Vehicle accident early warning method, zero terminal, system, medium and equipment

Abstract

The invention relates to a vehicle accident early warning method, a zero terminal, a system, a medium and equipment. Comprising the steps that a zero terminal notifies a camera to collect field image data of a vehicle based on a received pressure signal; wherein the pressure signal is a signal collected by the impacted sensor; the zero terminal performs hierarchical processing on the acquired field image data, and sends the processed field image data and the position information of the vehicle acquired by the zero terminal to the cloud server; and the zero terminal obtains the current lane, the staying time and the number of the collided sensors of the vehicle, and sends the current lane, the staying time and the number of the collided sensors to the cloud server. Through the method, the accident condition of the accident vehicle can be actively acquired, and the early warning information can be quickly generated, so that the rear driving vehicle can be timely notified, and the rear driving vehicle can timely avoid and pass.

Description

Background Art

[0002] When a vehicle is in motion, if it suddenly has a traffic accident, the vehicles behind it will continue to drive at normal speeds because they are unaware of the traffic accident ahead. This will cause traffic congestion, which can easily lead to another accident. In addition, after a vehicle has a traffic accident, if the navigation software is used to report the accident to the passing car owners and alert the vehicles behind, this method of relying heavily on the initiative of the car owners to report is likely to result in untimely reporting, which will also cause traffic congestion, which can easily lead to another accident.

[0003] Therefore, it is necessary to provide a new technical solution to improve one or more problems existing in the above 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 application, 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 this application is to provide a vehicle accident warning method, zero terminal, system, medium and device, thereby overcoming one or more problems caused by the limitations and defects of related technologies at least to a certain extent.

[0006] According to a first aspect of an embodiment of the present application, a vehicle accident warning method is provided, wherein a sensor is installed at different positions of the vehicle, and each of the sensors is connected to a zero terminal; the method comprises:

[0007] The zero terminal notifies the camera to collect on-site image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that is hit;

[0008] The zero terminal performs layered processing on the collected on-site image data, and sends the processed on-site image data and the location information of the vehicle acquired by the zero terminal to the cloud server;

[0009] The zero terminal obtains the current lane, residence time and the number of sensors hit by the vehicle, and sends the current lane, residence time and the number of sensors hit to the cloud server, so that the cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane and the cause of the accident based on the processed on-site image data, the location information, the current lane, the residence time and the number of sensors hit, so that the cloud server generates warning information based on the accident level, the exact location of the accident, the affected lane and the cause of the accident, and sends the warning information to the vehicle behind the vehicle in the accident.

[0010] In an embodiment of the present application, the step of the zero terminal performing layered processing on the collected on-site image data includes:

[0011] The null terminal encodes the data of the Y component in the live image data;

[0012] And the encoded on-site image data is sent to the cloud server.

[0013] In an embodiment of the present application, the current lane of the vehicle is obtained from third-party software via the zero terminal;

[0014] The dwell time is calculated by the zero terminal based on the time the vehicle is at the dwelling position after the accident and the time the vehicle is not at the dwelling position after the accident. The dwelling position is the position where the vehicle stops after the accident.

[0015] The number of the sensors impacted is determined by the number of the zero terminals transmitting information to the cloud server.

[0016] According to a second aspect of an embodiment of the present application, a vehicle accident warning method is provided, wherein a sensor is installed at different positions of the vehicle, and each of the sensors is connected to a zero terminal, and the method comprises:

[0017] The cloud server receives the vehicle location information, the vehicle's current lane, the dwell time, the number of sensors impacted, and processed scene image data sent by the zero terminal; wherein the processed scene image data is data obtained by the zero terminal performing layered processing on the collected scene image data; the scene image data is the scene image data of the vehicle collected by the zero terminal notifying the camera based on the received pressure signal; the pressure signal is a signal collected by the sensor impacted;

[0018] The cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, the location information, the current lane, the dwell time, and the number of the sensors hit;

[0019] The cloud server generates warning information according to the accident level, the accurate location of the accident, the affected lanes and the cause of the accident, and sends the warning information to the vehicles behind the vehicle in the accident.

[0020] In an embodiment of the present application, the current lane of the vehicle is obtained from third-party software via the zero terminal;

[0021] The dwell time is calculated by the zero terminal based on the time the vehicle is at the dwelling position after the accident and the time the vehicle is not at the dwelling position after the accident. The dwelling position is the position where the vehicle stops after the accident.

[0022] The number of the sensors impacted is determined by the number of the zero terminals transmitting information to the cloud server.

[0023] In an embodiment of the present application, the cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, the location information, the current lane, the dwell time, and the number of the sensors hit, including:

[0024] The cloud server obtains the accident level of the vehicle according to the processed on-site image data;

[0025] The cloud server obtains the accurate location of the accident based on the location information and the current lane;

[0026] The cloud server acquires the affected lane according to the current lane;

[0027] The cloud server obtains the cause of the accident based on the processed on-site image data.

[0028] In an embodiment of the present application, the step of the cloud server acquiring the accident level of the vehicle according to the processed on-site image data includes:

[0029] If the on-site image data shows that the number of affected lanes is one, then the accident level of the vehicle is determined to be a minor accident;

[0030] If the on-site image data shows that there are two affected lanes, then the accident level of the vehicle is determined to be a serious accident;

[0031] If the on-site image data shows that three or more lanes are affected, the accident level of the vehicle is determined to be a major accident.

[0032] In an embodiment of the present application, after the step of the cloud server generating warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and sending the warning information to the vehicle behind the vehicle where the accident occurred, the step further includes:

[0033] When the vehicle involved in the accident stays in the current lane for less than a preset time period and the accident level is a minor accident, the vehicle involved in the accident sends the warning information to the rear vehicle traveling at a preset distance from the vehicle involved in the accident, so that the rear vehicle can avoid and pass in advance;

[0034] When the vehicle involved in the accident stays in the current lane for longer than a preset time period and the accident level is a serious accident or a major accident, the vehicle involved in the accident will send the warning information to the rear vehicle that is at a preset distance from the first fork in the road behind the vehicle involved in the accident, so that the rear vehicle can give way in advance.

[0035] According to a third aspect of an embodiment of the present application, a zero terminal is provided, and the vehicle accident warning method described in any one of the above embodiments is applied. The zero terminal includes:

[0036] A notification module is used for the zero terminal to notify the camera to collect on-site image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that has been hit;

[0037] A layered processing module, used for the zero terminal to perform layered processing on the collected on-site image data, and send the processed on-site image data and the location information of the vehicle acquired by the zero terminal to the cloud server;

[0038] An acquisition and sending module is used for the zero terminal to acquire the current lane, residence time and the number of sensors hit by the vehicle, and send the current lane, residence time and the number of sensors hit to the cloud server, so that the cloud server can acquire the accident level of the vehicle, the exact location of the accident, the affected lane and the cause of the accident based on the processed on-site image data, the location information, the current lane, the residence time and the number of sensors hit; so that the cloud server can generate warning information based on the accident level, the exact location of the accident, the affected lane and the cause of the accident, and send the warning information to the vehicle traveling behind the vehicle in the accident.

[0039] According to a fourth aspect of an embodiment of the present application, a vehicle accident warning system is provided, applying the vehicle accident warning method described in any one of the above embodiments, the system comprising:

[0040] A receiving module, used for the cloud server to receive the vehicle's location information, the vehicle's current lane, the vehicle's stay time, the number of sensors hit, and processed scene image data sent by the zero terminal; wherein the processed scene image data is data obtained by the zero terminal performing layered processing on the collected scene image data, and the scene image data is data of the scene image data of the vehicle where the zero terminal notifies the camera to collect after receiving the pressure signal of the sensor when any of the sensors on the vehicle is hit;

[0041] An acquisition module, configured for the cloud server to acquire the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, the location information, the current lane, the dwell time, and the number of the sensors hit;

[0042] A generating and sending module is used for the cloud server to generate warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and send the warning information to the rear vehicles of the vehicle involved in the accident.

[0043] According to a fifth aspect of an embodiment of the present application, 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 accident warning method described in any one of the above embodiments are implemented.

[0044] According to a sixth aspect of an embodiment of the present application, there is provided an electronic device, including:

[0045] Processor; and

[0046] A memory, configured to store executable instructions of the processor;

[0047] Wherein, the processor is configured to execute the steps of the vehicle accident warning method described in any one of the above embodiments by executing the executable instructions.

[0048] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0049] In one embodiment of the present application, through the above method, the zero terminal obtains the current lane, dwell time and number of sensors hit by the vehicle, and sends the processed on-site image data, location information, current lane, dwell time and number of sensors hit to the cloud server, so as to obtain the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident, and generate warning information, which is then sent to the rear vehicles to enable the rear vehicles to avoid and pass in advance. Through this method, not only can the accident situation of the accident vehicle be actively obtained and warning information be quickly generated so that the rear vehicles can be notified in time so that the rear vehicles can avoid and pass in time, but also road congestion and the probability of another accident can be reduced.

[0050] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 A flowchart schematically showing a method for early warning of a vehicle accident in an exemplary embodiment of the present application;

[0053] Figure 2 A flowchart schematically showing another method for early warning of a vehicle accident in an exemplary embodiment of the present application;

[0054] Figure 3 A block diagram schematically shows a zero terminal in an exemplary embodiment of the present application;

[0055] Figure 4 A block diagram schematically shows a vehicle accident warning system in an exemplary embodiment of the present application;

[0056] Figure 5 A schematic diagram of a program product in an exemplary embodiment of the present application is schematically shown;

[0057] Figure 6 A schematic diagram of an electronic device in an exemplary embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0058] 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 this application will be more comprehensive and complete and 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.

[0059] In addition, the accompanying drawings are only schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus 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.

[0060] In this example implementation, a vehicle accident warning method is first provided, wherein a sensor is installed at different positions of the vehicle, and each of the sensors is connected to a zero terminal. Figure 1 As shown in , the method may include: steps S101 to S103.

[0061] Wherein, step S101: the zero terminal notifies the camera to collect on-site image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that is hit;

[0062] Step S102: the zero terminal performs layered processing on the collected on-site image data, and sends the processed on-site image data and the location information of the vehicle acquired by the zero terminal to the cloud server;

[0063] Step S103: The zero terminal obtains the vehicle's current lane, dwell time and the number of sensors that have been hit, and sends the current lane, dwell time and the number of sensors that have been hit to the cloud server, so that the cloud server can obtain the vehicle's accident level, the exact location of the accident, the affected lane and the cause of the accident based on the processed on-site image data, location information, current lane, dwell time and the number of sensors that have been hit, so that the cloud server can generate warning information based on the accident level, the exact location of the accident, the affected lane and the cause of the accident, and send the warning information to the vehicles behind the vehicle where the accident occurred.

[0064] In one embodiment of the present application, through the above method, the zero terminal obtains the current lane, dwell time and number of sensors hit by the vehicle, and sends the processed on-site image data, location information, current lane, dwell time and number of sensors hit to the cloud server, so as to obtain the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident, and generate warning information, which is then sent to the rear vehicles to enable the rear vehicles to avoid and pass in advance. Through this method, not only can the accident situation of the accident vehicle be actively obtained and warning information can be quickly generated so that the rear vehicles can be notified in time so that the rear vehicles can avoid and pass in time, but also road congestion and the probability of another accident can be reduced.

[0065] Next, we will refer to Figure 1 Each step of the above method in this example implementation is described in more detail.

[0066] Before discussing the method of the present application, the sensor and the zero terminal are first explained.

[0067] A sensor is installed at different positions of the vehicle. Exemplarily, a sensor is installed at the left front position of the front of the vehicle, the middle position of the front of the vehicle, the right front position of the front of the vehicle, the middle position of the left and right sides of the vehicle body, the left rear position of the rear of the vehicle, the middle position of the rear of the vehicle, and the right rear position of the rear of the vehicle. And each sensor is individually connected to a zero terminal, and each zero terminal is individually connected to a camera. In addition, each zero terminal is connected to a communication device, and the communication device is a 4G / 5G communication device. Among them, the sensor is a pressure sensor, and when the sensor is hit by an external force, a pressure signal is generated. Therefore, when the sensor is hit by an external force, the sensor is used to collect the pressure signal. Each sensor is individually connected to a zero terminal for sending the pressure signal to the zero terminal. The zero terminal is an image acquisition zero terminal.

[0068] In step S101, when a vehicle is driving and an accident occurs, the sensor at the corresponding position on the vehicle will also be hit. When the sensor is hit, the sensor will collect a pressure signal. After the sensor collects the pressure signal, it will send the pressure signal to the zero terminal connected to the sensor. At this time, the zero terminal will trigger the camera to collect the scene image data of the vehicle where the accident occurred based on the received pressure signal, so as to facilitate the subsequent processing of the scene image data.

[0069] In step S102, after the zero terminal collects the on-site image data, the on-site image data corresponding to the on-site image data is subjected to layered processing. The specific layered processing process includes the following sub-step S1021 contents:

[0070] The zero terminal encodes the data of the Y component in the live image data;

[0071] And send the encoded on-site image data to the cloud server.

[0072] It should be noted that hierarchical processing is hierarchical coding processing, and hierarchical coding only encodes the data of the Y component, but not the data of the U component and the V component. This is mainly because: the human eye is more sensitive to brightness information (Y component) and less sensitive to chrominance information (U component, V component); compression of chrominance components can significantly improve coding efficiency while having little impact on visual quality; by reducing the resolution of U and V components, the amount of data can be greatly reduced, and the computational complexity can be reduced without affecting visual perception. Therefore, encoding only the data of the Y component can minimize the impact on visual quality while ensuring a high compression rate.

[0073] After the layered processing is completed, the zero terminal sends the encoded on-site image data to the cloud server for subsequent processing.

[0074] In addition, the zero terminal can obtain the vehicle's location information through a positioning module (such as GPS), and send the vehicle's location information to the cloud server for subsequent processing by the cloud server.

[0075] In step S103, when the zero terminal obtains the current lane of the vehicle, it obtains the current lane through a third-party software. The third-party software may be Amap or Tencent Map. The zero terminal obtains the dwell time based on the time the vehicle is at the dwell position after the accident and the time the vehicle is not at the dwell position after the accident. The dwell position is the position where the vehicle stops after the accident. The number of sensors that are impacted is determined by the number of zero terminals that transmit information to the cloud server.

[0076] The zero terminal sends the acquired current lane, dwell time and number of sensors hit to the cloud server, so that the cloud server conducts a comprehensive analysis of the received processed on-site image data, location information, current lane, dwell time and number of sensors hit to determine the vehicle's accident level, the exact location of the accident, the affected lane and the cause of the accident.

[0077] Furthermore, the cloud server obtains the accident level of the vehicle based on the processed on-site image data; the cloud server obtains the exact location of the accident based on the location information and the current lane; the cloud server obtains the affected lane based on the current lane; the cloud server obtains the cause of the accident based on the processed on-site image data.

[0078] It should be noted that the affected lane may be the current lane or the adjacent lane, depending on the actual situation, which will not be elaborated in this application.

[0079] By analyzing the processed on-site image data, the cause of the vehicle accident can be determined, which may be a vehicle collision, road collapse, landslide or mud-rock flow.

[0080] Furthermore, the step of the cloud server obtaining the accident level of the vehicle according to the processed on-site image data includes:

[0081] If the on-site image data shows that there is only one affected lane, the accident level of the vehicle is determined to be a minor accident;

[0082] If the on-site image data shows that there are two affected lanes, the accident level of the vehicle is determined to be a serious accident;

[0083] If the on-site image data shows that three or more lanes are affected, the vehicle's accident level is determined to be a major accident.

[0084] It is understandable that the above method of determining the accident level can accurately

[0085] The cloud server generates warning information according to the accident level, the exact location of the accident, the affected lanes and the cause of the accident, and sends the warning information to the vehicles behind the vehicle where the accident occurred, including the following steps:

[0086] When the vehicle involved in the accident stays in the current lane for less than a preset time period and the accident level is a minor accident, the vehicle involved in the accident will send a warning message to the vehicle behind it that is at a preset distance from the vehicle involved in the accident, so that the vehicle behind it can give way in advance.

[0087] When the vehicle involved in the accident stays in the current lane for longer than a preset time period and the accident level is a serious accident or a major accident, the vehicle involved in the accident will send a warning message to the rear vehicle traveling at a preset distance from the first fork behind the vehicle involved in the accident, so that the rear vehicle can give way in advance.

[0088] It is understandable that the stay time can be 30min-1h, and the preset time period can be set according to actual conditions, which will not be elaborated in this application.

[0089] For minor accidents, the stay time of the vehicle involved in the accident is generally short, and the scene can usually be cleared quickly by traffic police and tow trucks. The stay time of a vehicle involved in a minor accident is generally 30 minutes to 1 hour. The preset time period can be set according to actual conditions, and this application will not go into details.

[0090] When the vehicle involved in the accident stays in the current lane for 30 minutes to 1 hour (this time period is less than the preset time period), and the accident level is a minor accident, it does not affect traffic. At this time, when the accident occurs and the vehicle behind the vehicle drives to the preset distance from the vehicle involved in the accident, the vehicle involved in the accident notifies the vehicle behind it through the third-party software to inform the vehicle behind that a traffic accident has occurred at a preset distance ahead at a certain time, and to facilitate the driver of the vehicle behind to drive carefully and avoid traffic in advance.

[0091] For serious or major accidents, the vehicles involved in the accident usually stay for a long time, seriously affecting traffic. The vehicles involved in serious or major accidents usually stay for more than 1 hour.

[0092] When the vehicle involved in the accident stays in the current lane for more than 1 hour (this time period is greater than the preset time period), and the accident level is a serious accident or a major accident, which seriously affects traffic. At this time, when the accident occurs from the vehicle behind the vehicle to the preset distance of the first fork behind the vehicle involved in the accident, the vehicle involved in the accident notifies the vehicle behind it through the third-party software to inform the vehicle behind it that a traffic accident occurred at a preset distance of the fork ahead at a certain time, and to facilitate the driver of the vehicle behind to drive carefully and avoid traffic in advance.

[0093] It should be noted that the preset distance can be 1km or other values, which can be set according to actual conditions, and this application will not go into details.

[0094] This example implementation also provides a vehicle accident warning method, in which a sensor is installed at different positions of the vehicle, and each sensor is connected to a zero terminal. Figure 2 The method includes: step S201 to step S203.

[0095] Wherein, step S201: the cloud server receives the location information of the vehicle, the current lane of the vehicle, the dwell time, the number of sensors hit and the processed scene image data sent by the zero terminal; wherein the processed scene image data is the data obtained by the zero terminal performing layered processing on the collected scene image data; the scene image data is the scene image data of the vehicle collected by the zero terminal based on the received pressure signal notified by the camera; the pressure signal is the signal collected by the sensor hit;

[0096] Step S202: The cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, location information, current lane, dwell time, and the number of sensors hit;

[0097] Step S203: The cloud server generates warning information according to the accident level, the exact location of the accident, the affected lanes and the cause of the accident, and sends the warning information to the vehicles behind the vehicle where the accident occurred.

[0098] In one embodiment, the current lane of the vehicle is obtained from third-party software via a zero terminal;

[0099] The zero-terminal dwell time is calculated based on the time the vehicle spends at the dwelling location after the accident and the time the vehicle is not at the dwelling location after the accident. The dwelling location is the location where the vehicle stops after the accident.

[0100] The number of sensors hit is determined by the number of zero terminals that transmit information to the cloud server.

[0101] In one embodiment, the cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, location information, current lane, dwell time, and number of sensors hit, including:

[0102] The cloud server obtains the accident level of the vehicle based on the processed on-site image data;

[0103] The cloud server obtains the exact location of the accident based on the location information and the current lane;

[0104] The cloud server obtains the affected lane based on the current lane;

[0105] The cloud server obtains the cause of the accident based on the processed on-site image data.

[0106] In one embodiment, the step of obtaining the accident level of the vehicle according to the processed on-site image data by the cloud server includes:

[0107] If the on-site image data shows that there is only one affected lane, the accident level of the vehicle is determined to be a minor accident;

[0108] If the on-site image data shows that there are two affected lanes, the accident level of the vehicle is determined to be a serious accident;

[0109] If the on-site image data shows that three or more lanes are affected, the vehicle's accident level is determined to be a major accident.

[0110] In one embodiment, the cloud server generates warning information according to the accident level, the exact location of the accident, the affected lanes and the cause of the accident, and sends the warning information to the vehicles behind the vehicle where the accident occurred, further comprising:

[0111] When the vehicle involved in the accident stays in the current lane for less than a preset time period and the accident level is a minor accident, the vehicle involved in the accident will send a warning message to the rear vehicle traveling at a preset distance from the vehicle involved in the accident, so that the rear vehicle will give way in advance;

[0112] When the vehicle involved in the accident stays in the current lane for longer than a preset time period and the accident level is a serious accident or a major accident, the vehicle involved in the accident will send a warning message to the rear vehicle traveling at a preset distance from the first fork behind the vehicle involved in the accident, so that the rear vehicle can give way in advance.

[0113] It should be noted that the discussion of the vehicle accident warning method when the cloud server of this application is the execution subject has been elaborated in detail in the above embodiment when the zero terminal is the execution subject, and this application will not repeat it.

[0114] It should be noted that, although the steps of the method in the present application are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution, etc. In addition, it is also easy to understand that these steps may be, for example, executed synchronously or asynchronously in multiple modules / processes / threads.

[0115] Furthermore, in this exemplary embodiment, a zero terminal is also provided. Figure 3 As shown in , the zero terminal 100 includes: a notification module 110, a hierarchical processing module 120 and an acquisition and sending module 130. The notification module 110 is used for the zero terminal to notify the camera to collect the scene image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that is hit; the hierarchical processing module 120 is used for the zero terminal to perform hierarchical processing on the collected scene image data, and send the processed scene image data and the location information of the vehicle obtained by the zero terminal to the cloud server; the acquisition and sending module 130 is used for the zero terminal to obtain the current lane, the stay time and the number of sensors that are hit by the vehicle, and send the current lane, the stay time and the number of sensors that are hit to the cloud server, so that the cloud server can obtain the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident according to the processed scene image data, location information, the current lane, the stay time and the number of sensors that are hit; and so that the cloud server can generate warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and send the warning information to the vehicle behind the vehicle that has the accident.

[0116] In one embodiment, the null terminal further includes:

[0117] An encoding module, used for encoding the Y component data in the field image data at the zero terminal;

[0118] The sending module is used to send the encoded on-site image data to the cloud server.

[0119] In this exemplary embodiment, a vehicle accident warning system is also provided. Figure 4 As shown in , the system 200 includes: a receiving module 210, an acquisition module 220 and a generation and sending module 230. The receiving module 210 is used for the cloud server to receive the location information of the vehicle, the current lane of the vehicle, the dwell time, the number of sensors hit and the processed scene image data sent by the zero terminal; the processed scene image data is the data obtained by the zero terminal performing layered processing on the collected scene image data, and the scene image data is the data of the scene image data of the vehicle where the zero terminal notifies the camera to collect after receiving the pressure signal of the sensor when any sensor on the vehicle is hit; the acquisition module 220 is used for the cloud server to obtain the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident according to the processed scene image data, location information, the current lane, the dwell time and the number of sensors hit; the generation and sending module 230 is used for the cloud server to generate warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and send the warning information to the vehicle behind the vehicle where the accident occurred.

[0120] In one embodiment, the system further comprises:

[0121] The first acquisition submodule is used for the cloud server to obtain the accident level of the vehicle according to the processed on-site image data;

[0122] The second acquisition submodule is used for the cloud server to obtain the accurate location of the accident based on the location information and the current lane;

[0123] The third acquisition submodule is used for the cloud server to acquire the affected lane according to the current lane;

[0124] The fourth acquisition submodule is used for the cloud server to obtain the cause of the accident based on the processed on-site image data.

[0125] In one embodiment, the system further comprises:

[0126] A first determination module, configured to determine that the accident level of the vehicle is a minor accident if the scene image data shows that the affected lane is one;

[0127] A second determination module is used to determine that the accident level of the vehicle is a serious accident if the scene image data shows that there are two affected lanes;

[0128] The third determination module is used to determine that the accident level of the vehicle is a major accident if the on-site image data shows that three or more lanes are affected.

[0129] In one embodiment, the system further comprises:

[0130] The first generation and sending submodule is used for, when the vehicle involved in the accident stays in the current lane for less than a preset time period and the accident level is a minor accident, the vehicle involved in the accident sends a warning message to the rear vehicle traveling at a preset distance from the vehicle involved in the accident, so that the rear vehicle can avoid and pass in advance;

[0131] The second generation and sending submodule is used for, when the vehicle involved in the accident stays in the current lane for more than a preset time period and the accident level is a serious accident or a major accident, the vehicle involved in the accident will send a warning message to the rear vehicle traveling at a preset distance from the first fork behind the vehicle involved in the accident, so that the rear vehicle can avoid and pass in advance.

[0132] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0133] It should be noted that although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the implementation mode of the present application, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of a module or unit described above can be further divided into multiple modules or units for concretization. The components displayed as modules or units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the present application scheme. Those of ordinary skill in the art can understand and implement it without paying creative work.

[0134] In an exemplary embodiment of the present application, a computer-readable storage medium is also provided, on which a computer program is stored, and when the program is included in a processor and executed, the steps of the vehicle accident warning method described in any of the above embodiments can be implemented. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary embodiments of the present invention described in the above vehicle accident warning method section of this specification.

[0135] refer to Figure 5 As shown, a program product 300 for implementing the above method according to an embodiment of the present invention is described, 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 of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0136] The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may 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 (a 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.

[0137] The computer readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or used in combination with it. The program code contained on the readable storage medium may be transmitted with any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0138] Program code for performing the operations 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 conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, 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).

[0139] In an exemplary embodiment of the present application, an electronic device is also provided, which may include a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to execute the steps of the vehicle accident warning method described in any one of the above embodiments by executing the executable instructions.

[0140] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0141] Refer to the following Figure 6 The electronic device 600 according to this embodiment of the present invention is described. Figure 6 The electronic device 600 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0142] like Figure 6 As shown, the electronic device 600 is in the form of a general computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different system components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0143] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps of various exemplary embodiments of the present invention described in the vehicle accident warning method section above. For example, the processing unit 610 can execute the following steps: Figure 1Follow the steps shown in .

[0144] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0145] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 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 the implementation of a network environment.

[0146] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0147] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. Furthermore, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. 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 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0148] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation method of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including a number of instructions to enable a computing device (which can be a personal computer, a server or a network device, etc.) to execute the above-mentioned vehicle accident warning method according to the implementation method of the present application.

[0149] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the art that are not disclosed in the present application.

Claims

1. A vehicle accident early warning method, characterized in that: A sensor is installed at different positions of the vehicle, and each of the sensors is connected to a zero terminal; the method comprises: The zero terminal notifies the camera to collect on-site image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that is hit; The zero terminal performs layered processing on the collected on-site image data, and sends the processed on-site image data and the location information of the vehicle acquired by the zero terminal to the cloud server; The zero terminal obtains the current lane, residence time and the number of sensors hit by the vehicle, and sends the current lane, residence time and the number of sensors hit to the cloud server, so that the cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane and the cause of the accident based on the processed on-site image data, the location information, the current lane, the residence time and the number of sensors hit, so that the cloud server generates warning information based on the accident level, the exact location of the accident, the affected lane and the cause of the accident, and sends the warning information to the vehicle behind the vehicle in the accident.

2. The vehicle accident warning method according to claim 1, characterized in that: The step of the zero terminal performing layered processing on the collected on-site image data includes: The null terminal encodes the data of the Y component in the live image data; The encoded on-site image data is sent to the cloud server.

3. The vehicle accident warning method according to claim 1, characterized in that: The current lane of the vehicle is obtained from third-party software via the zero terminal; The dwell time is calculated by the zero terminal based on the time the vehicle is at the dwelling position after the accident and the time the vehicle is not at the dwelling position after the accident. The dwelling position is the position where the vehicle stops after the accident. The number of the sensors impacted is determined by the number of the zero terminals transmitting information to the cloud server.

4. A vehicle accident early warning method, characterized in that: A sensor is installed at different positions of the vehicle, and each of the sensors is connected to a zero terminal. The method includes: The cloud server receives the vehicle location information, the vehicle's current lane, the dwell time, the number of sensors impacted, and processed scene image data sent by the zero terminal; wherein the processed scene image data is data obtained by the zero terminal performing layered processing on the collected scene image data; the scene image data is the scene image data of the vehicle collected by the zero terminal notifying the camera based on the received pressure signal; the pressure signal is a signal collected by the sensor impacted; The cloud server obtains the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, the location information, the current lane, the dwell time, and the number of the sensors hit; The cloud server generates warning information according to the accident level, the accurate location of the accident, the affected lanes and the cause of the accident, and sends the warning information to the vehicles behind the vehicle in the accident.

5. The vehicle accident warning method according to claim 4, characterized in that: The current lane of the vehicle is obtained from third-party software via the zero terminal; The dwell time is calculated by the zero terminal based on the time the vehicle is at the dwelling position after the accident and the time the vehicle is not at the dwelling position after the accident. The dwelling position is the position where the vehicle stops after the accident. The number of the sensors impacted is determined by the number of the zero terminals transmitting information to the cloud server.

6. The vehicle accident warning method according to claim 4, characterized in that: The step of obtaining the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident by the cloud server according to the processed on-site image data, the location information, the current lane, the dwell time and the number of the sensors hit includes: The cloud server obtains the accident level of the vehicle according to the processed on-site image data; The cloud server obtains the accurate location of the accident based on the location information and the current lane; The cloud server acquires the affected lane according to the current lane; The cloud server obtains the cause of the accident based on the processed on-site image data.

7. The vehicle accident warning method according to claim 6, characterized in that: The step of the cloud server acquiring the accident level of the vehicle according to the processed on-site image data includes: If the on-site image data shows that the number of affected lanes is one, then the accident level of the vehicle is determined to be a minor accident; If the on-site image data shows that there are two affected lanes, then the accident level of the vehicle is determined to be a serious accident; If the on-site image data shows that three or more lanes are affected, the accident level of the vehicle is determined to be a major accident.

8. The vehicle accident warning method according to claim 4, characterized in that: The cloud server generates warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and sends the warning information to the vehicle behind the vehicle where the accident occurred, further comprising: When the vehicle involved in the accident stays in the current lane for less than a preset time period and the accident level is a minor accident, the vehicle involved in the accident sends the warning information to the rear vehicle traveling at a preset distance from the vehicle involved in the accident, so that the rear vehicle can avoid and pass in advance; When the vehicle involved in the accident stays in the current lane for longer than a preset time period and the accident level is a serious accident or a major accident, the vehicle involved in the accident will send the warning information to the rear vehicle that is at a preset distance from the first fork in the road behind the vehicle involved in the accident, so that the rear vehicle can give way in advance.

9. A zero terminal, characterized in that: The vehicle accident warning method according to any one of claims 1 to 8 is applied, and the zero terminal comprises: A notification module is used for the zero terminal to notify the camera to collect on-site image data of the vehicle based on the received pressure signal; wherein the pressure signal is a signal collected by the sensor that has been hit; A layered processing module, used for the zero terminal to perform layered processing on the collected on-site image data, and send the processed on-site image data and the location information of the vehicle acquired by the zero terminal to the cloud server; An acquisition and sending module is used for the zero terminal to acquire the current lane, residence time and the number of sensors hit by the vehicle, and send the current lane, residence time and the number of sensors hit to the cloud server, so that the cloud server can acquire the accident level of the vehicle, the accurate location of the accident, the affected lane and the cause of the accident based on the processed on-site image data, the position information, the current lane, the residence time and the number of sensors hit, so that the cloud server can generate warning information based on the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and send the warning information to the vehicle traveling behind the vehicle in the accident.

10. A vehicle accident warning system, characterized in that: The vehicle accident warning method according to any one of claims 1 to 8 is applied, and the system comprises: A receiving module, used for the cloud server to receive the vehicle's location information, the vehicle's current lane, the vehicle's stay time, the number of sensors hit, and processed scene image data sent by the zero terminal; wherein the processed scene image data is data obtained by the zero terminal performing layered processing on the collected scene image data, and the scene image data is data of the scene image data of the vehicle where the zero terminal notifies the camera to collect after receiving the pressure signal of the sensor when any of the sensors on the vehicle is hit; An acquisition module, configured for the cloud server to acquire the accident level of the vehicle, the exact location of the accident, the affected lane, and the cause of the accident based on the processed on-site image data, the location information, the current lane, the dwell time, and the number of the sensors hit; A generating and sending module is used for the cloud server to generate warning information according to the accident level, the accurate location of the accident, the affected lane and the cause of the accident, and send the warning information to the rear vehicles of the vehicle involved in the accident.

11. 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 8 are implemented.

12. 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 8 by executing the executable instructions.

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