CN109738205B - Passenger protection method integrating automatic emergency braking of vehicle and safety air bag system - Google Patents
Passenger protection method integrating automatic emergency braking of vehicle and safety air bag system Download PDFInfo
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- CN109738205B CN109738205B CN201910020502.3A CN201910020502A CN109738205B CN 109738205 B CN109738205 B CN 109738205B CN 201910020502 A CN201910020502 A CN 201910020502A CN 109738205 B CN109738205 B CN 109738205B
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Abstract
The invention discloses a passenger protection method integrating automatic emergency braking of a vehicle and an air bag safety system, which comprises the following steps: establishing a reference model of an occupant restraint system; step two, testing the damage index of the reference model established in the step one; thirdly, predicting the head position of the passenger by using an SVM model; step four, judging the accuracy of the head position of the passenger predicted in the step three; and step five, when a collision accident occurs, setting the automatic emergency braking deceleration constraint condition by using the optimal protection area selected in the step four as the constraint condition. According to the passenger protection method integrating the automatic emergency braking of the vehicle and the safety airbag system, through the arrangement of the steps from one to five, the optimal control parameters are output to the braking system of the vehicle after the model is established and the damage is predicted, so that the braking system of the vehicle can protect passengers who are not wearing safety belts in a collision accident.
Description
Technical Field
The invention relates to a protection method, in particular to a passenger protection method integrating automatic emergency braking of a vehicle and an air bag system.
Background
With the increase of the degree of intellectualization of automobiles, more and more driving assistance systems are proposed and put to industrialization, including: a front collision early warning system, a lane departure early warning system, an adaptive cruise system, an automatic emergency braking system and the like. The automatic emergency braking system can automatically brake the vehicle based on the vehicle risk perception result at the current moment under the condition of no driver input, can effectively reduce collision loss, and is an intelligent driving auxiliary system for the key test of the current third-party evaluation mechanism.
During the research on the automatic emergency braking technology, although the system can significantly reduce the collision velocity of the vehicle, the large braking deceleration during braking may cause the upper torso portion of the human body to lean forward and move away from the normal position (out of position). Because current vehicle occupant restraint systems (e.g., seat belts and airbags) are designed based on sitting postures of normal occupants, if the occupant is out of position, the occupant restraint system is likely to fail to achieve the original protection effect and even cause more serious injury. For those who wear a harness, it is now possible to help improve the out-of-position sitting position by pre-tightening the harness in advance. However, for unbelted occupants, there is currently no effective occupant protection improvement.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a passenger protection method integrating automatic emergency braking of a vehicle and an air bag system, which is mainly used for solving the problem of protecting the out-of-position passenger who is not fastened with a safety belt under the action of the automatic emergency braking system and by combining the air bag system, and fills the blank of the existing method for solving the problem.
In order to achieve the purpose, the invention provides the following technical scheme: an occupant protection method for an integrated vehicle automatic emergency braking and airbag system, comprising the steps of:
establishing a reference model of an occupant restraint system;
step two, testing the damage index of the reference model established in the step one, judging whether the damage index is consistent with the test result, if so, continuing the next step, and if not, returning to the step one to reestablish the reference model;
thirdly, predicting the head position of the passenger by using an SVM model;
step four, judging the accuracy of the head position of the passenger predicted in the step three, judging whether the predicted accuracy exceeds 90%, selecting an optimal protection area if the predicted accuracy exceeds 90%, and returning to the step three for predicting if the predicted accuracy does not exceed 90%;
step five, when a collision accident occurs, the optimal protection area selected in the step four is used as a constraint condition, an automatic emergency braking deceleration constraint condition is set at the same time, an optimization objective function is solved under the two constraint conditions, the maximum collision speed reduction is solved, and optimization is carried out to obtain the optimal control parameter A of the emergency braking systempre_decelerationAnd Tbrake_timeInputting the obtained optimal control parameters into a brake system to drive the brake system to act;
wherein A ispre_decelerationFor optimal braking deceleration, Tbrake_timeThe optimal braking time is obtained.
As a further improvement of the present invention, the step of establishing the reference model of the occupant restraint system in the step one specifically includes the following steps:
step one, arranging an instrument panel, a steering wheel, an air bag, a dummy model, a safety belt model and an automobile seat model, wherein the instrument panel and the steering wheel adopt a multi-body dynamic model, and the air bag, the dummy model, the safety belt model and the automobile seat model adopt a limited unit model;
and step two, carrying out collection according to the models set in the step one to form a reference model.
As a further improvement of the present invention, the testing step in the second step specifically includes the following steps:
after a reference model is established, carrying out computer simulation on the model, and extracting damage indexes of all parts of the dummy;
step two, acquiring damage indexes suffered by the actual dummy through an actual trolley experiment;
and step two, comparing the damage indexes obtained in the step two and the step two, judging whether the two damage indexes are consistent, and completing the test of the damage indexes.
As a further improvement of the present invention, the injury index in the second step includes a head injury index, a chest injury index and a neck injury index, wherein the head injury index is calculated by the following formula:
in the formula, HIC15Is an index of head injury, t2-t1Is 15ms, PheadThe risk probability of head injury, t time of injury generation;
the chest injury index is calculated by the following formula:
in the formula, PchestD represents the chest compression amount of the dummy model, wherein the chest damage risk probability is shown as D;
the neck injury index is calculated by the following formula:
in the formula (I), the compound is shown in the specification,
Pneck_T，Pneck_Crespectively the probability of damage to the upper part of the neck, the probability of damage to the middle part of the neck and the probability of damage to the lower part of the neck, NijT, C, respectively, indicate the upper part of the neck, the middle part of the neck, and the lower part of the neck.
As a further improvement of the present invention, the step of predicting the position of the head of the occupant in the step three specifically includes the following steps:
step three, dividing the distance between the head of the passenger and the steering wheel into 5 sections, and defining the sections as areas 1-5 as labels in SVM classification;
and step two, setting different collision deceleration values by using a computer, carrying out simulation, acquiring training and verification data of the SVM, and then determining the label of the head position of the passenger according to the acquired training and verification data. As a further improvement of the present invention, the selecting step of the optimal protection area in the fourth step is as follows:
step four, respectively adjusting the head positions of the dummy model to the middle positions of 5 areas, and performing computer simulation;
step four, calculating a comprehensive damage function Pcombine＝1-(1-Phead)(1-Pneck)(1-Pchest) The size of (d);
step four and three, selecting PcombineAnd taking the minimum value as an optimal protection area.
The method has the advantages that through the arrangement of the first step to the fifth step, the corresponding reference model can be effectively established, then the established reference model is used, the position of the head of the passenger is predicted by utilizing the SVM model, the optimal protection area is selected, then the optimal protection area and the reference model are used as corresponding constraint conditions when a collision accident happens, the optimal control parameters are provided to drive the brake system to act, so that an effective protection effect is carried out on the passenger who is not tied with the safety belt on the vehicle, and the blank in the prior art is filled up
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FIG. 1 is a flow chart of the guarding method of the present invention.
Detailed Description
The invention will be further described in detail with reference to the following examples, which are given in the accompanying drawings.
Referring to fig. 1, the occupant protection method of the integrated automatic emergency braking and airbag system for a vehicle according to the present embodiment includes the steps of:
establishing a reference model of an occupant restraint system;
step two, testing the damage index of the reference model established in the step one, judging whether the damage index is consistent with the test result, if so, continuing the next step, and if not, returning to the step one to reestablish the reference model;
thirdly, predicting the head position of the passenger by using an SVM model;
step four, judging the accuracy of the head position of the passenger predicted in the step three, judging whether the predicted accuracy exceeds 90%, selecting an optimal protection area if the predicted accuracy exceeds 90%, and returning to the step three for predicting if the predicted accuracy does not exceed 90%;
step five, when a collision accident occurs, the optimal protection area selected in the step four is used as a constraint condition, an automatic emergency braking deceleration constraint condition is set at the same time, an optimization objective function is solved under the two constraint conditions, the maximum collision speed reduction is solved, and optimization is carried out to obtain the optimal control parameter A of the emergency braking systempre_decelerationAnd Tbrake_timeInputting the obtained optimal control parameters into a brake system to drive the brake system to act;
wherein A ispre_decelerationFor optimal braking deceleration, Tbrake_timeFor optimal braking time, in the process of using the passenger protection method in this embodiment, a function of presetting a control parameter can be effectively performed on a control system in a vehicle through the setting of the first step to the fourth step, then when a collision accident occurs during the driving of the vehicle by a driver, the previously preset control parameter is utilized to effectively protect the personnel who are not wearing the safety belt on the vehicle when the collision accident occurs, compared with the common control system in the prior art, the passenger who are not wearing the safety belt on the vehicle can be effectively protected when the collision accident occurs, a corresponding gap is filled, the problem that the personnel who are not wearing the safety belt fly out of the vehicle or are seriously injured due to collision caused by sudden braking when the collision accident occurs is avoided, wherein the first step to the fourth step in this embodiment can be divided into an early preparation stage, and step five is divided into actual application stages.
As an improved specific implementation manner, the step of establishing the reference model of the occupant restraint system in the step one specifically includes the following steps:
step one, arranging an instrument panel, a steering wheel, an air bag, a dummy model, a safety belt model and an automobile seat model, wherein the instrument panel and the steering wheel adopt a multi-body dynamic model, and the air bag, the dummy model, the safety belt model and the automobile seat model adopt a limited unit model;
and step two, the models set in the step one are collected to form a reference model, the set of the steps can effectively utilize a computer to simulate the existing collision test model, and then a computer unit is utilized to carry out a mode of multiple times of simulation, so that a reference model can be formed and used as a standard for subsequently judging the damage of the passengers in the collision accident process.
As a modified specific embodiment, the testing step in the second step specifically includes the following steps:
after a reference model is established, carrying out computer simulation on the model, and extracting damage indexes of all parts of the dummy;
step two, acquiring damage indexes suffered by the actual dummy through an actual trolley experiment;
and step two, comparing the damage indexes obtained in the step two and the step two, judging whether the two damage indexes are consistent, and completing the test of the damage indexes, so that the constructed reference model can be effectively verified, the reference model can be more accurately close to the existing actual condition, and the problem that the finally output optimal control parameters are not appropriate due to overlarge deviation between the reference model and the actual condition is avoided.
As a specific embodiment of the improvement, the injury index in the second step includes a head injury index, a chest injury index and a neck injury index, wherein the head injury index is calculated by the following formula:
in the formula, HIC15Is an index of head injury, t2-t1Is 15ms, PheadThe risk probability of head injury, t time of injury generation;
the chest injury index is calculated by the following formula:
in the formula, PchestD represents the chest compression amount of the dummy model, wherein the chest damage risk probability is shown as D;
the neck injury index is calculated by the following formula:
in the formula (I), the compound is shown in the specification,
Pneck_T，Pneck_Crespectively the probability of damage to the upper part of the neck, the probability of damage to the middle part of the neck and the probability of damage to the lower part of the neck, NijT, C represents the upper portion of neck respectively, the middle part of neck, the lower part of neck, so effectual carry out effectual computational analysis with the most important position damage condition of passenger in the collision accident to through the mode of the important position index of contrast, the effectual condition of pressing close to of judging benchmark model and actual test process avoids because the optimal parameter that the final acquisition that benchmark model and actual test difference lead to is not conform to actual conditions's problem.
As an improved specific embodiment, the step of predicting the position of the head of the occupant in the step three specifically includes the following steps:
step three, dividing the distance between the head of the passenger and the steering wheel into 5 sections, and defining the sections as areas 1-5 as labels in SVM classification;
step two, setting different collision deceleration values by using a computer, simulating to obtain training and verification data of the SVM, and then determining the label of the head position of the passenger according to the obtained training and verification dataThe reference model is then used to obtain a reference model of the unbelted occupant restraint system, specifically by removing the belt module before the reference model is used. The brake deceleration in the reference model is then set to simulate the brake deceleration of the emergency braking system. Set deceleration as ai0.1g, 1, 10, wherein g is 9.8m/s2The braking continuous deceleration time is 1s, the 10 groups of set values are simulated, and the braking deceleration value, the braking deceleration time and the area where the head of the passenger is located are recorded, so that a training and verification data set can be obtained. The obtained training set is trained using equations (4) - (7) to obtain a classification function f (x). Then, the classification effect of the classification function f (x) is verified by using a verification data set, and the ratio of the correctly classified samples to the verification aggregated samples is defined as the accuracy PcorrectIf P iscorrect>90%, the model is considered to be usable. If P iscorrect<90%, need readjust sigma and C in the SVM model, and retrain again, the precision of SVM meets the requirements, and need carry out SVM training operation at the in-process that carries out SVM prediction passenger position, the training process is: the classification process in the invention is a multi-classification process, for convenience of explanation, a two-classification problem is adopted to explain the training method, and the multi-classification problem can be analogized. For the SVM classification problem, an optimization problem solution can be formed:
and satisfies:
wherein α ═ (α)1,...αm) Representing a lagrangian factor vector; m represents a sample with m; c represents model parameters; x is the number ofiThe feature vector representing the ith sample, in this embodiment, is represented as the braking deceleration and the braking time length, yiA sample label indicating the i-th, in this embodiment, the region where the head of the occupant is located; k (x)i,xj)＝exp[-(xi-xj)*2σ2]Represents the kernel function and σ represents the kernel function parameters.
After the vector α is solved by the optimization function, ω and b are obtained by the formula, and the decision function f (x) is obtained.
Wherein S is the number of support vectors
f(x)＝sign(w*x+b*) (7)
In the formula (I), the compound is shown in the specification,
verifying the obtained model by using data samples except for m, readjusting parameters sigma and C of the SVM when the accuracy does not exceed 90%, and circularly repeating until the accuracy exceeds 90%, wherein the prediction model is considered to be accurate, and prediction can be performed after SVM training is completed, and the prediction process is as follows: when a new data (x) is obtainednew,ynew) The new data may then be classified using a decision function f (x).
As a specific embodiment of the improvement, the selecting step of the optimal protection area in the fourth step is as follows:
step four, respectively adjusting the head positions of the dummy model to the middle positions of 5 areas, and performing computer simulation;
step four, calculating a comprehensive damage function Pcombine＝1-(1-Phead)(1-Pneck)(1-Pchest) The size of (d);
step four and three, selecting PcombineThe minimum value is used as the optimal protection area, so that the optimal protection area can be effectively selected, and the control parameters can be referred according to the optimal protection area to obtain the optimal control parameters.
In summary, the protection method of the embodiment is based on the SVM machine learning algorithm, so as to better solve the problem of cooperative control between the automatic emergency braking system and the airbag system, improve the protection method for passengers who are not wearing a seat belt under the action of the automatic emergency system, and solve the problem of incompleteness of the existing method.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may occur to those skilled in the art without departing from the principle of the invention, and are considered to be within the scope of the invention.
Claims (5)
1. A passenger protection method of an integrated vehicle automatic emergency braking and safety air bag system is characterized in that: the method comprises the following steps:
establishing a reference model of an occupant restraint system;
step two, testing the damage index of the reference model established in the step one, judging whether the damage index is consistent with the test result, if so, continuing the next step, and if not, returning to the step one to reestablish the reference model;
thirdly, predicting the head position of the passenger by using an SVM model;
step four, judging the accuracy of the head position of the passenger predicted in the step three, judging whether the predicted accuracy exceeds 90%, selecting an optimal protection area if the predicted accuracy exceeds 90%, and returning to the step three for predicting if the predicted accuracy does not exceed 90%;
step five, when a collision accident occurs, the optimal protection area selected in the step four is used as a constraint condition, an automatic emergency braking deceleration constraint condition is set at the same time, an optimization objective function is solved under the two constraint conditions, the maximum collision speed reduction is solved, and optimization is carried out to obtain the optimal control parameter A of the emergency braking systempre_decelerationAnd Tbrake_timeAnd inputting the obtained optimal control parameters into the braking systemIn the system, a brake system is driven to act;
wherein A ispre_decelerationFor optimal braking deceleration, Tbrake_timeThe optimal braking time is obtained.
2. The occupant protection method of an integrated vehicle automatic emergency brake and airbag system according to claim 1, wherein: the step of establishing the reference model of the occupant restraint system in the first step specifically comprises the following steps:
step one, arranging an instrument panel, a steering wheel, an air bag, a dummy model, a safety belt model and an automobile seat model, wherein the instrument panel and the steering wheel adopt a multi-body dynamic model, and the air bag, the dummy model, the safety belt model and the automobile seat model adopt a limited unit model;
and step two, carrying out collection according to the models set in the step one to form a reference model.
3. The occupant protection method of an integrated vehicle automatic emergency brake and airbag system according to claim 1 or 2, wherein: the testing step in the second step specifically comprises the following steps:
after a reference model is established, carrying out computer simulation on the model, and extracting damage indexes of all parts of the dummy;
step two, acquiring damage indexes suffered by the actual dummy through an actual trolley experiment;
and step two, comparing the damage indexes obtained in the step two and the step two, judging whether the two damage indexes are consistent, and completing the test of the damage indexes.
4. The occupant protection method of an integrated vehicle automatic emergency brake and airbag system according to claim 1 or 2, wherein: the step of predicting the position of the head of the occupant in the third step specifically includes the following steps:
step three, dividing the distance between the head of the passenger and the steering wheel into 5 sections, and defining the sections as areas 1-5 as labels in SVM classification;
and step two, setting different collision deceleration values by using a computer, carrying out simulation, acquiring training and verification data of the SVM, and then determining the label of the head position of the passenger according to the acquired training and verification data.
5. The occupant protection method of an integrated vehicle automatic emergency brake and airbag system according to claim 4, wherein: the selection of the optimal protection area in the fourth step comprises the following steps:
step four, respectively adjusting the head positions of the dummy model to the middle positions of 5 areas, and performing computer simulation;
step four, calculating a comprehensive damage function Pcombine＝1-(1-Phead)(1-Pneck)(1-Pchest) The size of (d);
step four and three, selecting PcombineAnd taking the minimum value as an optimal protection area.
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| CN110766213A (en) * | 2019-10-15 | 2020-02-07 | 清华大学 | Automobile passenger collision damage prediction method and computer equipment |
| CN110851958B (en) * | 2019-10-16 | 2021-04-20 | 清华大学 | Collision severity prediction method for passenger injury risk |
| CN113188807B (en) * | 2021-02-05 | 2024-05-03 | 深圳大雷汽车检测股份有限公司 | Automatic abs result judging algorithm |
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