Accident early warning method, device and system, electronic equipment and vehicle networking server

Abstract

The invention provides an accident early warning method, device and system, electronic equipment and an Internet of Vehicles server. The accident early warning method comprises the following steps: acquiring first position information of a first vehicle and a corresponding first geofence; under the condition that the accident information of the first vehicle is received, sending the accident information to the client and a second vehicle; wherein the second vehicle is another vehicle which is located in the first geo-fence and is associated with the first vehicle. The invention relates to the technical field of Internet of Vehicles, and can improve the timeliness of early warning of vehicle accidents.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, and in particular to an accident warning method, device, system, electronic equipment and Internet of Vehicles server. BACKGROUND

[0002] With the continuous growth of motor vehicles, driving safety and parking safety related problems have attracted widespread attention. When parking in public areas, vehicles may be damaged due to unexpected accidents. For example, vehicles may be subjected to collisions, scratches, parking penalties, etc. At present, the accident information is usually pushed to the user in time through the interaction between the vehicle end and the client, however, this accident warning method cannot provide warning information to the user before the accident occurs, resulting in low efficiency of vehicle accident warning. SUMMARY

[0003] In view of the above, it is necessary to provide an accident warning method, device, system, electronic equipment and Internet of Vehicles server to solve the technical problem of low efficiency of warning of vehicle accidents.

[0004] The present application provides an accident warning method applied to an electronic equipment, the electronic equipment is in communication connection with a first vehicle and a client respectively, and the method comprises: acquiring first position information of the first vehicle and a corresponding first geofence; in the case that accident information of the first vehicle is received, sending the accident information to the client and a second vehicle; wherein the second vehicle is other vehicles associated with the first vehicle located in the first geofence.

[0005] In some embodiments, the method further comprises determining the first geofence of the first vehicle, and the determining the first geofence of the first vehicle comprises: determining environmental information corresponding to the first vehicle according to the first position information; the environmental information is used to indicate the total number of vehicles in the surrounding of the first vehicle determined based on the video stream of the first vehicle; determining the first geofence corresponding to the first vehicle according to the environmental information.

[0006] In some embodiments, the determining the first geofence of the first vehicle comprises: determining road condition information corresponding to the first vehicle according to the environmental information; the road condition information is used to indicate the traffic load of the area where the first vehicle is located; determining the first geofence corresponding to the first vehicle according to the environmental information and the road condition information.

[0007] In some embodiments, the determining the first geofence of the first vehicle comprises: determining a risk level of the first vehicle having an accident according to pre-stored historical position information and the first position information, wherein the historical position information is used to indicate a position where a vehicle accident has occurred; and determining the first geofence of the first vehicle according to the risk level.

[0008] In some embodiments, the determining the first geofence of the first vehicle comprises: determining a plurality of candidate geofences of the first vehicle based on the environment information and the road condition information; and determining the first geofence from the plurality of candidate geofences according to the risk level. In some embodiments, the method further comprises: determining a corresponding accident type according to the accident information before determining the second vehicle in the first geofence; the accident type is used to indicate semantics of the accident information; and updating the first geofence according to the accident type to obtain an updated first geofence.

[0009] Embodiments of the present application also provide an accident early warning device applied to an electronic device, the electronic device being communicatively connected with a first vehicle and a client, the device comprising: a positioning module configured to acquire first position information of the first vehicle and a corresponding first geofence; and an early warning module configured to send accident information of the first vehicle to the client and a second vehicle in the case that the accident information is received, wherein the second vehicle is another vehicle associated with the first vehicle and located in the first geofence.

[0010] Embodiments of the present application also provide an accident early warning system, the system comprising: an electronic device, a first vehicle and a client, the electronic device being communicatively connected with the first vehicle and the client; the electronic device being configured to: acquire first position information of the first vehicle and a corresponding first geofence; and send accident information of the first vehicle to the client and a second vehicle in the case that the accident information is received, wherein the second vehicle is another vehicle associated with the first vehicle and located in the first geofence.

[0011] Embodiments of the present application also provide an electronic device, the electronic device comprising a processor and a memory, the processor being configured to implement the accident early warning method when executing a computer program stored in the memory.

[0012] Embodiments of the present application also provide a vehicle networking server, the vehicle networking server comprising the electronic device.

[0013] It can be seen from the above technical solutions that the embodiments of the present application transmit the accident information in real time through multi-terminal communication. In the case of an accident of the first vehicle, the electronic device of the vehicle networking server timely transmits the accident information to the client corresponding to the first vehicle, and immediately triggers the early warning process. The first geographic fence is determined in real time based on the geographic location and environmental information of the area where the first vehicle is located, so as to ensure that more potential affected second vehicles can be covered when the accident information is pushed. The load of processing invalid data of non-accident information is reduced through the authorization information transmitted between the vehicle and the electronic device, thereby improving the utilization rate of the vehicle networking computing resources. The range of the accident information push is determined according to the first geographic fence, so as to ensure that the vehicle networking in the electronic device broadcasts the accident information to the surrounding vehicles, reduce the probability of secondary accidents, and improve the efficiency of accident early warning. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is an application scenario of an accident early warning method provided by an embodiment of the present application.

[0015] Figure 2 is a flowchart of an accident early warning method provided by an embodiment of the present application.

[0016] Figure 3 is a flowchart of a method for determining a first geographic fence provided by an embodiment of the present application.

[0017] Figure 4 is a flowchart of a method for determining a first geographic fence provided by another embodiment of the present application.

[0018] Figure 5 is a flowchart of a method for determining a first geographic fence provided by another embodiment of the present application.

[0019] Figure 6 is a flowchart of a method for determining a first geographic fence provided by another embodiment of the present application.

[0020] Figure 7 is a flowchart of a method for determining an updated first geographic fence provided by an embodiment of the present application.

[0021] Figure 8 is a flowchart of an accident early warning method provided by another embodiment of the present application.

[0022] Figure 9 is a flowchart of a method for determining accident information provided by an embodiment of the present application.

[0023] Figure 10 is a functional module diagram of an accident early warning device provided by an embodiment of the present application.

[0024] Figure 11is a schematic diagram of an accident warning system provided by an embodiment of the present application.

[0025] Figure 12 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to more clearly understand the purpose, features and advantages of the present application, the present application is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict. In the following description, a large number of specific details are set forth in order to facilitate a full understanding of the present application, and the described embodiments are only some of the embodiments of the present application, but not all the embodiments.

[0027] In addition, the terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used in the specification of the present application are only for the purpose of describing the specific embodiments of the present application, and are not intended to limit the present application. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0029] The embodiments of the present application provide an accident warning method, which can be applied to one or more electronic devices. The electronic device is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions. The hardware thereof includes but is not limited to microprocessors, application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0030] The electronic device can be any electronic product that can interact with the client, such as a personal computer, a tablet computer, a smart phone, a personal digital assistant (PDA), a game console, an interactive Internet Protocol Television (IPTV), a smart wearable device, and the like.

[0031] The electronic device can also include a network device and / or a client device. The network device includes, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of hosts or network servers based on cloud computing.

[0032] The network in which the electronic device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), and the like.

[0033] As Figure 1 The application provides an application scenario diagram of an accident early warning method. The accident early warning method can be applied to an accident early warning system 1. The accident early warning system 1 includes an electronic device 100, a first vehicle 200, and a client 300. The electronic device 100 is communicatively connected to the first vehicle 200 and the client 300. Specifically, the electronic device 100 can be communicatively connected to the first vehicle 200 and the client 300 through a 4G / 5G network, cellular Internet of Vehicles, Bluetooth, Wi-Fi, or the like. The electronic device 100 can be any cloud server with data transmission and data processing functions. The specific form of the electronic device 100 is not limited in the application.

[0034] The electronic device 100 is configured to determine first location information of the first vehicle 200 and a corresponding first geographic fence when receiving authorization information sent by the first vehicle 200, send accident information to the client 300 when receiving accident information of the first vehicle 200, determine second location information of any vehicle according to authorization information received by the electronic device 100, determine a second vehicle 400 in the first geographic fence according to the second location information and the first geographic fence, and send the accident information to the second vehicle 400.

[0035] The first vehicle 200 is configured to acquire video information of the first vehicle 200 in real time, perform target detection on a plurality of video frames in the video information to obtain a target detection result of each video frame, determine semantic information of each video frame according to the target detection result, and determine accident information of the first vehicle 200 according to the semantic information of each video frame.

[0036] In the present application, after the electronic device 100 starts to execute the program applied to the accident warning, the electronic device 100 monitors the authorization information of the first vehicle 200 in real time. When receiving the authorization information sent by the first vehicle 200, it indicates that the electronic device 100 has the right to obtain the geographic position and video information of the first vehicle 200, and then the electronic device 100 determines the first position information of the first vehicle 200 and the corresponding first geographic fence according to the authorization information. Wherein, the first geographic fence is used to indicate the physical boundary of the position where the first vehicle 200 is located. For example, the first geographic fence of the first vehicle 200 can be Figure 1 the first geographic fence 210 shown in the figure.

[0037] In the present application, when the first vehicle 200 identifies the accident information according to the video information around the vehicle body, the accident information is sent to the electronic device 100. The electronic device 100 sends the accident information to the client 300 to inform the user that the first vehicle 200 has an accident, so as to realize the real-time accident warning of the first vehicle 200.

[0038] In the present application, in order to warn the vehicles around the first vehicle 200 of the accident, that is, to warn the vehicles in the first geographic fence 210 of the accident, the second position information of any vehicle received by the electronic device 100 can be determined according to the authorization information of the vehicle, and the second vehicle in the first geographic fence can be determined according to the second position information and the first geographic fence 210. Specifically, when the second position information of any vehicle falls within the range of the first geographic fence 210, it is determined that the vehicle is a second vehicle. For example, Figure 1 As shown in the figure, the second position information of the vehicle 410 and the second position information of the vehicle 420 are used to indicate that the vehicle 410 and the vehicle 420 are within the range of the first geographic fence 210, so the vehicle 410 and the vehicle 420 can be determined as the second vehicle. The second position information of the vehicle 430 and the second position information of the vehicle 440 are used to indicate that the vehicle 430 and the vehicle 440 are outside the range of the first geographic fence 210, so the vehicle 430 and the vehicle 440 are not determined as the second vehicle.

[0039] In the present application, in order to improve the efficiency of the accident warning of the vehicles in the first geographic fence 210, the electronic device 100 can generate a warning information according to the accident information of the first vehicle 200, and send the accident information and the warning information to the second vehicle (for example, Figure 1 the vehicle 410 and the vehicle 420 shown in the figure). In this way, when the first vehicle 200 has an accident, the owner can be informed in time through the client 300. And the second vehicle (for example, Figure 1 the vehicle 410 and the vehicle 420 shown in the figure) within the range of the first geographic fence 210 can be informed synchronously, so as to improve the efficiency of the accident warning of the vehicles in the first geographic fence 210.

[0040] As shown in Figure 2 , it is a flow chart of an accident warning method provided by an embodiment of the present application. The order of steps in the flow chart can be changed according to different needs, and some steps can be omitted. The accident warning method provided by the embodiment of the present application includes the following steps.

[0041] S20, obtaining first position information of the first vehicle and a corresponding first geofence.

[0042] In an embodiment of the present application, when the server-based electronic device performs real-time accident warning on the vehicle, the electronic device in the server monitors the authorization information of the vehicle in real time. In the case of receiving the authorization information sent by the first vehicle, it indicates that the electronic device has the right to obtain the geographic position of the first vehicle, and then the electronic device sends a positioning request information to the first vehicle, and determines the first position information of the first vehicle and the corresponding first geofence according to the response information sent by the first vehicle. Wherein, the first position information can be the latitude and longitude information of the first vehicle, and the specific form of the first position information is not limited in the present application.

[0043] In an embodiment of the present application, the first geofence can be a location-based service (LBS) technology provided by a vehicle networking server running an electronic device to the first vehicle. It is used to indicate the virtual geographical boundary drawn in the electronic map based on the global positioning system, Beidou and other satellite navigation systems. When the vehicle enters, leaves or moves within the first geofence, the vehicle networking server running the electronic device can trigger a preset operation (for example, accident warning, speed limit prompt, or trajectory recording, etc.), so that the boundary defined by the geographical range where the first vehicle is located can be used to control the position of the first vehicle.

[0044] In an embodiment of the present application, multi-source fusion positioning of the first vehicle can be realized based on multiple positioning technologies to improve the accuracy of determining the first geofence based on the first position information. For example, the first position information can be determined based on satellite positioning signals, cellular network signals (such as 4G network or 5G network), wireless network signals, Bluetooth signals and other communication signals, so as to improve the positioning accuracy when the first vehicle is in a complex geographical environment. For example, when the first vehicle is in a complex environment such as urban road, tunnel, viaduct, etc., by comparing multiple positioning signals with third-party map data, the positioning deviation of the first vehicle can be corrected, thereby improving the accuracy of judging the boundary of the first geofence.

[0045] In an embodiment of the present application, the specific way to determine the geofence of the first vehicle is described in Figure 3 , Figure 4 , Figure 5 and Figure 6 Corresponding detailed description.

[0046] S21. Upon receiving the accident information of the first vehicle, the accident information is sent to the client and a second vehicle; wherein the second vehicle is another vehicle located within the first geographic fence and associated with the first vehicle.

[0047] In one embodiment of the present application, in order to improve the timeliness of reporting the accident information of the first vehicle, the accident information can be sent to the client and the second vehicle when the accident information of the first vehicle is received. The second vehicle is another vehicle located in the first geographic fence and associated with the first vehicle. The accident information can be used to indicate that the first vehicle has collided or scratched, and the accident information can also be used to indicate that the temporary parking location of the first vehicle has been investigated. The present application does not limit the specific content of the accident information. Specifically, the second location information of any vehicle is determined based on the authorization information of the arbitrary vehicle received by the electronic device; the second vehicle in the first geographic fence is determined based on the second location information and the first geographic fence; and the accident information is sent to the second vehicle.

[0048] Exemplarily, when a sensor in a first vehicle receives an accident signal, the onboard communication module collects data such as the accident time, the first vehicle's coordinates (e.g., latitude and longitude), and a vehicle identification code (e.g., vehicle frame number or engine serial number), and encapsulates the data into a message in a preset communication format (e.g., JSON format). The message is encrypted using an encryption algorithm (e.g., a hash algorithm) and transmitted via a cellular network to an IoV server. The accident signal can indicate, for example, that the first vehicle's sensor has received a signal indicating airbag deployment or an acceleration value exceeding a limit. Upon receiving the encrypted message from the vehicle, the IoV server, which runs an electronic device, decrypts the message using a preset decryption algorithm to obtain plaintext information. The server then parses the vehicle coordinates and vehicle identification code from the plaintext information to obtain vehicle-associated client information (e.g., owner ID, client account information). The server then transmits the accident information to the vehicle-associated client using a preset communication protocol (e.g., TCP, HTTP, etc.).

[0049] In an embodiment of the present application, in order to improve the efficiency of the accident warning, the electronic device further determines the second position information of the arbitrary vehicle according to the authorization information of the arbitrary vehicle. Specifically, after the arbitrary vehicle starts, the communication module of the arbitrary vehicle establishes an encrypted channel with the Internet of Vehicles server running the electronic device. In the case that the electronic device receives the authorization information sent by the arbitrary vehicle, it indicates that the electronic device has the right to obtain the geographic position of the arbitrary vehicle, then the electronic device sends a positioning request information to the arbitrary vehicle, and determines the second position information of the arbitrary vehicle according to the response information sent by the arbitrary vehicle. The second position information can be the latitude and longitude information of the arbitrary vehicle, and the specific form of the second position information is not limited in the present application.

[0050] In an embodiment of the present application, when the second position information of the arbitrary vehicle is obtained, the second position information and the first geographic fence are used to determine whether the arbitrary vehicle is within the range of the first geographic fence, and then determine whether to inform the vehicle of the accident information. In order to improve the accuracy of determining whether the arbitrary vehicle is within the range of the first geographic fence, the first geographic fence is updated according to the accident information before the second vehicle is determined according to the first geographic fence of the first vehicle and the second position information. For details of the method for determining the updated first geographic fence, please refer to Figure 7 The corresponding detailed description.

[0051] In an embodiment of the present application, in order to determine whether to push the accident information to the arbitrary vehicle for accident warning, the second position information of the vehicle and the geometric relationship of the first geographic fence are also calculated to determine whether the vehicle is in the range of the first geographic fence. Specifically, the second position information can include the latitude and longitude coordinates of the arbitrary vehicle, and can also include the altitude and timestamp of the arbitrary vehicle; when the first geographic fence is a circular boundary, the parameters of the first geographic fence include the center coordinates of the first geographic fence and the radius of the first geographic fence; when the first geographic fence is a polygon boundary, the parameters of the first geographic fence include the sequence of the vertex coordinates of the polygon. The specific shape of the first geographic fence is not limited in the present application.

[0052] For example, when the boundary shape of the first geographic fence is a circle, the distance between the vehicle and the center of the first geographic fence can be determined according to the second position information of the vehicle. If the distance is less than the radius of the first geographic fence, it is determined that the second position information of the vehicle is within the boundary of the first geographic fence, and then it is determined that the vehicle is the second vehicle.

[0053] For example, when the boundary of the first geofence is polygonal, whether the vehicle is within the first geofence can be determined based on the number of intersections between the vehicle and the boundary of the first geofence. Specifically, an extension line can be determined in any direction starting from the vehicle's location, and whether the vehicle is within the first geofence can be determined based on the number of intersections between the extension line and the boundary of the first geofence. Specifically, if the number of intersections is an odd number, the vehicle is within the first geofence; if the number of intersections is an even number, the vehicle is outside the first geofence.

[0054] In one embodiment of the present application, after receiving accident information, the electronic device in the connected vehicle server verifies the integrity of the accident information using a preset information verification algorithm (e.g., a JSON Schema validation algorithm), and cross-verifies the locations of the first and second vehicles to determine the legitimacy of the accident information. For example, historical traffic data may be used to determine whether the area where the first and second vehicles are located is a high-accident area. If the area where the first and second vehicles are located is determined to be a high-accident area, the accuracy of the accident information may be determined to be high. If the area where the first and second vehicles are located is determined not to be a high-accident area, the accuracy of the accident information may be determined to be low.

[0055] In one embodiment of the present application, after determining the second vehicle within the first geofence, the accident information can be sent to the second vehicle according to a pre-set communication protocol. For example, the accident information can be pushed to the second vehicle in a one-way manner over a cellular network to reduce the delay in transmitting the accident information.

[0056] It can be seen from the above technical solutions that the embodiment of the present application forwards accident information in real time through multi-terminal communication. In the event of an accident with the first vehicle, the accident information is promptly transmitted to the client corresponding to the first vehicle through the electronic device of the Internet of Vehicles server, and the early warning process is immediately triggered. The first geographic fence is determined in real time based on the geographical location and environmental information of the area where the first vehicle is located to ensure that more potentially affected second vehicles can be covered when pushing accident information. The load of processing invalid data of non-accident information is reduced by the authorization information transmitted between the vehicle and the electronic device, thereby improving the utilization rate of the Internet of Vehicles computing resources. The scope of the accident information push is determined based on the first geographic fence to ensure that the Internet of Vehicles in the electronic device broadcasts the accident information to surrounding vehicles, reducing the probability of secondary accidents, and improving the efficiency of accident warnings.

[0057] like Figure 3 1 is a flowchart of a method for determining a first geofence according to an embodiment of the present application. The order of the steps in the flowchart may be changed, and some steps may be omitted, depending on different needs. The method for determining a first geofence according to an embodiment of the present application includes the following steps.

[0058] S30, determine environment information corresponding to the first vehicle according to the first position information; the environment information is used to indicate a total number of vehicles in a surrounding of the first vehicle determined based on a video stream of the first vehicle.

[0059] In an embodiment of the present application, the first geographic fence of the first vehicle can be adaptively generated by dynamically monitoring the environment information of the surrounding of the first vehicle. The environment information can be used to indicate a total number of vehicles in a region where the first vehicle is located. Specifically, when determining the first geographic fence, the parameters (e.g., radius, side length, shape) of the first geographic fence can be adaptively adjusted according to the vehicle density in the region where the first vehicle is located, so as to ensure that the boundary of the first geographic fence matches the virtual boundary of the traffic condition.

[0060] Specifically, the environment information corresponding to the first vehicle can be determined from the pre-stored map information according to the position information. The pre-stored map information includes lane topology, speed limit information, and traffic signal position. The map information further includes annotation information of geographic positions, such as annotation information of parking lots, gas stations, schools, etc. The map information further includes historical traffic data, such as time-periodic traffic volume statistics or seasonal traffic volume statistics.

[0061] In an embodiment of the present application, the first position information of the first vehicle can be subjected to coordinate conversion. Specifically, the latitude and longitude coordinates of the vehicle can be converted to projection coordinates in the map, so as to ensure that the first position information is aligned with the map data. The map in the pre-stored map information can be divided into a plurality of grids, and the total number of vehicles in the region where the first vehicle is located can be determined according to the historical average traffic volume of each grid in the surrounding of the first vehicle.

[0062] In an embodiment of the present application, in order to improve the accuracy of determining the first geographic fence, the traffic volume data can be corrected by a state transition algorithm (e.g., Kalman filtering algorithm, hidden Markov chain algorithm) according to real-time Internet of Vehicles data, and the total number of vehicles in the region where the first vehicle is located can be determined according to the corrected traffic volume data.

[0063] S31, determine a first geographic fence corresponding to the first vehicle according to the environment information.

[0064] In an embodiment of the present application, the environment information is used to indicate the total number of vehicles in the region where the first vehicle is located, which is determined based on the video stream of the first vehicle. In order to improve the accuracy of the accident warning, the first geofence can be determined according to the environment information of the first vehicle, so as to ensure that the range of the first geofence meets the constraints of the environment information. For example, when the region where the first vehicle is located is an open area with a small total number of vehicles, the radius of the first geofence can be determined according to the total number of vehicles in the region where the first vehicle is located, and the first position information corresponding to the first vehicle is determined as the center of the first geofence, so as to obtain a circular first geofence. For another example, when the region where the first vehicle is located is a city road area with a large total number of vehicles, the first geofence area can be dynamically generated according to the shape of the city road, so as to ensure that the range of the first geofence can cover the road section of the city road.

[0065] For example, when the total number of vehicles in the region where the first vehicle is located is less than a preset threshold range, the radius of the first geofence can be determined as 500 meters; when the total number of vehicles in the region where the first vehicle is located is within the preset threshold range, the radius of the first geofence can be determined as 300 meters; and when the total number of vehicles in the region where the first vehicle is located exceeds the preset threshold range, the radius of the first geofence can be determined as 100 meters.

[0066] For example, when the first position information corresponding to the first vehicle is (116.3912°E, 39.9067°N), the map grid data at the longitude of 116.3912 degrees and the latitude of 39.9067 degrees can be determined according to the pre-stored map grid data. When the historical average traffic volume in the three map grids within 500 meters around the longitude and latitude coordinates is determined as 15 vehicles, the region can be determined as a medium-density area, and the radius of the first geofence can be determined as 300 meters.

[0067] As shown in FIG. 1, it is a flowchart of a method for determining a first geofence provided by an embodiment of the present application. The order of the steps in the flowchart can be changed, and some steps can be omitted according to different needs. The method for determining a first geofence provided by an embodiment of the present application includes the following steps. Figure 4

[0068] S40, determining the road condition information corresponding to the first vehicle according to the environment information; the road condition information is used to indicate the traffic load of the region where the first vehicle is located.

[0069] ​In an embodiment of the present application, in order to improve the accuracy of determining the first geofence, thereby avoiding false triggering of the push of the accident information, the first geofence of the first vehicle can also be generated based on the environmental information of the first vehicle and the third-party database. The environmental information can be used to indicate the total number of vehicles in the area where the first vehicle is located. Specifically, when determining the first geofence, the first geofence parameters (such as radius, side length, shape) can be adjusted according to the vehicle density of the area where the first vehicle is located, so as to ensure that the boundary of the first geofence matches the virtual boundary of the traffic condition.

[0070] Specifically, the third-party database can be used to store road condition information. For example, the third-party database can be a real-time traffic data source, such as a congestion index data interface published by the traffic committee; the third-party database can also be a commercial platform, such as a traffic trend interface of a commercial map or a road condition query service of a commercial map; the third-party database can also be a historical data source for storing historical congestion records and accident-prone road segment data.

[0071] Specifically, the road condition data within a preset radius (for example, 1 kilometer) centered on the first geographic position corresponding to the first vehicle can be determined. And the real-time congestion degree, the average speed of vehicles on the road, the road closure information, etc. are determined according to the road condition data. Based on the coupling model of the environmental information and the road condition information, the first geofence matching the traffic load is generated. The traffic load is used to indicate the congestion degree of the vehicles in the area where the first vehicle is located. For example, the more the total number of vehicles in the area where the first vehicle is located, the higher the congestion degree, and the higher the traffic load. In the area where the first vehicle is located, the lower the average speed of vehicles, the higher the congestion degree, and the higher the traffic load.

[0072] S41, according to the environmental information and the road condition information, determining the first geofence corresponding to the first vehicle.

[0073] In an embodiment of the present application, in order to improve the accuracy of the accident warning, the first geofence can be determined according to the environmental information and the road condition information of the first vehicle, so as to ensure that the range of the first geofence conforms to the constraints of the environmental information and the road condition information. For example, when the area where the first vehicle is located is an open area with a small total number of vehicles, the radius of the first geofence can be determined according to the total number of vehicles in the area where the first vehicle is located, and the first position information corresponding to the first vehicle is determined as the center of the first geofence, thereby obtaining a circular first geofence. When the traffic load of the area where the first vehicle is located is higher, it indicates that the vehicle density inside the area where the first vehicle is located is higher, and the radius of the first geofence is smaller.

[0074] For example, if the first vehicle is located in an urban area with a high vehicle count, a first geo-fence area can be dynamically generated based on the shape of the urban roads, ensuring that the first geo-fence covers all sections of the urban roads. If congestion in the area where the first vehicle is located is low, the number or area of ​​urban roads covered by the first geo-fence can be increased to ensure that more vehicles receive accident warning information in a timely manner. If congestion in the area where the first vehicle is located is high, the number or area of ​​urban roads covered by the first geo-fence can be reduced, and sections with high congestion levels can be prioritized for the first geo-fence.

[0075] For example, when generating a circular first geofence, the radius of the first geofence can be determined based on a traffic load threshold in the area where the first vehicle is located. For example, if the traffic load in the area where the first vehicle is located is less than a preset load threshold, the radius of the first geofence can be determined to be 500 meters; if the traffic load in the area where the first vehicle is located is within the preset load threshold, the radius of the first geofence can be determined to be 300 meters; and if the traffic load in the area where the first vehicle is located exceeds the preset load threshold, the radius of the first geofence can be determined to be 100 meters. For example, if the first location information corresponding to the first vehicle is (116.3912°E, 39.9067°N), traffic load data at 116.3912°E and 39.9067°N can be determined from a third-party database. If the traffic load in the area at these longitude and latitude coordinates is determined to be within the preset load threshold, the radius of the first geofence can be determined to be 100 meters.

[0076] In one embodiment of the present application, to improve the accuracy of determining the range of the first geo-fence, the range of the first geo-fence may be updated in real time. For example, the radius or area of ​​the first geo-fence may be dynamically adjusted based on the average vehicle speed in the area where the first vehicle is located. For example, if the average vehicle speed in the area where the first vehicle is located is less than 10 kilometers per hour, the radius of the first geo-fence may be determined to be 50 meters.

[0077] like Figure 5 1 is a flowchart of a method for determining a first geofence according to an embodiment of the present application. The order of the steps in the flowchart may be changed, and some steps may be omitted, depending on different needs. The method for determining a first geofence according to an embodiment of the present application includes the following steps.

[0078] S50, determining the risk level of an accident involving the first vehicle based on pre-stored historical location information and the first location information; wherein the historical location information is used to indicate a location where a vehicle accident has occurred.

[0079] In one embodiment of the present application, the first location information may be the latitude and longitude information of the first vehicle, and the present application does not limit the specific form of the first location information. The first geo-fence may be a location-based service (LBS) technology provided by a vehicle network server running an electronic device to the first vehicle. For example, the first location information may be determined based on a combination of communication signals such as satellite positioning signals, cellular network signals (for example, 4G networks or 5G networks), wireless network signals, and Bluetooth signals, thereby improving positioning accuracy when the first vehicle is in a complex geographical environment. For example, when the first vehicle is in a complex environment such as an urban road, tunnel, or overpass, the positioning deviation of the first vehicle can be corrected by comparing a variety of positioning signals with third-party map data, thereby improving the accuracy of judging the boundary of the first geo-fence.

[0080] In one embodiment of the present application, historical location information is used to indicate the location where a vehicle accident occurred. The risk level of an accident involving the first vehicle can be determined based on the relative position between the historical location information and the first location information. Specifically, when the relative position between the historical location information and the first location information is closer, it indicates that the probability of an accident occurring when the first vehicle is at the first location is higher, and it can be determined that the risk level of an accident involving the first vehicle is higher; when there is more historical location information within the preset initial geographic fence where the first location information is located, it indicates that there are more accident locations within the preset initial geographic fence, and the probability of an accident occurring with the first vehicle is higher, and it can be determined that the risk level of an accident involving the first vehicle is higher. The present application does not limit the specific method for determining the risk level of an accident involving the first vehicle.

[0081] S51: Determine a first geographic fence of the first vehicle according to the risk level.

[0082] In one embodiment of the present application, if the risk level of an accident involving the first vehicle is higher, it indicates that the probability of an accident involving the first vehicle at the first location information is higher, and the probability of an accident occurring around the first vehicle is also higher. Therefore, the range of the preset initial geo-fence can be increased to obtain a first geo-fence for the first vehicle, wherein the historical location information is within the range of the first geo-fence.

[0083] like Figure 6 1 is a flowchart of a method for determining a first geofence according to an embodiment of the present application. The order of the steps in the flowchart may be changed, and some steps may be omitted, depending on different needs. The method for determining a first geofence according to an embodiment of the present application includes the following steps.

[0084] S60: Determine a plurality of candidate geo-fences for the first vehicle based on the environmental information and the road condition information.

[0085] In an embodiment of the present application, in order to improve the accuracy of determining the first geofence, thereby avoiding the false triggering of the push of the accident information, a plurality of candidate geofences of the first vehicle can be determined based on the environment information and the road condition information. The environment information can be used to indicate the total number of vehicles in the area where the first vehicle is located. Specifically, the parameters (e.g., radius, side length, shape) of the candidate geofence can be adjusted according to the vehicle density of the area where the first vehicle is located, so as to ensure that the boundary of the candidate geofence matches the traffic conditions. The third-party database can be used to store the road condition information. For example, the third-party database can be a real-time traffic data source, such as a congestion index data interface published by the traffic committee; the third-party database can also be a commercial platform, such as a traffic trend interface of a commercial map or a road condition query service of a commercial map; the third-party database can also be a historical data source for storing historical congestion records and accident-prone road segment data.

[0086] Specifically, the road condition data within a preset radius (e.g., 1 km) centered on the first geographic position of the first vehicle can be determined. The real-time congestion degree, the average speed of vehicles on the road, the road closure information, etc. can be determined according to the road condition data. Based on the environment information and the road condition information coupling model, the candidate geofence matching the traffic load can be generated. The traffic load is used to indicate the congestion degree of vehicles in the area where the first vehicle is located. For example, the more the total number of vehicles in the area where the first vehicle is located, the higher the congestion degree, and the higher the traffic load; the lower the average speed of vehicles in the area where the first vehicle is located, the higher the congestion degree, and the higher the traffic load.

[0087] S61, determining the first geofence from the plurality of candidate geofences according to the risk level.

[0088] In an embodiment of the present application, at least one candidate geofence can be determined as the first geofence from the plurality of candidate geofences based on the risk level of the first vehicle having an accident. Specifically, in the case that the risk level of the first vehicle having an accident is low, one of the plurality of candidate geofences closest to the first position information of the first vehicle can be determined as the first geofence; in the case that the risk level of the first vehicle having an accident is high, the range of the plurality of candidate geofences can be fused to obtain the first geofence. The number of candidate geofences used to determine the first geofence is proportional to the risk level of the first vehicle having an accident.

[0089] As Figure 7Fig. 1 is a flowchart of a method for determining an updated first geofence according to an embodiment of the present application. The order of the steps in the flowchart can be changed according to different needs, and some steps can be omitted. The method for determining an updated first geofence according to an embodiment of the present application includes the following steps.

[0090] S70, before determining the second vehicle in the first geofence, determining a corresponding accident type according to the accident information.

[0091] In an embodiment of the present application, in order to ensure that the range of the first geofence matches the accident information of the first vehicle and avoid the range of the first geofence being too large or too small to cause a high error in the accident information warning, the corresponding accident type can be determined according to the accident information before determining the second vehicle in the first geofence, and the range of the first geofence can be adjusted according to the accident type.

[0092] In an embodiment of the present application, the accident information includes structured data and unstructured data. For example, the structured data can be used to indicate the event type in the accident information, and the unstructured data can be used to indicate the accident description output by the accident identification module of the vehicle (for example, "vehicle rollover, oil leakage, and illegal parking penalty").

[0093] In an embodiment of the present application, the accident type is used to indicate the semantics of the accident information. The semantic analysis can be performed on the text description in the accident information based on a natural language processing algorithm (for example, a BERT model or a transfer learning model) to determine the accident type and the semantics represented by the accident type. Subsequently, the range of the first geofence can be adjusted according to the accident type and the corresponding semantics.

[0094] For example, in the case of a collision accident, the corresponding semantics of the accident type can be physical contact between vehicles or between a vehicle and an obstacle; in the case of a vehicle breakdown, the corresponding semantics of the accident type can be no physical contact; in the case of a fire accident, the corresponding semantics of the accident type can be a vehicle on fire with smoke or explosion risk; and in the case of a dangerous goods leakage, the corresponding semantics of the accident type can be a vehicle accident involving dangerous goods.

[0095] S71, updating the first geofence according to the accident type to obtain an updated first geofence.

[0096] In an embodiment of the present application, when the range of the first geofence is dynamically updated, the size or radius of the first geofence can be adjusted according to the accident type, the shape of the first geofence is adjusted, and the boundary change of the first geofence is azimuthally constrained according to the shape change of the first geofence.

[0097] For example, if the accident type is a collision, the semantics corresponding to the accident type may be physical contact between vehicles or between vehicles and obstacles. In this case, the radius of the first geofence may be increased and the boundaries of the first geofence may be expanded in all directions to avoid damage to other vehicles caused by the collision of the first vehicle. If the accident type is a vehicle breakdown and stoppage, the semantics corresponding to the accident may be no physical contact. In this case, the size or range of the first geofence may be maintained unchanged. If the accident type is a fire, the semantics corresponding to the accident may be vehicle fire and the risk of smoke / explosion. In this case, the radius of the first geofence may be significantly increased (for example, the radius of the updated geofence may be determined to be twice the radius before the update to avoid damage to vehicles within a large area caused by the accident). If the accident type is a hazardous chemical leak, the semantics of the accident may be an accident involving vehicles carrying hazardous materials. In this case, the radius of the updated first geofence may be determined to be five times the radius of the geofence before the update to avoid damage to vehicles and personnel within a large area caused by the accident.

[0098] In one embodiment of the present application, the first vehicle 200 determines accident information based on the surveillance video information around the vehicle. The accident information is sent to the electronic device 100 in real time, so that the Internet of Vehicles server running in the electronic device 100 promptly notifies other vehicles within the first geographic fence. Figure 8 , is a flowchart of an accident warning method provided in another embodiment of the present application. Depending on different needs, the order of the steps in the flowchart can be changed, and some steps can be omitted. An accident warning method provided in an embodiment of the present application includes the following steps.

[0099] S80: Acquire video information of the first vehicle in real time.

[0100] In one embodiment of the present application, video information of a first vehicle may be collected using an on-board visual sensor, where the video information of the first vehicle is used to indicate static and dynamic visual information surrounding the first vehicle. The on-board visual sensor may be a camera mounted on the outside or inside of the vehicle, and the present application does not limit the specific type of the on-board visual sensor.

[0101] S81, performing target detection on multiple video frames in the video information to obtain a target detection result for each video frame.

[0102] In one embodiment of the present application, a model for performing visual analysis may be deployed based on the visual analysis module of the first vehicle. For example, the model for performing visual analysis may be a deep learning model based on the YOLOv8 architecture, or a deep learning model based on a convolutional neural network. This application does not limit the specific type of visual analysis model.

[0103] In an embodiment of the present application, the target detection result in the video frame can be used to indicate an entity in the periphery of the first vehicle. For example, the target detection result corresponding to each video frame can be other vehicles in the periphery of the first vehicle; the target detection result can also be pedestrians in the periphery of the first vehicle; the target detection result can also be traffic signs in the periphery of the first vehicle; and the target detection result can also be road facilities in the periphery of the first vehicle.

[0104] S82, determining semantic information of each video frame according to the target detection result.

[0105] In an embodiment of the present application, the spatial features in the periphery of the first vehicle can be determined according to the target detection result, so as to segment the entity information in the periphery of the first vehicle. And the corresponding semantic information can be determined according to the entity information in the periphery of the first vehicle. The semantic information of each video frame can be used to indicate the spatial relationship (such as distance, relative speed, etc.) of different entities in the periphery of the first vehicle; the semantic information can be used to indicate the static features and motion features of different entities in the periphery of the first vehicle, for example, the semantic information can be used to indicate that there are people staying in the periphery of the first vehicle, and the semantic information can also be used to indicate that the first vehicle is in contact with other vehicles.

[0106] S83, determining the accident information of the first vehicle according to the semantic information of each video frame.

[0107] In an embodiment of the present application, in order to improve the accuracy of identifying the accident information of the first vehicle, the accident information of the first vehicle can be determined according to the semantic information of each video frame in the video information. For example, the semantic information of a plurality of continuous video frames can be input into an accident analysis model to obtain a probability distribution of the accident type in the video information. For example, the probability distribution of the accident type can be used to indicate the probability of a collision accident in the video information, and can also be used to indicate the probability of a rollover accident in the video information, and can also be used to indicate the probability of a rear-end collision accident in the video information, and can also be used to indicate the probability of a scratch accident in the video information. The accident analysis model can be any model with image processing function, for example, the accident analysis model can be a long short-term memory model, and the accident analysis model can also be a recurrent neural network model, and the specific type of the accident analysis model is not limited in the present application.

[0108] In an embodiment of the present application, the specific method of determining the accident information of the first vehicle according to the semantic information of each video frame can refer to Figure 9 the corresponding detailed description.

[0109] As Figure 9Fig. 1 is a flowchart of a method for determining accident information according to an embodiment of the present application. The order of steps in the flowchart can be changed according to different requirements, and some steps can be omitted. The method for determining accident information according to an embodiment of the present application includes the following steps.

[0110] S90, determining a semantic correlation degree of the plurality of video frames in the time dimension according to the semantic information of each video frame.

[0111] In an embodiment of the present application, the semantic information of any one video frame can represent target detection results (e.g., vehicles, pedestrians, traffic signs, etc.) in the video frame; can also represent key point positioning information (e.g., vehicle tire contact points, pedestrian joint points) in the video frame; and can also represent scene classification information (e.g., road intersections, highways, tunnels, etc.) in the video frame.

[0112] In an embodiment of the present application, the kinematic information of the plurality of video frames in the time dimension can be determined based on the semantic information of a plurality of adjacent video frames, to represent the semantic correlation degree of the plurality of video frames in the time dimension. Specifically, target tracking in the time dimension can be performed on the plurality of video frames based on a pre-trained deep learning model, to determine the kinematic information of the target in each video frame in the time dimension, and further determine the semantic correlation degree of the plurality of video frames in the time dimension. The semantic correlation degree of the plurality of video frames in the time dimension can represent the motion state of the target in the time dimension. For example, the semantic correlation degree of the plurality of video frames in the time dimension can represent the activity trajectory of a person in the video information around the first vehicle; and the semantic correlation degree of the plurality of video frames in the time dimension can also represent the motion trajectory of a vehicle in the video information around the first vehicle.

[0113] S91, determining the accident information of the first vehicle according to the semantic information of each video frame and the semantic correlation degree of the plurality of video frames in the time dimension.

[0114] In an embodiment of the present application, the category to which the entity in the periphery of the first vehicle belongs can be determined according to the semantic information of each video frame, and the accident information of the first vehicle can be determined according to the semantic correlation degree of the plurality of video frames in the time dimension. For example, when it is determined according to the semantic information in each video frame that there is another vehicle in the periphery of the first vehicle, the motion trajectory of the other vehicle can be determined according to the semantic correlation degree of the plurality of video frames in the time dimension, and in the case where the motion trajectory of the other vehicle intersects with the position of the first vehicle, it can be determined that the first vehicle has a collision accident or a scratch accident. When it is determined according to the semantic information in each video frame that there is a person in the periphery of the first vehicle, the motion trajectory of the person in the periphery of the first vehicle can be determined according to the semantic correlation degree of the plurality of video frames in the time dimension, and in the case where the motion trajectory of the person in the periphery of the first vehicle intersects with the position of the first vehicle, it can be determined that the first vehicle has a violation accident.

[0115] See Figure 10 , Figure 10 is a functional module diagram of an accident early warning device provided in an embodiment of the present application. The accident early warning device 81 comprises a positioning module 811 and an early warning module 812. The module / unit referred to in the present application refers to a series of computer readable instruction segments capable of being executed by the processor 13 and capable of completing a fixed function, which is stored in the memory 12. In the present embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0116] The positioning module 811 is configured to acquire first position information of the first vehicle and a corresponding first geofence.

[0117] The early warning module 812 is configured to, in the case where the accident information of the first vehicle is received, send the accident information to the client and a second vehicle; wherein the second vehicle is another vehicle located in the first geofence and associated with the first vehicle.

[0118] In some embodiments, the positioning module 811 is further configured to determine the first geofence of the first vehicle, comprising: determining the environment information corresponding to the first vehicle according to the position information; the environment information is used to indicate the total number of vehicles in the periphery of the first vehicle determined based on the video stream of the first vehicle; determining the first geofence corresponding to the first vehicle according to the environment information.

[0119] In some embodiments, the positioning module 811 is further configured to: determine the road condition information corresponding to the first vehicle according to the environment information; the road condition information is used to indicate the traffic load of the area where the first vehicle is located; determine the first geofence corresponding to the first vehicle according to the environment information and the road condition information.

[0120] In some embodiments, the positioning module 811 is also used to include: determining the risk level of an accident involving the first vehicle based on pre-stored historical location information and the first location information; wherein the historical location information is used to indicate the location where the vehicle accident occurred; and determining the first geographic fence of the first vehicle based on the risk level.

[0121] In some embodiments, the positioning module 811 is further configured to include: determining a plurality of candidate geofences for the first vehicle based on the environmental information and the road condition information; and determining a first geofence from the plurality of candidate geofences according to the risk level.

[0122] In some embodiments, the positioning module 811 is also used to determine the corresponding accident type based on the accident information before determining the second vehicle in the first geo-fence; the accident type is used to indicate the semantics of the accident information; and the first geo-fence is updated according to the accident type to obtain an updated first geo-fence.

[0123] See Figure 11 , is a schematic diagram of the structure of an accident warning system provided in an embodiment of the present application. Accident warning system 500 includes an electronic device 100, a first vehicle 210, and a client 300. Electronic device 100 is in communication with first vehicle 210 and client 300, respectively, and is connected to a memory. Electronic device 100 may be an electronic device for operating an Internet of Vehicles server.

[0124] Combine Figures 2 to 7 The electronic device 100 in the accident warning system 500 can execute multiple instructions in the memory to achieve: obtaining the first location information of the first vehicle and the corresponding first geo-fence; upon receiving the accident information of the first vehicle, sending the accident information to the client and the second vehicle; wherein, the second vehicle is another vehicle located within the first geo-fence and associated with the first vehicle.

[0125] Specifically, the specific implementation method of the electronic device 100 for the above instructions can refer to Figures 2 to 7 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0126] See Figure 12 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Electronic device 100 includes memory 12 and processor 13. Memory 12 is used to store computer-readable instructions, and processor 13 is used to execute the computer-readable instructions stored in the memory to implement an accident warning method described in any of the above embodiments. Electronic device 100 may be an electronic device used to run a connected vehicle server.

[0127] In an embodiment of the present application, the electronic device 100 further comprises a bus, a computer program stored in the memory 12 and executable on the processor 13, for example, an accident warning program.

[0128] Figure 12 Only the electronic device 100 with the memory 12 and the processor 13 is shown, and those skilled in the art can understand that, Figure 12 The structure shown does not constitute a limitation on the electronic device 100, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0129] In combination with Figure 2 The memory 12 in the electronic device 100 stores a plurality of computer readable instructions to implement the accident warning method, and the processor 13 can execute the plurality of instructions to achieve: obtaining first position information of the first vehicle and a corresponding first geographic fence; in the case of receiving accident information of the first vehicle, sending the accident information to the client and a second vehicle; wherein the second vehicle is other vehicles associated with the first vehicle located in the first geographic fence.

[0130] Specifically, the specific implementation method of the processor 13 on the above instructions can refer to Figure 2 The description of related steps in corresponding embodiments, which will not be repeated here.

[0131] Those skilled in the art can understand that the schematic diagram is only an example of the electronic device 100, and does not constitute a limitation on the electronic device 100. The electronic device 100 can be a bus type structure, or a star type structure. The electronic device 100 can further include more or less other hardware or software than shown, or different component arrangements, for example, the electronic device 100 can further include an input / output device, a network access device, etc.

[0132] It should be noted that the electronic device 100 is only an example, and other existing or future electronic products, such as those that can be adapted to the present application, should also be included within the scope of protection of the present application and are hereby incorporated by reference.

[0133] The memory 12 includes at least one type of readable storage medium, which can be non-volatile or volatile. The readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 12 can be an internal storage unit of the electronic device 100 in some embodiments, such as a mobile hard disk of the electronic device 100. The memory 12 can also be an external storage device of the electronic device 100 in other embodiments, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 100. The memory 12 can be used to store application software and various data installed on the electronic device 100, such as the code of an accident warning program, and can also be used to temporarily store data that has been output or will be output.

[0134] The processor 13 can be composed of an integrated circuit in some embodiments, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including one or more combinations of a central processing unit (CPU), a microprocessor, a digital processing chip, a graphics processor, and various control chips, etc. The processor 13 is the control core of the electronic device 100, which connects various components of the electronic device 100 through various interfaces and lines, executes programs or modules stored in the memory 12 (such as an accident warning program, etc.), and calls data stored in the memory 12 to perform various functions and process data of the electronic device 100.

[0135] The processor 13 executes the operating system and various application programs installed on the electronic device 100. The processor 13 executes the application programs to implement the steps in each of the above-mentioned accident warning method embodiments, such as Figures 2 to 7 The steps shown.

[0136] For example, the computer program can be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present application. The one or more modules / units can be a series of computer readable instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the electronic device 100. For example, the computer program can be divided into a positioning module 811 and a warning module 812.

[0137] The integrated units in the form of software function modules can be stored in a computer readable storage medium. The software function modules are stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a computer device, or a network device, etc.) or a processor to execute part of the accident early warning method described in various embodiments of the present application.

[0138] The modules / units integrated in the electronic device 100, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiments can also be implemented by a computer program to instruct related hardware devices to complete, and the computer program can be stored in a computer readable storage medium. When the processor executes the computer program, the steps of the above-mentioned various method embodiments can be implemented.

[0139] The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, and other memories, etc.

[0140] Further, the computer readable storage medium can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, etc.; and the data storage area can store data created according to the use of the blockchain node, etc.

[0141] The bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, only one arrow is used in Figure 12 , but it does not mean that there is only one bus or only one type of bus. The bus is arranged to realize the connection and communication between the memory 12, the at least one processor 13, etc.

[0142] The embodiment of the present application further provides a computer readable storage medium (not shown in figure), which stores computer readable instructions, and the computer readable instructions are executed by a processor in an electronic device to implement the accident early warning method in any of the above embodiments.

[0143] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the above described device embodiment is merely illustrative, and for example, the division of the modules is merely a logical function division, and there can be another division manner in actual implementation.

[0144] The modules described as separated components can or can not be physically separated, and the components displayed as modules can or can not be physical units, i.e., can be located in one place, or can be distributed on a plurality of network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0145] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software functional module.

[0146] In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The plurality of units or devices stated in the specification can also be implemented by one unit or device through software or hardware. The words "first", "second" and the like are used to indicate names, and do not indicate any specific order.

[0147] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. An accident warning method, applied to an electronic device, wherein the electronic device is communicatively connected to a first vehicle and a client, and characterized in that: The method comprises: Obtaining first location information of the first vehicle and a corresponding first geo-fence; Upon receiving the accident information of the first vehicle, the accident information is sent to the client and a second vehicle; wherein the second vehicle is another vehicle located within the first geo-fence and associated with the first vehicle.

2. The accident warning method according to claim 1, characterized in that: The method further includes determining a first geo-fence for the first vehicle, wherein determining the first geo-fence for the first vehicle includes: Determining environmental information corresponding to the first vehicle based on the first location information; the environmental information is used to indicate the total number of vehicles around the first vehicle determined based on the video stream of the first vehicle; A first geographic fence corresponding to the first vehicle is determined based on the environmental information.

3. The accident warning method according to claim 2, characterized in that: Determining a first geo-fence of the first vehicle includes: determining, based on the environmental information, road condition information corresponding to the first vehicle; the road condition information being used to indicate a traffic load in an area where the first vehicle is located; A first geographic fence corresponding to the first vehicle is determined based on the environmental information and the road condition information.

4. The accident warning method according to claim 3, characterized in that: Determining a first geo-fence of the first vehicle includes: Determining a risk level of an accident involving the first vehicle based on pre-stored historical location information and the first location information, wherein the historical location information indicates a location where a vehicle accident occurred; A first geo-fence for the first vehicle is determined based on the risk level.

5. The accident warning method according to claim 4, characterized in that: Determining a first geo-fence of the first vehicle includes: determining a plurality of candidate geo-fences for the first vehicle based on the environmental information and the road condition information; A first geo-fence is determined from the plurality of candidate geo-fences based on the risk level.

6. The accident warning method according to claim 1, characterized in that: The method further comprises: Before determining the second vehicle in the first geo-fence, determining a corresponding accident type based on the accident information; The first geo-fence is updated according to the accident type to obtain an updated first geo-fence.

7. An accident warning device, characterized in that: Applied to an electronic device, the electronic device is communicatively connected to a first vehicle and a client, and the device includes: a positioning module, configured to obtain first location information of the first vehicle and a corresponding first geo-fence; An early warning module is used to send the accident information to the client and a second vehicle when the accident information of the first vehicle is received; wherein the second vehicle is another vehicle located within the first geographic fence and associated with the first vehicle.

8. An accident warning system, characterized in that: The system includes: an electronic device, a first vehicle, and a client, wherein the electronic device is communicatively connected with the first vehicle and the client respectively; The electronic device is used to: obtain the first location information of the first vehicle and the corresponding first geo-fence; upon receiving accident information of the first vehicle, send the accident information to the client and the second vehicle; wherein, the second vehicle is another vehicle located within the first geo-fence and associated with the first vehicle.

9. An electronic device, characterized in that: The electronic device includes a processor and a memory, and the processor is used to implement the accident warning method according to any one of claims 1 to 6 when executing the computer program stored in the memory.

10. A vehicle networking server, characterized in that: The Internet of Vehicles server includes the electronic device as claimed in claim 9.

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