CN108320348A - The generation method and computer installation of traffic accident dynamic image, computer readable storage medium - Google Patents
The generation method and computer installation of traffic accident dynamic image, computer readable storage medium Download PDFInfo
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- CN108320348A CN108320348A CN201810121283.3A CN201810121283A CN108320348A CN 108320348 A CN108320348 A CN 108320348A CN 201810121283 A CN201810121283 A CN 201810121283A CN 108320348 A CN108320348 A CN 108320348A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/008—Registering or indicating the working of vehicles communicating information to a remotely located station
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
- G07C5/0866—Registering performance data using electronic data carriers the electronic data carrier being a digital video recorder in combination with video camera
Abstract
The present invention provides a kind of traffic accident dynamic image generation method, including obtaining data and accident vehicle geographical location information transmitted by the sensor on accident vehicle, data and geographical location information transmitted by sensor generate the dynamic image of accident vehicle in the event of an accident；According to the dynamic image generated, accident responsibility is determined, and accident responsibility assert that result is sent to preset terminal device.The computer installation of the present invention is provided with readable storage medium storing program for executing, computer program is stored on readable storage medium storing program for executing, and be performed and above-mentioned traffic accident dynamic image generation method may be implemented.The present invention can quickly generate the dynamic image of accident, and accident vehicle is avoided to be detained for a long time in the scene of the accident, while reducing traffic congestion, also ensure the personal safety of driver and conductor.
Description
Technical field
The present invention relates to road safety fields, specifically traffic accident dynamic when assert using traffic accident responsibility
Image generating method further relates to the computer installation and computer readable storage medium of realizing this method.
Background technology
As people's living standards have been gradually improved, vehicle has become the most important vehicles in people's life, purchase
The people of buying car is also more and more, however the frequency that traffic accident occurs also is being continuously improved, and especially vehicle rear-end collision accident accounts for
According to sizable ratio, and often result in the great number of casualties and economic loss.
The reason of most of rear-end collision is cannot to make warning rapidly after accident or failure occurs due to front truck or remove
Cause the vehicle at rear directly to knock into the back from scene and cause more, bigger traffic accident, or since accident vehicle warning is set
Standby differentiability is poor, with accident point at a distance of close, rear car without the enough reaction time, distance and cause more major break down.
After traffic accident occurs, after slight traffic accident especially occurs, many drivers are often at the scene
It waits for the scene inspection of traffic police department and judges accident responsibility, this often leads to accident vehicle and is detained scene, not only be easy to cause
Traffic congestion can also cause danger to the life security of driver and conductor.On the other hand, traffic police department depends merely on surveying in the scene of the accident
It tests and often fails quickly to judge accident responsibility, the in-situ processing time for being also easy to cause accident is longer.
And in recent years, with the development of car networking technology, more and more vehicles access car networking system, and car networking system is
By installing vehicle-mounted terminal equipment in vehicle instrument desk, realizes to vehicle all working situation and quiet, multidate information acquisition, deposits
It stores up and sends.In general, car networking system includes car-mounted terminal and cloud server, car-mounted terminal collection vehicle real time execution number
According to realizing to vehicle all working information and quiet, multidate information acquisition, storage and send.Vehicle-mounted terminal equipment includes a large amount of
Sensor, data collector, wireless sending module, include the operation row of driver for collection vehicle real time execution operating mode
For, power system operational supplemental characteristic etc..Cloud server receives and processes the information of vehicles that vehicle-mounted terminal equipment is acquired, and
Processing analysis is carried out to data.
However, existing car networking system is typically ex-post analysis to the processing of traffic accident, that is, traffic is occurring
After accident, the reason of by causing traffic accident to the analytical judgment of the running data of vehicle, this processing mode can not be
Early warning in advance, the generation that can not be avoided traffic accident.Due to present car networking system there is no when traffic accident occurs and
When peritropous vehicle send out warning information, cause subsequent vehicle that can not obtain front in time there is a situation where traffic accident,
It is easy to happen second accident.
Invention content
The main object of the present invention is to provide a kind of traffic accident dynamic image generation that can quickly determine accident responsibility
Method.
It is a further object of the present invention to provide a kind of computers for realizing above-mentioned traffic accident dynamic image generation method
Device.
Another object of the present invention is to provide a kind of computer for realizing above-mentioned traffic accident dynamic image generation method
Readable storage medium storing program for executing.
Main purpose to realize the present invention, traffic accident dynamic image generation method provided by the invention include obtaining thing
Therefore the data transmitted by the sensor on vehicle and accident vehicle geographical location information, data transmitted by sensor with
And geographical location information generates the dynamic image of accident vehicle in the event of an accident；According to the dynamic image generated, thing is determined
Therefore responsibility, and accident responsibility assert that result is sent to preset terminal device.
By said program as it can be seen that after traffic accident once occurs, cloud server can be by wireless network, such as 4G nets
Network etc. obtains the data of the sensor on accident vehicle, and obtains the geographical location information of accident vehicle, thus generates dynamic
Image, and automatically accident responsibility is determined according to dynamic image, and quickly it is sent to the end of the driver of accident vehicle
In end equipment.Since the transmission of accident responsibility protocol is automatically sent on preset terminal device by cloud server,
In this way, driver can receive accident responsibility protocol in very short time and quickly withdraw scene, driver is avoided for a long time
It is trapped in the scene of the accident, not only can also reduce the risk of casualties to avoid traffic congestion.
One Preferable scheme is that, acquired sensor is set on two or more accident vehicles；Generate Dynamic Graph
When picture, dynamic image is generated using the data of the sensor of two or more accident vehicles.
It can be seen that when accident is related to more accident vehicles, by the number for obtaining the sensor on more accident vehicles
According to, can more accurately generate the dynamic image of accident, to for determination responsibility more strong evidence is provided.
Further embodiment is, before generating dynamic image, also obtains the driving trace of accident vehicle；Generate dynamic image
When, also apply the driving trace of accident vehicle to generate dynamic image.
Optionally, before generating dynamic image, image scene of the accident vehicle after generation accident is also obtained；Generate Dynamic Graph
When picture, the image scene of accident vehicle is also applied to generate dynamic image.
Further scheme is, before generating dynamic image, also obtains the preset digital automobile model of accident vehicle；
When generating dynamic image, the digital automobile model of accident vehicle is also applied to generate dynamic image.
Further scheme is, before generating dynamic image, also obtains accident vehicle before generation accident in preset time
Traveling video information；When generating dynamic image, also application traveling video information generates dynamic image.
As it can be seen that before by using the picture of such as scene of the accident, the driving trace of accident vehicle, accident vehicle generation accident
Video information in preset time also uses the data such as digital automobile model to generate dynamic image, more can accurately calculate
It has automobile in the state before traffic accident occurs and when traffic accident occurs, to more accurately generate the dynamic of traffic accident
State image.In addition, since digital automobile model data is stored in advance in cloud server, in this way, cloud server can be with
The data for quickly obtaining digital automobile model, improve the efficiency for generating dynamic image.
Further embodiment is that the sensor being arranged on accident vehicle is 9D sensing systems.Due to 9D sensors system
System includes the multiple sensors such as triaxial accelerometer, three-axis gyroscope and three axis magnetometer, and the degree of freedom in 9 orientation is provided
Data, therefore stressing conditions when accident occurs for accident vehicle can be accurately calculated, to quickly generate dynamic image.
Further scheme is, after obtaining the data transmitted by the sensor on accident vehicle, is sent to nearby vehicle
Accident early warning information.
It can be seen that after determining generation traffic accident, cloud server can quickly peritropous vehicle be sent
Accident early warning information, allowing the driver of nearby vehicle to understand front in time, there is a situation where accidents, and driver is allowed to adopt in time
With measures to keep clear, then avoids that second accident occurs, ensure the safety of the driver and conductor on accident vehicle.
For the another object for being in realization, computer installation provided by the invention includes processor and computer-readable deposits
Storage media, computer-readable recording medium storage have computer program, processor to read and executed when running computer program
The traffic accident dynamic image generation method stated.
For a further object for being in realization, computer journey is stored on computer readable storage medium provided by the invention
Sequence, computer program are read out by the processor and execute above-mentioned traffic accident dynamic image generation method when running.
Description of the drawings
Fig. 1 is the structural schematic diagram using the traffic accident dynamic image generation method embodiment of the present invention.
Fig. 2 is the system block diagram using the traffic accident dynamic image generation method embodiment of the present invention.
Fig. 3 is the accident schematic diagram using the traffic accident dynamic image generation method embodiment of the present invention.
Fig. 4 is the scene of the accident schematic diagram using the traffic accident dynamic image generation method embodiment of the present invention.
Fig. 5 is the flow chart of traffic accident dynamic image generation method embodiment of the present invention.
The invention will be further described with reference to the accompanying drawings and embodiments.
Specific implementation mode
Beyond the clouds on server, which can connect for the traffic accident dynamic image generation method application of the present invention
The data transmitted by the sensor on accident vehicle are received, also, the geographical location information of accident vehicle can also be received.It is preferred that
, car networking prior-warning device is installed, and each prior-warning device can send warning information on vehicle, can also receive
The warning information that cloud server is sent out, and can be sent out by modes such as sound or light after receiving warning information
Warning message.
It is, therefore, to be understood that the traffic accident dynamic image generation method of the present invention operates on cloud server
Software program.In addition, the computer installation of the present invention can be cloud server, including a processor and computer-readable
Storage medium, the computer readable storage medium can be nonvolatile memory, such as EEPROM or FLASH, computer
The computer program for realizing above-mentioned traffic accident dynamic image generation method is stored on readable storage medium storing program for executing, but processor is read
And when running these programs, you can to realize above-mentioned traffic accident dynamic image generation method.
Traffic accident dynamic image generation method embodiment：
Referring to Fig. 1, system includes cloud server 12, high in the clouds used in the present embodiment traffic accident dynamic image generation method
Server 12 can receive the alarm signal that the prior-warning device 11 on vehicle 10 is sent out, it is preferred that prior-warning device 11 can be intelligence
The intelligent terminals such as energy mobile phone, tablet computer can also be to be integrated with global location chip, automobile data recorder, life-saving hammer, laser letter
The intelligent terminal of number source and wireless communication chips.
The information that cloud server 12 is reported in the accident of receiving, and determine and traffic accident and determining traffic thing occurs
Therefore scene after, warning information, the present embodiment can be sent out to other vehicles, such as prior-warning device 15 on vehicle 13
In, prior-warning device 15 is identical as 11 structure of prior-warning device, and identical function may be implemented.Also, prior-warning device 15 can be with
The information that cloud server 12 is sent out is received, such as directly receives the information that cloud server 12 is sent out, or is sent out by signal
It penetrates base station 14 and receives the information that cloud server 12 is sent out.
Preferably, it is provided with controller, locating module, radio receiving transmitting module etc. in prior-warning device 11, is additionally provided with early warning
Photographic device can also be arranged for shooting image, video information in information sending module certainly, in prior-warning device 11.Early warning
Device 11 can be to 12 transmission data of cloud server, such as sends captured video, image information, in order to avoid high in the clouds takes
Business device 12 receives a large amount of useless video, image information, can set only cloud server 12 and determine generation traffic accident
After, the video information before traffic accident occurs in preset time is obtained, as traffic accident regarding in 2 minutes in the past occurs
Frequency information.
Therefore, the photographic device on prior-warning device 11 can be arranged in vehicle and the front of face vehicle, shooting
On the one hand the video image of right ahead can obtain generation traffic accident to obtain the image information of right ahead
On the other hand the video information of moment can also obtain the video information that traffic accident occurs on running section.
The locating module of prior-warning device 11 can be GPS module or other modules with positioning function, for calculating
The specific location of prior-warning device 11, and the more specific location information of calculating is sent to controller.Since prior-warning device 11 is installed
In vehicle 10, therefore locating module is actually the specific location for obtaining vehicle 10.
The radio receiving transmitting module of prior-warning device 11 such as passes through for realizing the wireless communication between cloud server 12
GPRS network, 3G network or 4G networks send the signal to cloud server 12, and receive transmitted by cloud server 12
Information.Certainly, radio receiving transmitting module can also receive the wireless signal that signal transmitting base station 14 is sent out, for example, signal emits
What base station 14 was sent out is 2.4G number communications number, and mould of the setting one for receiving 2.4G number communications number is also required in prior-warning device 11
Block.
9D sensing systems 31, automobile data recorder 32 etc. are additionally provided on vehicle 10, automobile data recorder 32 is for shooting
The video in 10 front of vehicle, image information, it is preferred that the image captured by automobile data recorder 32 can be uploaded to cloud server
12, for example, automobile data recorder 32 be arranged wireless communication chips, by radio communication chip to cloud server 12 send video,
Image information.
Existing 9D sensing systems may be used in 9D sensing systems 31 comprising have triaxial accelerometer, three axis accelerometer
Instrument and three axis magnetometer, therefore, 9D sensing systems 31 are capable of providing the data of the degree of freedom in 9 orientation.Optionally, 9D is passed
An energy supply unit is also set up in sensor system 31（Such as hull cell）, energy collecting device and a wireless data
Converter.Therefore, 9D sensing systems 31 can determine current position by calculating magnetic field force and the motor pattern of the earth
Coordinate plays navigation function in the region that certain GPS navigation signals can not cover.
When traffic accident occurs for vehicle 10, since fierce shock, 9D sensing systems 31 often occur for vehicle 10
The angular speed of 10 3 axis of vehicle, i.e. X, Y and Z axis angular speed when can calculate shock, can also obtain X, Y and z axis adds
Speed, this carries out mechanics acquisition by triaxial accelerometer, three-axis gyroscope and three axis magnetometer and obtains, is hit to calculate
Dynamics and Vehicular impact position.Due to being provided with multiple sensors on vehicle 10, and the position of the installation of multiple sensors has one
Fixed difference will produce regular hour difference, can obtain Vehicular impact position by difference therein.
Also, since 9D sensing systems 31 integrate high-precision gyroscope, accelerometer, geomagnetic field sensors,
The calculation of Kalman's dynamic filter may be used after receiving the data that 9D sensing systems 31 are acquired in cloud server 12
Method, can rapid solving go out the real time kinematics posture of vehicle 10, the dynamic image that accident is accurately generated for cloud server 12 carries
Strong data are supplied.
It is wide that cloud server 12 is provided with dynamic image generation module 21, confirmation of responsibility module 22, sending module 23, accident
Broadcasting module 24 and digital automobile model library 25.Wherein, digital automobile model library 25 is previously stored with the digital automobile of vehicle 10
Model, for example, user inputs the model of automobile to cloud server 12 in advance, cloud server 12 can be from the production of automobile
Producer obtains the digital automobile model of the automobile of the model, the pattern number generated using digital automobile model as dynamic image
According to.
Dynamic image generation module 21 be used for generate accident occur when dynamic image, such as generate 3D dynamic image or
Person generates flat image.Dynamic image generation module 21 receives 9D sensing systems 31, automobile data recorder 32 and prior-warning device
Data transmitted by 11, and the data stored in digital automobile model library 25 are obtained, it is sent out using 9D sensing systems 31
The data for the multiple sensors acquisition sent, and using automobile data recorder 32 shoot before traffic accident occurs in the predetermined time
Video information, also obtain driving trace of the accident vehicle that is recorded of prior-warning device 11 before traffic accident occurs, generate and send out
Dynamic image when raw traffic accident.
Since 9D sensing systems 31 include a variety of sensings such as triaxial accelerometer, three-axis gyroscope and three axis magnetometer
Device, and the data for providing the degree of freedom in 9 orientation can be calculated and be hit using the data that 9D sensing systems 31 are acquired
The angular speed of 10 3 axis of vehicle, i.e. X, Y and Z axis angular speed, can also obtain X, Y and Z axis linear acceleration when hitting, to count
Calculate shock dynamics and Vehicular impact position.Certainly, if traffic accident is related to more automobiles, for example, be related to two automobiles or
More automobiles then need the data for acquiring the 9D sensing systems that more are related on the vehicle of traffic accident, to calculate
State and impingement position of each vehicle when traffic accident occurs, in order to more accurately generate the dynamic of traffic accident
State image.
Dynamic image when hitting is generated using 9D sensing systems 31 to have been applied in automobile impacting test, for example,
9D sensing systems are installed on tested automobile, and automobile impacting is calculated by acquiring the data of 9D sensing systems
When parameter, and generate dynamic image.Therefore, the present invention may be used existing 9D sensing systems and by acquiring 9D
The data of sensing system come generate traffic accident occur when dynamic image.
Certainly, the driving trace that vehicle can also be used when generating dynamic image, the geographical location that traffic accident occurs are believed
The information such as the later photo site of breath, generation traffic accident generate dynamic image, therefore, after sending traffic accident, drive
Member can shoot the picture of the scene of the accident by prior-warning device 11 or other terminal device, and by the picture of the scene of the accident
It is sent to cloud server 12, dynamic image generation module 21 can be using use site picture as the source number for generating dynamic image
According to.
After generating dynamic image, confirmation of responsibility module 22 will automatically generate accident responsibility protocol, for example, according to dynamic
State image determines whether act of violating regulations etc., and the responsibility of more accident vehicles can be determined according to dynamic image.Responsibility is recognized
Cover half block 22 can carry out confirmation of responsibility based on preset model.For example, preset such as knock into the back, make a dash across the red light, vehicle
It drives in the wrong direction, the confirmation of responsibility mode under a variety of different situations of compacting line lane change etc..As shown in Figure 3 and Figure 4, at the first moment
Under, vehicle 40 travels on respective track with vehicle 41, the dynamic image generated according to dynamic image generation module 21
It has been shown that, in the moment that traffic accident occurs, vehicle 40 enters the track where vehicle 41.At this point it is possible to according to preset
Database determines that vehicle 40 is all responsibility side, and vehicle 41 is without duty side.
For example, the photo site after acquisition accident, can obtain the mark etc. that ground when accident occurs for accident vehicle, such as
Whether ground is whether solid line, double amber lines or ground have other prohibitory signs etc..In addition, can be with by photo site
The accurate location for obtaining vehicle, to more accurately calculate the dynamic image of accident.
Certainly, if confirmation of responsibility module 22 can not obtain the data to match from preset database, also
It is that can not determine responsible party, then can be determined according to dynamic image by traffic police department each by the artificial judgement of traffic police department
The responsibility of accident vehicle.After the responsibility for determining each accident vehicle, confirmation of responsibility module 22 also generates traffic accident responsibility
Protocol, and preset terminal device is sent to by sending module 23, such as it is sent to the advance of accident vehicle 10
It on the terminal device of setting, that is, is sent on prior-warning device 11, generated confirmation of responsibility book is shown by prior-warning device 11.
In this way, after traffic accident occurs, the driver of accident vehicle 10 can obtain traffic thing in very short time
Therefore confirmation of responsibility book, driver can quickly withdraw scene, avoid being detained for a long time in the scene of the accident and leading to traffic congestion,
The risk that second accident occurs can also be reduced, to ensure the personal safety of driver and conductor.
In addition, dynamic image generation module 21 is after receiving the report information for sending traffic accident, and in determination
When traffic accident occurs, broadcast message can be sent to nearby vehicle by accident broadcast module 24, for example, obtaining accident vehicle
Location information, and other vehicles into accident vehicle periphery preset range, as other vehicles in 1 kilometer range are sent
Accident early warning information issues warning signal immediately after receiving warning information such as the prior-warning device 15 on vehicle 13, to prompt
Traffic accident occurs in front of driver, to avoid secondary accident occurs.
The flow of traffic accident dynamic image generation method is introduced with reference to Fig. 5.First, cloud server receives traffic
The information that accident reports executes step S1.For example, the abnormal data transmitted by the 9D sensing systems of a certain vehicle is received,
The abnormal data shows that fierce shock may occur for vehicle.Certainly, if only determining traffic accident by single data
Generation, then the case where there may be wrong reports, therefore can be in conjunction with after multiple warning messages, the just hair of determination traffic accident
It is raw.For example, can in conjunction with the driving trace of accident vehicle, the distress signals that prior-warning device is sent, the scene of the accident picture etc. it is more
A information.
After determining generation traffic accident, S2 is thened follow the steps, cloud server, which obtains to report, occurs traffic accident
Place, and to the information for the vehicle transmission accident early warning that traffic accident site periphery occurs, to prompt the driving of nearby vehicle
Traffic accident occurs for member front.
Then, step S3 is executed, cloud server obtains the data transmitted by the 9D sensing systems of accident vehicle, and
Obtain driving trace of the accident vehicle before traffic accident occurs in preset time, geographical location information, generation traffic accident with
The video information etc. in generation traffic accident for the previous period captured by rear photo site, automobile data recorder, also according to thing
Therefore the model of vehicle obtains the digital automobile model of accident vehicle from digital automobile model library, is generated in conjunction with the information received
Dynamic image executes step S4.
Certainly, 9D sensing systems are not necessarily installed on vehicle, other kinds of sensor can also be installed, are such as accelerated
The sensors such as sensor, three-axis gyroscope, velocity sensor are spent, it also can be dynamic to generate by acquiring the data of these sensors
State image.
Certainly, generate dynamic image when, can depend only on digital automobile model and 9D sensing systems data,
Geographical location information can also combine a variety of differences such as video recording, photo site, the driving trace captured by automobile data recorder
Data.Also, if being related to more accident vehicles, need to obtain the number of the 9D sensing systems on more accident vehicles
According to or more accident vehicles the data such as driving trace.
After generating dynamic image, step S5 is executed, accident responsibility is determined according to the dynamic image generated, is such as passed through
The accident responsibility to match is searched in preset database and assert type, to automatically generate accident responsibility protocol.It connects
It, executes step S6, cloud server sends accident responsibility protocol, preset terminal device to preset terminal device
It can be the terminal device of accident vehicle driver setting.In this way, accident vehicle can receive accident responsibility in very short time
Protocol.
Finally, step S7 is executed, judges whether accident vehicle withdraws the scene of the accident, such as determine by GPS positioning device
Whether accident vehicle has been moved off, or determines whether accident vehicle has been moved off accident by the video of nearby vehicle shooting
Scene etc..If accident vehicle has withdrawn the scene of the accident, S8 is thened follow the steps, the information of early warning is cancelled in publication, to notify week
The accident of side vehicle front has been disposed.
Certainly, method of the invention can also while determining accident responsibility, according to dynamic image determine vehicle by
Position is damaged, is supplied to related insurance company to settle a claim damaged vehicle situation, as Claims Resolution foundation.In addition, accident vehicle
Damage situations can also be sent to preset repair shop of more families by cloud server, and the impaired feelings of vehicle are assessed by repair shop
Condition and the bid modified, in order to which car owner quickly selects repair shop to repair.
As it can be seen that the method for the application present invention, can not only allow accident vehicle that the identification of accident responsibility is rapidly completed, and fast
Speed withdraws the scene of the accident, the case where reducing road congestion, but also can reduce the time that accident vehicle is exposed to danger zone,
To reduce the risk of casualties.In addition, for insurance company, it is possible to reduce the trouble of inspection of the scene of a crime personnel, and
The setting loss of vehicle is easy to operate, greatlys save Claims Resolution cost.In addition, for traffic police department, by obtaining the scene of the accident
Dynamic image, for traffic accident responsibility judge it is more accurate, and by dynamic image restore the scene of the accident the case where, responsibility is recognized
It is fixed that more there is convincingness.
Computer installation embodiment：
Computer installation provided by the invention can be cloud server comprising have power supply, memory and processor, storage
In memory and the computer program that can run on a processor.Wherein, it is realized when processor executes computer program above-mentioned
Each step of traffic accident dynamic image generation method.
Processor alleged by the present embodiment can be central processing unit, can also be other general processors, digital signal
Either other programmable logic device, discrete gate or transistor are patrolled for processor, application-specific integrated circuit, ready-made programmable gate array
Collect device, discrete hardware components etc..General processor can be microprocessor or the processor can also be any conventional
Processor etc., processor are the control centres of computer installation, utilize various interfaces and the entire computer installation of connection
Various pieces.
Memory can be used for storing computer program and/or module, processor are stored in memory by running or executing
Interior computer program and/or module, and the data being stored in memory are called, realize the various functions of terminal device.
Memory can include mainly storing program area and storage data field, wherein storing program area can storage program area, at least one
Application program etc. needed for function；Storage data field can be stored uses created data etc. according to mobile phone.
In addition, each functional unit in an embodiment of the present invention can be integrated in a processing unit, can also be
Each unit physically exists alone, can also be during two or more units are integrated in one unit.Above-mentioned integrated unit
Both the form that hardware may be used is realized, can also be realized in the form of SFU software functional unit.
Computer readable storage medium embodiment：
In the present embodiment, computer-readable recording medium storage has computer program, i.e. computer program to be stored in a meter
In the readable storage medium of calculation machine, including some instructions are used so that a computer equipment（Can be personal computer, service
Device or the network equipment etc.）Execute all or part of step of each embodiment method of the present invention.And storage medium packet above-mentioned
It includes：USB flash disk, mobile hard disk, read-only memory, random access memory, magnetic disc or CD etc. are various can to store program code
Medium.
Certainly, above-mentioned scheme is the preferred embodiment of the invention, and practical application is that can also have more variations,
For example, the change of the sensor used, the change etc. of accident early warning information sender formula, these changes do not affect the present invention's
Implement, also should include within the scope of the present invention.
Claims (10)
1. traffic accident dynamic image generation method, which is characterized in that including：
The data and accident vehicle geographical location information transmitted by the sensor on accident vehicle are obtained, according to the sensor
Transmitted data and the geographical location information generate the dynamic image of accident vehicle in the event of an accident；
According to the dynamic image generated, accident responsibility is determined, and accident responsibility assert that result is sent to preset terminal and sets
It is standby.
2. traffic accident dynamic image generation method according to claim 1, it is characterised in that：
Acquired sensor is set on two or more accident vehicles；
When generating the dynamic image, the Dynamic Graph is generated using the data of the sensor of two or more accident vehicles
Picture.
3. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
Before generating the dynamic image, also obtain：The driving trace of the accident vehicle；
When generating the dynamic image, the driving trace of the also application accident vehicle generates the dynamic image.
4. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
Before generating the dynamic image, also obtain：Image scene of the accident vehicle after generation accident；
When generating the dynamic image, the image scene of the also application accident vehicle generates the dynamic image.
5. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
Before generating the dynamic image, also obtain：The preset digital automobile model of accident vehicle；
When generating the dynamic image, the digital automobile model of the also application accident vehicle generates the dynamic image.
6. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
Before generating the dynamic image, also obtain：Traveling video recording letter of the accident vehicle before generation accident in preset time
Breath；
When generating the dynamic image, the also application traveling video information generates the dynamic image.
7. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
The sensor is 9D sensing systems.
8. traffic accident dynamic image generation method according to claim 1 or 2, it is characterised in that：
After obtaining the data transmitted by the sensor on accident vehicle, accident early warning information is sent to nearby vehicle.
9. computer installation, including processor and computer readable storage medium, the computer-readable recording medium storage
Have computer program, which is characterized in that executed when the processor reads and runs the computer program as claim 1 to
8 any one of them traffic accident dynamic image generation methods.
10. computer readable storage medium, is stored thereon with computer program, the computer program is read out by the processor and transports
Such as claim 1 to 8 any one of them traffic accident dynamic image generation method is executed when row.
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| CN (1) | CN108320348A (en) |
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| CN108986474A (en) * | 2018-08-01 | 2018-12-11 | 平安科技（深圳）有限公司 | Fix duty method, apparatus, computer equipment and the computer storage medium of traffic accident |
| CN109035118A (en) * | 2018-09-05 | 2018-12-18 | 盐城骏拔汽车零部件有限公司 | The small-sized quick processing system of traffic accident |
| CN109360137A (en) * | 2018-09-25 | 2019-02-19 | 平安科技（深圳）有限公司 | A kind of car accident appraisal procedure, computer readable storage medium and server |
| CN109559403A (en) * | 2018-11-30 | 2019-04-02 | 阿里巴巴集团控股有限公司 | A kind of car damage identification method, device and system for losing data based on vehicle part |
| CN109671006A (en) * | 2018-11-22 | 2019-04-23 | 斑马网络技术有限公司 | Traffic accident treatment method, apparatus and storage medium |
| CN109741194A (en) * | 2018-12-25 | 2019-05-10 | 斑马网络技术有限公司 | Processing method, equipment and the storage medium of vehicle collision |
| CN109886820A (en) * | 2019-01-23 | 2019-06-14 | 平安科技（深圳）有限公司 | Accident vehicle recognition methods and terminal device |
| CN109919140A (en) * | 2019-04-02 | 2019-06-21 | 浙江科技学院 | Vehicle collision accident responsibility automatic judging method, system, equipment and storage medium |
| CN109961056A (en) * | 2019-04-02 | 2019-07-02 | 浙江科技学院 | Traffic accident responsibility identification, system and equipment based on decision Tree algorithms |
| CN110562262A (en) * | 2019-09-03 | 2019-12-13 | 镁佳(北京)科技有限公司 | Vehicle motion state determination method and device, storage medium and vehicle |
| CN111256716A (en) * | 2018-12-03 | 2020-06-09 | 丰田自动车株式会社 | Information processing system, program, and control method |
| CN111339168A (en) * | 2020-03-06 | 2020-06-26 | 德联易控科技(北京)有限公司 | Data processing method, device, system, storage medium and processor |
| CN114724373A (en) * | 2022-04-15 | 2022-07-08 | 地平线征程(杭州)人工智能科技有限公司 | Traffic site information acquisition method and device, electronic device and storage medium |
| CN115100869A (en) * | 2022-08-02 | 2022-09-23 | 广西钛视科技有限公司 | Road secondary accident early warning system based on thing networking perception system |
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| CN108986474A (en) * | 2018-08-01 | 2018-12-11 | 平安科技（深圳）有限公司 | Fix duty method, apparatus, computer equipment and the computer storage medium of traffic accident |
| CN109035118A (en) * | 2018-09-05 | 2018-12-18 | 盐城骏拔汽车零部件有限公司 | The small-sized quick processing system of traffic accident |
| CN109360137A (en) * | 2018-09-25 | 2019-02-19 | 平安科技（深圳）有限公司 | A kind of car accident appraisal procedure, computer readable storage medium and server |
| CN109360137B (en) * | 2018-09-25 | 2023-04-18 | 平安科技（深圳）有限公司 | Vehicle accident assessment method, computer readable storage medium and server |
| CN109671006A (en) * | 2018-11-22 | 2019-04-23 | 斑马网络技术有限公司 | Traffic accident treatment method, apparatus and storage medium |
| CN109671006B (en) * | 2018-11-22 | 2021-03-02 | 斑马网络技术有限公司 | Traffic accident handling method, device and storage medium |
| CN109559403A (en) * | 2018-11-30 | 2019-04-02 | 阿里巴巴集团控股有限公司 | A kind of car damage identification method, device and system for losing data based on vehicle part |
| CN111256716A (en) * | 2018-12-03 | 2020-06-09 | 丰田自动车株式会社 | Information processing system, program, and control method |
| CN111256716B (en) * | 2018-12-03 | 2023-08-18 | 丰田自动车株式会社 | Information processing system, program, and control method |
| CN109741194A (en) * | 2018-12-25 | 2019-05-10 | 斑马网络技术有限公司 | Processing method, equipment and the storage medium of vehicle collision |
| CN109886820A (en) * | 2019-01-23 | 2019-06-14 | 平安科技（深圳）有限公司 | Accident vehicle recognition methods and terminal device |
| CN109961056A (en) * | 2019-04-02 | 2019-07-02 | 浙江科技学院 | Traffic accident responsibility identification, system and equipment based on decision Tree algorithms |
| CN109919140B (en) * | 2019-04-02 | 2021-04-09 | 浙江科技学院 | Automatic determination method, system, equipment and storage medium for vehicle collision accident responsibility |
| CN109919140A (en) * | 2019-04-02 | 2019-06-21 | 浙江科技学院 | Vehicle collision accident responsibility automatic judging method, system, equipment and storage medium |
| CN110562262A (en) * | 2019-09-03 | 2019-12-13 | 镁佳(北京)科技有限公司 | Vehicle motion state determination method and device, storage medium and vehicle |
| CN110562262B (en) * | 2019-09-03 | 2021-04-13 | 镁佳(北京)科技有限公司 | Vehicle motion state determination method and device, storage medium and vehicle |
| CN111339168A (en) * | 2020-03-06 | 2020-06-26 | 德联易控科技(北京)有限公司 | Data processing method, device, system, storage medium and processor |
| CN111339168B (en) * | 2020-03-06 | 2023-08-22 | 德联易控科技(北京)有限公司 | Data processing method, device, system, storage medium and processor |
| CN114724373A (en) * | 2022-04-15 | 2022-07-08 | 地平线征程(杭州)人工智能科技有限公司 | Traffic site information acquisition method and device, electronic device and storage medium |
| CN114724373B (en) * | 2022-04-15 | 2023-06-27 | 地平线征程(杭州)人工智能科技有限公司 | Traffic field information acquisition method and device, electronic equipment and storage medium |
| CN115100869A (en) * | 2022-08-02 | 2022-09-23 | 广西钛视科技有限公司 | Road secondary accident early warning system based on thing networking perception system |
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Application publication date: 20180724 |