Vehicle early warning method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention relates to a vehicle early warning method and system, electronic equipment and a storage medium. The method comprises the steps that an image acquisition zero terminal receives data exception information sent by an infrared sensor in a disaster occurrence area, wherein the data exception information comprises signal receiving failure information or signal exception change information; the image acquisition zero terminal notifies the cameras of the disaster occurrence area and the associated area to respectively acquire images of the disaster occurrence area and the associated area; the image acquisition zero terminal sends acquired image data and position information to the server; the server judges the disaster type and the road congestion condition according to the image data and the position information; and the server generates early warning information according to the disaster type and the road congestion condition, and sends the early warning information to the vehicles in the disaster occurrence area and the associated area. According to the invention, abnormity reporting does not depend on the initiative of the vehicle owner, the reporting is faster and more timely, the capability of quickly analyzing disaster and congestion conditions is provided, and the early warning accuracy is improved.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of vehicle warning technology, and in particular, to a vehicle warning method, system, electronic device, and storage medium. Background Art

[0002] When vehicles are driving, if an accident occurs in front, such as a natural disaster affecting road safety, or a traffic accident occurs in front of the vehicle, the rear vehicle will drive at a normal speed without receiving any warning, which may easily lead to another accident or increase the degree of congestion; if the rear vehicle receives a prompt message through the navigation software, it may be possible for the rear vehicle to avoid danger, but the accident information of the navigation software is usually obtained by the owner of the vehicle in front through active reporting. Therefore, this type of prompt information is heavily dependent on the initiative of the owner of the vehicle in front, and there is a possibility that untimely reporting will lead to more serious congestion or danger.

[0003] Therefore, it is necessary to improve one or more problems existing in the above-mentioned related technical solutions.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present disclosure is to provide a vehicle warning method, system, electronic device and storage medium, thereby overcoming one or more problems caused by the limitations and defects of the relevant technology at least to a certain extent.

[0006] According to a first aspect of an embodiment of the present disclosure, a vehicle warning method is provided, the method comprising the following steps:

[0007] The image acquisition zero terminal receives data anomaly information sent by infrared sensors in the disaster-occurring area, wherein the data anomaly information includes signal reception failure information or signal abnormal change information;

[0008] The image acquisition zero terminal notifies the cameras in the disaster-occurring area and the associated area to respectively acquire images of the disaster-occurring area and the associated area;

[0009] The image acquisition zero terminal sends the acquired image data and location information to the server;

[0010] The server determines the disaster type and road congestion situation according to the image data and the location information;

[0011] The server generates warning information according to the disaster type and road congestion, and sends the warning information to vehicles in the disaster-occurring area and the associated areas.

[0012] In an exemplary embodiment of the present disclosure, the data anomaly information includes: distance information between the obstacle and the infrared sensor or the road obtained according to the signal reception failure information or the signal abnormal change information.

[0013] In an exemplary embodiment of the present disclosure, the associated area includes: a driving area located behind the disaster occurrence area on the road.

[0014] In an exemplary embodiment of the present disclosure, the step of the image acquisition zero terminal sending the acquired image data and location information to the server includes:

[0015] The image acquisition zero terminal encodes the Y component of the acquired image data;

[0016] The encoded image data and location information are sent to the server.

[0017] In an exemplary embodiment of the present disclosure, the step of the server determining the disaster type and the road congestion situation according to the image data and the location information includes:

[0018] The server determines the congestion condition of the rear road section according to the image and location information of the associated area;

[0019] The server synthesizes the image data, location information and congestion conditions of the disaster area and the road sections behind into a three-dimensional model;

[0020] Comparing the three-dimensional model with a standard model stored in a database to determine the disaster type corresponding to the three-dimensional model;

[0021] Based on the current congestion situation of the rear road section and the type of disaster mentioned, the impact level on traffic flow in the later stage is estimated.

[0022] In an exemplary embodiment of the present disclosure, the method further includes:

[0023] The three-dimensional model is sent to the traffic control department.

[0024] In an exemplary embodiment of the present disclosure, the method further includes:

[0025] Determine the hazard level based on the type of disaster described;

[0026] The warning information is determined according to the hazard level and the impact level.

[0027] According to a second aspect of an embodiment of the present disclosure, a vehicle warning system is provided, the system comprising:

[0028] Multiple infrared sensors are set up in disaster-prone areas to monitor the environment around the road;

[0029] A plurality of cameras are arranged on a plurality of sections of the road, and are used to collect images on the plurality of sections;

[0030] A plurality of image acquisition zero terminals are connected to the plurality of infrared sensors and the plurality of cameras respectively, and are used to receive data anomaly information sent by the infrared sensors, and notify the cameras to collect images of the disaster-occurring area and the associated area;

[0031] The server is used to receive image data and location information sent by multiple image acquisition zero terminals, and determine the type of disaster and road congestion based on the image data and the location information, and then generate warning information based on the disaster type and road congestion, and send the warning information to the vehicles in the disaster-occurring area and the related areas.

[0032] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0033] Processor; and

[0034] A memory, configured to store executable instructions of the processor;

[0035] Wherein, the processor is configured to execute the steps of the vehicle warning method described in any of the above embodiments by executing the executable instructions.

[0036] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the steps of the vehicle warning method described in any one of the above embodiments are implemented.

[0037] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0038] In the embodiment of the present disclosure, the road sections prone to natural disasters are monitored by infrared sensors. When the infrared signal is abnormal, the data abnormality information is sent to the image acquisition zero terminal. The image acquisition zero terminal mobilizes the camera in the corresponding area to collect images of the area, and then sends the image data and location information to the server. The server then determines the type of disaster and road congestion and sends warning information to related vehicles. In this process, the abnormality reporting does not need to rely on the initiative of the car owner, the information reporting is faster and more timely, and has the ability to quickly analyze disasters and congestion, improve the accuracy of warnings, and provide a stronger guarantee for traffic safety and rapid relief of traffic obstacles.

[0039] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0041] Figure 1 A schematic diagram showing a flow chart of a vehicle warning method in an exemplary embodiment of the present disclosure;

[0042] Figure 2 A flowchart showing that an image acquisition zero terminal sends acquired image data and location information to a server in an exemplary embodiment of the present disclosure;

[0043] Figure 3 A flow chart showing a server determining a disaster type and a road congestion situation according to the image data and the location information in an exemplary embodiment of the present disclosure;

[0044] Figure 4 A schematic flow chart showing a vehicle warning method in another exemplary embodiment of the present disclosure;

[0045] Figure 5 A schematic structural diagram of a vehicle warning system in an exemplary embodiment of the present disclosure is shown;

[0046] Figure 6 A schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure is shown;

[0047] Figure 7 A schematic diagram showing the structure of a program product for implementing a vehicle warning method in an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0048] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0049] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0050] In this example implementation, a vehicle early warning method is first provided. Figure 1 As shown, the method may include the following steps:

[0051] S101, an image acquisition zero terminal receives data anomaly information sent by infrared sensors in a disaster-prone area, wherein the data anomaly information includes signal reception failure information or signal abnormal change information.

[0052] The disaster-prone areas in this process usually refer to the two sides of the bridge and locations prone to natural disasters such as collapse, landslide, and mud-rock flow. Multiple infrared sensors are installed in these dangerous areas. The infrared sensors emit infrared light and detect reflected light, or monitor changes in infrared radiation in the environment to determine whether there are objects blocking the way, thereby determining whether a disaster has occurred.

[0053] When a bridge shifts or collapses, or a natural disaster such as a landslide, mudslide, or debris flow occurs somewhere, the infrared sensor cannot receive the expected signal or signal change (reflected light), and then makes a "blocked" judgment, that is, the signal reception fails or the signal changes abnormally.

[0054] Typically, the data anomaly information includes: distance information between the obstacle and the infrared sensor or the road obtained according to the signal reception failure information or the signal abnormal change information. According to the distance information, it is possible to know where the disaster occurred.

[0055] S102, the image acquisition zero terminal notifies the cameras in the disaster-occurring area and the associated areas to respectively acquire images of the disaster-occurring area and the associated areas.

[0056] By collecting images of the disaster-occurring area, it is possible to further confirm whether a disaster has occurred and what kind of disaster has occurred. By collecting images of the associated area, the situation of the rear vehicles, such as the current congestion of the vehicles, etc., can be learned. For example, the associated area includes: a driving area on the road behind the disaster-occurring area.

[0057] S103, the image acquisition zero terminal sends the collected image data and location information to the server. The location information can be obtained by the preset number or device identification of the infrared sensor, camera or image acquisition zero terminal itself, and the location information and the image can be matched to quickly obtain the location and image of the disaster.

[0058] S104: The server determines the disaster type and road congestion situation according to the image data and the location information.

[0059] S105: The server generates warning information according to the disaster type and the road congestion situation, and sends the warning information to vehicles in the disaster-occurring area and the associated areas.

[0060] In this embodiment, infrared sensors are used to monitor road sections prone to natural disasters. When an infrared signal is abnormal, the data abnormality information is sent to the image acquisition zero terminal. The image acquisition zero terminal mobilizes the camera in the corresponding area to collect images of the area, and then sends the image data and location information to the server. The server then determines the type of disaster and road congestion and sends warning information to related vehicles. In this process, abnormal reporting does not need to rely on the initiative of the car owner, information reporting is faster and more timely, and has the ability to quickly analyze disasters and congestion, improve the accuracy of warnings, and provide a stronger guarantee for traffic safety and rapid relief of traffic obstacles.

[0061] Below, each step of the above method in this example implementation is described in more detail.

[0062] In step S101, the infrared sensor continuously or intermittently collects signals from the surrounding environment, and a normal data range can be set in advance. When the infrared sensor detects data abnormality or cannot receive data, the data abnormality information is sent to the image acquisition zero terminal connected to it. In one embodiment, when the information collected by the infrared sensor is within the normal data range, there is no need to send information to the image acquisition zero terminal.

[0063] In step S102, when a disaster occurs, not only image information of the disaster-occurring area can be collected, but also images of areas related to the disaster can be collected. This is because when a disaster occurs, although other areas have not yet been affected, they may also be in danger. Therefore, by collecting images of related areas, information on possible disasters can be collected more comprehensively and timely, or the scope of possible disasters can be predicted.

[0064] For specific explanation, please refer to Figure 2 , S103 specifically includes the following steps:

[0065] S201, the image acquisition zero terminal encodes the Y component of the acquired image data;

[0066] S202, sending the encoded image data and location information to the server.

[0067] In this embodiment, the image acquisition zero terminal layers the image, encodes only the Y component of the image data, and does not encode the U and V components, and transmits the encoded data to the storage server in real time through 4G / 5G communication equipment. This can improve the encoding and decoding efficiency, reduce the required bandwidth, and quickly convey danger information.

[0068] In addition, the images collected from the rear road section may be assigned different colors according to the degree of congestion, for example, red corresponds to severe congestion, yellow corresponds to moderate congestion, and green represents slight congestion.

[0069] Based on the above examples, please refer to Figure 3 Step S104 specifically includes the following steps:

[0070] S301, the server determines the congestion situation of the subsequent road section according to the image and location information of the associated area;

[0071] S302, the server synthesizes the image data, location information and congestion situation of the disaster area and the rear road section into a three-dimensional model;

[0072] S303, comparing the three-dimensional model with a standard model stored in a database to determine the disaster type corresponding to the three-dimensional model;

[0073] S304: Estimate the impact level on traffic flow in the later stage according to the current congestion situation of the rear road section and the disaster type.

[0074] In this embodiment, the standard model stored in the database is obtained by training a large amount of similar data. The standard model can be continuously trained to make it more accurate in restoring phenomena such as natural disasters.

[0075] The synthesis and comparison process of the 3D model is as follows:

[0076] First, use cameras to take multi-angle photos of both sides of the bridge and locations prone to natural disasters such as collapse, landslides, and mudslides, and record the location information of each photo. The multi-angle photos and location information are used to synthesize a normal three-dimensional model as the standard model.

[0077] Secondly, after a natural disaster occurs, the distance to obstacles and the location information of each infrared sensor are detected by multiple infrared sensors and marked on the three-dimensional model to obtain a three-dimensional model of the natural disaster scene. Then, combined with the traffic congestion situation captured by the infrared camera on the rear road section and marked on the three-dimensional model, a real-time three-dimensional model of the situation at the natural disaster scene and the traffic congestion situation can be obtained.

[0078] Finally, the actual three-dimensional model is compared with the standard model to determine the type of disaster that has occurred and to infer the level of impact on traffic.

[0079] It should be noted that, based on the above embodiments, please refer to Figure 4 The vehicle early warning method further comprises the following steps:

[0080] S401, determining a hazard level according to the disaster type;

[0081] S402: Determine warning information according to the hazard level and the impact level.

[0082] In this embodiment, the disaster types may include: bridge displacement, collapse, tunnel collapse, landslide, mudslide, etc., and may also include accidents such as vehicle collisions. When the disaster is serious and normal traffic is impossible, regardless of whether the rear vehicles are congested, an early warning message must be sent immediately to increase the warning level and prompt the vehicle to avoid danger as soon as possible. When the rear vehicle drives within a certain range, the rear vehicle is notified of the number of meters ahead and at what time a natural disaster has occurred, and the road cannot be normally passed, please take a detour.

[0083] When the accident is minor, there are still lanes that can be used normally. When the rear vehicle drives within a certain range, the rear vehicle will be prompted with a certain number of meters of road ahead and at what time a natural disaster has occurred, affecting several lanes and how many lanes can be used normally. Please drive carefully and avoid in advance.

[0084] The above notifications can be sent through navigation software or through communication base stations to mobile phones and other communication devices within the range. In an emergency, notifications can be made by phone to ensure the personal safety of the car owner to the greatest extent possible.

[0085] In addition, the generated 3D model can be sent to the traffic control department to provide accurate basis for traffic diversion and obstacle removal decision-making of the road management department. There can be multiple 3D models, specifically, a certain area corresponds to one 3D model.

[0086] This example implementation method secondly provides a vehicle warning system, referring to Figure 5 As shown, the system includes:

[0087] Multiple infrared sensors are set up in disaster-prone areas to monitor the environment around the road;

[0088] A plurality of cameras are arranged on a plurality of sections of the road, and are used to collect images on the plurality of sections;

[0089] A plurality of image acquisition zero terminals are connected to the plurality of infrared sensors and the plurality of cameras respectively, and are used to receive data anomaly information sent by the infrared sensors, and notify the cameras to collect images of the disaster-occurring area and the associated area;

[0090] The server is used to receive image data and location information sent by multiple image acquisition zero terminals, and determine the type of disaster and road congestion based on the image data and the location information, and then generate warning information based on the disaster type and road congestion, and send the warning information to the vehicles in the disaster-occurring area and the related areas.

[0091] In this embodiment, each infrared sensor can be connected to an image acquisition zero terminal, and each image acquisition zero terminal is also connected to a camera at the same time. More infrared sensors, image acquisition zero terminals and cameras are set in areas prone to disasters, and a small number are set in areas not prone to disasters. The above devices can be evenly set in areas not prone to disasters. At the same time, the data collection frequency of areas prone to disasters is increased, and the data collection frequency of areas not prone to disasters is reduced. Each infrared sensor, image acquisition zero terminal and camera can be numbered, and the number corresponds to the location information to quickly obtain the source of information.

[0092] The server may have storage and data processing functions to store and analyze the received image data and location information to determine the type of disaster and road congestion, and then generate warning information and send it to relevant vehicles or departments.

[0093] In this embodiment, infrared sensors are used to monitor road sections prone to natural disasters. When an infrared signal is abnormal, the data abnormality information is sent to the image acquisition zero terminal. The image acquisition zero terminal mobilizes the camera in the corresponding area to collect images of the area, and then sends the image data and location information to the server. The server then determines the type of disaster and road congestion and sends warning information to related vehicles. In this process, abnormal reporting does not need to rely on the initiative of the car owner, information reporting is faster and more timely, and has the ability to quickly analyze disasters and congestion, improve the accuracy of warnings, and provide a stronger guarantee for traffic safety and rapid relief of traffic obstacles.

[0094] See also Figure 6 The embodiment of the present invention further provides an electronic device 300, which includes at least one memory 310, at least one processor 320, and a bus 330 for connecting different platform systems.

[0095] The memory 310 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 311 and / or a cache memory 312 , and may further include a read-only memory (ROM) 313 .

[0096] Among them, the memory 310 also stores a computer program, which can be executed by the processor 320, so that the processor 320 executes the steps of the vehicle warning method in any embodiment of the present invention. Its specific implementation method is consistent with the implementation method and the technical effect achieved recorded in the above-mentioned vehicle warning method embodiment, and some contents will not be repeated here.

[0097] The memory 310 may also include a utility 314 having at least one program module 315, such program module 315 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0098] Accordingly, the processor 320 may execute the above-mentioned computer program and may execute the utility 314 .

[0099] Bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures.

[0100] The electronic device 300 may also communicate with one or more external devices 340 such as keyboards, pointing devices, Bluetooth devices, etc., and may also communicate with one or more devices that can interact with the electronic device 300, and / or communicate with any device (such as a router, a modem, etc.) that enables the electronic device 300 to communicate with one or more other computing devices. Such communication may be performed through an input / output interface 350. In addition, the electronic device 300 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 through a bus 330. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0101] An embodiment of the present invention also provides a computer-readable storage medium, which is used to store a computer program. When the computer program is executed, the steps of the vehicle warning method in the embodiment of the present invention are implemented. The specific implementation method is consistent with the implementation method and the technical effect achieved recorded in the embodiment of the above-mentioned vehicle warning method, and some contents will not be repeated here.

[0102] Figure 7 The program product 400 provided in this embodiment for implementing the above-mentioned vehicle warning method is shown, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product 400 of the present invention is not limited to this. In the present invention, the readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The program product 400 can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0103] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, wherein readable program codes are carried. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium may also be any readable medium, which may send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or for use in combination with it. The program code contained on the readable storage medium may be transmitted by any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above. The program code for performing the operation of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as C language or similar programming languages. The program code may be executed entirely on a user computing device, partially on a user device, as an independent software package, partially on a user computing device, partially on a remote computing device, or entirely on a remote computing device or server. Where a remote computing device is involved, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0104] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A vehicle early warning method, characterized in that: The method comprises the following steps: The image acquisition zero terminal receives data anomaly information sent by infrared sensors in the disaster-occurring area, wherein the data anomaly information includes signal reception failure information or signal abnormal change information; The image acquisition zero terminal notifies the cameras in the disaster-occurring area and the associated area to respectively acquire images of the disaster-occurring area and the associated area; The image acquisition zero terminal sends the acquired image data and location information to the server; The server determines the disaster type and road congestion situation according to the image data and the location information; The server generates warning information according to the disaster type and road congestion, and sends the warning information to vehicles in the disaster-occurring area and the associated areas.

2. The vehicle early warning method according to claim 1, characterized in that: The data abnormality information includes: distance information between the obstacle and the infrared sensor or the road obtained according to the signal reception failure information or the signal abnormal change information.

3. The vehicle early warning method according to claim 1, characterized in that: The associated area includes: a driving area on the road located behind the disaster occurrence area.

4. The vehicle early warning method according to claim 1, characterized in that: The step of the image acquisition zero terminal sending the acquired image data and location information to the server comprises: The image acquisition zero terminal encodes the Y component of the acquired image data; The encoded image data and location information are sent to the server.

5. The vehicle early warning method according to claim 1, characterized in that: The step of the server judging the disaster type and the road congestion situation according to the image data and the location information comprises: The server determines the congestion condition of the rear road section according to the image and location information of the associated area; The server synthesizes the image data, location information and congestion conditions of the disaster area and the road sections behind into a three-dimensional model; Comparing the three-dimensional model with a standard model stored in a database to determine the disaster type corresponding to the three-dimensional model; Based on the current congestion situation of the rear road section and the type of disaster mentioned, the impact level on traffic flow in the later stage is estimated.

6. The vehicle early warning method according to claim 5, characterized in that: The method further comprises: The three-dimensional model is sent to the traffic control department.

7. The vehicle early warning method according to claim 5, characterized in that: The method further comprises: Determine the hazard level based on the type of disaster described; The warning information is determined according to the hazard level and the impact level.

8. A vehicle warning system, characterized in that: The system comprises: Multiple infrared sensors are set up in disaster-prone areas to monitor the environment around the road; A plurality of cameras are arranged on a plurality of sections of the road, and are used to collect images on the plurality of sections; A plurality of image acquisition zero terminals are connected to the plurality of infrared sensors and the plurality of cameras respectively, and are used to receive data anomaly information sent by the infrared sensors, and notify the cameras to collect images of the disaster-occurring area and the associated area; The server is used to receive image data and location information sent by multiple image acquisition zero terminals, and determine the type of disaster and road congestion based on the image data and the location information, and then generate warning information based on the disaster type and road congestion, and send the warning information to the vehicles in the disaster-occurring area and the related areas.

9. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to execute the steps of the vehicle warning method according to any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the vehicle warning method according to any one of claims 1 to 7 are implemented.

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