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  • Driver physiological data-based driving suitability evaluation method and system
  • Driver physiological data-based driving suitability evaluation method and system
  • Driver physiological data-based driving suitability evaluation method and system

Examples

Experimental program
Comparison scheme
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specific Embodiment approach 1

[0047] Specific implementation mode 1: The suitability of the driver to be evaluated is divided into five grades (D1=poor, D2=poor, D3=pass, D4=good, D5=excellent), which are determined by the professional test sample data in the early stage The grade level value corresponding to each evaluation grade, let a 1 , a 2 , a 3 , a 4 , a 5 are the grade level values ​​corresponding to D1, D2, D3, D4, and D5 respectively, and a total of n groups of samples have been measured. The normal range of flexion and extension of the driver listed in Table 1 is based on the neutral position as each index corresponds to the poorness in the 5 grades (a 1 ) and excellent (a 5 ) level value, pass (a 3 ) takes the average value of the sample data, α 2 and a 4 Take the 20% and 80% sample levels respectively, that is, 20% and 80% of the sample values ​​are below this data.

[0048] The evaluation of driving suitability level in the early stage includes 16 indicators related to pressure measu...

specific Embodiment approach 2

[0051] Specific implementation mode 2: This embodiment is to obtain the main index affecting the suitability difference between the driver and the vehicle, so as to make targeted adjustments to the driver's posture and behavior.

[0052] The normal distribution is used as the basis for dividing the membership degree of each parameter level of the driver to be evaluated. The specific process is as follows: the membership function corresponding to the five levels all satisfies at the endpoint of the interval (endpoint value a 1 , a 2 , a 3 , a 4 , a 5 The confidence level between known) is 95%, and under the normal curve of each interval, the area in the horizontal axis interval (μ-1.96σ, μ-1.96σ) is 95.449974%, thus it can be obtained that in each membership function The σ value of , the following five membership functions are obtained:

[0053] The membership function of an index to the grade (too bad):

[0054]

[0055] The membership function of an index to grade (po...

specific Embodiment approach 3

[0066] Specific Implementation Mode Three: This implementation mode is to explore the closeness of multiple evaluation indicators related to the driver to each driving suitability level, so as to determine the correlation between different indicators and levels, which is expressed by gray correlation.

[0067] The evaluation database contains 16 indicators including the pressure, angle and distance measurement data of multiple parts of the body and the data that advances with the detection time. When the driver sits on the driver's seat, the data acquisition card acquires the first set of objective physiological parameter samples about the driver and the seat; when the driver performs a certain task during dynamic driving, the data acquisition card acquires the second A set of physiological parameter samples about the driver and the seat; when the driver finishes the driving task, the data acquisition card acquires a third set of comparative physiological parameter samples abou...

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Abstract

The invention discloses a driver physiological data-based driving suitability evaluation method. The method comprises the following steps of: arranging an angle measurement sensor on a driver, installing a pressure sensor on a driver seat, and installing a distance sensor in a vehicle; collecting human body data of a driver to be evaluated, and adjusting the position of the automobile seat according to the physical signs of the driver; adjusting the still sitting posture of the driver; acquiring data of a pressure sensor, a distance sensor and an angle sensor and transmitting the data to an analysis system; the analysis system calculating the membership degree and the grade correlation degree of the indexes according to a preset program; carrying out early warning on the indexes of which the suitability degrees are lower than the qualification degree; and outputting the suitability level of the driver. According to the method, indexes with low suitability can be screened, subjective evaluation is replaced by objective classification of a large amount of test data, then the objective evaluation grade is obtained, and a theoretical basis is provided for improving driver suitability in a targeted mode in the automobile seat detection technology in the future.

Description

technical field [0001] The invention belongs to the technical field of car seat detection, and in particular relates to a driving suitability evaluation method and system based on physiological data of a driver. Background technique [0002] With the continuous development of the economy, cars have become an indispensable part of travel needs. During long-term driving, a comfortable driving environment can effectively improve the driving experience, reduce driving fatigue, and improve driving safety. If the car seat is not designed properly, the driver will not be able to obtain a reasonable and comfortable sitting posture, and the suitability experience of human-vehicle interaction will be poor, which will easily increase the driver's discomfort and lead to vicious traffic accidents. Due to the large number of quantitative indicators for evaluating driving suitability, and the relationship between these indicators and the driver's evaluation criteria for driving space suita...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G01M17/007
CPCG06Q10/06393G01M17/007
Inventor 冯树民孙雅丽盛彬赵琥宋子龙黄秋菊
Owner HARBIN INST OF TECH
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