CN109886820B - Accident vehicle identification method and terminal equipment - Google Patents
Accident vehicle identification method and terminal equipment Download PDFInfo
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Abstract
The invention relates to the technical field of computers, and provides an accident vehicle identification method and terminal equipment. The method comprises the following steps: acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle; determining a classification result of the accident vehicle according to the vehicle running data, the vehicle state data and the preset classification rule; acquiring images acquired by camera devices in a preset area around a current accident place of an accident vehicle, and identifying a first image containing the accident vehicle from the acquired images; and verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result. According to the method, the classification result is obtained by using the vehicle running data, the vehicle state data and the preset classification rules, and then the classification result is verified by using the images acquired by the camera device in the preset area around the accident place, so that the recognition accuracy of the accident vehicle can be improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to an accident vehicle identification method and a terminal device.
Background
The amount of the automobile to be kept is gradually increased every year, and the occurrence rate of traffic accidents is also increased. Vehicle insurance refers to a commercial insurance that is responsible for compensating for personal injury or property loss of a motor vehicle due to natural disasters or accidents. For an automobile purchasing vehicle insurance, the owner can apply for insurance reimbursement after an accident occurs.
In the prior art, after an accident occurs on a vehicle, the vehicle can be applied to an insurance company, the insurance company sends staff to the site for investigation, the accident type of the accident vehicle is recognized on the site, the severity of the accident vehicle, whether fraudulent insurance behavior exists or not and the like are judged according to the vehicle condition of the accident site, and then corresponding treatment is carried out.
However, the staff classifies and identifies the accident vehicles by experience, so that on one hand, the subjective performance is high, on the other hand, the situation of the accident vehicles known by the staff on site is still limited, and the accident type identification error of the accident vehicles is easy to cause.
Disclosure of Invention
In view of the above, the embodiment of the invention provides an accident vehicle identification method and terminal equipment, so as to solve the problem that the type of the accident vehicle is identified by manual experience at present and is easy to identify errors.
A first aspect of an embodiment of the present invention provides an accident vehicle identification method, including:
Acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle;
Determining a classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and a preset classification rule;
Acquiring images acquired by camera devices in a preset area around the current accident site of the accident vehicle, and identifying a first image containing the accident vehicle from the acquired images;
And verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result.
A second aspect of an embodiment of the present invention provides an accident vehicle recognition apparatus including:
the first acquisition module is used for acquiring vehicle running data and vehicle state data of the accident vehicle in a preset time period through a sensor on the accident vehicle;
The first processing module is used for determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and a preset classification rule;
The second acquisition module is used for acquiring images acquired by the camera device in a preset area around the current accident place of the accident vehicle and identifying a first image containing the accident vehicle from the acquired images;
and the second processing module is used for verifying the classification result of the accident vehicle according to the first image and determining the accident classification of the accident vehicle according to the verification result.
A third aspect of the embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the accident vehicle identification method in the first aspect.
A fourth aspect of an embodiment of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the method for identifying an accident vehicle in the first aspect when executing the computer program.
Compared with the prior art, the embodiment of the invention has the beneficial effects that: acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle; then determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and the preset classification rule; acquiring images acquired by camera devices in a preset area around a current accident place of an accident vehicle, and identifying a first image containing the accident vehicle from the acquired images; and verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result, so that the accident vehicle can be accurately identified. According to the method and the device for identifying the accident vehicles, the classification results are obtained by means of the vehicle driving data, the vehicle state data and the preset classification rules, and then the classification results are verified by means of the images collected by the camera device in the preset area around the accident place, so that the identification accuracy of the accident vehicles can be improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of an implementation of an accident vehicle identification method provided by an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an implementation of determining a classification result of an accident vehicle according to vehicle driving data, vehicle status data and a preset classification rule in an accident vehicle recognition method according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating an implementation of determining a classification result of an accident vehicle according to vehicle driving data, vehicle status data and a preset classification rule in an accident vehicle recognition method according to another embodiment of the present invention;
Fig. 4 is a flowchart of implementation of corresponding processing according to a classification result of an accident vehicle in the accident vehicle recognition method provided by the embodiment of the present invention;
FIG. 5 is a flowchart for judging whether there is casualties on an accident vehicle and performing corresponding processing in the accident vehicle identification method provided by the embodiment of the invention;
FIG. 6 is a schematic diagram of an accident vehicle identification apparatus provided by an embodiment of the present invention;
Fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
Fig. 1 is a flowchart of an implementation of an accident vehicle recognition method according to an embodiment of the present invention, which is described in detail below:
s101, acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle.
In the present embodiment, the accident vehicle is a vehicle in which an accident occurs at present. The vehicle travel data may include, but is not limited to, a travel route point of the vehicle, a travel speed corresponding to each travel route point, a time corresponding to each travel route point, and the like. The vehicle state data may include a vehicle body state, an airbag state, a brake state, a state of an automatic transmission system, an engine state, and the like, which are not limited herein. The preset time period may be a time period of a preset duration including a time of occurrence of a current accident of the accident vehicle.
S102, determining a classification result of the accident vehicle according to the vehicle running data, the vehicle state data and a preset classification rule.
In the present embodiment, the classification result of the accident vehicle is a result of classifying the vehicle in which the accident occurred. The classification result of the accident vehicle can be obtained according to the vehicle running data, the vehicle state data and the preset classification rule analysis.
As one embodiment of the present invention, the vehicle running data includes a running speed, the vehicle state data includes a vehicle body state and an airbag state, and the classification result includes a false accident, a light accident, and a serious accident; as shown in fig. 2, S102 may include:
s201, if the vehicle body state is in a nondestructive state, acquiring monitoring data of each component of the accident vehicle, and if the monitoring data is not abnormal, judging that the classification result of the accident vehicle is a false accident.
S202, if the vehicle body state is a damaged state, acquiring the air bag state and the running speed, and if the air bag state is an opened state and the running speed exceeds a preset speed threshold, judging that the classification result of the accident vehicle is a serious accident; otherwise, judging the classification result of the accident vehicle as a slight accident.
In the present embodiment, the running speed is the vehicle speed of the accident vehicle at the time of the accident. The body state may include states of a door, window, chassis, body architecture, and the like.
The classification result of the accident vehicle can be obtained by analyzing according to the running speed, the vehicle body state, the air bag state and the preset classification rule, wherein the preset classification rule is as follows: firstly judging the state of the vehicle body, if the state of the vehicle body is a nondestructive state, calling monitoring data of all components of the accident vehicle, and judging the monitoring data as false accidents after no abnormality; if the vehicle body state is a damaged state, judging the state and the running speed of the safety air bag; if the safety air bag is opened and the running speed exceeds the preset speed threshold value, judging that the safety air bag is a serious accident; otherwise, a slight accident is determined.
According to the method, the device and the system, the initial classification is carried out through the vehicle body state, and then the classification result of the accident vehicle is analyzed by combining the monitoring data of each component of the accident vehicle, the safety airbag state and the running speed, so that the accuracy of the classification of the accident vehicle can be improved.
As one embodiment of the present invention, the vehicle travel data includes travel path information and travel time information; the vehicle state data includes a vehicle body state; the classification result comprises false accidents, slight accidents and serious accidents; as shown in fig. 3, S102 may include:
S301, searching first accident data in a pre-established accident database according to the travel path information and the travel time information; the first accident data are accident data with the current accident matching degree of the accident vehicle exceeding a preset matching threshold value; the accident database comprises accident path information, accident occurrence time and accident types corresponding to the accident data; the accident types include mild accidents and severe accidents.
S302, if the first accident data is not found in the accident database and the vehicle body state is a lossless state, judging that the classification result of the accident vehicle is a false accident.
And S303, if the first accident data is found in the accident database and the vehicle body state is a damaged state, taking the accident type of the first accident data as the classification result of the accident vehicle.
In the present embodiment, the travel path information may include an occurrence place of a current accident of the accident vehicle, a travel path point of the accident vehicle before the current accident occurs, and the like. The driving time information may include a current accident occurrence time of the accident vehicle and a time corresponding to each driving route point of the accident vehicle before the current accident occurs. The accident database is used for storing history data of accidents, and specifically can comprise accident path information, accident occurrence time and accident types corresponding to each accident data. Wherein the accident type may be an accident type determined according to the severity of each accident, including a mild accident and a severe accident.
The accident database can be pre-established according to the history data of the accident, and the first accident data, of which the current accident matching degree with the accident vehicle exceeds a preset matching threshold value, is searched in the accident database according to the driving path information and the driving time information of the accident vehicle. If the first accident data is not found in the accident database and the vehicle body state is a lossless state, it is determined as a false accident. If the first accident data is found in the accident database and the vehicle body state is a damaged state, the accident type of the first accident data is taken as the classification result of the accident vehicle. For example, if the accident type of the first accident data is a serious accident, the classification result of the accident vehicle is determined as a serious accident; if the accident type of the first accident data is a mild accident, the classification result of the accident vehicle is determined as a mild accident.
According to the method and the device, the current accident of the accident vehicle is matched with the historical accident data stored in the accident database according to the driving path information and the driving time information, and the accident type of the matched historical accident data is used as the classification result of the accident vehicle, so that the classification accuracy of the accident vehicle can be improved.
S103, acquiring images acquired by the camera device in a preset area around the current accident site of the accident vehicle, and identifying a first image containing the accident vehicle from the acquired images.
In the present embodiment, images taken by an imaging device of a road or a building in a surrounding area of an accident site are acquired and images including an accident vehicle are identified from the images.
And S104, verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result.
In the present embodiment, the image including the accident vehicle may be image-recognized, and the classification result of the accident vehicle may be verified based on the image-recognized result. If the image recognition result is consistent with the classification result of the accident vehicle, judging that the accident classification result is correct; if the image recognition result is inconsistent with the accident vehicle classification result, the manual verification information is sent to the terminal of the outworkers, so that the outworkers can go to the accident scene to carry out further accident vehicle classification result.
According to the embodiment of the invention, the sensor on the accident vehicle is used for acquiring the vehicle running data and the vehicle state data of the accident vehicle in a preset time period; then determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and the preset classification rule; acquiring images acquired by camera devices in a preset area around a current accident place of an accident vehicle, and identifying a first image containing the accident vehicle from the acquired images; and verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result, so that the accident vehicle can be accurately identified. According to the method and the device for identifying the accident vehicles, the classification results are obtained by means of the vehicle driving data, the vehicle state data and the preset classification rules, and then the classification results are verified by means of the images collected by the camera device in the preset area around the accident place, so that the identification accuracy of the accident vehicles can be improved.
As an embodiment of the present invention, as shown in fig. 4, after S104, the method may further include:
S401, if the classification result of the accident vehicle is a false accident, the credit grade of an insurer of the accident vehicle is reduced in a credit database, and the related data of the current accident of the accident vehicle is stored in the credit database.
S402, if the classification result of the accident vehicle is a slight accident or a serious accident, retrieving the insurance information of the insurer of the accident vehicle from an insurance database, determining the compensation amount according to the insurance information and the vehicle state data, and sending the compensation information containing the compensation amount to the terminal of the insurer.
In this embodiment, the insurance is the applicant of the accident vehicle. The credit database is used for storing vehicles corresponding to all insurers and historical accident data corresponding to all vehicles. After the classification result of the accident vehicle is verified and confirmed, corresponding processing can be performed according to the classification result. If the classification result of the accident vehicle is false accident, representing that the insurer of the accident vehicle has insurance fraud, the credit grade of the insurer of the accident vehicle is adjusted down in the credit database, and the current accident related data of the accident vehicle is stored in the credit database.
If the classification result of the accident vehicle is a slight accident or a serious accident, the insurance information of the insurer corresponding to the accident vehicle is called from the insurance database, the compensation amount is determined according to the vehicle state data of the current accident and the insurance information, compensation information containing the compensation amount is generated, and the compensation information is sent to the terminal of the insurer for the insurer to check and confirm.
Optionally, after S402, the method may further include:
If the reply information of the terminal of the insurer is not received within the preset time, the reimbursement information is sent to the terminal of the backup contact, and the first condition information is sent to the terminal of the backup contact; the first condition information includes time interval information between a first time and a current time, the first time being a time at which the reimbursement information including the reimbursement amount is transmitted to the insurer's terminal.
In this embodiment, the backup contact refers to other contacts of the accident vehicle stored in the insurance database than the insurance person. After the reimbursement information is sent to the terminal of the insurer, if the reply information of the terminal of the insurer is not received within the preset time, the insurer may be injured on an accident vehicle or the insurer cannot process the insurance matters for other reasons, and at this time, the reimbursement information can be sent to the terminal of the spare contact so that the spare contact can process the insurance matters.
The time interval information can be calculated according to the moment when the reimbursement information is sent to the terminal of the insurer and the current moment, and the time interval information is sent to the terminal of the standby contact person so that the standby contact person can know the situation and timely contact the insurer.
As an embodiment of the present invention, as shown in fig. 5, the method may further include:
S501, if the classification result of the accident vehicle is a serious accident, acquiring personnel status data of the accident vehicle through a sensor on the accident vehicle, and judging whether personnel casualties exist according to the first image and the personnel status data.
In the present embodiment, the person status data refers to status data of whether or not a person is injured. When the classification result of the accident vehicle is judged to be a serious accident, the personnel state data on the accident vehicle can be obtained through the sensor on the accident vehicle, and whether the accident vehicle has casualties or not is judged according to the first image and the personnel state data.
Alternatively, whether the casualties exist or not can be judged through the image shot by the camera device near the accident place and the sensing data of the safety sensors such as the safety air bags of the vehicles, and the personnel status data on the accident vehicles can be obtained. For example, the vehicle seat is provided with a sign monitoring device, and sensing data of the sign monitoring device can be acquired to judge whether the person has casualties; or an image acquisition device is arranged in the vehicle to acquire images of personnel in the vehicle, and whether the person is injured or not is judged in an image processing mode.
S502, if the existence of the casualties is judged, corresponding casualties information is generated, and the casualties information is sent to a terminal of a hospital.
In this embodiment, the casualty information may include information on the number of casualties, the injured parts of the persons, the degree of injury, and the like. If the casualties are judged to exist, corresponding casualties information is generated and sent to a terminal of hospital rescue, so that medical staff timely take out to rescue the casualties, and the casualties are timely rescued.
The embodiment of the invention has the following advantages: 1. the accident vehicles are identified more accurately, so that behaviors of cheating insurance or false alarm loss of the insured vehicles are prevented, and the insurance cost is reduced; 2. the sensor remotely sends information to judge the classification result of the accident vehicle, so that an insurance person does not need to go to the accident scene to judge the driving loss, the processing efficiency is improved, and the labor cost is reduced; 3. the classification result is verified through an imaging device near the accident place, so that the classification accuracy is improved; 4. when serious faults occur, related information is sent to police, hospitals, standby contacts and the like according to conditions, so that accident loss can be reduced; 5. after the false accident occurs, the false accident is identified and recorded, and the credit level of the corresponding insurer is lowered, so that the fraudulent insurance situation of the insurer can be reduced, and the manpower and material resource consumption caused by the false accident is reduced. 6. Storing and saving user data, analyzing the big data to form a user portrait, pushing vehicle insurance, trip insurance and the like related to the vehicle insurance to the user, or performing some other services according to the user portrait later.
According to the embodiment of the invention, the sensor on the accident vehicle is used for acquiring the vehicle running data and the vehicle state data of the accident vehicle in a preset time period; then determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and the preset classification rule; acquiring images acquired by camera devices in a preset area around a current accident place of an accident vehicle, and identifying a first image containing the accident vehicle from the acquired images; and verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result, so that the accident vehicle can be accurately identified. According to the method and the device for identifying the accident vehicles, the classification results are obtained by means of the vehicle driving data, the vehicle state data and the preset classification rules, and then the classification results are verified by means of the images collected by the camera device in the preset area around the accident place, so that the identification accuracy of the accident vehicles can be improved.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
Corresponding to the method for identifying an accident vehicle described in the above embodiments, fig. 6 shows a schematic diagram of an apparatus for identifying an accident vehicle according to an embodiment of the present invention. For convenience of explanation, only the portions related to the present embodiment are shown.
Referring to fig. 6, the apparatus includes a first acquisition module 61, a first processing module 62, a second acquisition module 63, and a second processing module 64.
The first obtaining module 61 is configured to obtain, by using a sensor on an accident vehicle, vehicle running data and vehicle state data of the accident vehicle in a preset period of time.
The first processing module 62 is configured to determine a classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and a preset classification rule.
The second obtaining module 63 is configured to obtain an image collected by a camera device in a preset area around a current accident site of the accident vehicle, and identify a first image including the accident vehicle from the obtained image.
The second processing module 64 is configured to verify the classification result of the accident vehicle according to the first image, and determine the accident classification of the accident vehicle according to the verification result.
Optionally, the vehicle driving data comprises driving speed, the vehicle state data comprises a vehicle body state and an airbag state, and the classification result comprises false accidents, mild accidents and serious accidents; the first processing module 62 is configured to:
If the vehicle body state is in a nondestructive state, acquiring monitoring data of each component of the accident vehicle, and if the monitoring data is not abnormal, judging that the classification result of the accident vehicle is a false accident;
if the vehicle body state is a damaged state, acquiring the air bag state and the running speed, and if the air bag state is an opened state and the running speed exceeds a preset speed threshold, judging that the classification result of the accident vehicle is a serious accident; otherwise, judging the classification result of the accident vehicle as a slight accident.
Optionally, the vehicle travel data includes travel path information and travel time information; the vehicle state data includes a vehicle body state; the classification result comprises false accidents, slight accidents and serious accidents; the first processing module 62 is configured to:
Searching first accident data in a pre-established accident database according to the driving path information and the driving time information; the first accident data are accident data with the current accident matching degree of the accident vehicle exceeding a preset matching threshold value; the accident database comprises accident path information, accident occurrence time and accident types corresponding to the accident data; the accident types include mild accidents and severe accidents;
If the first accident data is not found in the accident database and the vehicle body state is a lossless state, judging that the classification result of the accident vehicle is a false accident;
And if the first accident data is found in the accident database and the vehicle body state is a damaged state, taking the accident type of the first accident data as a classification result of the accident vehicle.
Optionally, the apparatus further comprises a third processing module, the third processing module being configured to:
if the classification result of the accident vehicle is a false accident, the credit level of an insurer of the accident vehicle is reduced in a credit database, and the related data of the current accident of the accident vehicle is stored in the credit database;
If the classification result of the accident vehicle is a slight accident or a serious accident, retrieving the insurance information of an insurer of the accident vehicle from an insurance database, determining the compensation amount according to the insurance information and the vehicle state data, and transmitting compensation information containing the compensation amount to a terminal of the insurer.
Optionally, the third processing module is configured to:
If the reply information of the terminal of the insurer is not received within the preset time, the reimbursement information is sent to the terminal of the backup contact, and the first condition information is sent to the terminal of the backup contact; the first condition information includes time interval information between a first time and a current time, the first time being a time at which the reimbursement information including the reimbursement amount is transmitted to the insurer's terminal.
Optionally, the third processing module is configured to:
If the classification result of the accident vehicle is a serious accident, acquiring personnel status data of the accident vehicle through a sensor on the accident vehicle, and judging whether personnel casualties exist according to the first image and the personnel status data;
if the casualties are judged to exist, corresponding casualties information is generated, and the casualties information is sent to a terminal of a hospital.
According to the embodiment of the invention, the sensor on the accident vehicle is used for acquiring the vehicle running data and the vehicle state data of the accident vehicle in a preset time period; then determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and the preset classification rule; acquiring images acquired by camera devices in a preset area around a current accident place of an accident vehicle, and identifying a first image containing the accident vehicle from the acquired images; and verifying the classification result of the accident vehicle according to the first image, so that the accident vehicle can be accurately identified. According to the method and the device for identifying the accident vehicles, the classification results are obtained by means of the vehicle driving data, the vehicle state data and the preset classification rules, and then the classification results are verified by means of the images collected by the camera device in the preset area around the accident place, so that the identification accuracy of the accident vehicles can be improved.
Fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 7, the terminal device 7 of this embodiment includes: a processor 70, a memory 71 and a computer program 72, e.g. a program, stored in said memory 71 and executable on said processor 70. The steps of the various method embodiments described above, such as steps 101 through 104 shown in fig. 1, are performed by the processor 70 when executing the computer program 72. Or the processor 70, when executing the computer program 72, performs the functions of the modules/units of the apparatus embodiments described above, such as the functions of the modules 61-64 shown in fig. 6.
By way of example, the computer program 72 may be partitioned into one or more modules/units that are stored in the memory 71 and executed by the processor 70 to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 72 in the terminal device 7.
The terminal device 7 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 70, a memory 71. It will be appreciated by those skilled in the art that fig. 7 is merely an example of the terminal device 7 and does not constitute a limitation of the terminal device 7, and may include more or less components than illustrated, or may combine certain components, or different components, e.g., the terminal device may further include an input-output device, a network access device, a bus, a display, etc.
The Processor 70 may be a central processing unit (Central Processing Unit, CPU), or may be another general purpose Processor, a digital signal Processor (DIGITAL SIGNAL Processor, DSP), an Application SPECIFIC INTEGRATED Circuit (ASIC), an off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 71 may be an internal storage unit of the terminal device 7, such as a hard disk or a memory of the terminal device 7. The memory 71 may be an external storage device of the terminal device 7, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like, which are provided on the terminal device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used for storing the computer program as well as other programs and data required by the terminal device. The memory 71 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other manners. For example, the apparatus/terminal device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium may include content that is subject to appropriate increases and decreases as required by jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is not included as electrical carrier signals and telecommunication signals.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (9)
1. A method of identifying an accident vehicle, comprising:
Acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle;
Determining a classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and a preset classification rule;
Acquiring images acquired by camera devices in a preset area around the current accident site of the accident vehicle, and identifying a first image containing the accident vehicle from the acquired images;
verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result; if the image recognition result is consistent with the classification result of the accident vehicle, judging that the accident classification result is correct;
the vehicle running data comprises running path information and running time information; the vehicle state data includes a vehicle body state; the classification result comprises false accidents, slight accidents and serious accidents;
The determining the classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and the preset classification rule comprises the following steps:
Searching first accident data in a pre-established accident database according to the driving path information and the driving time information; the first accident data are accident data with the current accident matching degree of the accident vehicle exceeding a preset matching threshold value; the accident database is used for storing history data of accidents and comprises accident path information, accident occurrence time and accident types corresponding to the accident data; the accident types include mild accidents and severe accidents;
If the first accident data is not found in the accident database and the vehicle body state is a lossless state, judging that the classification result of the accident vehicle is a false accident;
And if the first accident data is found in the accident database and the vehicle body state is a damaged state, taking the accident type of the first accident data as a classification result of the accident vehicle.
2. The accident-vehicle-identification method of claim 1, wherein the vehicle-travel-data includes a travel speed, the vehicle-state-data includes a vehicle-body state and an airbag state, and the classification result includes a false accident, a mild accident, and a severe accident;
The determining the classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and the preset classification rule comprises the following steps:
If the vehicle body state is in a nondestructive state, acquiring monitoring data of each component of the accident vehicle, and if the monitoring data is not abnormal, judging that the classification result of the accident vehicle is a false accident;
if the vehicle body state is a damaged state, acquiring the air bag state and the running speed, and if the air bag state is an opened state and the running speed exceeds a preset speed threshold, judging that the classification result of the accident vehicle is a serious accident; otherwise, judging the classification result of the accident vehicle as a slight accident.
3. The method of identifying an accident vehicle according to claim 2, further comprising, after said verifying the classification result of the accident vehicle from the first image:
if the classification result of the accident vehicle is a false accident, the credit level of an insurer of the accident vehicle is reduced in a credit database, and the related data of the current accident of the accident vehicle is stored in the credit database;
If the classification result of the accident vehicle is a slight accident or a serious accident, retrieving the insurance information of an insurer of the accident vehicle from an insurance database, determining the compensation amount according to the insurance information and the vehicle state data, and transmitting compensation information containing the compensation amount to a terminal of the insurer.
4. The accident-vehicle-identification method of claim 3, further comprising, after said sending the reimbursement information containing said reimbursement amount to the insurer's terminal:
If the reply information of the terminal of the insurer is not received within the preset time, the reimbursement information is sent to the terminal of the backup contact, and the first condition information is sent to the terminal of the backup contact; the first condition information includes time interval information between a first time and a current time, the first time being a time at which the reimbursement information including the reimbursement amount is transmitted to the insurer's terminal.
5. The accident vehicle identification method of claim 4, further comprising:
If the classification result of the accident vehicle is a serious accident, acquiring personnel status data of the accident vehicle through a sensor on the accident vehicle, and judging whether personnel casualties exist according to the first image and the personnel status data;
if the casualties are judged to exist, corresponding casualties information is generated, and the casualties information is sent to a terminal of a hospital.
6. An accident vehicle recognition apparatus, characterized by comprising:
the first acquisition module is used for acquiring vehicle running data and vehicle state data of the accident vehicle in a preset time period through a sensor on the accident vehicle;
The first processing module is used for determining the classification result of the accident vehicle according to the vehicle running data, the vehicle state data and a preset classification rule;
The second acquisition module is used for acquiring images acquired by the camera device in a preset area around the current accident place of the accident vehicle and identifying a first image containing the accident vehicle from the acquired images;
The second processing module is used for verifying the classification result of the accident vehicle according to the first image and determining the accident classification of the accident vehicle according to the verification result; if the image recognition result is consistent with the classification result of the accident vehicle, judging that the accident classification result is correct;
The vehicle running data comprises running path information and running time information; the vehicle state data includes a vehicle body state; the classification result comprises false accidents, slight accidents and serious accidents; the first processing module is specifically configured to:
Searching first accident data in a pre-established accident database according to the driving path information and the driving time information; the first accident data are accident data with the current accident matching degree of the accident vehicle exceeding a preset matching threshold value; the accident database is used for storing history data of accidents and comprises accident path information, accident occurrence time and accident types corresponding to the accident data; the accident types include mild accidents and severe accidents;
If the first accident data is not found in the accident database and the vehicle body state is a lossless state, judging that the classification result of the accident vehicle is a false accident;
And if the first accident data is found in the accident database and the vehicle body state is a damaged state, taking the accident type of the first accident data as a classification result of the accident vehicle.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 5.
8. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, realizes the steps of:
Acquiring vehicle running data and vehicle state data of an accident vehicle in a preset time period through a sensor on the accident vehicle;
Determining a classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and a preset classification rule;
Acquiring images acquired by camera devices in a preset area around the current accident site of the accident vehicle, and identifying a first image containing the accident vehicle from the acquired images;
verifying the classification result of the accident vehicle according to the first image, and determining the accident classification of the accident vehicle according to the verification result; if the image recognition result is consistent with the classification result of the accident vehicle, judging that the accident classification result is correct;
the vehicle running data comprises running path information and running time information; the vehicle state data includes a vehicle body state; the classification result comprises false accidents, slight accidents and serious accidents;
The determining the classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and the preset classification rule comprises the following steps:
Searching first accident data in a pre-established accident database according to the driving path information and the driving time information; the first accident data are accident data with the current accident matching degree of the accident vehicle exceeding a preset matching threshold value; the accident database is used for storing history data of accidents and comprises accident path information, accident occurrence time and accident types corresponding to the accident data; the accident types include mild accidents and severe accidents;
If the first accident data is not found in the accident database and the vehicle body state is a lossless state, judging that the classification result of the accident vehicle is a false accident;
And if the first accident data is found in the accident database and the vehicle body state is a damaged state, taking the accident type of the first accident data as a classification result of the accident vehicle.
9. The terminal device according to claim 8, wherein the vehicle running data includes a running speed, the vehicle state data includes a vehicle body state and an airbag state, and the classification result includes a false accident, a mild accident, and a severe accident;
The determining the classification result of the accident vehicle according to the vehicle driving data, the vehicle state data and the preset classification rule comprises the following steps:
If the vehicle body state is in a nondestructive state, acquiring monitoring data of each component of the accident vehicle, and if the monitoring data is not abnormal, judging that the classification result of the accident vehicle is a false accident;
if the vehicle body state is a damaged state, acquiring the air bag state and the running speed, and if the air bag state is an opened state and the running speed exceeds a preset speed threshold, judging that the classification result of the accident vehicle is a serious accident; otherwise, judging the classification result of the accident vehicle as a slight accident.
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| CN110738332B (en) * | 2019-09-27 | 2023-12-05 | 深圳市元征科技股份有限公司 | Accident vehicle identification method and system and storage medium |
| CN111177390A (en) * | 2019-12-30 | 2020-05-19 | 南京三百云信息科技有限公司 | Accident vehicle identification method and device based on hybrid model |
| CN111259935A (en) * | 2020-01-09 | 2020-06-09 | 斑马网络技术有限公司 | Vehicle accident recognition method, device, equipment and storage medium |
| CN111310696B (en) * | 2020-02-26 | 2023-09-15 | 广州小鹏汽车科技有限公司 | Parking accident identification method and device based on analysis of abnormal parking behaviors and vehicle |
| CN113724093A (en) * | 2021-08-26 | 2021-11-30 | 上海赢科信息技术有限公司 | Vehicle insurance accident verification method, system, electronic device and medium |
| CN115131960B (en) * | 2022-05-09 | 2024-01-02 | 合众新能源汽车股份有限公司 | Intelligent safety processing method and device for road vehicle accidents |
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