CN110210090A - Motor vehicle accident analysis method based on uncertainty theory and genetic algorithm - Google Patents
Motor vehicle accident analysis method based on uncertainty theory and genetic algorithm Download PDFInfo
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Abstract
The motor vehicle accident analysis method based on uncertainty theory and genetic algorithm that the invention discloses a kind of, the method reproduce scene when accident occurs for reduction motor vehicle by Data Management Analysis.This method passes through the collected data in the scene of the accident first and establishes speed prediction model, uncertain for input parameter carries out speed uncertainty evaluation, obtain the value interval of car crass speed, whether exceed the speed limit for accurate judgement automobile, optimum collision speed is solved with genetic Optimization Algorithm, finally combines Computer Simulation and injury of human contrast verification.Computational accuracy and reliability can be improved in automobile and electric bicycle accident reconstruction in the present invention, it to accident responsibility judgement and traffic accident prevention important in inhibiting, while may be that automobile and electric bicycle manufacturer provide fundamental basis in safety Design, provide reference frame for establishing and improve for traffic safety relevant laws and regulations.
Description
Technical field
The invention belongs to data analysis and emulation technologies, are specifically related to a kind of based on uncertainty theory and genetic algorithm
Motor vehicle accident analysis method.
Background technique
Because electric bicycle is provided simultaneously with traditional bicycle light and flexible and the quick advantage of motorcycle economy,
Demand increases year by year, and with flourishing for electric bicycle industry, China's electric bicycle industry size has leapt to the world the
One.At the same time, automobile becomes increasingly conspicuous with e-bike traffic accident, is related to electric bicycle accident and number and injures and deaths occur
Number is in rise year by year trend, seriously affects traffic order, causes strong social influence.Automobile is touched with electric bicycle
Frequent Accidents are hit, automobile and electric bicycle, the mutual collision for cycling the human world are related to.It is covered at present in processing without road monitoring
When the electric bicycle accident in section, identification method is more single, and there are many difficulties and master with regard to divisions of responsibility etc.
The property seen influences, and being limited to the acquisition of scene of the accident data, there are errors, often there is biggish error in speed identification, divisions of responsibility
It is commonly present larger dispute.
Therefore accident process is analyzed, suitably uses exemplary formula, the speed calculation method for the science of probing into is objective true
Accident process is reproduced on the spot, to accident responsibility judgement and traffic accident prevention important in inhibiting, while may be automobile
It provides fundamental basis with electric bicycle manufacturer in safety Design, mentioned for establishing and improve for traffic safety relevant laws and regulations
Foundation for reference.
Summary of the invention
Goal of the invention: for deficiency of the above-mentioned prior art in processing traffic accident, the present invention is intended to provide a kind of base
In the motor vehicle accident analysis method of uncertainty theory and genetic algorithm, realizes the data acquisition of the scene of a traffic accident and test
Card, improves the accuracy of speed prediction.
Technical solution: a kind of motor vehicle accident analysis method based on uncertainty theory and genetic algorithm, including it is as follows
Step:
(1) scene of a traffic accident data are acquired, including cyclist throws away from Lp, friction coefficient μ, equivalent matter between human body and road surface
Heart height Hp, collision cast angle, θ；
(2) scene of the accident data are based on, speed prediction model is established, calculate motor vehicle speed value when accident occurs；
(3) uncertainty evaluation of speed, including type A evaluation and type B evaluation are divided, it calculates motor vehicle and accident occurs most
Good collision speed value interval；
(4) speed interval that accident is occurred for motor vehicle solves optimum collision vehicle by genetic algorithm as constraint condition
Speed；
(5) analog simulation is carried out according to optimum collision vehicle speed value, including accident is verified by FInite Element and multi-rigid body method
Field data obtains cause of accident and conclusion.
Further, in step (2) by electric bicycle and its cyclist throw away from preresearch estimates Automobile Collision Velocity
Calculation formula it is as follows:
In formula, mpFor cyclist's mass, mcFor car mass, meFor electric bicycle quality, Hp、HeRespectively cyclist with
The equivalent height of center of mass of electric bicycle, μ, f are respectively the coefficient of friction between cyclist, electric bicycle and road surface, θ, θeRespectively
For cyclist, electric bicycle throwing angle.
Uncertainty evaluation described in step (3) calculates as follows:
Measurement obtains vehicle and personnel's mass, g are acceleration of gravity, is thrown based on cyclist away from Lp, rub between human body and road surface
Wipe coefficient μ, equivalent height of center of mass Hp, collision cast angle, θ as uncertain factor progress uncertainty evaluation, impact velocity table
Up to formula are as follows:
vc=F (μ, θ, Hp、LP)
The propagation coefficient of each uncertain factor is as follows in above formula:
Step (4) includes following calculating process:
If objective function is F (L, V), wherein L is that electric bicycle or cyclist throw the set away from value, V after the accident
For the set of impact velocity, the best value interval of Automobile Collision Velocity obtained by uncertainty evaluation；After collision it is electronic from
Driving and automobile people throw away from as follows with practical impact velocity model the most identical:
Above formula be solve the electric bicycle solved based on genetic algorithm throw away from cyclist throw away from actual measurement
As a result the mathematical model of error between, for solving the Automobile Collision Velocity problem closest to true accident, the number of objective function
It is as follows to learn model:
In formula: vc、μ、f、θ、θe、Hp、HeIt is variable.
Step (5) is emulated by PC-Crash, including is modeled and collided according to scene of the accident data
Journey cycles human body posture information, electric vehicle cyclist's head injury HIC value calculates.
The utility model has the advantages that compared with prior art, significant effect exists, the present invention automobile and electric bicycle accident again
Computational accuracy and reliability can be improved in existing, to accident responsibility judgement and traffic accident prevention important in inhibiting, while
It can be that automobile and electric bicycle manufacturer provide fundamental basis in safety Design, are traffic safety relevant laws and regulations
Offer reference frame is provided.
Detailed description of the invention
Fig. 1 is the analysis flow chart diagram of the method for the invention；
Fig. 2 is automobile and electric bicycle Accident Characteristic analysis flow chart diagram in the present invention；
Fig. 3 is the calculation method structure chart of automobile and electric bicycle accident in the present invention；
Fig. 4 is accident speed calculation flow chart in the present invention；
Fig. 5 is flow chart of the present invention in casualty data emulation；
Fig. 6 is the flow chart of finite element model for solving casualty data of the present invention；
Fig. 7 is the flow chart that multi-rigid body method of the present invention solves casualty data.
Specific embodiment
In order to which technical solution disclosed in this invention is described in detail, done combined with specific embodiments below with Figure of description
It is further elucidated above.
Provided by the present invention is a kind of motor vehicle accident analysis method based on uncertainty theory and genetic algorithm, side
Method includes: to establish speed prediction model by the collected data in the scene of the accident, and uncertain for input parameter carries out vehicle
Whether fast uncertainty evaluation obtains the value interval of car crass speed, exceed the speed limit for accurate judgement automobile, with genetic optimization
Algorithm solves optimum collision speed, finally combines Computer Simulation and injury of human contrast verification.
The present embodiment is by taking automobile and electric bicycle accident as an example, and main steps are as follows:
Step 1: scene of the accident data acquire
Be finally stopped position including vehicle, glass for vehicle window fragment be scattered situation, vehicle braking trace, relate to thing vehicle correlation ginseng
Number, human body relevant parameter, road surface type and road type, weather conditions etc.；
Specifically, step 1 includes being analyzed according to accident characteristic, as shown in Fig. 2, including mainly according to the scene of the accident
Collected data judge the accident origin cause of formation, and classify to accident；Collision process is made corresponding it is assumed that and analyzing cycling
The motion process of people；In conjunction with the damage location of human body, the micromechanism of damage of cyclist is studied.
Step 2: establishing speed prediction model
Whether there is road monitoring covering according to accident pattern and the scene of the accident, establish Automobile Collision Velocity prediction model,
As shown in figure 3, the section for being mainly included in road monitoring uses the methods of frame-to-frame differences method such as to carry out speed calculating；In no road
Monitoring covering in the case where, by impulse principle establish speed computation model, based on road surface braking track and collision throw away from etc.
Information establishes speed computation model etc.；
Step 3: speed uncertainty evaluation
For the uncertainty for inputting parameter in speed prediction model, uncertainty evaluation is carried out respectively, by uncertain
Degree synthesis, extension, obtain automobile optimum collision speed value interval, as shown in Figure 4.
Step 4: genetic algorithm solves optimum collision speed
Using the optimum collision speed value interval obtained by uncertainty evaluation as constraint condition, genetic algorithm is utilized
Best speed solution is carried out, as shown in figure 5, main includes establishing speed optimization object function, and encoded, creates initial kind
Group, calculates the fitness of population, by genetic manipulation, such as selects, intersects, makes a variation to meet termination condition, to obtain most
Good collision speed；If being unsatisfactory for termination condition, steps be repeated alternatively until identical；
Step 5: Computer Simulation
Computer Simulation is carried out using the best car crass speed solved by genetic algorithm as input parameter.It is main
It is divided into FInite Element and multi-rigid body method, as shown in Figure 6 and Figure 7.It is main include establish automobile, cyclist, electric bicycle touch
Model is hit, corresponding simulation parameter is set and is solved.
FInite Element, main includes establishing automobile and electric bicycle geometrical model, and carry out grid dividing, then to stroke
Point complete model carry out position components, material and attribute setting, connection setting, load setting, constraint setting, calculate and it is defeated
Setting etc. out, and corresponding solver is submitted to be calculated.It extracts calculated result and imports the poster processing soft, analysis result,
Accident reconstruction is completed if with practical coincide, if misfitting, adjusting parameter repeats aforesaid operations；
Multi-rigid body method mainly includes establishing automobile and electricity according to the scene of the accident and the collected accident information of other approach
Dynamic bicycle and cyclist's multi-rigid model, are arranged relevant parameter, such as the initial velocity of vehicle, collision angle and use PC-
Crash carries out simulation calculation.Analysis result completes accident reconstruction if with practical coincide, if misfitting, adjusting parameter
Repeat aforesaid operations；
Step 6: injury of human situation comparative analysis, including head injury analysis, thoracic injury analysis, lower extremity injury point
Analysis etc..
Step 7: vehicle damage situation comparative analysis, including automobile rearview mirror, bonnet, windshield, bumper equipotential
Set degree of impairment and electric bicycle body degree of impairment.
Step 8: people's vehicle is finally stopped position versus analysis, after accident, automobile, electric bicycle, between cyclist
Relative position analysis.
Step 9: test of many times is until obtaining the simulation result the most identical with actual accidents.
Step 10: exporting final Automobile Collision Velocity, automobile and electric bicycle accident reconstruction are completed.
Specifically, complex chart 1- content shown in Fig. 7, the processing of the method for the invention and analytic process are as follows:
1.1 Automobile Collision Velocity preresearch estimates
City suburbs or backroad are often not covered with monitoring device, before can not solving car crass using video image
Speed.At this point it is possible to find out its relationship with Automobile Collision Velocity by the analysis left trace in the scene of the accident, establish phase
Mathematical model is answered to solve Automobile Collision Velocity.
It, can be by the throwing of electric bicycle or cyclist away from foundation when live automobile brake trace can not be measured accurately
Car crass speed solving model.Automobile and electric bicycle crash event are complicated, but if by electric bicycle and its
Cyclist is reduced to particle, and the projectile motion model of particle can be established further according to projectile motion formula, thus can be with
Relatively simple speed before calculating collision.
It is as follows that the method away from preresearch estimates Automobile Collision Velocity is thrown using electric bicycle and its cyclist:
In formula, mpFor cyclist's mass, mcFor car mass, meFor electric bicycle quality, Hp、HeRespectively cyclist with
The equivalent height of center of mass of electric bicycle, μ, f are respectively the coefficient of friction between cyclist, electric bicycle and road surface, θ, θeRespectively
For cyclist, electric bicycle throwing angle.
1.2 Automobile Collision Velocity uncertainty evaluations
During establishing automobile and electric bicycle accident speed appraising model, if having been made to reduce model complexity
It does it is assumed that the value of correlated inputs parameter (attachment coefficient, position of collision between such as vehicle tyre and road surface) is only led in model
Measurement or empirical estimating are crossed, and there is certain influence to the accuracy for solving car crass speed in these parameters, solve
Automobile Collision Velocity will have certain error.It is therefore desirable to carry out uncertainty evaluation to relevant parameter, so that defeated
In the case where entering parameter in the presence of uncertainty, it is still able to maintain higher solving precision, is touched to improve automobile with electric bicycle
Hit the reproducing reliability of accident.
There are two types of the common assessment methods of standard uncertainty, i.e. type A evaluation and type B evaluation.
The 1.3 speed calculation methods based on genetic algorithm
Error caused by each uncertain factor can preferably be found out using uncertainty theory, to Automobile Collision Velocity into
The best value interval of the available collision speed of row uncertainty evaluation, but the value is in when section speed limit occurs for accident
When in section, it tends to be difficult to judge whether automobile drives over the speed limit.
Genetic algorithm (Genetic Algorithm) is the adaptive probability optimization skill of a kind of reference natural selection and evolution
Art, abbreviation GA, it is the method for a kind of global random searching and optimization, can search for the optimal of multiple targets on a large scale simultaneously
No matter solution is all widely used in terms of modeling or solving practical problems, can use genetic algorithm in the value interval
Inside solve optimum collision speed.
1.4 electric bicycles and cyclist's model
After the completion of optimum collision speed solves, can by the movement in accident of analysis electric bicycle and cyclist and
The reliability of degree of impairment verifying speed calculation method.Electric bicycle and its multi-rigid body of cyclist are established in PC-Crash
Model.Regard human body each section as shape size different rigid body, connected between each other by rotary joint, herein using
Verifying model through being obtained by developer's cadaver test, it is rigid comprising 24, head, trunk, pelvis, upper limb, lower limb and foot etc.
Body；Electric bicycle mainly includes the positions such as handle, vehicle frame, front and back wheel, seat, battery, and each position is connected by a hinge, passes through
Measure available electric bicycle each section geometric parameter.
Embodiment 2
Driver's first drives certain type car and travels from east to west along 104 township roads, until when neighbouring backroad intersection, and drives
The second of electric bicycle from south to north is sailed to collide, in accident, electric bicycle cyclist cranium brain is dead, automobile and it is electronic from
There is damage in various degree, the non-covering path monitoring in incident region in driving.According to police investigation information, scene of the accident photo,
And accident situ map is it is found that it is dry concrete road surface that section, which occurs, for the accident, is separately loaded with a passenger on car, it is electronic from
Driving is not loaded with other people.
After the accident, car head Xi Weidong stops at 104 township road road center positions to the west, and field ground leaves its length
The braking track of 2m, trace starting point is apart from its static rear left rear wheel about 12m.It relates to the electronic headstock Bei Weinan of thing and is stuck in car front-body
Before, field ground leaves its scratch that falls down to the ground, scratch starting point tail portion about 9m after parking car, and cyclist is thrown to car front-body
Right front, is finally stopped position away from electric bicycle scratch starting point about 18.5m, whole according to the accident vehicle information car that weighs
Standby quality 1380kg, electric bicycle quality 74.5kg.By accident section test can obtain automobile, electric bicycle with
Attachment coefficient between road surface relates to thing vehicle essential information and is shown in Table 1.
1 automobile of table and electric bicycle essential information
It brings above- mentioned information into cyclist to throw away from-impact velocity model, solves automobile equivalent impact speed vc1=
52.82km/h。
2.2 uncertainty evaluation
Observing and nursing (1), vehicle and personnel's mass can be obtained by measuring in formula, and acceleration of gravity is constant, value
For 9.8m/s2, altogether include 4 uncertain parameters, respectively cyclist throws away from Lp, friction coefficient μ, equivalent matter between human body and road surface
Heart height Hp, collision cast angle, θ.To probe into influence of these parameters to impact velocity, these parameters can be regarded as not really
Determine the factor and carry out uncertainty evaluation, model (1) can be rewritten as:
vc=F (μ, θ, Hp、LP) (3)
The propagation coefficient of each uncertain factor is as follows in formula (3):
Take its Coverage factor k under normal distribution value 0.9544pIt is 2, each uncertainty factor evaluation result is carried out
Summarize, as shown in table 2:
2 car crass speed uncertainty evaluation table of table
According to error estimate formula theory, equivalent impact speed vcRelated combined standard uncertaintyAre as follows:
The then opposite expanded uncertainty of automobile equivalent impact speed are as follows:
U '=kpU ' (v)=2.48%
According to cyclist throw away from-impact velocity model required by optimized vehicle speed value range are as follows:
It is maximum from the uncertainty propagation coefficient that can be seen that friction coefficient μ between cyclist and road surface in calculated result, be
11.075, illustrate that the parameter has an important influence automobile and the solving precision of electric bicycle collision speed.Automobile etc.
The opposite expanded uncertainty for imitating impact velocity is 2.48%, is much smaller than 5%, illustrates uncertainty evaluation method to collision speed
It calculates error and plays good control action.
2.3 genetic algorithm optimizations solve best Automobile Collision Velocity
It is into one by being evaluated to have obtained the optimum valuing range of automobile equivalent impact speed to each uncertain parameter
Step improves accident reconstruction precision, accurate to determine whether automobile exceeds the speed limit, and regards the equivalent collision speed of automobile as variable, when variable determines
Afterwards, it also needs to determine constraint condition.
In automobile and electric bicycle collision accident, due to the unstability of electric bicycle body structure, hit huge
Motion state will change moment under the action of hitting power, and electric bicycle, which will contact to earth, to be slid and generate scratch on road surface.It will fall down to the ground
Electric bicycle afterwards moves to scratch starting point and is positioned, then righting car body, and making contact point will be projected on electric bicycle
On front and back wheel line, collision can be positioned in conjunction with automobile and electric bicycle damage position and shape, position occurs, and then
Accurately measure electric bicycle and its cyclist throw away from.
Impact velocity optimization problem can be described are as follows: give an objective function F (L, V), wherein L is accident
Electric bicycle or cyclist throw the set away from value afterwards, and V is the set of impact velocity, i.e., the vapour obtained by uncertainty evaluation
The best value interval of vehicle impact velocity.
For solve enable to collision after electric bicycle and automobile people throw away from practical impact velocity the most identical,
Model (1), (2) can be deformed into:
Formula (8) be solve the electric bicycle solved based on genetic algorithm throw away from cyclist throw away from actual measurement
As a result the mathematical model of error between, for solving the Automobile Collision Velocity problem closest to true accident, objective function can be with
It is described with following mathematical model:
V in formulac、μ、f、θ、θe、Hp、HeIt is variable.Defining target Population Size is 100, iteration 80 times, is restrained
Journey.
As can be seen that under using the impact velocity after genetic algorithm optimization, electric bicycle and cyclist throw away from reality
Border error is minimum, and control errors illustrate that genetic algorithm plays good effect of optimization in 0.05m or so.
Gained optimal solution, which is calculated, using genetic algorithm is shown in Table 3:
3 genetic algorithm optimal solution of table
3PC-Crash emulation and contrast verification
3.1PC-Crash emulation
To verify above method reliability, this section will carry out emulation mould to the accident generating process with PC-Crash software
It is quasi-.Accident section road model is established according to scene of the accident photo, accident situ map and satellite map.Road model is believed substantially
Breath is shown in Table 4:
4 accident road parameters of table
Relating to thing vehicle is 2013 sections of Buick Excelle GT, measures to obtain its geometric parameter to real vehicle, is loaded into
Approximate vehicle and it is arranged relevant parameter (such as automobile appearance, quality, occupant's situation) in PC-Crash database, establishes vehicle mould
Type.To make simulation result and reality coincide, after the completion of the setting of vehicle basic parameter, also need to vehicle drive scheme, traveling speed
The driving such as degree, deceleration, brake factors dynamic is configured.
After the completion of accident road, automobile, electric bicycle and its cyclist's model buildings, by vehicle, electric bicycle and
Its cyclist places suitable position, constantly adjusts relative position, movement velocity, collision angle, automobile tire and ground between each model
The parameters such as coefficient of friction are finally wanted so that error reduces as far as possible between face attachment coefficient, electric bicycle and its cyclist and ground
Simulation result is asked to match with scene of the accident trace, it being capable of accurate reproduction accident generating process.
Observation relates to thing damaged vehicle situation, it can be found that bonnet damaged location is located approximately at longitudinal vehicle axis, and electronic
The bicycle longitudinal axis and automotive ordinate axis near normal, therefore can substantially determine that automotive front end and electric bicycle right side occur to hang down
Straight collision.50 simulation tests are carried out with PC-Crash, when simulation parameter such as table 5 is set, it can be found that emulation gained knot
Fruit and the true scene of the accident coincide the most.
The setting of 5 simulation parameter of table
The analysis of 3.2 collision process cyclist's athletic postures
It, can be in conjunction with the athletic posture in cyclist's collision process by cyclist's degree of impairment in analysis collision process
Restore automobile and electric bicycle collision accident generating process.The comprehensive accelerating curve of cyclist's right lower extremity is extracted, it can be found that
In t=0.099s, acceleration suffered by shank is steeply risen to peak-peak 3351.99m/s on the right side of cyclist2, may infer that this
When electric bicycle cyclist collide for the first time with automobile.
Cyclist continues to hit automobile under effect of inertia, extracts the comprehensive accelerating curve of the right femur of cyclist, Ke Yifa
Now and then in t=0.102s, acceleration sharp increase suffered by femur, can to 1 195.59m/s2 of high peaks on the right side of cyclist
To infer femur and car collision on the right side of cyclist at this time.
It extracts and cycles the comprehensive accelerating curve of head part, it can be found that it is anxious to cycle head part's comprehensive acceleration when t=0.15s
Play, which rises, reaches peak value 1472.03m/s2, may infer that electric bicycle cycles head part at this time and touches for the first time with automobile
It hits.
The evaluation of 3.3 electric bicycle cyclist's head injuries
Select head injury (HIC) value as electric bicycle cyclist's Damage Evaluation index, calculate HIC it can be found that
In t=0.165s, cyclist HIC reaches peak-peak 3183.36, is shown in Table 6.
HIC value when 6 peak-peak of table
It cycles to hit suffered by head part as t=1.719s and reaches the second peak value, HIC=551.12 is shown in Table 7.
HIC value when 7 second peak value of table
It can thus be appreciated that HIC value (HIC=when peak-peak, i.e., when cycling head part and windshield collide
3183.86) it is far longer than the security limit (HIC=1000) that human body is able to bear shocking damage, is to cause cyclist dead
The main reason for, craniocerebral injury also is died of with cyclist in judicial expertise result and is matched, and the reliability of simulation result is demonstrated.
3.4 car body damage and people's vehicle are finally stopped relative position contrast verification
By emulation it can be seen that cyclist's shank is first contacted with automotive front end after collision generation, moment generates huge
Impact force, under effect of inertia, do coiling moves and swings to automobile engine cover, subsequent stock basin, right lateral thigh to cyclist above the waist
And arm and automobile engine cover collide, impact force makes air-inlet grille for automobile upper end position recess to the right.
In t=0.15s, cycle head part and windshield and bump against, contacted with back part with windshield and after
It is continuous to slide backward.
Equally, windshield damage position also fits like a glove, and sufficiently demonstrates the validity of simulation result.
After collision, electric bicycle is stuck in immediately ahead of automobile, parallel with automotive front end contour line, in scene photograph
Two vehicles are finally stopped position and coincide.Electric bicycle in emulation, which is measured, with measurement facility is finally stopped position away from collision generation position
About 14.38m measures electric bicycle from the scene of the accident and falls down to the ground scratch length as 13.671m；In emulation cyclist be finally stopped in
In front of Automobile Right, position 18.98m occurs away from collision, measures cyclist final position away from position of collision 18.5m from the scene of the accident.
To embody the superiority for carrying out automobile and electric bicycle accident reconstruction method using genetic algorithm, using without not
The collision speed of degree of certainty evaluation and genetic algorithm optimization processing emulate under the same terms, and simulation result is as shown in table 8.
The comparison of 8 simulation result of table
Simulation result and field measurement data are compared it can be found that inputting the simulation result that collision speed after optimization obtains
In, cyclist, which collides, to be thrown away from being 2.59% with actually measured throw away from error, and it is 1.91% that electric bicycle collision, which is thrown away from error,；And
When inputting not optimized collision speed and being emulated, cyclist is thrown away from being 6.59% with actual error, electric bicycle throw away from
With actual error be 7.47%, significantly larger than speed optimization after simulation result.Therefore, the invention proposes automobile and it is electronic from
Driving accident reproducting method has higher precision and better reliability.
Show that uncertainty evaluation method proposed by the invention calculates error to collision speed and rises by above embodiments
Good control action is arrived.Also, the automobile based on uncertainty theory and genetic algorithm and electric bicycle accident reconstruction
Method can acquire optimum collision speed estimating in vehicle speed intervals.Final test shows relative to not optimized traditional vehicle
Fast calculation method, the method for the invention can improve playback accuracy 4%~6%.Accident reconstruction can be more accurately carried out, it is right
Automobile is identified with electric bicycle accident speed and divisions of responsibility is of great significance.
Claims (5)
1. a kind of motor vehicle accident analysis method based on uncertainty theory and genetic algorithm, it is characterised in that: including as follows
Step:
(1) scene of a traffic accident data are acquired, including cyclist throws away from Lp, friction coefficient μ, equivalent mass center are high between human body and road surface
Spend Hp, collision cast angle, θ；
(2) scene of the accident data are based on, speed prediction model is established, calculate motor vehicle speed value when accident occurs；
(3) uncertainty evaluation of speed, including type A evaluation and type B evaluation are divided, it calculates motor vehicle and most preferably touching for accident occurs
Speed of colliding value interval；
(4) speed interval that accident is occurred for motor vehicle solves optimum collision speed by genetic algorithm as constraint condition；
(5) analog simulation is carried out according to optimum collision vehicle speed value, including the scene of the accident is verified by FInite Element and multi-rigid body method
Data obtain cause of accident and conclusion.
2. the motor vehicle accident analysis method according to claim 1 based on uncertainty theory and genetic algorithm, special
Sign is: in step (2) by electric bicycle and its cyclist throw away from preresearch estimates Automobile Collision Velocity calculation formula
It is as follows:
In formula, mpFor cyclist's mass, mcFor car mass, meFor electric bicycle quality, Hp、HeRespectively cyclist with it is electronic
The equivalent height of center of mass of bicycle, μ, f are respectively the coefficient of friction between cyclist, electric bicycle and road surface, θ, θeRespectively ride
Vehicle people, electric bicycle throwing angle.
3. the motor vehicle accident analysis method according to claim 1 based on uncertainty theory and genetic algorithm, special
Sign is: uncertainty evaluation described in step (3) calculates as follows:
Measurement obtains vehicle and personnel's mass, g are acceleration of gravity, is thrown based on cyclist away from Lp, coefficient of friction between human body and road surface
μ, equivalent height of center of mass Hp, collision cast angle, θ as uncertain factor progress uncertainty evaluation, impact velocity expression formula
Are as follows:
vc=F (μ, θ, Hp、LP)
The propagation coefficient of each uncertain factor is as follows in above formula:
4. the motor vehicle accident analysis method according to claim 1 based on uncertainty theory and genetic algorithm, special
Sign is: step (4) includes following calculating process:
If objective function is F (L, V), wherein L is that electric bicycle or cyclist throw the set away from value after the accident, and V is to touch
The set for hitting speed, the best value interval of Automobile Collision Velocity obtained by uncertainty evaluation；Electric bicycle after collision
And automobile people throws away from as follows with practical impact velocity model the most identical:
Above formula be solve the electric bicycle solved based on genetic algorithm throw away from cyclist throw away from actual measured results
Between error mathematical model, for solve closest to true accident Automobile Collision Velocity problem, the mathematical modulo of objective function
Type is as follows:
In formula: vc、μ、f、θ、θe、Hp、HeIt is variable.
5. the motor vehicle accident analysis method according to claim 1 based on uncertainty theory and genetic algorithm, special
Sign is: step (5) is emulated by PC-Crash, including carries out modeling and collision process according to scene of the accident data
Cycle human body posture information, electric vehicle cyclist's head injury HIC value calculates.
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