CN117745448A

CN117745448A - Risk determination method, risk determination device, electronic equipment and storage medium

Info

Publication number: CN117745448A
Application number: CN202311678927.6A
Authority: CN
Inventors: 高如海; 张拥军; 闫学彬; 朱晓晖; 高娅楠; 韩喆; 刘璐; 周伟栋; 牟森; 完颜永劲; 张富程
Original assignee: China United Network Communications Group Co Ltd; China Pacific Property Insurance Co Ltd
Current assignee: China United Network Communications Group Co Ltd; China Pacific Property Insurance Co Ltd
Priority date: 2023-12-07
Filing date: 2023-12-07
Publication date: 2024-03-22

Abstract

The application provides a risk determination method, a risk determination device, electronic equipment and a risk determination storage medium, which relate to the technical field of vehicles and can accurately identify the behavior of a user for privately disassembling automobile spare parts and changing damaged spare parts into photo-cheating protection. The method comprises the following steps: after receiving the high-level signal through the pin of the OBD, determining a target accessory with an association relation with the pin and receiving time for receiving the high-level signal, acquiring vehicle characteristic data and a vehicle running state at the current moment, and determining the risk of manually dismantling the target accessory according to the vehicle characteristic data, the vehicle running state and the receiving time for receiving the high-level signal. The embodiment of the application is used in the risk determination process.

Description

Risk determination method, risk determination device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of vehicle technologies, and in particular, to a risk determining method, a risk determining device, an electronic device, and a storage medium.

Background

Vehicle insurance, i.e. motor vehicle insurance, is abbreviated as car insurance, also called car insurance. It refers to a commercial insurance responsible for the loss of life or property of motor vehicles due to natural disasters or accidents. Automotive insurance is a type of property insurance in which automotive insurance is a relatively young hazard, as it is generated and developed with the advent and popularity of automobiles. Meanwhile, unlike modern motor vehicle insurance, the automobile insurance is mainly carried out by a third party of the automobile in the early stage of the automobile insurance, and the automobile insurance gradually extends to risks such as collision loss of the automobile body.

Some users, however, exchange damaged parts to cheat the insurance company's claim money by handling car hazards and privately removing car parts.

Therefore, how to accurately identify the behavior of taking photos and cheating the user to disassemble the automobile spare and accessory parts privately and replace the damaged spare and accessory parts is a problem to be solved at present.

Disclosure of Invention

The application provides a risk determination method, a risk determination device, electronic equipment and a storage medium, which can accurately identify the behavior that a user privately dismounts automobile spare parts and changes damaged spare parts to photograph cheating protection.

In order to achieve the above purpose, the present application adopts the following technical scheme:

in a first aspect, the present application provides a risk determination method for use in an On-board automated diagnostic system (On-Board Diagnostics, OBD), the method comprising:

after receiving the high-level signal through the pin of the OBD, determining a target accessory with an association relation with the pin and receiving time for receiving the high-level signal, acquiring vehicle characteristic data and a vehicle running state at the current moment, and then determining the risk of manually dismantling the target accessory according to the vehicle characteristic data, the vehicle running state and the receiving time. Wherein, the target accessory is connected with the pin through a relay; the receiving time is the moment when the target accessory is disconnected with the relay; the vehicle characteristic data includes respective events occurring in the vehicle and occurrence times of the respective events.

Based on the above technical scheme, the risk determination method provided by the application can determine the target accessory with an association relation with the pin and the receiving time for receiving the high-level signal after receiving the high-level signal through the pin of the OBD, acquire the vehicle characteristic data and the vehicle running state at the current moment, and then determine the risk of manually dismantling the target accessory according to the vehicle characteristic data, the vehicle running state and the receiving time for receiving the high-level signal. Therefore, through the method, the behavior of shooting and cheating the user to disassemble the automobile parts privately and replace the damaged parts can be accurately identified.

Optionally, determining the risk of the target accessory being manually removed according to the vehicle characteristic data, the vehicle running state and the receiving time includes:

and determining a target time range according to the receiving time, determining target characteristic data with occurrence time within the target time range from the vehicle characteristic data, and then determining the risk of manually removing the target accessory according to the target characteristic data and the vehicle running state.

Optionally, the target characteristic data comprises vehicle collision data; determining the risk of the target accessory being manually removed according to the target characteristic data and the vehicle driving state, wherein the method comprises the following steps of:

Determining the risk of manually dismantling the target accessory as low risk when the vehicle running state identifies that the vehicle is in a stationary state and the vehicle collision data identifies that the vehicle has a collision event; and determining the risk of manually removing the target accessory as a risk of collision under the condition that the vehicle running state identifies that the vehicle is in the running state and the vehicle collision data identifies that the vehicle has a collision event.

Optionally, the target characteristic data includes vehicle collision data and vehicle brake data; determining the risk of the target accessory being manually removed according to the target characteristic data and the vehicle driving state, wherein the method comprises the following steps of:

when the vehicle running state indicates that the vehicle is in a static state, the vehicle collision data indicates that the vehicle does not have a collision event, and the vehicle braking data indicates that the vehicle does not have a braking event, the risk of manually dismantling the target accessory is determined to be high risk; determining the risk of manually dismantling the target accessory as a risk of collision when the vehicle running state identifies that the vehicle is in a running state, the vehicle collision data identifies that the vehicle has a collision event, and the vehicle brake data identifies that the vehicle has a brake event; and determining the risk of manually removing the target accessory as low risk when the vehicle running state indicates that the vehicle is in a running state, the vehicle collision data indicates that the vehicle does not have a collision event, and the vehicle braking data indicates that the vehicle does not have a braking event.

Optionally, the target characteristic data comprises vehicle brake data; determining the risk of the target accessory being manually removed according to the target characteristic data and the vehicle driving state, wherein the method comprises the following steps of:

and determining the risk of manually removing the target accessory as low risk when the vehicle running state identifies that the vehicle is running and the vehicle braking data identifies that the vehicle has a braking event.

In a second aspect, the present application provides a risk determination device, the device being located at an OBD, the device comprising:

the determining unit is used for determining a target accessory with an association relation with the pin and receiving time for receiving the high-level signal after receiving the high-level signal through the pin of the OBD; the target accessory is connected with the pin through a relay; the receiving time is the moment when the target accessory is disconnected with the relay;

an acquisition unit for acquiring vehicle characteristic data and a vehicle running state at the current moment; the vehicle characteristic data comprises various events which occur to the vehicle and the occurrence time of the various events;

and the processing unit is used for determining the risk of manually dismantling the target accessory according to the vehicle characteristic data, the vehicle running state and the receiving time.

Optionally, the processing unit is specifically configured to:

Optionally, the target characteristic data comprises vehicle collision data; the processing unit is specifically configured to:

Optionally, the target characteristic data includes vehicle collision data and vehicle brake data; the processing unit is specifically configured to:

Optionally, the target characteristic data comprises vehicle brake data; the processing unit is specifically configured to:

In a third aspect, the present application provides an electronic device, the apparatus comprising: a processor and a memory configured to store processor-executable instructions; wherein the processor is configured to execute the instructions to implement any of the optional risk determination methods of the first aspect described above.

In a fourth aspect, the present application provides a computer readable storage medium having instructions stored therein which, when run on a terminal, cause the terminal to perform a risk determination method as described in any one of the possible implementations of the first aspect and the first aspect.

Drawings

Fig. 1 is an application scenario diagram of a risk determining method provided in an embodiment of the present application;

fig. 2 is a diagram of connection relationship among a rearview mirror, an OBD and a relay according to an embodiment of the present application;

fig. 3 is a schematic diagram of an OBD pin according to an embodiment of the present disclosure;

Fig. 4 is a schematic connection diagram of a relay and pins of an OBD according to an embodiment of the present disclosure;

fig. 5 is a schematic flow chart of a risk determining method according to an embodiment of the present application;

FIG. 6 is a graph of the relationship between the time of receipt and the time of occurrence of each event according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a risk determining apparatus according to an embodiment of the present application;

fig. 8 is a schematic diagram of one possible structure of an electronic device according to an embodiment of the present application.

Detailed Description

The following describes a time screening method and device provided in the embodiments of the present application in detail with reference to the accompanying drawings.

The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone.

The terms "first" and "second" and the like in the description and in the drawings are used for distinguishing between different objects or for distinguishing between different processes of the same object and not for describing a particular sequential order of objects.

Furthermore, references to the terms "comprising" and "having" and any variations thereof in the description of the present application are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or apparatus.

It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.

In order to solve the technical problem, according to the risk determination method provided by the application, after a high-level signal is received through a pin of an OBD, a target accessory with an association relation with the pin and receiving time for receiving the high-level signal are determined, vehicle characteristic data are obtained, and then the risk that the target accessory is manually removed is determined according to the vehicle characteristic data and the receiving time. Therefore, through the method, the behavior of shooting and cheating the user to disassemble the automobile parts privately and replace the damaged parts can be accurately identified.

Fig. 1 is an application scenario diagram of a risk determination method provided in an embodiment of the present application, where, as shown in fig. 1, the application scenario diagram includes an OBD101, a relay 102 and an accessory 103. An accessory 103 may be connected to OBD101 via a relay 102.

In the present embodiment, the fitting 103 may be any fitting on a vehicle, such as a headlight, a bumper, a door, or a rearview mirror. The following describes a connection relationship between the OBD101, the relay 102, and the accessory 103, taking the accessory 103 as a rearview mirror.

Fig. 2 is a diagram of connection relationship among a rearview mirror, an OBD101 and a relay 102 according to an embodiment of the present application. As shown in fig. 2, during vehicle installation, a worker may connect the rear view mirror and the relay 102 with a thin wire, form a weak current loop, and connect the relay 102 and the OBD101 with a thin wire so that the relay 102 may send a level signal to the OBD 101.

In an embodiment of the present application, the OBD101 may include a plurality of pins, and each pin may be connected to one device. Exemplary, fig. 3 is a schematic diagram of a pin of an OBD according to an embodiment of the present application. As shown in fig. 3, the OBD101 includes 16 pins, from pin 1 to pin 16, respectively, wherein pin 1, pin 3, pin 8, pin 9, pin 11, pin 12, and pin 13 are idle pins.

Pin 2, pin 4, pin 5, pin 6, pin 7, pin 10, pin 14, pin 15, and pin 16 are the pins used. The No. 2 pin is a bus positive wire (bus positive Line) pin, the No. 4 pin is a chassis ground wire (chassis ground) pin, the No. 5 pin is a signal ground wire (signal ground) pin, the No. 6 pin is a CAN high wire (CAN-H Line) pin, the No. 7 pin is a K-Line pin, the No. 10 pin is a bus negative wire (Bus negative Line) pin, the No. 14 pin is a CAN low wire (CAN-L Line) pin, the No. 15 pin is an L-Line pin, and the No. 16 interface is a power supply pin.

In the process of connecting the relay 102 and the OBD101, one free pin in the OBD101 may be used to connect one relay. The following description will take as an example that the relay 102 is connected to the pin 14 of the idle pins of the OBD101.

For example, fig. 4 is a schematic connection diagram of a relay 102 and a pin 14 of an OBD101 provided IN the embodiment of the present application, as shown IN fig. 4, an IN interface of the relay 102 may be connected to the pin 14 of the OBD101, and an accessory 103 is connected to an NO interface and a COM interface of the relay 102 to form a weak current loop.

After the OBD101, the relay 102 and the accessory 103 are connected IN the above manner, the IN interface of the relay 102 may output a low-level signal to the OBD101 when the weak current loop between the relay 102 and the accessory 103 is not disconnected, and the IN interface of the relay 102 may output a high-level signal to the OBD101 when the weak current loop between the relay 102 and the accessory 103 is disconnected.

After the OBD101 receives the high-level signal through a certain pin of the OBD101, determining the accessory having an association relation with the pin and the receiving time of the high-level signal, acquiring vehicle characteristic data, and finally determining the risk of manually dismantling the target accessory according to the vehicle characteristic data and the receiving time of the high-level signal.

Fig. 5 is a flow chart of a risk determining method according to an embodiment of the present application, as shown in fig. 5, where the method includes:

in step S501, after receiving the high-level signal through the pin of the OBD, the target accessory having an association relationship with the pin and the receiving time for receiving the high-level signal are determined.

The target accessory is connected with the pin through a relay. Specifically, reference may be made to the connection manners of fig. 1, fig. 2 and fig. 4, which are not described herein.

The reception time of the high-level signal is the time when the target accessory is disconnected from the relay.

Specifically, after a thin wire connected between any accessory on the vehicle and the relay is disconnected, the relay can send a high-level signal to the OBD, and after the OBD receives the high-level signal through a certain pin, the OBD can determine a target accessory having an association relation with the pin and a receiving time for receiving the high-level signal.

Step S502, acquiring vehicle characteristic data and a vehicle running state at the current time.

The vehicle characteristic data includes each event that a vehicle occurs and the occurrence time of each event, for example, the occurrence time of a collision event that the vehicle occurs and the occurrence time of the collision event, and the occurrence time of a braking event that the vehicle occurs and the occurrence time of the braking event.

In an alternative embodiment, the OBD may also record vehicle characteristic data in real time.

Specifically, in some embodiments, assuming that the vehicle characteristic data includes vehicle braking data and vehicle collision data, the OBD may acquire a speed of the vehicle at preset time intervals, and determine whether a braking event and a collision event occur to the vehicle according to the speed of the vehicle. In the event that a braking event is determined to occur in the vehicle, the OBD may store the braking event and the time of occurrence of the braking event, and in the event that a collision event is determined to occur in the vehicle, the OBD may store the collision event and the time of occurrence of the collision event.

The process of determining whether a braking event and a collision event occur in a vehicle may refer to the prior art, and will not be described herein.

Step S503, determining the risk of the target accessory being manually removed according to the vehicle characteristic data, the vehicle running state and the receiving time.

After the target accessory having the association relationship with the pin and the receiving time for receiving the high-level signal are obtained through the steps S501 and S502, the OBD may first obtain the vehicle feature data and the vehicle running state at the current moment, and then determine the risk of the target accessory being manually removed according to the vehicle feature data, the vehicle running state and the receiving time.

Specifically, in some embodiments, in the process of determining the risk of manually removing the target accessory according to the vehicle feature data and the receiving time, the OBD may determine the target time range according to the receiving time, then determine the target feature data with the occurrence time within the target time range from the vehicle feature data, and finally determine the risk of manually removing the target accessory according to the target feature data and the vehicle driving state.

Optionally, in determining the target time range according to the receiving time, the target time range may be obtained according to the receiving time and a preset duration.

In the embodiment of the present application, the preset duration may be 1 minute or 30 seconds, and the embodiment of the present application does not specifically limit the preset duration.

Illustratively, in one embodiment, the vehicle characteristic data includes 3 events (event a, event B, and event C) and 3 event occurrence times, where the event a occurrence time is 9:30, the event B occurrence time is 10:00, and the event C occurrence time is 10:01. Assuming a receive time of 10:01 and a preset duration of 1 minute, the OBD may determine the target time range to be 10:00-10:02.

After the target time range is determined, the OBD can screen vehicle characteristic data (namely an event B and an event C) with the occurrence time between 10:00 and 10:02 from the vehicle characteristic data according to the occurrence time of each event in the vehicle characteristic data, take the event B and the event C as target characteristic data, and finally determine the risk of manually dismantling the target accessory according to the event B, the event C and the vehicle running state at the current moment.

In other embodiments, in the process of determining the risk of manually removing the target accessory according to the vehicle feature data and the receiving time, the OBD may first determine a time difference between the occurrence time and the receiving time of each event, then take the vehicle feature data with the time difference smaller than the time difference threshold as the target feature data, and finally determine the risk of manually removing the target accessory according to the target feature data and the vehicle driving state.

In the embodiment of the present application, the time difference threshold may be 1 minute or 30 seconds, and the time difference threshold is not specifically limited in the embodiment of the present application.

For example, suppose that the OBD records vehicle characteristic data include vehicle braking data and vehicle crash data, the vehicle braking data includes respective braking events and occurrence times of the respective braking events occurring in the vehicle, and the vehicle crash data includes respective crash events and occurrence times of the respective crash events occurring in the vehicle. Fig. 6 is a graph of a relationship between a receiving time and an occurrence time of each event provided in the embodiment of the present application, as shown in fig. 6, T1 is a receiving time when the OBD receives a high level signal, that is, T1 is an event that a thin line between the target accessory and the relay is broken. T2 is the occurrence time of each braking event, and T3 is the occurrence time of each crash event. T2 and T3 each include a plurality of times. Δta is the difference between the occurrence time of each braking event and T1, and Δtb is the difference between the occurrence time of each crash event and T1. Each of Δta and Δtb includes a plurality of differences.

Assuming that the time difference threshold is QT, the OBD can take a braking event corresponding to a difference value smaller than QT in DeltaTA and a collision event corresponding to a difference value smaller than QT in DeltaTB as target feature data, and finally determining the risk of manually dismantling the target accessory according to the target feature data and the vehicle running state at the current moment.

In an alternative embodiment, the target feature data may include at least one of vehicle collision data and vehicle brake data, and the following will include the vehicle collision data from the target feature data; B. the target characteristic data comprises vehicle brake data; C. the target characteristic data comprises vehicle collision data and vehicle brake data, and the risk of determining the target accessory to be manually removed according to the target characteristic data and the running state of the vehicle at the current moment is described in detail.

A. The target characteristic data comprises vehicle collision data

In the case where the target feature data includes vehicle collision data, in the process of determining the risk of the target accessory being manually removed according to the target feature data, the OBD may determine the risk of the target accessory being manually removed as a low risk when the vehicle running state identifies that the vehicle is in a stationary state and the vehicle collision data identifies that the vehicle is in a collision event (i.e., when the vehicle is in a stopped state, the thin line between the target accessory and the relay is broken).

Alternatively, the OBD may determine the risk of the target accessory being manually removed as a risk of collision if the vehicle travel state identifies that the vehicle is in a travel state, and the vehicle collision data identifies that the vehicle is in a collision event (i.e., that the vehicle is crashed during travel resulting in a thin wire between the target accessory and the relay being broken).

B. The target characteristic data comprises vehicle brake data

In the case where the target feature data includes vehicle braking data, in the process of determining the risk of manually removing the target accessory according to the target feature data, the OBD may determine the risk of manually removing the target accessory as a low risk when the vehicle is in a driving state according to the vehicle driving state, and the vehicle braking data identifies that a braking event occurs in the vehicle (i.e., when the vehicle brakes during driving to cause a thin line between the target accessory and the relay to be disconnected).

C. The target characteristic data comprises vehicle collision data and vehicle brake data

In the case where the target feature data includes vehicle collision data and vehicle brake data, in the process of determining the risk of the target accessory being manually removed according to the target feature data, the OBD may determine the risk of the target accessory being manually removed as a high risk in the case where the vehicle is in a stationary state as identified by the vehicle driving state, the vehicle collision data identifies that the vehicle is not involved in a collision event, and the vehicle brake data identifies that the vehicle is not involved in a brake event (i.e., the target accessory is manually removed in a stopped state, resulting in a thin line break between the target accessory and the relay).

Or, the OBD may determine a risk of the target accessory being manually removed as a risk of a collision if the vehicle running state identifies that the vehicle is in a running state, the vehicle collision data identifies that the vehicle is in a collision event, and the vehicle braking data identifies that the vehicle is in a braking event (i.e., the vehicle actively brakes during running to cause a thin line between the target accessory and the relay to be broken).

Or, the OBD may determine the risk of the target accessory being manually removed as a low risk when the vehicle running state identifies that the vehicle is in a running state, the vehicle collision data identifies that the vehicle is not experiencing a collision event, and the vehicle braking data identifies that the vehicle is not experiencing a braking event (i.e., that a jolt of the vehicle during running results in a thin line between the target accessory and the relay being broken).

By the method, the disconnection reason can be determined timely through the vehicle brake data and the vehicle collision data at the moment when the target accessory is disconnected with the relay, so that the risk that the target accessory is manually dismantled is determined, and therefore, the user can be accurately identified by the method for privately dismantling the automobile spare and accessory parts.

In an alternative embodiment, after determining the risk of the target accessory being manually removed in the above manner, the OBD may output a corresponding risk parameter in response to a risk determination instruction for the target accessory.

Specifically, the risk parameter corresponding to the high risk is assumed to be a first parameter, the risk parameter corresponding to the medium risk is assumed to be a second parameter, and the risk parameter corresponding to the low risk is assumed to be a third parameter, wherein the first parameter is larger than the second parameter, and the second parameter is larger than the third parameter. If the risk of the target accessory being manually removed is high risk, the OBD may output a first parameter in response to a risk determination instruction for the target accessory. If the risk of the target accessory being manually removed is a stroke risk, the OBD may output a second parameter in response to a risk determination instruction for the target accessory. If the risk of the target accessory being manually removed is low, the OBD may output a third parameter in response to a risk determination instruction for the target accessory.

In this embodiment of the present application, the first parameter may be 3, the second parameter may be 2, and the third parameter may be 1.

After staff of the insurance company obtains the risk parameter of the target accessory being manually removed through the above manner, corresponding claim settlement processing can be made, for example, if the risk parameter is 1, the risk of the target accessory being manually removed is low risk, the insurance company can directly settle the claim, if the risk parameter is not 1, the risk of the target accessory being manually removed is medium risk or high risk, the insurance company can request the insurance applicant to provide auxiliary proof data, and the claim settlement is carried out after the data verification is passed.

By the method, users can be prevented from disassembling automobile spare parts privately or falsifying accident sites to cheat car insurance compensation, and staff of an insurance company can judge whether the insurance company belongs to fraudulent behaviors according to weak current loop interruption time and the vehicle characteristic data recorded by OBD. Thus, the identification capability of insurance fraud can be improved, and rights and interests of insurance companies and consumers can be protected.

Fig. 7 is a schematic structural diagram of a risk determining apparatus according to an embodiment of the present application, as shown in fig. 7, where the apparatus includes:

a determining unit 701, configured to determine, after receiving the high-level signal through the pin of the OBD, a target accessory having an association relationship with the pin and a receiving time for receiving the high-level signal; the target accessory is connected with the pin through a relay; the receiving time is the moment when the target accessory is disconnected with the relay;

an acquiring unit 702, configured to acquire vehicle characteristic data and a vehicle running state at a current time; the vehicle characteristic data comprises various events which occur to the vehicle and the occurrence time of the various events;

a processing unit 703 for determining the risk of the target accessory being manually removed based on the vehicle characteristic data, the vehicle driving status and the time of receipt.

Optionally, the processing unit 703 is specifically configured to:

Optionally, the target characteristic data comprises vehicle collision data; the processing unit 703 is specifically configured to:

Optionally, the target characteristic data includes vehicle collision data and vehicle brake data; the processing unit 703 is specifically configured to:

Optionally, the target characteristic data comprises vehicle brake data; the processing unit 703 is specifically configured to:

Fig. 8 illustrates a schematic block diagram of an example electronic device 800 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the electronic device 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory 802 or a computer program loaded from a storage unit 808 into a random access memory 803. In the random access memory (Random Access Memory, RAM) 803, various programs and data required for the operation of the electronic device 800 can also be stored. The computing unit 801, a Read-Only Memory (ROM) 802, and a RAM803 are connected to each other through a bus 804. An input/output interface 805 is also connected to the bus 804.

The various components in the electronic device 800 are connected to an Input/Output (I/O) interface 805, including: an input unit 806 such as a keyboard, mouse, etc.; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, or the like. The communication unit 809 allows the electronic device 800 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

The computing unit 801 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 801 include, but are not limited to, a central processing unit, a graphics processing unit (Graphics Processing Unit, GPU), various dedicated artificial intelligence (Artificial Intelligence, AI) computing chips, various computing units running machine learning model algorithms, digital signal processors, and any suitable processors, controllers, microcontrollers, and the like. The computing unit 801 performs the respective methods and processes described above, such as a software version update method. For example, in one embodiment, the risk determination method may be implemented as a computer version program tangibly embodied on a machine-readable medium, such as the storage unit 808. In one embodiment, part or all of the computer program may be loaded and/or installed onto the electronic device 800 via the ROM802 and/or the communication unit 809. When a computer program is loaded into RAM803 and executed by computing unit 801, one or more steps of the risk determination method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the risk determination method by any other suitable means (e.g. by means of firmware).

Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays, application specific integrated circuits, application specific standard products (Application Specific Standard Parts, ASSP), system On Chip (SOC), complex programmable logic devices (Complex Programmable Logic Device, CPLD), computer hardware, firmware, versions, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone version package, partly on the machine and partly on a remote machine or entirely on a remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical fiber, a portable compact disc read-only memory, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device for displaying information to a user, for example, a Cathode Ray Tube (CRT) or a liquid crystal display (Liquid Crystal Display, LCD) monitor; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local area network (Local Area Network, LAN), wide area network (Wide Area Network, WAN) and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel or sequentially or in a different order, provided that the desired results of the technical solutions of the present disclosure are achieved, and are not limited herein.

The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims

1. A risk determination method for use in an on-board automatic diagnostic system, OBD, the method comprising:

after receiving a high-level signal through a pin of the OBD, determining a target accessory with an association relation with the pin and receiving time for receiving the high-level signal; the target accessory is connected with the pin through a relay; the receiving time is the moment when the target accessory is disconnected with the relay;

Acquiring vehicle characteristic data and a vehicle running state at the current moment; the vehicle characteristic data comprises various events which occur to the vehicle and the occurrence time of the various events;

and determining the risk of manually dismantling the target accessory according to the vehicle characteristic data, the vehicle running state and the receiving time.

2. The method of claim 1, wherein the determining the risk of the target accessory being manually removed based on the vehicle characteristic data, the vehicle travel state, and the time of receipt comprises:

determining a target time range according to the receiving time;

determining target feature data with occurrence time within the target time range from the vehicle feature data;

and determining the risk of manually dismantling the target accessory according to the target characteristic data and the vehicle running state.

3. The method of claim 2, wherein the target characteristic data comprises vehicle collision data;

the determining the risk of manually removing the target accessory according to the target characteristic data and the vehicle running state comprises the following steps:

determining the risk of the target accessory being manually removed as a low risk if the vehicle travel state identifies that the vehicle is in a stationary state and the vehicle collision data identifies that the vehicle is in a collision event;

And determining the risk of the target accessory being manually removed as a risk of collision if the vehicle driving state identifies that the vehicle is in a driving state and the vehicle collision data identifies that the vehicle is in a collision event.

4. The method of claim 2, wherein the target characteristic data includes vehicle collision data and vehicle brake data;

determining the risk of the target accessory being manually removed as a high risk when the vehicle running state identifies that the vehicle is in a stationary state, the vehicle collision data identifies that the vehicle is not subject to a collision event, and the vehicle braking data identifies that the vehicle is not subject to a braking event;

determining the risk of the target accessory being manually removed as a risk of collision when the vehicle running state identifies that the vehicle is in a running state, the vehicle collision data identifies that the vehicle is in a collision event, and the vehicle braking data identifies that the vehicle is in a braking event;

and determining the risk of manually removing the target accessory as low risk when the vehicle running state identifies that the vehicle is in a running state, the vehicle collision data identifies that the vehicle does not have a collision event, and the vehicle braking data identifies that the vehicle does not have a braking event.

5. The method of claim 2, wherein the target characteristic data comprises vehicle brake data;

6. A risk determination device, wherein the device is located at an OBD, the device comprising:

7. The apparatus according to claim 6, wherein the processing unit is specifically configured to:

determining a target time range according to the receiving time;

8. The apparatus of claim 7, wherein the target characteristic data comprises vehicle collision data; the processing unit is specifically configured to:

9. The apparatus of claim 7, wherein the target characteristic data comprises vehicle crash data and vehicle brake data; the processing unit is specifically configured to:

10. The apparatus of claim 7, wherein the target characteristic data comprises vehicle brake data; the processing unit is specifically configured to:

11. An electronic device, the electronic device comprising:

a processor;

a memory configured to store the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the risk determination method of any of claims 1-5.

12. A computer readable storage medium having instructions stored therein, wherein when executed by a computer, the computer performs the risk determination method of any of claims 1-5.