CN111923859B - Method and system for predicting injury of rear-row passengers and calling for help externally under frontal collision - Google Patents

Method and system for predicting injury of rear-row passengers and calling for help externally under frontal collision Download PDF

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CN111923859B
CN111923859B CN202010739832.0A CN202010739832A CN111923859B CN 111923859 B CN111923859 B CN 111923859B CN 202010739832 A CN202010739832 A CN 202010739832A CN 111923859 B CN111923859 B CN 111923859B
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injury level
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CN111923859A (en
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陆颖
吕羽竞
殷越洲
束瑜
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Jiangsu University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • B60R21/01—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents
    • B60R21/013—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over
    • B60R21/0136—Electrical circuits for triggering passive safety arrangements, e.g. airbags, safety belt tighteners, in case of vehicle accidents or impending vehicle accidents including means for detecting collisions, impending collisions or roll-over responsive to actual contact with an obstacle, e.g. to vehicle deformation, bumper displacement or bumper velocity relative to the vehicle
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • B60R2021/003—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks characterised by occupant or pedestian
    • B60R2021/0039—Body parts of the occupant or pedestrian affected by the accident
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • B60R2021/003—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks characterised by occupant or pedestian
    • B60R2021/0039—Body parts of the occupant or pedestrian affected by the accident
    • B60R2021/0044—Chest
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R21/00—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks
    • B60R2021/003—Arrangements or fittings on vehicles for protecting or preventing injuries to occupants or pedestrians in case of accidents or other traffic risks characterised by occupant or pedestian
    • B60R2021/0039—Body parts of the occupant or pedestrian affected by the accident
    • B60R2021/0048—Head

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  • Mechanical Engineering (AREA)
  • Emergency Alarm Devices (AREA)
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Abstract

The invention discloses a method and a system for predicting the injury condition of a rear-row passenger under frontal collision and calling for help externallyThe speed variation in the process of surface collision is respectively used for obtaining the head evaluation index HIC of the rear passenger 15 Neck evaluation index N ij Chest evaluation index D max (ii) a According to the head evaluation index HIC of the rear passenger 15 Neck evaluation index N ij Chest evaluation index D max Respectively obtaining the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the passengers in the back row; respectively setting threshold values of the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability, and judging whether external call for help is needed or not according to the threshold values, the head AIS injury level probability of rear passengers, the neck AIS injury level probability and the chest AIS injury level probability.

Description

Method and system for predicting injury of rear-row passenger under frontal collision and calling for help externally
Technical Field
The invention belongs to the technical field of injury prediction, and particularly relates to a method and a system for predicting injury of rear-row passengers and calling for help from the outside under frontal collision.
Background
With the rapid development of economy in China, the automobile is more and more popular in use. Automobile accidents often result in large economic losses and casualties. Has become a hot point of discussion and research direction today. Once a traffic accident occurs, if the traffic accident is not handled in time, secondary damage is likely to be caused, and greater damage and loss are likely to be caused.
At present, the passenger injury prediction under the automobile collision is still incomplete, the research on the front row of the automobile is more, and the research on the rear row of the automobile is insufficient. Such as the lack of injury prediction for rear occupants in a frontal collision. The front row and the rear row of the automobile have great difference and cannot be considered integrally. There is also a problem in determining a threshold value in a collision.
In the chinese patent 201710060276, the acceleration of the head and the load force of the upper neck of the dummy are collected, and the head and the face of the dummy are painted with paint to judge the degree of head injury. The design has the disadvantages that in practical application, the neck load force on the human body is difficult to measure, and the design is only limited to head measurement and does not contain other measurement.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a method for predicting the injury of the passengers in the back row under the frontal collision and calling for help to the outside,
the technical scheme adopted by the invention is as follows:
a method for predicting injury of rear-row passengers and calling for help externally under frontal collision comprises the following steps:
s1, acquiring images of a rear seat of a vehicle, judging whether a passenger is in the rear seat, if so, turning to S2, otherwise, ending;
s2, transmitting a signal to a vehicle-mounted computer according to an automobile collision intensity signal detected by a collision sensor when the automobile collides, and judging whether the automobile collides frontally;
s3, by
Figure BDA0002606397370000011
Calculating the speed variation, t, during a frontal collision 1 Acceleration start time, t n The acceleration end time, t the current time, and a (t) the acceleration.
S4, respectively obtaining head evaluation indexes HIC of rear-row passengers based on speed variation in the frontal collision process 15 Neck evaluation index N ij Chest evaluation index D max (ii) a According to the head evaluation index HIC of the rear passenger 15 Neck evaluation index N ij Chest evaluation index D max Respectively obtaining the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the passengers in the back row;
s5, respectively setting threshold values of the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability, and judging whether calling for help is needed according to the threshold values, the head AIS injury level probability of the rear passengers, the neck AIS injury level probability and the chest AIS injury level probability;
further, the head evaluation index HIC of the rear passenger is calculated in the step 4 15 Neck evaluation index N ij Chest evaluation index D max The method comprises the following steps of carrying out regression analysis on the injury degree of the head, the neck and the chest and the automobile speed variation during frontal collision to respectively obtain:
head evaluation index HIC 15 Fitting formula:
HIC 15 ＝-1979.859+57.521Δv
neck evaluation index N ij Fitting formula:
N ij ＝0.239+0.014Δv
chest evaluation index D max Fitting formula:
D max ＝1.786+0.761Δv
wherein Δ v is the velocity change amount;
further, in the step 4, the method for calculating the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the rear passenger includes:
head AIS injury level probability:
Figure BDA0002606397370000021
neck AIS injury level probability:
Figure BDA0002606397370000022
AIS injury level probability of the thorax:
Figure BDA0002606397370000023
wherein e is an irrational number.
Further, the method for respectively calculating the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability threshold comprises the following steps:
aiming at the head AIS injury level probability, substituting the speed variation quantity corresponding to the maximum limit value of 46km/h into a head AIS injury level probability calculation formula to obtain a threshold value of 0.29 as the head AIS injury level probability threshold value;
aiming at the neck AIS injury level probability, substituting the speed variation quantity corresponding to the maximum limit value as 95km/h into a neck AIS injury level probability calculation formula to obtain a threshold value of 0.48 as the neck AIS injury level probability threshold value.
Aiming at the AIS injury level probability of the chest, substituting the speed variation corresponding to the maximum limit value into the AIS injury level probability calculation formula of the chest to obtain a threshold value of 0.13 as the AIS injury level probability threshold value of the chest.
The utility model provides a rear passenger's injury prediction and external distress system under frontal collision, includes car monitoring device, and car monitoring device includes triaxial acceleration sensor, camera, collision sensor and GPS module. The system comprises a triaxial acceleration sensor, a collision sensor, a camera and a GPS module, wherein the triaxial acceleration sensor, the collision sensor, the camera and the GPS module are all connected with a vehicle-mounted computer, a collision module is arranged in the vehicle-mounted computer, and a head AIS (automatic identification system) injury level probability calculation method, a neck AIS injury level probability calculation method, a chest AIS injury level probability calculation method, a head AIS injury level probability threshold, a neck AIS injury level probability threshold and a chest AIS injury level probability threshold are preset in the collision module; and the vehicle-mounted battery respectively supplies power to the triaxial acceleration sensor, the camera, the collision sensor, the GPS module and the vehicle-mounted computer.
Further, the camera is installed in the vehicle, and whether passengers exist in the rear row of the vehicle is identified through the vehicle-mounted computer; judging whether the frontal collision of the automobile occurs or not through data transmitted to an on-board computer by a collision sensor; the vehicle information is collected in real time by the triaxial acceleration sensor, the collected information is transmitted to the vehicle-mounted computer, the vehicle-mounted computer calculates the speed value when collision occurs according to the acceleration cumulant through an algorithm, the vehicle-mounted computer obtains the injury grade probability of the head, the neck and the chest of the rear seat passenger at that time through the algorithm, compares the injury grade probability with the originally set threshold value, and sends out distress call information if the injury grade probability exceeds the threshold value.
The invention has the beneficial effects that:
the invention judges the injury prediction of the rear-row passengers under the frontal collision through the speed variation. The speed variation is easy to obtain, when a frontal collision accident of the automobile occurs, the head, neck and chest injury levels of passengers in the rear row of the automobile can be judged in time, and a rescue scheme can be appointed by a rescue center conveniently for calling for help.
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FIG. 1 is a flow chart of a method for predicting injury of a rear-row passenger and calling for help from outside in a frontal collision according to the present invention;
FIG. 2 is a block diagram of a system for predicting injury of rear-row passengers and calling for help in case of frontal collision according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
A method for predicting the injury of the rear-row passengers and calling for help at the outside under the condition of frontal collision is shown in figure 1 and comprises the following steps:
s1, acquiring images of a rear seat of a vehicle, judging whether a passenger is in the rear seat, if so, turning to S2, otherwise, ending;
s2, transmitting a signal to a vehicle-mounted computer according to an automobile collision strength signal detected by a collision sensor when the automobile collides, and judging whether the automobile collides frontally;
s3, by
Figure BDA0002606397370000041
The amount of speed change during a frontal collision is calculated. In the formula t 1 Acceleration start time, t n The acceleration end time, t the current time, and a (t) the acceleration.
S4, respectively obtaining head evaluation indexes HIC of rear-row passengers based on speed variation in the frontal collision process 15 Neck evaluation index N ij Chest evaluation index D max (ii) a According to the head evaluation index HIC of the rear passenger 15 Neck evaluation index N ij Chest evaluation index D max Respectively obtaining the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the passengers in the back row; the specific process is as follows:
s4.1, collecting the head, neck and chest injury degrees of 500 fake people in the vehicle during frontal collision under different acceleration conditions;
s4.2, performing regression analysis on the injury degree of the head, the neck and the chest and the automobile speed variation during frontal collision by using SPSS 23.0 software to respectively obtain:
obtaining head evaluation index HIC 15 Fitting formula:
HIC 15 ＝-1979.859+57.521Δv (1)
obtaining a neck evaluation index N ij Fitting formula:
N ij ＝0.239+0.014Δv (2)
obtaining a chest evaluation index D max Fitting formula:
D max ＝1.786+0.761Δv (3)
wherein Δ v is the velocity change amount;
s4.3, the method for calculating the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability comprises the following steps:
the head AIS injury level probability formula is as follows:
Figure BDA0002606397370000042
the neck AIS injury grade probability formula is as follows:
Figure BDA0002606397370000043
the chest AIS level probability formula is:
Figure BDA0002606397370000051
wherein e is an irrational number, D max The maximum compression of the chest.
Different speed variation under frontal collision and head HIC 15 Neck N ij And chest D max Substituting the corresponding regression equation into the formulas (4), (5) and (6) to obtain:
Figure BDA0002606397370000052
Figure BDA0002606397370000053
Figure BDA0002606397370000054
s5, judging whether calling for help is needed according to the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the passengers in the back row; the specific method comprises the following steps: respectively setting threshold values of the head AIS injury level probability, the neck AIS injury level probability and the breast AIS injury level probability:
substituting the speed variation amount corresponding to the maximum limit value into an equation (7) according to the head AIS injury level probability to obtain a threshold value of 0.29 as the head AIS injury level probability threshold value; when the AIS injury level probability exceeds the value, calling for help is conducted outwards.
Aiming at the neck AIS injury level probability, substituting the speed variation corresponding to the maximum limit value as 95km/h into the formula (8) to obtain a threshold value of 0.48 as the neck AIS injury level probability threshold value; when the neck AIS injury level probability exceeds the value, calling for help is conducted outwards.
Aiming at the AIS injury level probability of the chest, substituting the speed variation corresponding to the maximum limit value into an equation (9) to obtain a threshold value of 0.13 as the AIS injury level probability threshold value of the chest; when the AIS injury grade probability of the chest exceeds the value, calling for help is carried out.
In order to realize the method for predicting the injury of the rear-row passengers and calling for help from the outside under the frontal collision, the invention also designs a system for predicting the injury of the rear-row passengers and calling for help from the outside under the frontal collision, which comprises an automobile monitoring device, wherein the automobile monitoring device comprises a three-axis acceleration sensor, a camera, a collision sensor and a GPS module. The three-axis acceleration sensor, the collision sensor, the camera and the GPS module are all connected with a vehicle-mounted computer, a collision module is arranged in the vehicle-mounted computer, and formulas (7), (8) and (9) and a threshold value are preset in the collision module. And the vehicle-mounted battery respectively supplies power to the triaxial acceleration sensor, the camera, the collision sensor, the GPS module and the vehicle-mounted computer.
The camera is installed in the automobile, and whether passengers exist in the rear row of the automobile or not is identified through the vehicle-mounted computer. And then whether the frontal collision of the automobile occurs is judged according to the data transmitted to the vehicle-mounted computer by the collision sensor. The vehicle information is collected in real time by the three-axis acceleration sensor, the collected information is transmitted to the vehicle-mounted computer, the vehicle-mounted computer calculates the speed value when collision occurs according to the accumulated acceleration value through an algorithm, the vehicle-mounted computer obtains the head, neck and chest injury grade probability of the rear seat passenger at that time through the algorithm, the head, neck and chest injury grade probability is compared with the originally set threshold value, and if the head, neck and chest injury grade probability exceeds the threshold value, the vehicle-mounted computer sends out distress call information.
The above embodiments are only used for illustrating the design idea and features of the present invention, and the purpose of the present invention is to enable those skilled in the art to understand the content of the present invention and implement the present invention accordingly, and the protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes and modifications made in accordance with the principles and concepts disclosed herein are intended to be included within the scope of the present invention.

Claims (4)

1. A method for predicting injury of rear-row passengers and calling for help externally under frontal collision is characterized by comprising the following steps:
s1, acquiring images of a rear seat of a vehicle, judging whether a passenger is in the rear seat, if so, turning to S2, otherwise, ending;
s2, transmitting a signal to a vehicle-mounted computer according to an automobile collision intensity signal detected by a collision sensor when the automobile collides, and judging whether the automobile collides frontally;
s3, by
Figure FDA0003683186090000011
Calculating the speed variation, t, during a frontal collision 1 As acceleration start time, t n The acceleration ending time, t is the current moment, and a (t) is the acceleration;
s4, respectively obtaining head evaluation indexes HIC of rear-row passengers based on speed variation in the frontal collision process 15 Neck evaluation index N ij Chest evaluation index D max (ii) a According to the head evaluation index HIC of the rear-row passenger 15 Neck evaluation index N ij Chest evaluation index D max Respectively obtaining the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability of the passengers in the back row;
s5, respectively setting threshold values of the head AIS injury level probability, the neck AIS injury level probability and the chest AIS injury level probability, and judging whether calling for help is needed according to the threshold values, the head AIS injury level probability of the rear passengers, the neck AIS injury level probability and the chest AIS injury level probability;
the head evaluation index HIC of the rear passenger is calculated in the step 4 15 Neck evaluation index N ij Chest evaluation index D max The method comprises the following steps of carrying out regression analysis on the injury degree of the head, the neck and the chest and the automobile speed variation during frontal collision to respectively obtain:
head evaluation index HIC 15 Fitting formula:
HIC 15 ＝-1979.859+57.521Δv
neck evaluation index N ij Fitting formula:
N ij ＝0.239+0.014Δv
chest evaluation index D max Fitting formula:
D max ＝1.786+0.761Δv
wherein Δ v is the velocity change amount;
in the step 4, the method for calculating the AIS injury level probability of the head, the neck and the chest of the back-row passenger comprises the following steps:
head AIS injury level probability:
Figure FDA0003683186090000021
neck AIS injury level probability:
Figure FDA0003683186090000022
AIS injury level probability of the thorax:
Figure FDA0003683186090000023
wherein e is an irrational number.
2. The method for predicting the injury and calling for help of the passengers in the back row under the head-on collision according to claim 1, wherein the method for respectively calculating the head AIS injury level probability, the neck AIS injury level probability and the AIS injury level probability threshold of the chest comprises the following steps:
aiming at the head AIS injury level probability, substituting the speed variation quantity corresponding to the maximum limit value of 46km/h into a head AIS injury level probability calculation formula to obtain a threshold value of 0.29 as the head AIS injury level probability threshold value;
aiming at the neck AIS injury level probability, substituting the speed variation quantity corresponding to the maximum limit value as 95km/h into a neck AIS injury level probability calculation formula to obtain a threshold value of 0.48 as the neck AIS injury level probability threshold value.
Aiming at the AIS injury level probability of the chest, substituting the speed variation amount corresponding to the maximum limit value into the AIS injury level probability calculation formula of the chest to obtain a threshold value of 0.13 as the AIS injury level probability threshold of the chest.
3. The system for predicting the injury of the rear-row passengers and calling for help externally in the case of frontal collision as claimed in claim 1, which is characterized by comprising an automobile monitoring device, wherein the automobile monitoring device comprises a three-axis acceleration sensor, a camera, a collision sensor and a GPS module. The system comprises a triaxial acceleration sensor, a collision sensor, a camera and a GPS module which are all connected with a vehicle-mounted computer, wherein a collision module is arranged in the vehicle-mounted computer, and a head AIS injury level probability calculation method, a neck AIS injury level probability calculation method, a chest AIS injury level probability calculation method, a head AIS injury level probability threshold, a neck AIS injury level probability threshold and a chest AIS injury level probability threshold are preset in the collision module; and the vehicle-mounted battery respectively supplies power to the triaxial acceleration sensor, the camera, the collision sensor, the GPS module and the vehicle-mounted computer.
4. The system for predicting the injury of the passengers in the rear row under the frontal collision and calling for help for others as claimed in claim 3, wherein the camera is installed in the vehicle, and the vehicle-mounted computer is used for identifying whether the passengers exist in the rear row of the vehicle; judging whether the frontal collision of the automobile occurs or not through data transmitted to an on-board computer by a collision sensor; the vehicle information is collected in real time by the triaxial acceleration sensor, the collected information is transmitted to the vehicle-mounted computer, the vehicle-mounted computer calculates the speed value when collision occurs according to the acceleration cumulant through an algorithm, the vehicle-mounted computer obtains the injury grade probability of the head, the neck and the chest of the rear seat passenger at that time through the algorithm, compares the injury grade probability with the originally set threshold value, and sends out distress call information if the injury grade probability exceeds the threshold value.
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