Road information collection method, device, storage medium and electronic device

Abstract

The present application discloses a road information collection method, device, storage medium and electronic device. The server method includes: receiving a road information collection request sent by a client, the request carries the route information to be collected, the start time for the request and multiple time points for collecting road picture information; based on the route information to be collected, determining the online vehicle information and creating an audio and video acquisition request, and sending it to the vehicle terminal; when receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal, extracting the road key frame at each time point from the historical audio and video data; when the road key frame at each time point meets the preset verification conditions, sending the road key frame to the client. Therefore, by adopting the present application, the mobile performance of the truck can cover the areas that are difficult for fixed cameras to reach, and audio and video data can be collected from the vehicle in a timely manner for processing and analysis, providing timely information support for traffic management and road maintenance.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a road information collection method, device, storage medium and electronic device. Background Art

[0002] In the field of intelligent transportation and road information management, with the development of Internet of Things (IoT) and artificial intelligence (AI) technology, the demand for real-time and accurate road information is growing. A typical application scenario is that the traffic management department or map service provider needs to collect road information of a specific section of road for road maintenance, traffic flow analysis or map data update.

[0003] In the related art, the collection of road information mainly relies on cameras and sensors at fixed locations. These devices can provide continuous monitoring, but they have some limitations. Fixed cameras have limited coverage and cannot cover all roads, especially in remote areas or areas where it is difficult to install cameras, which affects the real-time collection of road information. Summary of the invention

[0004] The embodiments of the present application provide a road information collection method, device, storage medium and electronic device. In order to have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important components or describe the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0005] In a first aspect, an embodiment of the present application provides a method for collecting road information, the method comprising:

[0006] Receive a road surface information collection request sent by a client, where the road surface information collection request carries route information to be collected, a start time for the request, and multiple time points for collecting road image information;

[0007] Based on the route information to be collected, determine the online vehicle information and create an audio and video acquisition request, which is sent to the vehicle terminal;

[0008] When receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal, extract the road key frame at each time point from the historical audio and video data;

[0009] When the road key frame at each time point meets the preset verification conditions, the road key frame is sent to the client to complete the road information.

[0010] Optionally, based on the route information to be collected, determine the online vehicle information and create an audio and video acquisition request, including:

[0011] Acquire at least one target truck information corresponding to the route information to be collected from the pre-constructed mapping relationship between the route information and the truck information;

[0012] According to each target truck information, obtain the driving trajectory of each target truck information within a period of time from the current moment;

[0013] The target truck information whose driving trajectory is located on the road indicated by the route information to be collected is used as the online vehicle information;

[0014] Integrate online vehicle information, start time, and multiple time points into audio and video acquisition requests.

[0015] Optionally, the mapping relationship between the pre-built route information and the truck information is generated according to the following steps, including:

[0016] Obtain the historical trajectory data of each truck within a preset period;

[0017] According to the historical trajectory data and the preset road network information, the driving routes of each truck whose driving frequency is greater than the preset frequency threshold are counted to obtain the long-distance running route of each truck;

[0018] Get the truck information for each truck;

[0019] The mapping relationship between the route information of the long-distance running route of the first truck and the truck information of the first truck is stored to obtain a pre-constructed mapping relationship between the route information and the truck information; the first truck is each truck.

[0020] Optionally, extract road key frames at each time point from historical audio and video data, including:

[0021] The online vehicle information, the audio and video data to be analyzed, the start time and each time point are input as parameters into the preset image extraction model for image extraction processing;

[0022] Output the road key frame at each time point corresponding to the audio and video data to be analyzed;

[0023] The preset image extraction model is a mathematical model that extracts and analyzes key information from audio and video data.

[0024] Optionally, before sending the road keyframe to the client, it also includes:

[0025] Obtain the target trajectory data of the truck corresponding to the online vehicle information between the start time and the last time point through the start time and each time point;

[0026] In the case that the target trajectory data is not missing, the target trajectory data is regarded as the valid trajectory data;

[0027] The road key frame at each time point is verified with the valid trajectory data to determine whether the road key frame at each time point meets the preset verification conditions.

[0028] Optionally, the method further includes:

[0029] Perform road matching through target trajectory data to obtain road matching data;

[0030] When the target trajectory data is missing, obtain the start time and the trajectory points at each time point;

[0031] Use uniform acceleration or uniform deceleration algorithm to supplement trajectory data between the start time and the trajectory points at each time point to obtain complete trajectory data;

[0032] The complete trajectory data is adjusted using the road matching data to obtain the effective trajectory data.

[0033] Optionally, perform point-by-point verification of the road keyframes and valid trajectory data at each time point, including:

[0034] Determine whether the road key frame at each time point meets the preset image format conditions; determine whether the vehicle camera indicated by the road key frame at each time point is a forward-facing camera;

[0035] If not, mark the vehicle to which the online vehicle information belongs as unavailable;

[0036] If yes, compare the valid trajectory data with the road position points represented by the road image information at different time points to determine whether the position deviation is greater than a preset threshold;

[0037] When the position deviation is less than or equal to a preset threshold, the vehicle to which the online vehicle information belongs is marked as available, and it is determined that the road key frame at each time point meets the preset verification conditions.

[0038] In a second aspect, an embodiment of the present application provides a road information collection device, the device comprising:

[0039] A receiving module, used to receive a road surface information collection request sent by a client, the road surface information collection request carries route information to be collected, a start time for the request, and multiple time points for collecting road image information;

[0040] The sending module is used to determine the online vehicle information and create an audio and video acquisition request based on the route information to be collected, and send it to the vehicle terminal;

[0041] The extraction module is used to extract the road key frame at each time point from the historical audio and video data when receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal;

[0042] The sending module is used to send the road key frame to the client to improve the road information when the road key frame at each time point meets the preset verification conditions.

[0043] In a third aspect, an embodiment of the present application provides a computer storage medium, which stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the above-mentioned method steps.

[0044] In a fourth aspect, an embodiment of the present application provides a device, which may include: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0045] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0046] In the embodiment of the present application, by determining online vehicle information and creating audio and video acquisition requests for distribution, the mobile performance of trucks can cover areas that are difficult for fixed cameras to reach, and audio and video data can be collected in a timely manner for processing and analysis, providing timely information support for traffic management and road maintenance. At the same time, after receiving historical audio and video data fed back by the vehicle terminal, the system can automatically extract the road key frames at each time point from the data, providing intuitive visual data for road information analysis.

[0047] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0049] Figure 1 It is a flowchart of a road information collection method provided in an embodiment of the present application;

[0050] Figure 2 This is a data representation of the mapping relationship between truck information and route information provided by this application;

[0051] Figure 3 is a schematic diagram of a trajectory point in trajectory completion provided by the present application;

[0052] Figure 4 It is a structural schematic diagram of a road information collection device provided in an embodiment of the present application;

[0053] Figure 5 It is a structural schematic diagram of a device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following description and the accompanying drawings sufficiently illustrate specific embodiments of the present application to enable those skilled in the art to practice them.

[0055] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0056] When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0057] In the description of the present application, it should be understood that the terms "first", "second", etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to the specific circumstances. In addition, in the description of the present application, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship.

[0058] The present application provides a road information collection method, device, storage medium and electronic device to solve the problems existing in the above-mentioned related technical issues. In the embodiment of the present application, by determining the online vehicle information and creating an audio and video acquisition request for distribution, the mobile performance of the truck covers areas that are difficult for fixed cameras to reach, and the audio and video data can be collected in time for processing and analysis, providing timely information support for traffic management and road maintenance. At the same time, after receiving the historical audio and video data fed back by the vehicle terminal, the system can automatically extract the road key frames at each time point from the data, providing intuitive visual data for road surface information analysis, which is described in detail below using an exemplary embodiment.

[0059] The following will be combined with the attached Figure 1 -Attached Figure 3 , a road information collection method provided by an embodiment of the present application is introduced in detail. The method can be implemented by a computer program and can be run on a road information collection device based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application.

[0060] See also Figure 1 , which is a flow chart of a road information collection method provided in an embodiment of the present application.

[0061] like Figure 1 As shown, the method of the embodiment of the present application may include the following steps:

[0062] S101, receiving a road surface information collection request sent by a client, the road surface information collection request carrying route information to be collected, a start time for the request, and multiple time points for collecting road image information;

[0063] Among them, the client refers to the entity that initiates the road surface information collection request, which may be a traffic management department, a map service provider, or other organization or individual that needs road surface information. A road surface information collection request is a request used to ask the system for road surface information of a specific road section at a specific time. The route information to be collected refers to the road section identifier or description specified in the request for which information needs to be collected. The start time of the request refers to the starting time point for road surface information collection. From this time point, the truck will start collecting road audio and video. The multiple time points for collecting road image information refer to the specific time points for collecting audio and video information after the start time, and these time points are evenly distributed.

[0064] In some embodiments, suppose that a map provider needs to collect road surface information of a remote road in order to complete the road information. When requesting, the client specifies the road sign or description of the road, and the client sets 7:00 in the morning as the start time of the request. The client selects 7:00, 7:15, 7:30, 7:45 and 8:00 as the time points for collecting road image information. The client encapsulates the above parameters into a road surface information collection request and sends it to the server. After receiving the road surface information collection request, the server extracts the route information to be collected, the start time for the request, and the multiple time points for collecting road image information in the road surface information collection request.

[0065] S102, based on the route information to be collected, determine the online vehicle information and create an audio and video acquisition request, and send it to the vehicle terminal;

[0066] Among them, online vehicle information refers to the information of vehicles currently traveling on the route to be collected. The audio and video acquisition request is used to request the vehicle terminal of the online vehicle to provide historical audio and video data within a specific time period. The vehicle terminal refers to the vehicle-mounted computer system installed on the vehicle, which can receive, process and execute instructions from external systems, such as audio and video acquisition requests.

[0067] In some embodiments of the present application, the specific process of determining online vehicle information and creating an audio and video acquisition request based on route information to be collected includes: obtaining at least one target truck information corresponding to the route information to be collected from a pre-constructed mapping relationship between route information and truck information; based on each target truck information, obtaining the driving trajectory corresponding to each target truck information within a period of time from the current moment; using the target truck information whose driving trajectory is on the road indicated by the route information to be collected as the online vehicle information; and integrating the online vehicle information, the start time, and multiple time points into an audio and video acquisition request.

[0068] In the embodiment of the present application, by determining online vehicles based on the route information to be collected, and creating audio and video acquisition requests and sending them to the vehicle terminal, the system can achieve real-time monitoring and data collection of specific routes. The present application improves the pertinence and efficiency of data collection, reduces dependence on fixed monitoring equipment, reduces infrastructure costs, and enhances the understanding and response capabilities of traffic conditions through real-time data analysis.

[0069] In some embodiments of the present application, the specific process of generating a mapping relationship between pre-constructed route information and truck information includes: obtaining historical trajectory data of each truck within a preset period; based on the historical trajectory data and preset road network information, counting the driving routes of each truck whose driving frequency is greater than a preset frequency threshold, and obtaining the long-distance route of each truck; obtaining the truck information of each truck; storing the mapping relationship between the route information of the long-distance route of the first truck and the truck information of the first truck, and obtaining the mapping relationship between the pre-constructed route information and the truck information; the first truck is each truck.

[0070] For example Figure 2 As shown, the truck information may be the license plate number, and the route information may be the long-distance running routes 1, 2, ..., N. In this case, the mapping relationship data table may be, for example, Figure 2 shown.

[0071] In some embodiments, the map service provider determines the route for which information needs to be collected, identifies the online vehicles traveling on the route through mapping relationships, and the system creates audio and video acquisition requests for these online vehicles, and sends the audio and video acquisition requests to the vehicle terminals of these online vehicles. Within the requested time period, the vehicle terminal activates the vehicle's front camera, starts collecting audio and video data, and feeds it back to the server.

[0072] S103, when receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal, extracting the road key frame at each time point from the historical audio and video data;

[0073] In some embodiments of the present application, historical audio and video data from a start time to a last time point fed back by a server is received, and a road key frame at each time point can be extracted from the historical audio and video data.

[0074] In some embodiments of the present application, the specific process of extracting road key frames at each time point from historical audio and video data includes: inputting online vehicle information, audio and video data to be analyzed, start time and each time point as parameters into a preset image extraction model for image extraction processing; outputting the road key frames at each time point corresponding to the audio and video data to be analyzed; wherein the preset image extraction model is a mathematical model for extracting and analyzing key information from audio and video data.

[0075] The preset image extraction model is a predefined mathematical model used to extract and analyze key information from audio and video data. This model is based on machine learning, deep learning or other image processing technologies, and can recognize and process image data to achieve specific functions such as object recognition, scene understanding, feature extraction, etc.

[0076] Furthermore, after obtaining the road key frame at each time point, it is also necessary to determine whether the road key frame at each time point meets the preset verification condition.

[0077] In some embodiments of the present application, the specific process of determining whether the road key frame at each time point meets the preset verification conditions includes: obtaining the target trajectory data of the truck corresponding to the online vehicle information between the start time and the last time point through the start time and each time point; when the target trajectory data is not missing, using the target trajectory data as valid trajectory data; performing point graph verification on the road key frame at each time point and the valid trajectory data to determine whether the road key frame at each time point meets the preset verification conditions.

[0078] In other embodiments of the present application, road matching is performed using the target trajectory data to obtain road matching data; when the target trajectory data is missing, the start time and the trajectory points at each time point are obtained; a uniform acceleration or uniform deceleration algorithm is used to supplement the trajectory data between the start time and the trajectory points at each time point to obtain complete trajectory data; and the road matching data is used to adjust the complete trajectory data to obtain valid trajectory data.

[0079] For example, when supplementing trajectory data, obtain the continuous target trajectory data of the truck within a time period. The interval between continuous trajectories cannot exceed 60 seconds. Use the target trajectory data to perform road matching to obtain road matching data. If the trajectory between time points 3 and 4 is missing, the trajectory can be supplemented. Assuming that the time interval between the trajectories of time points 3 and 4 is X seconds, the vehicle performs uniform acceleration or uniform deceleration during X seconds, calculate △t and acceleration a, and determine that the speed at time point 3 is normal, which is the initial value v, △t = t4-t3, and by the formula S = vt+1 / 2at 2 The interpolation points are calculated. The interpolation points calculated at this time are S1, S2, S3, S4... Among them,

[0080] The result returned by multi-point matching is marked as a point {P1, P2, P3, P4...}, and the distance from each point in the point sequence to the starting point P1 is {L1, L2, L3, L4...}.

[0081] So we need to find the point Tn corresponding to Sn that satisfies Lm<=Sn<=Lm+1, and finally:

[0082] Each insertion point, such as Figure 3 As shown.

[0083] In some embodiments of the present application, the specific process of performing point-to-point graph verification on the road key frame at each time point and the valid trajectory data includes: determining whether the road key frame at each time point meets the preset image format conditions; determining whether the vehicle camera indicated by the road key frame at each time point is a forward-facing camera; if not, marking the vehicle to which the online vehicle information belongs as unavailable; if yes, comparing the valid trajectory data with the road position points represented by the road image information at different time points to determine whether the position deviation is greater than a preset threshold; when the position deviation is less than or equal to the preset threshold, marking the vehicle to which the online vehicle information belongs as available, and determining that the road key frame at each time point meets the preset verification conditions.

[0084] S104, when the road key frame at each time point meets the preset verification conditions, the road key frame is sent to the client to improve the road information.

[0085] Among them, improving road information means using the collected key frames to update and improve the existing road database or map information to make it more accurate and comprehensive.

[0086] In some embodiments of the present application, for key frames that meet the verification conditions, the system sends them to the client of the traffic monitoring system. After receiving the key frames, the client of the traffic monitoring system uses these images to update the traffic signs and road condition information in the database. The updated road information is published to the public map service or used for internal traffic management to provide more accurate navigation guidance and traffic condition analysis.

[0087] In the embodiment of the present application, by determining online vehicle information and creating audio and video acquisition requests for distribution, the mobile performance of trucks can cover areas that are difficult for fixed cameras to reach, and audio and video data can be collected in a timely manner for processing and analysis, providing timely information support for traffic management and road maintenance. At the same time, after receiving historical audio and video data fed back by the vehicle terminal, the system can automatically extract the road key frames at each time point from the data, providing intuitive visual data for road information analysis.

[0088] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0089] See also Figure 4 , which shows a schematic diagram of the structure of a road information collection device provided by an exemplary embodiment of the present application. The road information collection device can be implemented as all or part of a device through software, hardware or a combination of both. The device 1 includes a receiving module 10, a sending module 20, an extraction module 30, and a sending module 40.

[0090] The receiving module 10 is used to receive a road surface information collection request sent by a client, where the road surface information collection request carries route information to be collected, a start time for the request, and multiple time points for collecting road image information;

[0091] The sending module 20 is used to determine the online vehicle information and create an audio and video acquisition request based on the route information to be collected, and send it to the vehicle terminal;

[0092] The extraction module 30 is used to extract the road key frame at each time point from the historical audio and video data when receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal;

[0093] The sending module 40 is used to send the road key frame to the client to improve the road information when the road key frame at each time point meets the preset verification conditions.

[0094] It should be noted that the road information collection device provided in the above embodiment only uses the division of the above functional modules as an example when executing the road information collection method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the road information collection device provided in the above embodiment and the road information collection method embodiment belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0095] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0096] In the embodiment of the present application, by determining online vehicle information and creating audio and video acquisition requests for distribution, the mobile performance of trucks can cover areas that are difficult for fixed cameras to reach, and audio and video data can be collected in a timely manner for processing and analysis, providing timely information support for traffic management and road maintenance. At the same time, after receiving historical audio and video data fed back by the vehicle terminal, the system can automatically extract the road key frames at each time point from the data, providing intuitive visual data for road information analysis.

[0097] The present application also provides a computer-readable medium having program instructions stored thereon, and when the program instructions are executed by a processor, the road information collection methods provided by the above-mentioned various method embodiments are implemented.

[0098] The present application also provides a computer program product including instructions, which, when executed on a computer, enables the computer to execute the road information collection method of each of the above method embodiments.

[0099] See also Figure 5 , which is a schematic diagram of the structure of a device provided in the embodiment of the present application. Figure 5 As shown, the device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0100] The communication bus 1002 is used to realize the connection and communication between these components.

[0101] The user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.

[0102] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0103] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect the various parts of the entire device 1000, and executes various functions and processes data of the device 1000 by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes operating devices, user interfaces and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0104] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing the operating device, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may also be optionally at least one storage device located away from the aforementioned processor 1001. As Figure 5 As shown, the memory 1005 as a computer storage medium may include an operating device, a network communication module, a user interface module, and a road information collection application.

[0105] exist Figure 5In the device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call the road information collection application stored in the memory 1005 and specifically perform the following operations:

[0106] Receive a road surface information collection request sent by a client, where the road surface information collection request carries route information to be collected, a start time for the request, and multiple time points for collecting road image information;

[0107] Based on the route information to be collected, determine the online vehicle information and create an audio and video acquisition request, which is sent to the vehicle terminal;

[0108] When receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal, extract the road key frame at each time point from the historical audio and video data;

[0109] When the road key frame at each time point meets the preset verification conditions, the road key frame is sent to the client to complete the road information.

[0110] In one embodiment, when the processor 1001 determines online vehicle information and creates an audio and video acquisition request based on the route information to be collected, the processor 1001 specifically performs the following operations:

[0111] Acquire at least one target truck information corresponding to the route information to be collected from the pre-constructed mapping relationship between the route information and the truck information;

[0112] According to each target truck information, obtain the driving trajectory of each target truck information within a period of time from the current moment;

[0113] The target truck information whose driving trajectory is located on the road indicated by the route information to be collected is used as the online vehicle information;

[0114] Integrate online vehicle information, start time, and multiple time points into audio and video acquisition requests.

[0115] In one embodiment, when the processor 1001 generates a mapping relationship between pre-built route information and truck information, the processor 1001 specifically performs the following operations:

[0116] Obtain the historical trajectory data of each truck within a preset period;

[0117] According to the historical trajectory data and the preset road network information, the driving routes of each truck whose driving frequency is greater than the preset frequency threshold are counted to obtain the long-distance running route of each truck;

[0118] Get the truck information for each truck;

[0119] The mapping relationship between the route information of the long-distance running route of the first truck and the truck information of the first truck is stored to obtain a pre-constructed mapping relationship between the route information and the truck information; the first truck is each truck.

[0120] In one embodiment, when the processor 1001 extracts the road key frame at each time point from the historical audio and video data, the processor 1001 specifically performs the following operations:

[0121] The online vehicle information, the audio and video data to be analyzed, the start time and each time point are input as parameters into the preset image extraction model for image extraction processing;

[0122] Output the road key frame at each time point corresponding to the audio and video data to be analyzed;

[0123] The preset image extraction model is a mathematical model that extracts and analyzes key information from audio and video data.

[0124] In one embodiment, before executing sending the road key frame to the client, the processor 1001 further performs the following operations:

[0125] Obtain the target trajectory data of the truck corresponding to the online vehicle information between the start time and the last time point through the start time and each time point;

[0126] In the case that the target trajectory data is not missing, the target trajectory data is regarded as the valid trajectory data;

[0127] The road key frame at each time point is verified with the valid trajectory data to determine whether the road key frame at each time point meets the preset verification conditions.

[0128] In one embodiment, the processor 1001 further performs the following operations:

[0129] Perform road matching through target trajectory data to obtain road matching data;

[0130] When the target trajectory data is missing, obtain the start time and the trajectory points at each time point;

[0131] Use uniform acceleration or uniform deceleration algorithm to supplement trajectory data between the start time and the trajectory points at each time point to obtain complete trajectory data;

[0132] The complete trajectory data is adjusted using the road matching data to obtain the effective trajectory data.

[0133] In one embodiment, when the processor 1001 performs point-graph verification on the road key frame at each time point and the valid trajectory data, the following operations are specifically performed:

[0134] Determine whether the road key frame at each time point meets the preset image format conditions; determine whether the vehicle camera indicated by the road key frame at each time point is a forward-facing camera;

[0135] If not, mark the vehicle to which the online vehicle information belongs as unavailable;

[0136] If yes, compare the valid trajectory data with the road position points represented by the road image information at different time points to determine whether the position deviation is greater than a preset threshold;

[0137] When the position deviation is less than or equal to a preset threshold, the vehicle to which the online vehicle information belongs is marked as available, and it is determined that the road key frame at each time point meets the preset verification conditions.

[0138] In the embodiment of the present application, by determining online vehicle information and creating audio and video acquisition requests for distribution, the mobile performance of trucks can cover areas that are difficult for fixed cameras to reach, and audio and video data can be collected in a timely manner for processing and analysis, providing timely information support for traffic management and road maintenance. At the same time, after receiving historical audio and video data fed back by the vehicle terminal, the system can automatically extract the road key frames at each time point from the data, providing intuitive visual data for road information analysis.

[0139] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program for collecting road information can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium of the program for collecting road information can be a magnetic disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0140] The above disclosure is only the preferred embodiment of the present application, which certainly cannot be used to limit the scope of rights of the present application. Therefore, equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A road information collection method, characterized in that: Applied to the server, the method includes: Receive a road surface information collection request sent by a client, the road surface information collection request carrying route information to be collected, a start time for the request, and multiple time points for collecting road image information; Based on the route information to be collected, determine the online vehicle information and create an audio and video acquisition request, and send it to the vehicle terminal; When receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal, extracting the road key frame at each time point from the historical audio and video data; When the road key frame at each time point meets the preset verification condition, the road key frame is sent to the client to complete the road information.

2. The method according to claim 1, characterized in that The determining online vehicle information and creating an audio and video acquisition request based on the route information to be collected includes: Acquire at least one target truck information corresponding to the route information to be collected from a pre-constructed mapping relationship between route information and truck information; According to each target truck information, obtain the driving trajectory of each target truck information within a period of time from the current moment; The target truck information whose driving trajectory is located on the road indicated by the route information to be collected is used as online vehicle information; The online vehicle information, the start time and multiple time points are integrated into an audio and video acquisition request.

3. The method according to claim 2, characterized in that The following steps are used to generate a mapping relationship between pre-built route information and truck information, including: Obtain the historical trajectory data of each truck within a preset period; According to the historical trajectory data and the preset road network information, the driving routes of each truck whose driving frequency is greater than the preset frequency threshold are counted to obtain the long-distance running route of each truck; Obtaining truck information of each truck; A mapping relationship between route information of a long-distance running route of a first truck and truck information of the first truck is stored to obtain a pre-constructed mapping relationship between route information and truck information; the first truck is each truck.

4. The method according to claim 1, characterized in that: The step of extracting a road key frame at each time point from the historical audio and video data includes: The online vehicle information, the audio and video data to be analyzed, the start time and each time point are input as parameters into a preset image extraction model for image extraction processing; Output the road key frame at each time point corresponding to the audio and video data to be analyzed; wherein, The preset picture extraction model is a mathematical model for extracting and analyzing key information from audio and video data.

5. The method according to claim 1, characterized in that Before sending the road key frame to the client, the method further includes: Obtain target trajectory data of the truck corresponding to the online vehicle information between the start time and the last time point through the start time and each time point; In a case where the target trajectory data is not missing, taking the target trajectory data as valid trajectory data; The road key frame at each time point is verified with the valid trajectory data to determine whether the road key frame at each time point meets the preset verification condition.

6. The method according to claim 5, characterized in that The method further comprises: Performing road matching through the target trajectory data to obtain road matching data; When the target trajectory data is missing, obtain the start time and the trajectory point at each time point; Use uniform acceleration or uniform deceleration algorithm to supplement trajectory data between the start time and the trajectory points at each time point to obtain complete trajectory data; The complete trajectory data is adjusted using the road matching data to obtain effective trajectory data.

7. The method according to claim 5, characterized in that The performing point graph verification on the road key frame at each time point and the valid trajectory data includes: Determine whether the road key frame at each time point meets the preset image format condition; determine whether the vehicle camera indicated by the road key frame at each time point is a forward-facing camera; If not, marking the vehicle to which the online vehicle information belongs as unavailable; If yes, comparing the valid trajectory data with the road position points represented by the road picture information at different time points to determine whether the position deviation is greater than a preset threshold; In the case where the position deviation is less than or equal to a preset threshold, the vehicle to which the online vehicle information belongs is marked as available, and it is determined that the road key frame at each time point meets the preset verification condition.

8. A road information collection device, characterized in that: The device comprises: A receiving module, used to receive a road surface information collection request sent by a client, wherein the road surface information collection request carries route information to be collected, a start time for the request, and multiple time points for collecting road image information; A sending module, used for determining online vehicle information and creating an audio and video acquisition request based on the route information to be collected, and sending the request to the vehicle terminal; An extraction module, configured to extract a road key frame at each time point from the historical audio and video data when receiving the historical audio and video data from the start time to the last time point fed back by the vehicle terminal; The sending module is used to send the road key frame to the client to improve the road information when the road key frame at each time point meets the preset verification conditions.

9. A computer storage medium, characterized in that: The computer storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the method according to any one of claims 1 to 7.

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