Vehicle signal loss diagnosis method, device and equipment
By obtaining the latitude and longitude information before vehicle signal loss and determining the gray area of the map, the error alarm problem caused by unknown reasons for vehicle signal loss is solved, and accurate signal loss diagnosis and fault alarm are achieved.
Patent Information
- Application Number
- CN202510434998.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-08
- Publication Date
- 2025-07-22
Smart Images
Figure CN120358128A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the technical field of vehicle diagnosis, and particularly relates to a vehicle signal loss diagnosis method, device, and equipment. Background Art
[0002] With the rapid development of vehicle networking technology, the on-vehicle terminal of a vehicle will collect various vehicle signals, such as signals related to the vehicle's geographical location, speed, battery state, and communication state, and upload the vehicle signals to the server through the network. During the process of uploading vehicle signals, there may be a situation where vehicle signals are lost, and the reason for the loss of vehicle signals may be that the vehicle is in a coverage hole, or it may be a vehicle's own fault (such as a damaged communication module).
[0003] In the related art, usually when a vehicle signal is lost, the server determines whether to output a fault alarm message to the vehicle management platform according to the length of time the vehicle signal is lost. If the vehicle signal is lost for a long time, regardless of the reason for the loss of the vehicle signal, the vehicle management platform will receive the fault alarm message, which may cause the vehicle management platform to receive incorrect fault alarm messages and then take unnecessary fault response measures. Summary of the Invention
[0004] Embodiments of the present application provide a vehicle signal loss diagnosis method, device, and equipment, which can at least to a certain extent diagnose the reason for the loss of vehicle signals, so as to avoid outputting incorrect fault alarm messages to the vehicle management platform when the vehicle signals are lost due to network reasons.
[0005] Other features and advantages of the present application will become apparent through the following detailed description, or be learned in part through the practice of the present application.
[0006] According to the first aspect of the embodiments of the present application, a vehicle signal loss diagnosis method is provided, including:
[0007] In the case where the vehicle signal of the target vehicle is lost, obtain the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal is lost;
[0008] In the case where the first longitude and latitude information is within the gray area, determine that the reason for the loss of the vehicle signal is that the vehicle is in a coverage hole, where the gray area is used to represent an area on the map where the number of times the vehicle signal is lost due to the coverage hole is greater than a preset number;
[0009] In the case where the first longitude and latitude information is not within the gray area, determine that the reason for the loss of the vehicle signal is a vehicle fault.
[0010] In some embodiments, the vehicle signal loss diagnosis method further includes:
[0011] Determine the second longitude and latitude information of a vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole according to the historical data corresponding to multiple vehicles;
[0012] Determine a gray area on the map according to the second longitude and latitude information.
[0013] In some embodiments, the historical data includes historical positioning data and historical log data. Determining the second longitude and latitude information of a vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole according to the historical data corresponding to multiple vehicles includes:
[0014] Determine the third longitude and latitude information in the historical positioning data corresponding to each vehicle;
[0015] For each vehicle, fill in the missing values of the historical positioning data according to the third longitude and latitude information to obtain lost positioning data;
[0016] According to the historical log data corresponding to each vehicle, screen out the target positioning data whose reason for loss is that the vehicle is in a coverage hole from the lost positioning data;
[0017] Determine the longitude and latitude information in the target positioning data as the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole.
[0018] In some embodiments, filling in the missing values of the historical positioning data according to the third longitude and latitude information includes:
[0019] Fill in the missing values of the historical positioning data according to the third longitude and latitude information and the linear interpolation method.
[0020] In some embodiments, screening out the target positioning data whose reason for loss is that the vehicle is in a coverage hole from the lost positioning data according to the historical log data corresponding to each vehicle includes:
[0021] Determine the historical log data corresponding to the lost positioning data;
[0022] Mark the reason for loss of the lost positioning data according to whether there is vehicle fault information in the historical log data corresponding to the lost positioning data, where the reasons for loss include the vehicle being in a coverage hole and vehicle fault;
[0023] Determine the lost positioning data whose reason for loss is marked as the vehicle being in a coverage hole as the target positioning data.
[0024] In some embodiments, determining a gray area on the map according to the second longitude and latitude information includes:
[0025] Cluster the second longitude and latitude information to obtain multiple clustering clusters;
[0026] Determine the minimum convex polygon of all clustering points in each clustering cluster;
[0027] Map the boundary of each minimum convex polygon to the map to obtain the boundary of the gray area in the map;
[0028] Render the boundary of the gray area in the map to obtain the gray area.
[0029] In some embodiments, after determining that the reason for the vehicle signal loss is a vehicle failure, the vehicle signal loss diagnosis method further includes:
[0030] Send a vehicle failure alarm message to the vehicle management platform.
[0031] According to the second aspect of the embodiments of the present application, there is provided a vehicle signal loss diagnosis device, including:
[0032] A vehicle position acquisition module, configured to acquire the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal loss when the vehicle signal of the target vehicle is lost;
[0033] A first reason determination module, configured to determine that the reason for the vehicle signal loss is that the vehicle is in a coverage hole when the first longitude and latitude information is within the gray area, where the gray area is used to represent an area in the map where the number of vehicle signal losses caused by coverage holes is greater than a preset number;
[0034] A second reason determination module, configured to determine that the reason for the vehicle signal loss is a vehicle failure when the first longitude and latitude information is not within the gray area.
[0035] According to the third aspect of the embodiments of the present application, there is provided a vehicle signal loss diagnosis device, including a processor and a memory, the memory stores computer program instructions that can be executed by the processor, and when the processor executes the computer program instructions, the steps of the method according to any one of the first aspects are implemented.
[0036] According to the fourth aspect of the embodiments of the present application, there is provided a computer-readable storage medium, in which computer program instructions are stored, and when the computer program instructions are executed by a processor, the processor is prompted to implement the steps of the method according to any one of the first aspects.
[0037] In this application, in the case of the loss of the vehicle signal of the target vehicle, the first longitude and latitude information uploaded by the target vehicle for the last time before the loss of the vehicle signal is obtained; in the case where the first longitude and latitude information is within the gray area, it is determined that the reason for the loss of the vehicle signal is that the vehicle is in a coverage hole, where the gray area is used to represent the area in the map where the number of times the vehicle signal is lost due to the coverage hole is greater than the preset number; in the case where the first longitude and latitude information is not within the gray area, it is determined that the reason for the loss of the vehicle signal is a vehicle failure. The above solution can diagnose the reason for the loss of the vehicle signal through the gray area in the map, so as to avoid outputting incorrect fault alarm information to the vehicle management platform when the vehicle signal is lost due to the vehicle being in a coverage hole.
[0038] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] The accompanying drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application. Obviously, the accompanying drawings in the following description are only some embodiments of this application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts. In the drawings:
[0040] Figure 1 shows a schematic diagram of the application environment of the vehicle signal loss diagnosis method according to some embodiments of this application;
[0041] Figure 2 shows a schematic flowchart of the vehicle signal loss diagnosis method according to some embodiments of this application;
[0042] Figure 3 shows the determination Figure 2 of the gray area in the flowchart;
[0043] Figure 4 shows a block diagram of the vehicle signal loss diagnosis device according to some embodiments of this application;
[0044] Figure 5 shows a schematic structural diagram of the vehicle signal loss diagnosis device according to some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0045] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only some of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application.
[0046] In addition, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.
[0047] The block diagrams shown in the drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, 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.
[0048] The flowcharts shown in the drawings are only illustrative and not necessarily include all the content and operations / steps, nor are they necessarily executed in the order described. For example, some operations / steps can be decomposed, while some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.
[0049] It should also be noted that the terms "first", "second", etc. in the specification, claims, and above-mentioned drawings of the present application are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the objects so used can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described.
[0050] To enable those skilled in the art to better understand the present application, the technical background related to the present application will be briefly described first.
[0051] The in-vehicle terminal of a vehicle collects vehicle signals and uploads the vehicle signals to a server through a network. During the process of the vehicle uploading vehicle signals, there may be a situation where vehicle signals are lost. The reason for the loss of vehicle signals may be that the vehicle is in a coverage hole (an area with a coverage blind spot or weak signal in the network), or it may be a vehicle's own fault (such as a damaged communication module). In the related art, if the server detects the loss of vehicle signals, regardless of the reason for the loss of vehicle signals, it will send a fault alarm message to the vehicle management platform. After receiving the fault alarm message, the vehicle management platform will remind relevant personnel to take rescue measures. The present application provides a method for diagnosing the loss of vehicle signals. By pre-drawing the high-incidence areas where signal loss is caused by the vehicle being in a coverage hole as gray areas in a map, in the case of the loss of vehicle signals of a target vehicle, combining the latitude and longitude information uploaded for the last time before the vehicle signal loss and the gray areas, the reason for the loss of vehicle signals can be effectively identified, avoiding the output of incorrect fault alarm messages to the vehicle management platform.
[0052] The method for diagnosing the loss of vehicle signals provided by the embodiments of the present application can be applied to, for example Figure 1 the application environment shown. Figure 1 FIG. shows a schematic diagram of the application environment of the method for diagnosing the loss of vehicle signals according to some embodiments of the present application. Among them, vehicle 102 communicates with server 104 through a network. The data storage system can store the data that server 104 needs to process. The data storage system can be integrated on server 104, or can be placed in the cloud or other network servers. In the case of the loss of vehicle signals of a target vehicle, server 104 obtains the first latitude and longitude information uploaded for the last time before the vehicle signal loss of the target vehicle; in the case where the first latitude and longitude information is within the gray area, it is determined that the reason for the loss of vehicle signals is that the vehicle is in a coverage hole, where the gray area is used to represent the area in the map where the number of times of vehicle signal loss caused by the coverage hole is greater than a preset number; in the case where the first latitude and longitude information is not within the gray area, it is determined that the reason for the loss of vehicle signals is a vehicle fault. Server 104 can be implemented by an independent server or a server cluster composed of multiple servers.
[0053] Figure 2 FIG. shows a schematic flowchart of the method for diagnosing the loss of vehicle signals according to some embodiments of the present application. As Figure 2 shown, a method for diagnosing the loss of vehicle signals is provided. This method can be applied to Figure 1 the server in, and this method may include the following steps 201 to 203.
[0054] In step 201, in the case of the loss of vehicle signals of a target vehicle, obtain the first latitude and longitude information uploaded for the last time before the vehicle signal loss of the target vehicle.
[0055] Among them, vehicle signals may include positioning data, log data, vehicle speed, battery data, etc. The vehicle can collect vehicle signals in real time through an on-vehicle terminal (such as a T-BOX).
[0056] According to the GB32960 regulation, the vehicle needs to upload vehicle signals to the server of the enterprise background. Therefore, the server can obtain vehicle signals of multiple different vehicles. During the process of obtaining vehicle signals, if the server cannot continuously obtain the vehicle signals of a certain vehicle, it can regard this vehicle as the target vehicle and determine that the vehicle signals of the target vehicle are lost.
[0057] When the server determines that the vehicle signals of the target vehicle are lost, it can extract longitude and latitude information from the vehicle signals uploaded last time before the loss of the vehicle signals of the target vehicle and use it as the first longitude and latitude information.
[0058] In step 202, when the first longitude and latitude information is within the gray area, it is determined that the reason for the loss of vehicle signals is that the vehicle is in a coverage hole, where the gray area is used to represent the area on the map where the number of times of vehicle signal loss caused by the coverage hole is greater than the preset number.
[0059] Among them, the coverage hole refers to an area with a coverage blind spot or weak signal in the network.
[0060] It can be understood that if the first longitude and latitude information is within the gray area, it means that the vehicle is in an area where vehicle signals are often easily lost due to a network coverage blind spot or weak network coverage. In this case, it can be determined that the loss of vehicle signals is caused by the vehicle being in a coverage hole.
[0061] In some embodiments, the server can determine the second longitude and latitude information of the vehicle in the case of vehicle signal loss caused by the vehicle being in a coverage hole according to the historical data corresponding to multiple vehicles; and determine the gray area on the map according to the second longitude and latitude information.
[0062] Among them, the historical data is the vehicle signals within a period of time before obtaining the first longitude and latitude information. This period of time can be measured in days, months or years, and the embodiments of the present application do not limit this.
[0063] It should be noted that the historical data corresponding to the vehicle used to determine the gray area may or may not include the historical data of the target vehicle, and the embodiments of the present application do not limit this.
[0064] For each vehicle, the server can determine the second longitude and latitude information of the vehicle in the case of vehicle signal loss caused by the vehicle being in a coverage hole according to its corresponding historical data, and determine the gray area on the map according to the second longitude and latitude information of all vehicles.
[0065] In some embodiments, the historical data includes historical positioning data and historical log data. The server can determine the third longitude and latitude information in the historical positioning data corresponding to each vehicle. For each vehicle, the missing values in the historical positioning data are filled according to the third longitude and latitude information to obtain missing positioning data. According to the historical log data corresponding to each vehicle, the target positioning data with the reason for loss being that the vehicle is in a coverage hole is screened out from the missing positioning data. The longitude and latitude information in the target positioning data is determined as the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole.
[0066] In the implementation process, after obtaining the third longitude and latitude information, the server can also perform outlier detection on the third longitude and latitude information, and delete the data with longitude and latitude exceeding the reasonable range (such as longitude range -180° to 180°, latitude range -90° to 90°) from the third longitude and latitude information to improve the accuracy of the gray area.
[0067] When filling the missing values in the historical positioning data, the linear interpolation method can be used to fill the temporarily lost data to obtain the missing positioning data. Taking a vehicle with the third longitude and latitude information of 108°21′42″ east longitude and 29°01′53″ north latitude at time t1, and the third longitude and latitude information of 108°21′45″ east longitude and 29°01′56″ north latitude at time t1 + 3s, and the vehicle signal being lost from time t1 + 1s to t1 + 2s as an example, the missing positioning data can be 108°21′43″ east longitude and 29°01′54″ north latitude, and 108°21′44″ east longitude and 29°01′55″ north latitude.
[0068] As mentioned above, the reason for the vehicle signal loss may be that the vehicle is in a coverage hole or the vehicle has a fault. Therefore, the missing positioning data is also divided into two categories. The first category is the missing positioning data corresponding to the vehicle being in a coverage hole, and the second category is the missing positioning data corresponding to the vehicle fault. The server needs to screen out the missing positioning data corresponding to the vehicle being in a coverage hole from the missing positioning data as the target positioning data, and then determine the gray area according to the target positioning data.
[0069] In some embodiments, the server can determine the historical log data corresponding to the missing positioning data. According to whether there is vehicle fault information in the historical log data corresponding to the missing positioning data, the reason for loss of the missing positioning data is marked, where the reasons for loss include the vehicle being in a coverage hole and the vehicle having a fault. The missing positioning data with the reason for loss marked as the vehicle being in a coverage hole is determined as the target positioning data.
[0070] It can be understood that the server can obtain the log data of the vehicle during the period when the vehicle signal is lost, use it as the historical log data corresponding to the lost positioning data, and extract vehicle fault information (such as fault codes) from the historical log data. If the extraction is successful, it can be determined that there is vehicle fault information in the historical log data, and the reason for the loss of the corresponding lost positioning data is marked as vehicle fault; if the extraction fails, it can be determined that there is no vehicle fault information in the historical log data, and the reason for the loss of the corresponding lost positioning data is marked as the vehicle being in a coverage hole. By annotating the lost positioning data, the target positioning data can be quickly screened out from the lost positioning data, and then the second longitude and latitude information can be determined.
[0071] In some embodiments, after the second longitude and latitude information is determined, the second longitude and latitude information can be clustered to obtain multiple clustering clusters; determine the minimum convex polygon of all the clustering points in each clustering cluster; map the boundary of each minimum convex polygon to the map to obtain the boundary of the gray area in the map; render the boundary of the gray area in the map to obtain the gray area.
[0072] In the implementation process, the DBSCAN (density-based spatial clustering of application with noise) algorithm can be used to cluster the second longitude and latitude information. Specifically, the parameters of the DBSCAN algorithm can be set first, including the neighborhood radius (such as 0.5 km) and the minimum number of samples (such as 10 points), and then the DBSCAN algorithm is run to cluster the second longitude and latitude information, excluding the noise points (i.e., the isolated second longitude and latitude information) to obtain multiple clustering clusters. The DBSCAN algorithm can effectively process noise data and is used in the scenarios where a large amount of data needs to be processed in the embodiments of the present application, greatly improving the data processing efficiency.
[0073] In the implementation process, the convex hull algorithm can also be used to determine the minimum convex polygon of all the clustering points in each clustering cluster. It should be noted that since the longitude and latitude information in the vehicle signal uploaded by the vehicle uses the global positioning system (GPS) standard coordinate system - the WGS-84 (world geodetic system 1984) coordinate system, while the map display uses the Web Mercator projection coordinate system, the coordinates corresponding to the boundary of the minimum convex polygon need to be converted from the WGS-84 coordinate system to the Web Mercator coordinate system to map the boundary of the minimum convex polygon to the map to obtain the boundary of the gray area in the map.
[0074] When rendering the boundary of the gray area on the map, various methods such as vector boundary rendering, raster boundary rendering, or dynamic contour extraction can be used. The embodiments of the present application do not limit the specific rendering method.
[0075] In step 203, when the first longitude and latitude information is not within the gray area, it is determined that the reason for the vehicle signal loss is a vehicle fault.
[0076] It can be understood that if the first longitude and latitude information is not within the gray area, it means that the vehicle is not in an area where the vehicle signal is often easily lost due to network coverage blind spots or weak network coverage. In this case, it can be determined that the vehicle signal loss is caused by a vehicle fault.
[0077] In some embodiments, after determining that the reason for the vehicle signal loss is a vehicle fault, the server can also send a vehicle fault alarm message to the vehicle management platform.
[0078] Among them, the vehicle fault alarm message can include information such as the vehicle identification number (VIN) of the vehicle, the first longitude and latitude information of the vehicle, the time of vehicle signal loss, and the vehicle status.
[0079] After receiving the vehicle fault alarm message, the vehicle management platform can send the vehicle fault alarm message to the relevant personnel via text message or APP to remind the relevant personnel to take corresponding measures in a timely manner, improving the safety of the vehicle.
[0080] In the above vehicle signal loss diagnosis method, when the vehicle signal of the target vehicle is lost, the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal loss is obtained; when the first longitude and latitude information is within the gray area, it is determined that the reason for the vehicle signal loss is that the vehicle is in a coverage hole, where the gray area is used to represent an area on the map where the number of vehicle signal losses caused by the coverage hole is greater than a preset number; when the first longitude and latitude information is not within the gray area, it is determined that the reason for the vehicle signal loss is a vehicle fault. The above method can diagnose the reason for the vehicle signal loss through the gray area on the map to avoid outputting incorrect fault alarm messages to the vehicle management platform when the vehicle signal loss is caused by the vehicle being in a coverage hole.
[0081] Figure 3 Shows the determination Figure 2 of the gray area in the Figure 3 flow schematic diagram. As
[0082] In step 301, the third longitude and latitude information in the historical positioning data corresponding to each vehicle is determined;
[0083] In step 302, for each vehicle, the missing values in the historical positioning data are filled according to the third longitude and latitude information and the linear interpolation method to obtain the missing positioning data;
[0084] In step 303, the historical log data corresponding to the missing positioning data is determined;
[0085] In step 304, according to whether there is vehicle fault information in the historical log data corresponding to the missing positioning data, the reason for the loss of the missing positioning data is marked, where the reasons for the loss include the vehicle being in a coverage hole and vehicle fault;
[0086] In step 305, the missing positioning data whose reason for the loss is marked as the vehicle being in a coverage hole is determined as the target positioning data;
[0087] In step 306, the longitude and latitude information in the target positioning data is determined as the second longitude and latitude information of the vehicle in the case where the vehicle signal is lost due to the vehicle being in a coverage hole;
[0088] In step 307, the second longitude and latitude information is clustered to obtain multiple clusters;
[0089] In step 308, the minimum convex polygon of all the cluster points in each cluster is determined;
[0090] In step 309, the boundary of each minimum convex polygon is mapped to the map to obtain the boundary of the gray area in the map;
[0091] In step 310, the boundary of the gray area is rendered in the map to obtain the gray area.
[0092] By making full use of the historical data uploaded by the vehicle, the embodiments of the present application mine the areas where the vehicle signal is often easily lost due to network coverage blind spots or weak network coverage, and intuitively display the area in the map, improving the accuracy and reliability of vehicle signal loss diagnosis.
[0093] The following introduces the device embodiments of the present application, which can be used to execute the vehicle signal loss diagnosis method in the above embodiments of the present application. For the details not disclosed in the device embodiments of the present application, please refer to the embodiments of the vehicle signal loss diagnosis method above of the present application.
[0094] Figure 4 The block diagram of the vehicle signal loss diagnosis device according to some embodiments of the present application is shown. As shown Figure 4As shown in the figure, the vehicle signal loss diagnosis device according to the embodiment of the present application includes: a vehicle position acquisition module 401, a first cause determination module 402, and a second cause determination module 403. Among them, the vehicle position acquisition module 401 is configured to acquire the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal loss when the vehicle signal of the target vehicle is lost; the first cause determination module 402 is configured to determine that the cause of the vehicle signal loss is that the vehicle is in a coverage hole when the first longitude and latitude information is within the gray area, where the gray area is used to represent the area in the map where the number of vehicle signal losses caused by the coverage hole is greater than a preset number; the second cause determination module 403 is configured to determine that the cause of the vehicle signal loss is a vehicle failure when the first longitude and latitude information is not within the gray area.
[0095] In some embodiments, based on the foregoing solution, the vehicle signal loss diagnosis device further includes a gray area determination module (not shown in the figure), which is configured to determine the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole according to the historical data corresponding to multiple vehicles; and determine the gray area in the map according to the second longitude and latitude information.
[0096] In some embodiments, based on the foregoing solution, the gray area determination module is further configured to determine the third longitude and latitude information in the historical positioning data corresponding to each vehicle; for each vehicle, fill in the missing values of the historical positioning data according to the third longitude and latitude information to obtain the missing positioning data; according to the historical log data corresponding to each vehicle, screen out the target positioning data whose missing cause is that the vehicle is in a coverage hole from the missing positioning data; and determine the longitude and latitude information in the target positioning data as the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole.
[0097] In some embodiments, based on the foregoing solution, the gray area determination module is further configured to fill in the missing values of the historical positioning data according to the third longitude and latitude information and the linear interpolation method.
[0098] In some embodiments, based on the foregoing solution, the gray area determination module is further configured to determine the historical log data corresponding to the missing positioning data; mark the missing cause of the missing positioning data according to whether there is vehicle failure information in the historical log data corresponding to the missing positioning data, where the missing causes include the vehicle being in a coverage hole and vehicle failure; and determine the missing positioning data whose missing cause is marked as the vehicle being in a coverage hole as the target positioning data.
[0099] In some embodiments, based on the foregoing solution, the gray area determination module is further configured to cluster the second longitude and latitude information to obtain multiple clustering clusters; determine the minimum convex polygon of all the clustering points in each clustering cluster; map the boundary of each minimum convex polygon to the map to obtain the boundary of the gray area in the map; and render the boundary of the gray area in the map to obtain the gray area.
[0100] In some embodiments, the second cause determination module 403 is further configured to send vehicle fault alarm information to a vehicle management platform.
[0101] Based on the same inventive concept, an embodiment of the present application further provides a vehicle signal loss diagnosis device. Refer to Figure 5 , which shows a schematic structural diagram of the vehicle signal loss diagnosis device in the embodiment of the present application. The vehicle signal loss diagnosis device includes one or more memories 504, one or more processors 502, and at least one computer program (computer program instructions) stored on the memory 504 and executable on the processor 502. When the processor 502 executes the computer program, the method described above is implemented.
[0102] Among them, in Figure 5 , the bus architecture (represented by the bus 500), the bus 500 may include any number of interconnected buses and bridges. The bus 500 links various circuits including one or more processors represented by the processor 502 and the memory represented by the memory 504 together. The bus 500 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art. Therefore, they will not be further described herein. The bus interface 505 provides an interface between the bus 500 and the receiver 501 and the transmitter 503. The receiver 501 and the transmitter 503 may be the same element, that is, a transceiver, providing a unit for communicating with various other devices on the transmission medium. The processor 502 is responsible for managing the bus 500 and general processing, while the memory 504 may be used to store data used by the processor 502 when performing operations.
[0103] Based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed by a processor, the processor is caused to implement the steps of the method described above.
[0104] Based on the same inventive concept, an embodiment of the present application provides a computer program product including a computer program. When the computer program product is executed by a processor, the processor is caused to implement the steps of the method described above.
[0105] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored on or transmitted via a computer-readable medium as one or more instructions or code. Other examples and implementations are within the scope and spirit of this application and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwiring, or any combination of these. In addition, each functional unit can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit.
[0106] In several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings or direct couplings or communication connections shown or discussed with each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.
[0107] The units described as separate components may or may not be physically separated. The components serving as control devices may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0108] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: USB flash drives, read-only memory (ROM), random access memory (RAM), mobile hard disks, magnetic disks, or optical discs, etc., which can store computer program instructions.
[0109] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.
Claims
1. A method for diagnosing vehicle signal loss, characterized in that, Including: When the vehicle signal of the target vehicle is lost, obtaining the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal is lost; When the first longitude and latitude information is within the gray area, determining that the reason for the vehicle signal loss is that the vehicle is in a coverage hole, where the gray area is used to represent an area in the map where the number of vehicle signal losses caused by coverage holes is greater than a preset number; When the first longitude and latitude information is not within the gray area, determining that the reason for the vehicle signal loss is a vehicle failure.
2. The vehicle signal loss diagnosis method according to claim 1, wherein Also including: According to the historical data corresponding to multiple vehicles, determining the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole; According to the second longitude and latitude information, determining the gray area in the map.
3. The vehicle signal loss diagnosis method according to claim 2, wherein The historical data includes historical positioning data and historical log data. The determining the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole according to the historical data corresponding to multiple vehicles includes: Determining the third longitude and latitude information in the historical positioning data corresponding to each vehicle; For each vehicle, filling in the missing values of the historical positioning data according to the third longitude and latitude information to obtain missing positioning data; According to the historical log data corresponding to each vehicle, screening out the target positioning data with the reason for loss being that the vehicle is in a coverage hole from the missing positioning data; Determining the longitude and latitude information in the target positioning data as the second longitude and latitude information of the vehicle when the vehicle signal is lost due to the vehicle being in a coverage hole.
4. The vehicle signal loss diagnosis method according to claim 3, characterized in that, The filling in the missing values of the historical positioning data according to the third longitude and latitude information includes: Filling in the missing values of the historical positioning data according to the third longitude and latitude information and the linear interpolation method.
5. The vehicle signal loss diagnosis method according to claim 3, wherein The screening out the target positioning data with the reason for loss being that the vehicle is in a coverage hole from the missing positioning data according to the historical log data corresponding to each vehicle includes: Determining the historical log data corresponding to the missing positioning data; According to whether there is vehicle failure information in the historical log data corresponding to the missing positioning data, marking the reason for loss of the missing positioning data, where the reasons for loss include the vehicle being in a coverage hole and vehicle failure; Determining the missing positioning data with the reason for loss marked as the vehicle being in a coverage hole as the target positioning data.
6. The vehicle signal loss diagnosis method according to claim 2, characterized in that The determining the gray area in the map according to the second longitude and latitude information includes: Clustering the second longitude and latitude information to obtain multiple clustering clusters; Determining the minimum convex polygon of all clustering points in each clustering cluster; Mapping the boundary of each minimum convex polygon to the map to obtain the boundary of the gray area in the map; Rendering the boundary of the gray area in the map to obtain the gray area.
7. The vehicle signal loss diagnosis method according to any one of claims 1 to 6, characterized in that After determining that the reason for the vehicle signal loss is a vehicle failure, the method further includes: Sending a vehicle failure alarm message to the vehicle management platform.
8. A vehicle signal loss diagnosis device, characterized in that, Including: A vehicle position acquisition module, configured to obtain the first longitude and latitude information uploaded by the target vehicle for the last time before the vehicle signal of the target vehicle is lost when the vehicle signal is lost; The first cause determination module is configured to determine that the reason for the vehicle signal loss is that the vehicle is in a coverage hole when the first longitude and latitude information is within the gray area, where the gray area is used to represent an area on the map where the number of vehicle signal losses caused by coverage holes is greater than a preset number; The second cause determination module is configured to determine that the reason for the vehicle signal loss is a vehicle fault when the first longitude and latitude information is not within the gray area.
9. A vehicle signal loss diagnosis device, comprising a processor and a memory, characterized in that, The memory stores computer program instructions that can be executed by the processor. When the processor executes the computer program instructions, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium, characterized in that, Computer program instructions are stored in the computer-readable storage medium. When the computer program instructions are executed by the processor, the processor is caused to implement the steps of the method according to any one of claims 1 to 7.