CN112308723A - Vehicle detection method and system - Google Patents

Vehicle detection method and system Download PDF

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CN112308723A
CN112308723A CN201910704231.3A CN201910704231A CN112308723A CN 112308723 A CN112308723 A CN 112308723A CN 201910704231 A CN201910704231 A CN 201910704231A CN 112308723 A CN112308723 A CN 112308723A
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不公告发明人
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Beijing Taifang Technology Co ltd
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Abstract

The invention provides a vehicle detection method and a system, wherein the method comprises the following steps: acquiring an elastic wave signal generated when a vehicle collides through a sensor arranged on the vehicle; calculating collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; calculating to obtain vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; and, obtaining position data of the vehicle at the time of the collision; and associating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database.

Description

Vehicle detection method and system
Technical Field
The invention relates to the field of vehicle monitoring, in particular to a vehicle detection method and system.
Background
In the current era of high-speed informatization development, a vehicle-mounted GPS system is widely applied, but based on the consideration of privacy and the like, the vehicle-mounted GPS is usually only used for providing functions of vehicle owner navigation and the like, and related specific position data is not disclosed and interacted with the outside; secondly, most of the existing vehicles have insurance application behaviors so as to be convenient for the vehicles to be compensated when unknown accidents happen and reduce the risks of vehicle owners and personnel involved in the accidents; after a common vehicle is insured and an accident occurs, the process flow is that an insurance specialist goes to evaluate the occurrence reason of the vehicle accident and the damage degree of the vehicle according to the address reported by the insurer, and the process has the risk of 'cheating insurance' because the insurance specialist cannot know the first accident site of the vehicle at the first time; after the accident happens due to the illegal operation, the applicant can disguise the scene at other places to cover the fact of the illegal operation, thereby cheating the premium.
In view of the above situation, there is a need in the art for a safe and effective monitoring scheme to prevent vehicle insurance fraud and provide a basis for subsequent insurance claims.
Disclosure of Invention
The invention aims to provide a safe and effective insurance fraud prevention detection method which can efficiently determine accident levels and retain basis when a vehicle has an accident, is convenient for effectively supervising and closing insurance vehicles, reduces the probability of insurance fraud and improves the risk control capability.
To achieve the above object, the present invention provides a vehicle detecting method, which specifically includes: acquiring an elastic wave signal generated when a vehicle collides through a sensor arranged on the vehicle; calculating collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; calculating to obtain vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; and, obtaining position data of the vehicle at the time of the collision; and associating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database.
In the above vehicle detection method, preferably, the method further includes: and acquiring panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle, associating the panoramic image data and/or the front and rear image data with the position data and the damage degree data, and sending the associated panoramic image data and/or the front and rear image data to a preset database.
In the above vehicle detection method, preferably, the method further includes: and obtaining current image information of the vehicle driver according to the elastic wave signal, and sending the image information of the vehicle driver to a preset database after associating the image information of the vehicle driver with the position data and the damage degree data.
In the above vehicle detection method, preferably, the method further includes: and obtaining the driving track data in a preset period when the vehicle is collided, and sending the driving track data to a preset database after associating the driving track data with the position data and the damage degree data.
In the above vehicle detection method, preferably, the vehicle trajectory data is obtained by an acceleration sensor mounted on the vehicle; and obtaining the position data of the current vehicle through the vehicle-mounted GPS on the vehicle.
In the above vehicle detection method, preferably, the method further includes: obtaining current weight information of the vehicle; and obtaining the current load data of the vehicle according to the current weight information of the vehicle and preset vehicle information, and sending the current load data of the vehicle to a preset database after associating the current load data of the vehicle with the position data and the damage degree data.
In the above vehicle detection method, preferably, the obtaining of the vehicle damage degree data by calculation according to the collision position information, the collision strength information, and preset vehicle information includes: obtaining structural information of a collision position corresponding to the vehicle according to the collision position information and preset vehicle information; acquiring collision load data according to the structural information; and calculating to obtain vehicle damage degree data according to the collision strength information and the collision load data.
In the above vehicle detection method, preferably, the method further includes, after acquiring an elastic wave signal generated when the vehicle collides with a sensor provided in the vehicle: and comparing the signal intensity of the elastic wave signal with a preset threshold value, and when the signal intensity is higher than the preset threshold value, acquiring operation according to the subsequent collision position information, collision intensity information and position data.
In the above vehicle detection method, preferably, the method further includes: and obtaining object type information colliding with the vehicle according to the elastic wave signal, and sending the object type information, the position data and the damage degree data to a preset database after being associated.
In the above vehicle detection method, it is preferable that obtaining the object type information that collides with the vehicle from the elastic wave signal includes: obtaining a feature vector corresponding to the elastic wave signal according to the elastic wave signal; comparing the characteristic vector with a pre-stored corresponding table to obtain object type information of the vehicle collision; or establishing a characteristic model through a machine learning algorithm according to the characteristic vectors of elastic wave signals generated when different objects collide with the vehicle; and obtaining the type information of the object of the vehicle collision according to the feature model and the feature vector.
In the above vehicle detection method, preferably, the obtaining of the position data of the current vehicle further includes: when the position data of the current vehicle cannot be obtained, acquiring the position data of the vehicle according to a preset period; until position data of the vehicle is obtained.
In the above vehicle detection method, preferably, the obtaining of the position data of the current vehicle further includes: caching the position data of the vehicle according to a preset period and storing the position data into a preset memory; when the elastic wave signal is acquired, the position data with the latest time is obtained in the preset memory and is used as the position data of the current vehicle.
The invention also provides a vehicle detection system, which comprises a data acquisition device, a calculation module, a communication module and one or more sensors; the sensor is arranged on the vehicle and used for collecting elastic wave signals generated by collision when the vehicle collides; the data acquisition device is used for calculating and obtaining collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; and obtaining position data of the current vehicle when the vehicle collides; the calculation module is used for calculating and obtaining vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; and the communication module is used for correlating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database.
In the above vehicle detection system, preferably, the data acquisition device further includes an image acquisition module and a vehicle-mounted acceleration sensor; the image acquisition module is used for acquiring panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle, associating the panoramic image data and/or the front and rear image data with the position data and the damage degree data, and then sending the panoramic image data and/or the front and rear image data to a preset database through the communication module; the vehicle-mounted acceleration sensor is used for obtaining driving track data in a preset period of the vehicle according to the elastic wave signals, associating the driving track data with the position data and the damage degree data, and then sending the driving track data to a preset database through the communication module.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
The invention has the beneficial technical effects that: the collision strength, the collision position, the collision object characteristics, the collision position, the images inside and outside the vehicle when the collision occurs and the speed change condition of the vehicle before and after the collision can be obtained at the first time; and then the conditions of personnel in the vehicle, the speed change condition of the vehicle, the collision strength and the collision object when the collision occurs are known, and the claim of the insured vehicle is supervised and checked based on the conditions, so that the probability of insurance cheating is reduced, the risk control capability is improved, and the insurance premium is reduced.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
fig. 1 is a schematic flow chart of a vehicle detection method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a vehicle detection method according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart illustrating a vehicle detection method according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart illustrating a vehicle detection method according to an embodiment of the present invention;
fig. 5 is a schematic view illustrating a process of calculating a vehicle loss in the vehicle detection method according to an embodiment of the present invention;
FIG. 6 is a flowchart illustrating a vehicle detection method according to an embodiment of the present invention;
FIG. 7 is a schematic flow chart of a vehicle detection system according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, unless otherwise specified, the embodiments and features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
Additionally, the steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions and, although a logical order is illustrated in the flow charts, in some cases, the steps illustrated or described may be performed in an order different than here.
Referring to fig. 1, the vehicle detection method provided by the present invention specifically includes: s101, acquiring an elastic wave signal generated when a vehicle collides through a sensor arranged on the vehicle; s102, calculating and obtaining collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; s103, calculating to obtain vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; and S104, acquiring position data when the vehicle is collided; and S105, associating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database. The steps S102, S103 and S104 are not in sequence, and the simultaneous acquisition may be performed or the sequence may be selected according to actual situations, which is not limited in the present invention.
The vehicle detection method provided by the application can be applied to vehicle insurance fraud prevention, and the probability of insurance fraud can be reduced; the method can also be applied to the fields of car networking, car big data of car factories and the like.
In the above embodiment, the vehicle detection method may further include comparing the vehicle damage degree data with a preset threshold, and outputting an alarm signal to a preset target when the vehicle is seriously damaged; for example, when the calculated and obtained vehicle damage degree data relates to safety of drivers, warning data can be sent to contact persons preset by the drivers or local first aid, traffic management, road rescue and the like through a communication system of the vehicles or communication equipment such as Bluetooth mobile phones connected with the vehicles, and rescue is requested.
In the above embodiment, obtaining the position data of the current vehicle further includes: when the position data of the current vehicle cannot be obtained, acquiring the position data of the vehicle according to a preset period; until position data of the vehicle is obtained; or caching the position data of the vehicle according to a preset period and storing the position data into a preset memory; when the elastic wave signal is acquired, the position data with the latest time is obtained in the preset memory and is used as the position data of the current vehicle. Specifically, in actual work, because it cannot be guaranteed that position data of a vehicle can be obtained at various positions, the invention further provides two solutions for caching the position data in advance or supplementing the position data in the future, specifically, the cached position data comprises current position information of the vehicle cached in real time according to a preset period, and when the vehicle collides to obtain an elastic wave signal, the latest position information in the cached data is used as the current position data of the vehicle, so as to avoid the problem that the position data cannot be obtained; the mode of supplementing and acquiring the position data afterwards is that the position data of the current vehicle is acquired in real time after the elastic wave signal is acquired, if the acquisition is unsuccessful due to no signal or other reasons, a position acquisition task thread is established, the acquisition is circulated according to a preset period until the position data of the vehicle is acquired, and the position data of the vehicle is sent to a preset database; of course, there are various solutions for the vehicle not being able to collect the current position information, and those skilled in the art can select the setting according to the actual needs, and the present invention is not described in detail herein.
Referring to fig. 2, in an embodiment of the present invention, the method may further include: s115, acquiring panoramic image data in a preset range near the vehicle and/or front and rear image data of the vehicle; s116, associating the panoramic image data and/or the front and back image data with the position data and the damage degree data, and then sending the associated data to a preset database. In the embodiment, the image information in the preset period before and after the vehicle is in an accident can be obtained through the travel recorder and the vehicle-mounted panoramic image equipment, so that the accident reason and the damage condition can be accurately and respectively generated according to the image information in the subsequent insurance responsibility determination, and the accident responsibility determination can be effectively realized by matching the images, thereby avoiding the situations such as subsequent evidence loss and the like; certainly, when the driver does not collide with the vehicle, for example, when the vehicle stops on a street or a parking lot, the image acquisition can be performed by taking the elastic wave signal generated when the vehicle body collides as a trigger signal, so that the subsequent driver can conveniently find the accident reason and place; the situation that the automobile cannot follow the duty after the accident due to the fact that the owner is not near the automobile is effectively avoided.
In the above embodiment, the method may further include: and obtaining the image information of the current vehicle driver, associating the image information of the vehicle driver with the position data and the damage degree data, and sending the image information of the vehicle driver to a preset database. In actual work, the current driver of the vehicle can be obtained through the vehicle-mounted camera arranged in the vehicle, so that the identity of the driver or the information such as whether the driver breaks rules and drives or not can be conveniently confirmed when a subsequent accident happens.
Referring to fig. 3, in an embodiment of the present invention, the method may further include: s125, obtaining the driving track data of the vehicle in a preset period when the vehicle is collided, and S126, associating the driving track data with the position data and the damage degree data and then sending the data to a preset database. In this embodiment, the trajectory data may be obtained by an acceleration sensor onboard the vehicle; and obtaining the position data of the current vehicle through the vehicle-mounted GPS on the vehicle. Therefore, the driving state of the vehicle owner can be effectively known through the vehicle driving track, so that whether the vehicle owner has drunk driving and other conditions or not is further deduced, and a more comprehensive evaluation basis is provided for subsequent insurance liability assessment.
Referring to fig. 4, in an embodiment of the present invention, the method further includes: s135, obtaining the current weight information of the vehicle; s136, obtaining the current load data of the vehicle according to the current weight information of the vehicle and preset vehicle information, and S137, associating the current load data of the vehicle with the position data and the damage degree data and then sending the data to a preset database. Certainly, in actual work, the infrared thermal imaging camera can be started at the moment of collision to detect the number of people in the passenger car; in the mode, the infrared thermal imaging camera can detect the number of drivers and passengers in the automobile and is not influenced by the intensity of natural light; the vehicle weight can be detected by adopting a slide rheostat, for example, a slide rheostat is fixed near a shock absorber, the distance between a frame and an axle is reduced during loading, the resistance value is reduced, the current is increased, and thus the load weight can be reflected by an ammeter; a set of automobile load self-testing device is arranged at each damping fulcrum of the automobile, and the total load of the automobile can be obtained by adding the numbers of all the automobile load self-testing devices; the person skilled in the art can select a specific weight detection mode according to actual needs, and the invention is not listed here. Referring to fig. 5, in an embodiment of the present invention, the obtaining of the vehicle damage degree data by calculation according to the collision position information, the collision strength information, and the preset vehicle information includes: s501, obtaining structural information of a collision position corresponding to the vehicle according to the collision position information and preset vehicle information; s502, acquiring collision load data according to the structural information; s503, calculating and obtaining vehicle damage degree data according to the collision strength information and the collision load data. In this embodiment, the elastic wave signal can be used to obtain the collision strength of the vehicle in the collision, and then the limit collision value that the vehicle body can bear is further analyzed and calculated according to the collision position and the structural characteristics of the vehicle body at the position, so that the damage condition of the vehicle in the collision can be effectively inferred based on the limit collision value and the actual collision strength, and the subsequent insurance claim settlement can be compared based on the damage condition to provide a reference for the actual claim settlement; the collision load data obtained according to the structural information can be obtained by comparing the collision load data with a conventional comparison table, for example, a large amount of vehicle body collision experiment data may be stored in a safety detection process before the vehicle leaves a factory, the collision load data, i.e., the limit collision value, at each position of the vehicle can be accurately obtained based on the experiment data, and based on this, the damage condition of the known vehicle can be judged and known under the condition of obtaining the collision position and the collision strength.
In the above embodiment, the collision strength can be mainly calculated by the following formula:
Figure BDA0002151634910000071
wherein E is the signal energy value collected by the sensor, namely collision strength, and m is the number of collected signal points; n is the number of signal points determined by selecting the wavelength of the voltage signal with a predetermined length according to actual conditions, and those skilled in the art can select the setting according to actual needs, and the application is not further limited herein.
In order to avoid interference caused by an extraneous signal, in an embodiment of the present invention, the acquiring, by a sensor disposed on a vehicle, an elastic wave signal generated when the vehicle collides further includes: and comparing the signal intensity of the elastic wave signal with a preset threshold value, and outputting the elastic wave signal when the signal intensity is higher than the preset threshold value. Therefore, when the collision signal is small or slight friction occurs, the elastic wave signals can be discarded without subsequent processing, and in the actual work, a worker can set a preset threshold value in advance to adjust the identification sensitivity of the vehicle detection method, so that the slight collision signal which does not cause vehicle damage is discarded, and the problem of subsequent data backlog is reduced; of course, in actual work, due to different conditions of vehicle body structures, materials, and the like, the preset threshold value also has differences, and related technicians in the field can select the setting according to actual conditions, and the invention is not further limited herein.
Referring to fig. 6, in an embodiment of the present invention, the method further includes: s145, obtaining object type information of the vehicle in collision according to the elastic wave signal, and S146, associating the object type information with the position data and the damage degree data and then sending the object type information to a preset database. Specifically, the obtaining of the object type information of the collision with the vehicle from the elastic wave signal includes: obtaining a feature vector corresponding to the elastic wave signal according to the elastic wave signal; comparing the characteristic vector with a pre-stored corresponding table to obtain object type information of the vehicle collision; or establishing a characteristic model through a machine learning algorithm according to the characteristic vectors of elastic wave signals generated when different objects collide with the vehicle; and obtaining the type information of the object of the vehicle collision according to the feature model and the feature vector. Specifically, the signal characteristic value of the elastic wave signal acquired by the sensor may be compared with a pre-stored reference characteristic value to obtain corresponding information of the touch object. For example, converting an elastic wave signal into a corresponding voltage signal, and then obtaining a signal characteristic value of the voltage signal according to a signal waveform characteristic of the voltage signal; then, a characteristic model can be established through a machine learning algorithm and/or a deep learning algorithm according to a voltage signal converted when a preset touch object touches the vehicle; calculating to obtain a signal characteristic value of the voltage signal according to the voltage signal and the characteristic model; in this embodiment, a feature model may also be established by a support vector machine algorithm according to a voltage signal converted by a predetermined touch object touching the vehicle and a corresponding reference feature value; specifically, in actual work, a worker can collect elastic wave signals generated when different objects touch a vehicle in advance, convert the elastic wave signals into voltage signals, train the voltage signals as input signals through a machine learning algorithm and/or a deep learning algorithm to obtain a feature model for extracting signal feature values in the voltage signals, and manually analyze feature parts with higher differences in the voltage signals to obtain feature values corresponding to the voltage signals, wherein the feature values are reference feature values corresponding to the voltage signals; at the moment, the voltage signal is used as input, the reference characteristic value is used as output, and a characteristic model is established through a deep learning algorithm or a machine learning algorithm; therefore, when an actual accident occurs, the voltage signal converted from the elastic wave signal can be analyzed and calculated through the characteristic model to obtain a corresponding signal characteristic value. Certainly, in actual work, a feature model can be obtained by collecting a large number of voltage signals generated by touch and utilizing the voltage signals through a machine learning algorithm and/or a deep learning algorithm, a signal feature value of the touch can be obtained through the feature model and the voltage signals generated by actual touch of a user in a later period, and then the type information of an object can be obtained according to the signal feature value; the invention is not limited in detail, and those skilled in the art can select the application according to the actual needs.
In an embodiment of the invention, current time information of the vehicle in the collision can be acquired when the vehicle is in the collision, and the time information is associated with the position data and the damage degree data and then sent to the preset database. According to the time information acquisition method and device, the time information can be acquired from the network side through being connected to the internet when the vehicle collides, the time information can also be acquired through acquiring the system time of the vehicle, and the time information when the vehicle collides can also be acquired through calling the time recorded by the processing circuit connected with the sensor.
In summary, in actual work, when a vehicle has an event of collision, scratch and smash, elastic wave signals generated by the collision of the vehicle are converted into electric signals through sensors (such as piezoelectric sensors, film sensors, fiber bragg grating sensors, resistance strain sensors and other sensors with an elastic wave signal acquisition function), so as to obtain collision signals; then, analyzing the collision signal to obtain the collision strength, the specific body part where the collision occurs and the type information of the collision object; then, at the moment of collision, giving an instruction through a collision signal, starting a vehicle-mounted GPS (global positioning system), a vehicle-mounted panoramic camera and a vehicle-mounted front and rear direction automobile data recorder in a vehicle, and calling information of a vehicle-mounted acceleration sensor five seconds before and after the collision so as to finish acquisition of an evidence chain; finally, the collision analysis result (collision strength, collision object type, collision vehicle body part, collision time) and the position information of the collision, the vehicle speed change information and the picture or short video information of the collision moment are stored and sent to the insurance company or other related data centers for the first time by using the technology such as the mobile honeycomb.
Referring to fig. 7, the present invention further provides a vehicle detection system, which includes a data acquisition device, a calculation module, a communication module, and one or more sensors; the sensor is arranged on the vehicle and used for collecting elastic wave signals generated by collision when the vehicle collides; the data acquisition device is used for calculating and obtaining collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; and obtaining position data of the current vehicle when the vehicle collides; the calculation module is used for calculating and obtaining vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; and the communication module is used for correlating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database. The data acquisition device also comprises an image acquisition module and a vehicle-mounted acceleration sensor; the image acquisition module is used for acquiring panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle, associating the panoramic image data and/or the front and rear image data with the position data and the damage degree data, and then sending the panoramic image data and/or the front and rear image data to a preset database through the communication module; the vehicle-mounted acceleration sensor is used for obtaining driving track data in a preset period of the vehicle according to the elastic wave signals, associating the driving track data with the position data and the damage degree data, and then sending the driving track data to a preset database through the communication module.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method when executing the computer program.
The present invention also provides a computer-readable storage medium storing a computer program for executing the above method.
In an embodiment of the present invention, an electronic device is provided, which may be a desktop computer, a tablet computer, a vehicle center controller, a mobile terminal, and the like, but is not limited thereto. In this embodiment, the electronic device may refer to the implementation of the above method and the above apparatus, and the contents thereof are incorporated herein, and repeated descriptions thereof are omitted.
Fig. 8 is a schematic block diagram of a system configuration of an electronic apparatus 600 according to an embodiment of the present invention. As shown in fig. 8, the electronic device 600 may include a central processor 100 and a memory 140; the memory 140 is coupled to the central processor 100. Notably, this diagram is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, collision position information and collision strength information of vehicle collision are calculated and obtained according to the elastic wave signals; calculating to obtain vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information; obtaining the position data of the current vehicle according to the elastic wave signal; and associating the position data with the damage degree data, and sending the position data and the damage degree data to a preset database to be written into the central processing unit.
Wherein, according to the collision position information, the collision strength information and the preset vehicle information, the calculation to obtain the vehicle damage degree data comprises: obtaining structural information of a collision position corresponding to the vehicle according to the collision position information and preset vehicle information; acquiring collision load data according to the structural information; and calculating to obtain vehicle damage degree data according to the collision strength information and the collision load data.
Wherein, gather the elastic wave signal that produces when the vehicle bumps through the sensor that sets up on the vehicle still contains: and comparing the signal intensity of the elastic wave signal with a preset threshold value, and outputting the elastic wave signal when the signal intensity is higher than the preset threshold value.
In one embodiment, panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle are obtained according to the elastic wave signal, and the panoramic image data and/or the front and rear image data are associated with the position data and the damage degree data and then sent to a preset database to be written into the central processing unit.
In one embodiment, the driving track data in the preset period of the vehicle is obtained according to the elastic wave signal, and the driving track data is associated with the position data and the damage degree data and then sent to a preset database to be written into the central processing unit.
In one embodiment, the driving track data is obtained through an acceleration sensor on the vehicle; the position data of the current vehicle obtained by the vehicle-mounted GPS on the vehicle is written into the central processing unit.
In one embodiment, the current weight information of the vehicle is obtained according to the elastic wave signal; and obtaining the current load data of the vehicle according to the current weight information of the vehicle and preset vehicle information, associating the current load data of the vehicle with the position data and the damage degree data, and sending the associated data to a preset database to be written into the central processing unit.
In one embodiment, the method includes obtaining object type information of the vehicle colliding with the vehicle according to the elastic wave signal, associating the object type information with the position data and the damage degree data, and sending the object type information, the position data and the damage degree data to a preset database to be written into the central processing unit.
Wherein obtaining object type information of a collision with the vehicle from the elastic wave signal includes: obtaining a feature vector corresponding to the elastic wave signal according to the elastic wave signal; comparing the characteristic vector with a pre-stored corresponding table to obtain object type information of the vehicle collision; or establishing a characteristic model through a machine learning algorithm according to the characteristic vectors of elastic wave signals generated when different objects collide with the vehicle; and obtaining the type information of the object of the vehicle collision according to the feature model and the feature vector.
As shown in fig. 8, the electronic device 600 may further include: communication module 110, input unit 120, audio processing unit 130, display 160, power supply 170. It is noted that the electronic device 600 does not necessarily include all of the components shown in FIG. 8; furthermore, the electronic device 600 may also comprise components not shown in fig. 8, which may be referred to in the prior art.
As shown in fig. 8, the central processor 100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, the central processor 100 receiving input and controlling the operation of the various components of the electronic device 600.
The memory 140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 100 may execute the program stored in the memory 140 to realize information storage or processing, etc.
The input unit 120 provides input to the cpu 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display an object to be displayed, such as an image or a character. The display may be, for example, an LCD display, but is not limited thereto.
The memory 140 may be a solid state memory such as Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 140 may also be some other type of device. Memory 140 includes buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application/function storage section 142, and the application/function storage section 142 is used to store application programs and function programs or a flow for executing the operation of the electronic device 600 by the central processing unit 100.
The memory 140 may also include a data store 143, the data store 143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by the electronic device. The driver storage portion 144 of the memory 140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging application, address book application, etc.).
The communication module 110 is a transmitter/receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter/receiver) 110 is coupled to the central processor 100 to provide an input signal and receive an output signal, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132 to implement general telecommunications functions. Audio processor 130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, an audio processor 130 is also coupled to the central processor 100, so that recording on the local can be enabled through a microphone 132, and so that sound stored on the local can be played through a speaker 131.
According to the embodiment of the invention, based on the intelligent touch technology of the elastic wave, the physical phenomenon that the structure of a hard solid material in any shape can generate the elastic wave after being touched is grasped, the piezoelectric sensor is used for detecting the elastic wave (vibration) signal generated by the contact, and machine learning and deep learning algorithms are integrated through signal capturing, signal processing and analyzing technologies, so that the accurate acquisition of rich information such as the position (positioning), the strength (force) and the property (the hardness degree and the contact time of a contact body) of the touch event is finally realized. Compared with an acceleration sensor, the elastic wave intelligent touch technology can effectively prevent various false touches through an intelligent algorithm, can effectively monitor various states of the surface of the automobile body, and can effectively monitor low-speed scratching and scratching events particularly; the GPS system is additionally arranged on the vehicle body, which is a traditional technical means, but is also a novel point of the scheme by combining with the elastic wave intelligent touch technology. Collision information and position information when collision occurs are pain points and strong requirements of an insurance company, but GPS position information is pain points of users, and the users do not want the position information of vehicles to be under the control of the insurance company all the day; in the scheme, the GPS system is not started all the day, but the collision signal generated by the collision of the automobile triggers the GPS system to determine the vehicle position information at the moment of collision. Therefore, the privacy of the user is protected, and the functions of uploading the collision information and the position information when the collision happens to the insurance company are also taken into consideration, so that the market popularization and the rapid popularization of the scheme are facilitated.
In addition, the acceleration sensor is used for judging the speed change of the vehicle and the automobile data recorder is used for judging the personnel condition in the vehicle, and the monitoring is a side monitoring for judging whether the driving behavior of the driver is in compliance or not. The method is favorable for more comprehensively acquiring the condition information of the whole vehicle at the moment of collision. And the later claim settlement decision is convenient to make.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (17)

1. A vehicle detection method, characterized in that the method comprises:
acquiring an elastic wave signal generated when a vehicle collides through a sensor arranged on the vehicle;
calculating collision position information and collision strength information of the vehicle in collision according to the elastic wave signals;
calculating to obtain vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information;
and, obtaining position data of the vehicle at the time of the collision;
and associating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database.
2. The vehicle detection method according to claim 1, characterized in that the method further comprises: obtaining panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle when the vehicle collides, associating the panoramic image data and/or the front and rear image data with the position data and the damage degree data, and sending the associated panoramic image data and/or the front and rear image data to a preset database.
3. The vehicle detection method according to claim 1, characterized in that the method further comprises: and obtaining the image information of the current vehicle driver, associating the image information of the vehicle driver with the position data and the damage degree data, and sending the image information of the vehicle driver to a preset database.
4. The vehicle detection method according to claim 1, characterized in that the method further comprises: and obtaining the driving track data in a preset period when the vehicle is collided, and sending the driving track data to a preset database after associating the driving track data with the position data and the damage degree data.
5. The vehicle detection method according to claim 4, characterized in that the trajectory data is obtained by an acceleration sensor onboard the vehicle; and obtaining the position data of the current vehicle through the vehicle-mounted GPS on the vehicle.
6. The vehicle detection method according to claim 1, characterized in that the method further comprises: obtaining current weight information of the vehicle; and obtaining the current load data of the vehicle according to the current weight information of the vehicle and preset vehicle information, and sending the current load data of the vehicle to a preset database after associating the current load data of the vehicle with the position data and the damage degree data.
7. The vehicle detection method according to claim 1, wherein the calculating of the vehicle damage degree data based on the collision position information, the collision strength information, and preset vehicle information includes:
obtaining structural information of a collision position corresponding to the vehicle according to the collision position information and preset vehicle information;
acquiring collision load data according to the structural information;
and calculating to obtain vehicle damage degree data according to the collision strength information and the collision load data.
8. The vehicle detecting method according to claim 1, further comprising, after acquiring the elastic wave signal generated when the vehicle collides with the sensor provided in the vehicle: and comparing the signal intensity of the elastic wave signal with a preset threshold value, and executing subsequent collision position information, collision intensity information and position data acquisition operation when the signal intensity is higher than the preset threshold value.
9. The vehicle detection method according to claim 1, characterized in that the method further comprises: and obtaining object type information colliding with the vehicle according to the elastic wave signal, and sending the object type information, the position data and the damage degree data to a preset database after being associated.
10. The vehicle detection method according to claim 9, wherein obtaining the object type information that collides with the vehicle from the elastic wave signal includes: obtaining a feature vector corresponding to the elastic wave signal according to the elastic wave signal;
comparing the characteristic vector with a pre-stored corresponding table to obtain object type information of the vehicle collision;
or establishing a characteristic model through a machine learning algorithm according to the characteristic vectors of elastic wave signals generated when different objects collide with the vehicle; and obtaining the type information of the object of the vehicle collision according to the feature model and the feature vector.
11. The vehicle detection method according to claim 1, wherein obtaining the position data at the time of the vehicle collision further comprises: when the position data of the current vehicle cannot be obtained, acquiring the position data of the vehicle according to a preset period; until position data of the vehicle is obtained.
12. The vehicle detection method according to claim 1, wherein obtaining the position data at the time of the vehicle collision further comprises: caching the position data of the vehicle according to a preset period and storing the position data into a preset memory; and when the elastic wave signal is acquired, the position data with the latest time obtained in the preset memory is used as the position data of the current vehicle.
13. The vehicle detection method according to claim 1, characterized in that the method further comprises: and acquiring time information when the vehicle is collided, and sending the time information, the position data and the damage degree data to a preset database after being associated.
14. A vehicle detection system, comprising a data acquisition device, a computing module, a communication module, and one or more sensors;
the sensor is arranged on the vehicle and used for collecting elastic wave signals generated by collision when the vehicle collides;
the data acquisition device is used for calculating and obtaining collision position information and collision strength information of the vehicle in collision according to the elastic wave signals; and obtaining position data of the current vehicle when the vehicle collides;
the calculation module is used for calculating and obtaining vehicle damage degree data according to the collision position information, the collision strength information and preset vehicle information;
and the communication module is used for correlating the position data with the damage degree data and then sending the position data and the damage degree data to a preset database.
15. The vehicle detection system of claim 14, wherein the data acquisition device further comprises an image acquisition module and an on-board acceleration sensor;
the image acquisition module is used for acquiring panoramic image data and/or front and rear image data of the vehicle within a preset range near the vehicle, associating the panoramic image data and/or the front and rear image data with the position data and the damage degree data, and then sending the panoramic image data and/or the front and rear image data to a preset database through the communication module;
the vehicle-mounted acceleration sensor is used for obtaining driving track data in a preset period of the vehicle according to the elastic wave signals, associating the driving track data with the position data and the damage degree data, and then sending the driving track data to a preset database through the communication module.
16. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 13 when executing the computer program.
17. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 13.
CN201910704231.3A 2019-07-31 2019-07-31 Vehicle detection method and system Pending CN112308723A (en)

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