Road traffic facility inspection and collection method, system and medium based on vehicle-mounted equipment

Abstract

The present invention discloses a method, system and medium for inspecting and collecting road traffic facilities based on in-vehicle devices, including obtaining road images and their corresponding road information, compressing a preset number of road images into video data packets and storing the road information corresponding to the video data packets as a road information table; obtaining the vehicle speed and the network speed for data upload, and calculating the amount of data D1 that can be uploaded according to the preset time and the network speed; when D1≥preset threshold, temporarily storing the video data packets and their corresponding road information tables into the real-time data transmission queue respectively, and when D1 is less than the preset threshold, temporarily storing the video data packets and their corresponding road information tables into the offline cache transmission queue respectively; uploading the data in the real-time data transmission queue and the cache transmission queue in sequence according to the set priority upload order, and by classifying and grading the data to be uploaded, timely transmitting the data to be uploaded back to the cloud server for storage to avoid data loss.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic facility safety, and particularly relates to a road traffic facility inspection and acquisition method, system and medium based on vehicle-mounted equipment. Background Art

[0002] The traffic safety facilities on national and provincial roads play a crucial role in ensuring road traffic safety, improving road operation efficiency, and promoting road network connectivity. The main traffic safety facilities on national and provincial roads include traffic signs, traffic markings, and guardrails, which play an important role in preventing traffic accidents.

[0003] Traditional methods conduct regular manual inspections and maintenance. Personnel visually inspect the problems of traffic safety facilities, and when problems are found, images are taken with a mobile phone and information such as the current defect location and category is manually recorded. The efficiency of manual inspections is relatively low and the subjectivity is strong, making it difficult to meet the current refined management and maintenance requirements for traffic safety facilities on national and provincial roads. Moreover, in some areas such as mountainous regions of national and provincial roads, the signal is weak, and during inspection and acquisition, generally tens of thousands of kilometers are continuously acquired. Among them, pictures are the main acquisition data, and a huge amount of data is waiting to be uploaded. The upload of ultra-large data has high requirements for network stability. Summary of the Invention

[0004] The purpose of the present invention is to provide a road traffic facility inspection and acquisition method, system and medium based on vehicle-mounted equipment, which classify and transmit the data to be uploaded in a timely manner, and timely transmit the data to be uploaded back to the cloud server for storage to avoid data loss.

[0005] To achieve the above purpose, the present invention proposes the following solutions:

[0006] On the one hand, the present invention provides a road traffic facility inspection and acquisition method based on vehicle-mounted equipment, which specifically includes the following steps:

[0007] S1. Obtain the road images and their corresponding road information acquired by each acquisition device installed on the vehicle-mounted equipment at a fixed frequency, compress a preset number of road images into video data packets, and store the road information corresponding to the video data packets as a road information table;

[0008] S2. Obtain the vehicle speed of the current vehicle-mounted equipment and the network speed of the current data upload, calculate the preset time for data upload according to the vehicle speed and the fixed frequency, and calculate the data volume D1 that can be uploaded according to the preset time and the network speed;

[0009] S3. When the data volume D1 is greater than or equal to the preset threshold, temporarily store the video data packet and its corresponding road information table into the real-time data transmission queue respectively. When the data volume D1 is less than the preset threshold, temporarily store the video data packet and its corresponding road information table into the offline cache transmission queue respectively;

[0010] S4. Upload the data in the real-time data transmission queue and the cache transmission queue to the cloud server in sequence according to the set priority upload order.

[0011] In some specific implementation schemes, the specific process of step S1 is as follows:

[0012] S11. Store the road images associated with road information into the image dataset in sequence;

[0013] S12. Count whether the number of road images in the image dataset reaches the preset quantity. If so, compress the preset quantity of road images into video segments;

[0014] S13. Encrypt the video segments, create an encryption key based on the road information corresponding to the first-frame road image of the video segments, and obtain the encrypted video data packets.

[0015] In some specific implementation schemes, the acquisition device includes an image acquisition device, a positioning device for acquiring position information, and a measurement device for acquiring road information;

[0016] The image acquisition device includes a marking acquisition camera for acquiring road marking images, a sign acquisition camera for acquiring road sign images, and a guardrail acquisition camera for acquiring road guardrail images. For each road image, bind and associate the road image with the corresponding position information and road information, so that each road image carries the position information and road information at the moment when the road image is acquired;

[0017] The image dataset includes a marking image dataset for storing road marking images, a sign image dataset for storing road sign images, and a guardrail image dataset for storing road guardrail images;

[0018] The video data packets include marking video data packets, sign video data packets, and guardrail video data packets.

[0019] In some specific implementation schemes, pack the marking video data packet, sign video data packet, and guardrail video data packet obtained at the same acquisition moment into the same video transmission data packet, and pack the road information tables corresponding to each video data packet into the same file data packet;

[0020] Take the total data volume of the same video transmission data packet and the same file data packet as the preset threshold;

[0021] When the data volume D1 is greater than or equal to the preset threshold, temporarily store the same video transmission data packet into the real-time video data transmission queue A1, and temporarily store the same file data packet into the real-time file data transmission queue A2.

[0022] When the data volume D1 is less than the preset threshold, the same video transmission data packet is temporarily stored in the offline video data transmission queue B1, and the same file data packet is temporarily stored in the offline file data transmission queue B2.

[0023] In some specific implementation manners, the set priority upload order is as follows:

[0024] The real-time file data transmission queue A2 > the real-time video data transmission queue A1 > the offline file data transmission queue B2 > the offline video data transmission queue B1.

[0025] In some specific implementation manners, before executing step S3, the following steps are further included:

[0026] Query whether the data in the real-time file data transmission queue A2 is empty. If it is not empty, the same video transmission data packet is temporarily stored in the offline video data transmission queue B1, and the same file data packet is temporarily stored in the offline file data transmission queue B2;

[0027] If the data in the file data transmission queue A2 is empty, then execute step S3.

[0028] In some specific implementation manners, the calculation method of the preset upload time t is as follows:

[0029] t = s * n / v, where s represents the interval length of the fixed frequency, n represents the preset quantity, and v represents the vehicle speed.

[0030] In some specific implementation manners, each acquisition camera adjusts the camera parameters during acquisition through an automatic exposure control adjustment algorithm when acquiring road images. The specific process of the automatic exposure control adjustment algorithm is as follows:

[0031] S01. Convert the road image captured by the current acquisition camera from the RGB color space to the HSV color space, and calculate the average value Vnow of the brightness of the ROI region of the current image;

[0032] S02. After converting the standard image corresponding to the current image from the RGB color space to the HSV color space, calculate the average value Vstd of the brightness of the ROI region in the standard image;

[0033] S03. Calculate the brightness difference Vdiff between the current road image and the standard image;

[0034] S04. According to the relationship between the brightness difference and the exposure parameter, calculate the adjustment amplitude of the exposure parameter of the acquisition camera when shooting the next frame of the road image, and obtain the exposure parameter of the acquisition camera when shooting the next frame of the road image.

[0035] Second aspect, the present application proposes a road traffic facility inspection and collection system based on in-vehicle devices, including in-vehicle devices, several collection devices installed on the in-vehicle devices, and a data processing device that processes the data collected by each collection device and uploads it to a cloud server. The data processing device includes:

[0036] A data collection module, which is used to obtain road images and their corresponding road information acquired by each collection device at a fixed frequency, compress a preset number of road images into video data packets, and store the road information corresponding to the video data packets as a road information table;

[0037] A network detection module, which is used to obtain the vehicle speed of the current in-vehicle device and the network speed of the current data upload, calculate the preset time for data upload according to the vehicle speed and the fixed frequency, and calculate the data volume D1 that can be uploaded according to the preset time and the network speed;

[0038] A data cache module, which is used to temporarily store the video data packets and their corresponding road information tables in the real-time data transmission queue respectively when the data volume D1 is greater than or equal to the preset threshold, and temporarily store the video data packets and their corresponding road information tables in the offline cache transmission queue respectively when the data volume D1 is less than the preset threshold;

[0039] A data upload module, which is used to upload the data in the real-time data transmission queue and the cache transmission queue to the cloud server in sequence according to the set priority upload order.

[0040] A data receiving module, which is used to parse the backhaul data, mainly involving parsing the video data into pictures, and then matching the picture information with the road information and displaying the data.

[0041] Third aspect, the present application provides a computer-readable storage medium, including:

[0042] One or more processors;

[0043] A storage unit, which is used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors can implement a road traffic facility inspection and collection method based on in-vehicle devices as described in the first aspect.

[0044] The beneficial effects of the present invention are:

[0045] Taking a professional inspection vehicle as the carrier, respectively collecting signs, markings, guardrails, and traffic safety facilities in the national and provincial road environments. In order to reduce the requirement for network stability, the collected videos are compressed into a small video every preset number for caching;

[0046] Stream processing using a buffer: Using a large buffer reduces the number of read and write operations, thereby improving efficiency. Through stream reading and writing, it is possible to avoid loading the entire file into memory at once. This can effectively process large files and reduce memory consumption. To address network signal issues in different regions, the data to be transmitted is also classified and transmitted separately according to the transmission priorities of different types of data. Description of the Drawings

[0047] Figure 1 Flowchart of the road traffic facility inspection and collection method based on in-vehicle equipment provided by an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the data transmission process provided by an embodiment of the present invention. Detailed Embodiments

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way limits the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of the present invention.

[0050] Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions, and numerical values described in these embodiments do not limit the scope of the present invention.

[0051] At the same time, it should be understood that, for the sake of description, the dimensions of the various parts shown in the drawings are not drawn in actual proportional relationships.

[0052] In addition, for the sake of clarity and conciseness, the descriptions of well-known structures, functions, and configurations may be omitted. Those of ordinary skill in the art will recognize that various changes and modifications can be made to the examples described herein without departing from the spirit and scope of the present disclosure.

[0053] For technologies, methods, and devices known to those of ordinary skill in the relevant fields, detailed discussions may not be made, but where appropriate, the technologies, methods, and devices should be regarded as part of the authorization specification.

[0054] In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0055] Embodiment 1

[0056] AsFigure 1 As shown in Figure 1 , this embodiment provides a method for inspecting and collecting road traffic facilities based on in-vehicle devices, which specifically includes the following steps:

[0057] S1. Obtain the road images and their corresponding road information acquired by each collection device installed on the in-vehicle device at a fixed frequency, compress a preset number of road images into video data packets, and store the road information corresponding to the video data packets as a road information table;

[0058] The specific process of step S1 is as follows:

[0059] S11. Sequentially store the road images associated with road information into the image dataset;

[0060] S12. Count whether the number of road images in the image dataset reaches the preset number. If so, compress the preset number of road images into a video segment;

[0061] S13. Encrypt the video segment, create an encryption key based on the road information corresponding to the first-frame road image of the video segment, and obtain the encrypted video data packet.

[0062] Specifically, the collection device includes an image collection device, a positioning device for collecting position information, and a measurement device for collecting road information;

[0063] The image collection device includes a marking collection camera for collecting road marking images, a sign collection camera for collecting road sign images, and a guardrail collection camera for collecting road guardrail images. For each road image, bind and associate the road image with the corresponding position information and road information, so that each road image carries the position information and road information at the time of road image collection;

[0064] The image dataset includes a marking image dataset for storing road marking images, a sign image dataset for storing road sign images, and a guardrail image dataset for storing road guardrail images;

[0065] The video data packet includes a marking video data packet, a sign video data packet, and a guardrail video data packet.

[0066] S2. Obtain the vehicle speed of the current in-vehicle device and the network speed of the current data upload, calculate the preset time for data upload according to the vehicle speed and the fixed frequency, and calculate the data volume D1 that can be uploaded according to the preset time and the network speed;

[0067] Specifically, the calculation method of the preset time t for upload is:

[0068] t = s * n / v, where s represents the interval length of the fixed frequency, n represents the preset number, and v represents the vehicle speed.

[0069] Since the table information contained in the file data packet includes information such as positioning that needs to be parsed and displayed in real time, its priority is relatively high. When transmitting, it is necessary to first determine whether there is remaining data in the real-time video data transmission queue A1. If there is remaining data, the data in the real-time queue needs to be uploaded first, and then the data in other data queues can be uploaded.

[0070] S21. Query whether the data in the real-time file data transmission queue A2 is empty. If it is not empty, temporarily store the same video transmission data packet in the offline video data transmission queue B1 and the same file data packet in the offline file data transmission queue B2.

[0071] If the data in the file data transmission queue A2 is empty, execute step S3.

[0072] S3. When the data volume D1 is greater than or equal to the preset threshold, temporarily store the video data packet and its corresponding road information table in the real-time data transmission queue respectively. When the data volume D1 is less than the preset threshold, temporarily store the video data packet and its corresponding road information table in the offline cache transmission queue respectively.

[0073] Since the three acquisition cameras collect data simultaneously at the same moment, the video data packets collected by the three cameras need to be uploaded together during transmission. Therefore, the marking video data packet, the sign video data packet, and the guardrail video data packet obtained at the same acquisition moment are packaged into the same video transmission data packet, and the road information tables corresponding to each video data packet are packaged into the same file data packet.

[0074] In this way, the preset threshold can be set as: taking the total data volume of the same video transmission data packet and the same file data packet as the preset threshold.

[0075] When the data volume D1 is greater than or equal to the preset threshold, temporarily store the same video transmission data packet in the real-time video data transmission queue A1 and the same file data packet in the real-time file data transmission queue A2.

[0076] When the data volume D1 is less than the preset threshold, temporarily store the same video transmission data packet in the offline video data transmission queue B1 and the same file data packet in the offline file data transmission queue B2.

[0077] S4. Upload the data in the real-time data transmission queue and the cache transmission queue to the cloud server in turn according to the set priority upload order. Specifically, the set priority upload order is as follows:

[0078] Real-time file data transmission queue A2 > Real-time video data transmission queue A1 > Offline file data transmission queue B2 > Offline video data transmission queue B1.

[0079] It is understandable that the overall concept of this application is as follows: Assuming that when the vehicle speed v is constant, three industrial acquisition cameras are used to respectively acquire images of the safety facilities of signs, markings, and guardrails on national and provincial roads, including signs in the front and on the roadside, large-scale roadside facilities, lane lines of the driving lane, and roadside guardrails. A measuring device is used to simultaneously acquire road information such as road width, tunnel height, and slope information of highway engineering technical indicators. During driving, other road information during the acquisition process can also be recorded, and finally video data and table data with high-precision position information, timestamp information, and road information are generated. Then, the acquired video data and table data are uploaded to the cloud for corresponding algorithm processing, and finally the data after algorithm processing is statistically analyzed to complete the technical condition assessment.

[0080] Specifically, the information to be acquired in this embodiment includes:

[0081] 1. Image information: The image acquisition device includes a sign acquisition camera, a marking acquisition camera, and a guardrail acquisition camera, which respectively acquire the safety facilities of signs, markings, and guardrails on national and provincial roads. For the convenience of technical condition assessment, the acquisition method is external trigger acquisition, and the three acquisition cameras synchronously acquire road images at a fixed frequency, for example, every 5 meters.

[0082] Due to the complex road conditions of national and provincial roads, the rapid changes in external environments such as tree shade occlusion and direct sunlight can easily cause the acquired image information to be overexposed or underexposed. At the same time, the reflection characteristics of signs, markings, and guardrails are extremely different. In the case of unstable external lighting environments, if the same acquisition camera is used to acquire these three types of facilities, it is very difficult to obtain good images of signs, markings, and guardrails simultaneously. In this embodiment, three acquisition cameras are used to respectively acquire signs, markings, and guardrails. At the same time, during the acquisition process, the exposure and gain parameters of each are adjusted through an automatic exposure control adjustment algorithm, so that the acquired images are neither overexposed nor underexposed, and good image effects are obtained for signs, markings, and guardrails. The automatic exposure adjustment algorithm process is as follows:

[0083] S01. Convert the road image captured by the current acquisition camera from the RGB color space to the HSV color space, and calculate the average value Vnow of the brightness of the ROI region of the current image.

[0084] S02. Calculate the average value Vstd of the brightness of the ROI region in the standard image after converting the standard image corresponding to the current image (taking the image with good effect as the standard image) from the RGB color space to the HSV color space.

[0085] S03. Calculate the brightness difference Vdiff between the current road image and the standard image.

[0086] S04. Calculate the adjustment range ExpDiff of the exposure parameter Expnow of the acquisition camera when capturing the next frame of the road image according to the relationship between the brightness difference value and the exposure parameter, where Expdiff = K*Vdiff + D, and K and D are the coefficient and the constant respectively, and obtain the exposure parameter Expnext = Expnow + ExpDiff of the acquisition camera when capturing the next frame of the road image.

[0087] Since the standard image features of signs, markings, and guardrails are different, the Vstd values of the standard images corresponding to each scene are different. Therefore, each acquisition camera will perform separate calculations for camera exposure adjustment.

[0088] 2. Location information: The positioning device includes a GNSS satellite positioning device, an inertial navigation, and a longitudinal distance positioning device, which can obtain geographical location information such as longitude, latitude, and mileage at the current moment in real time, with an accuracy up to the sub-meter level. There is a certain difference between the kilometer posts on the actual road conditions and the actual mileage. The mileage can be corrected at the kilometer posts of the road signs as needed, which is convenient for later position positioning of the detected signs, markings, and guardrails.

[0089] 3. Road information: The measurement device includes a height sensor and an attitude sensor. The height sensor can measure the tunnel height of the passing tunnel to obtain tunnel height information, and the attitude sensor can measure the vehicle body attitude to further reflect the road surface condition and obtain road surface slope information. Using the XYZ angles of the attitude sensor, calculate the road surface slope to provide slope-related data for the general survey of highway engineering technical indicators. When the tunnel marker is turned on, obtain the measured value Hvar of the height sensor, and then add the installation height Hcar to get the center height Hsum = Hvar + Hcar of the tunnel. The measurement of the road surface slope information obtains the lateral tilt angle, longitudinal tilt angle, and heading angle of the attitude sensor installed on the vehicle chassis to calculate the cross slope, longitudinal slope, and curvature of the road surface respectively.

[0090] In addition, the road information also includes the following information that needs to be recorded:

[0091] 3.1. Project information: Includes basic information such as line number, inspection area, test direction, starting mileage, operator, storage path, etc., which is used to record relevant information of the detection area.

[0092] 3.2. Label information: Includes information labels such as road conditions, vehicle conditions, guardrail markings, measurement markings, etc. The information labels are mainly divided into the following categories:

[0093] (1) Status markers (abnormal conditions): muddy, traffic jam, overtaking, closed construction, which can mark the abnormal road conditions during the driving acquisition process.

[0094] (2)Guardrail Markings (Abnormal Conditions): Mark, roadside facilities, can mark obvious guardrail abnormalities and roadside facilities during driving, facilitating quick positioning of data in the later stage and reducing the data calculation volume for classification and statistics;

[0095] (3)Measurement Markings: Road width, tunnel clearance height. For sections with obvious road width changes, turn on the road width marking, and the road width can be calculated for images with road width markings. For tunnel scenes, turn on the tunnel clearance height marking to measure the tunnel clearance height.

[0096] (4)Status Markings (Special Sections): Sharp curves and steep slopes, dangerous roadside areas, tunnels, passing through towns, can mark special sections, facilitating quick positioning of category data in the later stage.

[0097] After obtaining the above image information and road information, according to the acquisition time of the road image, associate the position information and road information corresponding to the acquisition time with each road image, so that the image information and its corresponding road information can be transmitted separately when uploading. Since the amount of data collected is large, collecting continuously for tens of thousands of kilometers will form a huge amount of data, with pictures being the main data. Based on the FFmpeg technology, continuous pictures are compressed into videos for storage while ensuring the data resolution. Uploading ultra-large data has high requirements for network stability. To reduce the requirements for network stability, the collected videos are compressed into a small video as a video segment according to a preset quantity (such as every 200 pictures) and stored in the local cache.

[0098] At the same time, to provide high-security protection and prevent unauthorized access to video data, the AES-256 encryption algorithm is used to encrypt the video data. Create a password based on the road information and position information in the table data corresponding to the first frame data of each video segment, and use the password to create an encryption key. Use a buffer for streaming processing: Use a large buffer to reduce the number of read and write operations, thereby improving efficiency. Through streaming read and write, it is possible to avoid loading the entire file into memory at once. This can effectively process large files and reduce memory consumption.

[0099] When uploading data, there are differences in network signals in different regions. For remote areas, the network signal is poor and data cannot be transmitted in time. Therefore, in order to upload all data, it is divided into two functions: real-time sending and offline sending, corresponding to two situations of good network conditions and poor network conditions respectively. When the router network is good, the encrypted video and table files are sent to the cloud server. After confirming that the cloud server has successfully received them, the local files are deleted. For remote areas, when the router network is poor, you can wait until the network environment is better and use the offline sending function to query all unsent data collected by the current device. To further solve the network signal problems in different regions, different priority transmission orders are set for the data. Specifically:

[0100] Due to network transmission problems, the unsent data to be transmitted includes two parts: real-time new data and offline cached data. And each newly added data includes the same video transmission data packet and the same file data packet; the same file data packet contains information such as positioning that needs to be parsed and displayed in real time with a higher priority. To ensure real-time performance, the order of sending data needs to be determined according to the data priority. The size of the data to be sent is estimated based on the current network speed.

[0101] As Figure 2 shown, the specific process is as follows:

[0102] 1. Obtain the current vehicle speed V and estimate the total data volume D2 of the newly added data in t time = the data volume D3 of the same video transmission data packet + the data volume D4 of the same file data packet. Since data is collected every 5 meters and every 200 images form a same video transmission data packet and a same file data packet, therefore, every 1 kilometer will generate 1 file data packet and a video transmission data packet composed of 3 encrypted video data.

[0103] According to the current vehicle speed v, it can be estimated that after t = 1 / v, a new piece of data will be generated. If calculated at the maximum vehicle speed of 120 km / h, t = 1 km / 120 km / h = 30 s, that is, no new data will be generated within 30 s. Set t = 30 s and estimate every 30 s.

[0104] 2. Obtain the current upload network rate and calculate the data volume D1 that can be sent in t time.

[0105] 3. Classify the newly added data by priority. When the newly added data is obtained, determine whether there is any remaining data in the real-time file data transmission queue A2; if there is remaining data in the real-time file data transmission queue A2, add the same video transmission data packet to the offline video data transmission queue B1, and temporarily store the same file data packet in the offline file data transmission queue B2.

[0106] If there is no remaining data in the real-time file data transmission queue A2, continue to judge the sizes of data volumes D1 and D2;

[0107] When D1≥D2, temporarily store the same video transmission data packet in the real-time video data transmission queue A1 and the same file data packet in the real-time file data transmission queue A2. Otherwise, temporarily store the same video transmission data packet in the offline video data transmission queue B1 and the same file data packet in the offline file data transmission queue B2;

[0108] 4. When uploading data, upload in the order of real-time file data transmission queue A2 > real-time video data transmission queue A1 > offline file data transmission queue B2 > offline video data transmission queue B1.

[0109] Embodiment 2

[0110] This embodiment provides a road traffic facility inspection and acquisition system based on a vehicle-mounted device for implementing the inspection and acquisition method of Embodiment 1, including a vehicle-mounted device, several acquisition devices installed on the vehicle-mounted device, and a data processing device that processes the data collected by each acquisition device and uploads it to a cloud server. The data processing device includes:

[0111] A data acquisition module, which is used for each acquisition device to obtain road images and their corresponding road information at a fixed frequency, compress a preset number of road images into video data packets, and store the road information corresponding to the video data packets as a road information table;

[0112] A network detection module, which is used to obtain the vehicle speed of the current vehicle-mounted device and the network speed of the current data upload, calculate the preset time for data upload according to the vehicle speed and the fixed frequency, and calculate the data volume D1 that can be uploaded according to the preset time and the network speed;

[0113] A data caching module, which is used to temporarily store the video data packets and their corresponding road information tables in the real-time data transmission queue respectively when the data volume D1 is greater than or equal to the preset threshold, and temporarily store the video data packets and their corresponding road information tables in the offline cache transmission queue respectively when the data volume D1 is less than the preset threshold;

[0114] A data upload module, which is used to upload the data in the real-time data transmission queue and the cache transmission queue to the cloud server in turn according to the set priority upload order.

[0115] A data receiving module, which is used to parse the backhaul data, mainly involves decrypting the video data and extracting it into pictures, and then matching the picture information with the road information and displaying the data. According to the upload order of the data upload module, the cloud server will receive the road information and the corresponding video information. When receiving the road information table, it will first parse the position information such as longitude, latitude, and stake number of the table, and draw it on the GIS map of the platform, so that the current operating status of the detection device can be intuitively seen. After receiving a complete set of road information and the corresponding video information, a password is generated using the road information and position information of the first frame image in the table data, and the decryption key is generated using the password to decrypt the video. After the video is decrypted, the videos of the marking acquisition camera, the guardrail acquisition camera, and the sign acquisition camera are extracted into pictures and then bound to the road-related information in the table to obtain a set of basic data including image information from different perspectives and its corresponding road information, and store it in the database for detailed information display and review.

[0116] Embodiment 3

[0117] This embodiment provides a computer-readable storage medium, including:

[0118] One or more processors;

[0119] A storage unit for storing one or more programs, which when executed by the one or more processors, can enable the one or more processors to implement a method for inspecting and collecting road traffic facilities based on in-vehicle devices as described in the first aspect.

[0120] As mentioned above, it is only a preferred embodiment of the present invention, and does not impose any form of limitation on the present invention. Based on the technical essence of the present invention, within the spirit and principle of the present invention, any simple modification, equivalent replacement, and improvement made to the above embodiments still fall within the protection scope of the technical solution of the present invention.

Claims

1. A road traffic facility inspection and collection method based on vehicle-mounted equipment, characterized in that: The following steps are involved: S1. Obtain road images and their corresponding road information acquired by each acquisition device installed on the vehicle-mounted device at a fixed frequency, compress a preset number of road images into video data packets, and store the road information corresponding to the video data packets into a road information table; S2, obtaining the current vehicle speed of the vehicle-mounted device and the current network speed for data uploading, calculating the preset time for data uploading according to the vehicle speed, the interval length of the fixed frequency and the preset number, and calculating the amount of data that can be uploaded D1 according to the preset time and the network speed; The preset upload time t is calculated as follows: t=s*n / v, where s represents the fixed frequency interval length, i.e., the distance that triggers the acquisition camera to collect road images, n represents the preset number, i.e., the number of road images compressed into video data, and v represents the vehicle speed; S3, when the data volume D1 is greater than or equal to a preset threshold, the video data packet and the corresponding road information table are temporarily stored in the real-time data transmission queue, and when the data volume D1 is less than the preset threshold, the video data packet and the corresponding road information table are temporarily stored in the offline cache transmission queue; S4. Upload the data in the real-time data transmission queue and the offline cache transmission queue to the cloud server in sequence according to the set priority upload order.

2. According to claim 1, a road traffic facility inspection and collection method based on vehicle-mounted equipment is characterized in that: The specific process of step S1 is: S11, storing the road images associated with the road information in the image data set in sequence; S12, counting whether the road images in the image data set have reached a preset number, and if so, compressing the preset number of road images into video clips; S13, encrypting the video clip, creating an encryption key based on the road information corresponding to the first frame road image of the video clip, and obtaining an encrypted video data packet.

3. A road traffic facility inspection and collection method based on vehicle-mounted equipment according to claim 2, characterized in that: The acquisition device includes an image acquisition device, a positioning device for acquiring position information, and a measuring device for acquiring road information; The image acquisition device includes a road marking acquisition camera for acquiring road marking images, a road sign acquisition camera for acquiring road sign images, and a guardrail acquisition camera for acquiring road guardrail images. For each road image, the road image is bound and associated with the corresponding position information and road information, so that each road image carries the position information and road information at the time of road image acquisition; The image dataset includes a road marking image dataset for storing road marking images, a road sign image dataset for storing road sign images, and a guardrail image dataset for storing road guardrail images; The video data packets include marking video data packets, sign video data packets and guardrail video data packets.

4. A road traffic facility inspection and collection method based on vehicle-mounted equipment according to claim 3, characterized in that: Packing the marking video data packets, sign video data packets and guardrail video data packets obtained at the same acquisition time into the same video transmission data packet, and packing the road information tables corresponding to each video data packet into the same file data packet; The total data volume of the same video transmission data packet and the same file data packet is used as a preset threshold; When the data volume D1 is greater than or equal to the preset threshold, the same video transmission data packet is temporarily stored in the real-time video data transmission queue A1, and the same file data packet is temporarily stored in the real-time file data transmission queue A2. When the data volume D1 is less than a preset threshold, the same video transmission data packet is temporarily stored in the offline video data transmission queue B1, and the same file data packet is temporarily stored in the offline file data transmission queue B2.

5. A road traffic facility inspection and collection method based on vehicle-mounted equipment according to claim 4, characterized in that: The priority upload order is as follows: Real-time file data transmission queue A2>real-time video data transmission queue A1>offline file data transmission queue B2>offline video data transmission queue B1.

6. A road traffic facility inspection and collection method based on vehicle-mounted equipment according to claim 5, characterized in that: Before executing step S3, the method further includes the following steps: Check whether the data in the real-time file data transmission queue A2 is empty. If it is not empty, temporarily store the same video transmission data packet in the offline video data transmission queue B1 and temporarily store the same file data packet in the offline file data transmission queue B2; If the data in the file data transmission queue A2 is empty, step S3 is executed.

7. A road traffic facility inspection and collection method based on vehicle-mounted equipment according to claim 3, characterized in that: When collecting road images, each acquisition camera adjusts the camera parameters during acquisition through an automatic exposure control adjustment algorithm. The specific process of the automatic exposure control adjustment algorithm is as follows: S01, converting the road image currently captured by the acquisition camera from the RGB color space to the HSV color space, and calculating the mean value Vnow of the brightness of the ROI area of ​​the current image; S02, after converting the standard image corresponding to the current image from the RGB color space to the HSV color space, calculate the mean value Vstd of the brightness of the ROI area in the standard image; S03, calculating the brightness difference Vdiff between the current road image and the standard image; S04. Calculate the adjustment range of the exposure parameter of the camera when shooting the next frame of road image according to the relationship between the brightness difference and the exposure parameter, and obtain the exposure parameter of the camera when shooting the next frame of road image.

8. A road traffic facility inspection and collection system based on vehicle-mounted equipment, characterized in that: It includes a vehicle-mounted device, several collection devices installed on the vehicle-mounted device, and a data processing device that processes the data collected by each collection device and uploads it to the cloud server. The data processing device includes: A data acquisition module, used for each acquisition device to obtain road images and corresponding road information at a fixed frequency, compress a preset number of road images into video data packets and store the road information corresponding to the video data packets into a road information table; The network detection module is used to obtain the current vehicle speed of the vehicle-mounted device and the current network speed of data uploading, calculate the preset time of data uploading according to the vehicle speed, the interval length of the fixed frequency and the preset number, and calculate the amount of data that can be uploaded D1 according to the preset time and the network speed; The preset upload time t is calculated as follows: t=s*n / v, where s represents the fixed frequency interval length, i.e., the distance that triggers the acquisition camera to collect road images, n represents the preset number, i.e., the number of road images compressed into video data, and v represents the vehicle speed; A data cache module, used to temporarily store the video data packet and the corresponding road information table in the real-time data transmission queue when the data volume D1 is greater than or equal to the preset threshold, and temporarily store the video data packet and the corresponding road information table in the offline cache transmission queue when the data volume D1 is less than the preset threshold; The data upload module is used to upload the data in the real-time data transmission queue and the offline cache transmission queue to the cloud server in sequence according to the set priority upload order.

9. A computer-readable storage medium, characterized in that: include: one or more processors; A storage unit, used to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors can implement a road traffic facility inspection and collection method based on a vehicle-mounted device as described in any one of claims 1-7.

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