Road digital marking system and identification method thereof

Abstract

The invention discloses a road digital marking system and an identification method thereof, the road digital marking system comprises a marking robot and an unmanned vehicle, the marking robot comprises a driving assembly, an image acquisition assembly, a measurement assembly, a data processing assembly, a storage assembly, a marking assembly and a communication assembly, the image acquisition assembly is used for acquiring marked line images completed on the two sides of the road by image acquisition equipment; the unmanned vehicle comprises a binocular camera assembly, a map database, a data processing system, a positioning and navigation system, a communication assembly and a feedback system, and the binocular camera assembly comprises a binocular camera installed on the unmanned vehicle and used for capturing and analyzing digital marking images on a road; a pavement image is shot in real time, and the exact position of the digital marking is determined by using a pixel positioning technology. According to the system, specific digital marking lines are drawn on a road through the marking robot, and precise positioning under the condition of no satellite positioning is realized by combining a binocular camera and a map database on the unmanned vehicle, so that the safety and reliability of the unmanned vehicle are improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, in particular to a road digital marking system and a recognition method thereof. Background Art

[0002] Intelligent transportation system is to effectively and comprehensively apply advanced science and technology to transportation, service control and vehicle manufacturing, strengthen the connection between vehicles, roads and users, and thus form a comprehensive transportation system that ensures safety, improves efficiency, improves the environment and saves energy. The construction of intelligent transportation system is an effective means to solve the current problems of urban traffic, and it is also an important indicator of "smart city" construction. The system solves existing traffic problems by building an urban traffic collection system, further integrates various road traffic resources, builds a city "traffic brain", digs into massive traffic data, deconstructs the operation laws and characteristics of urban traffic, and realizes precise, scientific and normal governance of urban traffic, making people's transportation safer, more convenient and more efficient. With the development of unmanned driving technology, vehicles have higher and higher requirements for environmental perception. Although traditional road markings can provide guidance information for drivers, these markings may become difficult to recognize in bad weather or night conditions. In addition, in environments such as tunnels where satellite signals cannot be received, the precise positioning of unmanned vehicles has become a major challenge.

[0003] Chinese patent number CN118038695A provides a method and system for identifying highway signs and markings, which belongs to the technical field of traffic signs. The identification method includes: receiving electromagnetic wave signals in a preset detection area; parsing the electromagnetic wave signals into digital signals; identifying signs and markings based on the distribution of high potentials in the digital signals in the detection area; wherein the signs and markings are composed of multiple high potentials; each lane is pre-buried with multiple road signs and markings of equal specifications; each road sign and marking is evenly installed with multiple oscillators, and different oscillators are controlled to be turned on and off to make the received electromagnetic wave signals different. By controlling different numbers of oscillators to be turned on, the signs and markings composed of oscillators can be identified according to the distribution of the turned-on oscillators; when the type of signs and markings needs to be adjusted, different numbers of oscillators can be controlled to be turned on, so that the type of signs and markings can be changed, thereby improving the applicability of signs and markings.

[0004] Digital road marking systems and recognition methods in the prior art. Although there are some vision-based positioning systems on the market, they often rely on complex algorithms and a large amount of computing resources, and are unstable in certain specific environments.

[0005] At the same time, the existing unmanned vehicle camera laser SLAM three-dimensional reconstruction positioning cost is high, and the accuracy cannot meet the requirements of edge positioning for unmanned sweepers. In some places where the scenery is similar, it is easy to fall into a maze and cannot be positioned. The present invention can achieve high reliability and low cost mm-level positioning in complex environments through the digital road marking recognition method of the present invention. Summary of the invention

[0006] In view of the deficiencies of the prior art, an object of the present invention is to provide a road digital marking system for accurate navigation and a recognition method thereof.

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a road digital marking system and a recognition method thereof adopt a technical solution: comprising a road marking robot and an unmanned vehicle, wherein the road marking robot comprises a driving component, an image acquisition component, a measurement component, a data processing component, a storage component, a road marking component and a communication component, Image acquisition component: The image acquisition device acquires images of the road markings completed on both sides of the road; Measurement component: The measurement component measures and counts the distance of the acquired image; Data processing component: digitizes the data obtained by the image acquisition component and the measurement component; Road marking component: The road marking component uses a robot to draw geometric figures as digital road markings on both sides of the road according to the preset mode. The unmanned vehicle includes a binocular camera component, a map database, a data processing system, a positioning and navigation system, a communication component and a feedback system. Binocular camera assembly: The binocular camera is installed on the unmanned vehicle to capture and analyze the digital road marking images on the road; it takes real-time road images and uses pixel positioning technology to determine the exact position of the digital road markings; Map database: stores all information about digital road markings for query by unmanned vehicles; Positioning and navigation system: combines the real-time location information provided by the binocular camera and the records in the map database.

[0008] As a preferred solution, at least one or more road marking robots are used to draw digital road markings of a specific pattern on the road, receive task instructions from a control center, including information such as the location, type and style of the road markings, drive to a designated location along a predetermined path, and draw digital road markings on the ground using special paint.

[0009] As a preferred solution, the binocular camera uses pixel positioning technology to accurately measure the relative distance between the vehicle and the digital marking, captures the road surface image in real time, and uses pixel positioning technology to determine the exact position of the digital marking.

[0010] As a preferred solution, the map database matches the extracted information with the records in the map database to determine the current position of the vehicle.

[0011] As a preferred solution, the driving component enables the marking robot to move, and the storage component stores the obtained data.

[0012] As a preferred solution, the communication component in the road marking robot transmits both the collected data and the produced data to the control center.

[0013] As a preferred solution, the road marking robot: uses a road marking robot to draw geometric figures as digital road markings on both sides of the road according to a preset pattern. The figures include not only basic shapes such as straight lines and curves, but also complex patterns in the form of QR codes, etc., which are used to convey more information.

[0014] As a preferred solution, the data processing system in the unmanned vehicle processes the acquired data, extracts the characteristic information of the line markings, imports the line marking label data into the unmanned vehicle in advance, calls for comparison and positioning, and uses the line marking patterns on both sides to detect and calculate which lane the vehicle is in on the road when the graphics are partially worn.

[0015] A method for recognizing digital road markings comprises the following steps: S1: Use a binocular camera to capture the digital road marking image and use pixel positioning technology to determine the exact position of the digital road marking; S2: Process the acquired data, analyze the image data, and extract the characteristic information of the marking line; S3: Compare with the records in the map database to determine the current position of the vehicle, collect the operation reports of all road marking robots, and ensure that the position information of each digital road marking is accurately recorded; S4: Combining the real-time location information provided by the binocular camera and the records in the map database, the unmanned vehicle can maintain good navigation performance even when there is no satellite signal; S5: Feedback the recognized digital identification information and data to the control center, which will regularly check the validity and accuracy of the data in the database, update or delete invalid records in a timely manner, and support external import of new road marking data to adapt to the changes and development of urban roads.

[0016] Compared with the prior art, the present invention provides a road digital marking system and a recognition method thereof, which have the following beneficial effects: 1. The system adopted by the present invention uses a road marking robot to draw specific digital markings on the road. Combined with the binocular camera and map database on the unmanned vehicle, it achieves accurate positioning without satellite positioning, thereby improving the safety and reliability of the unmanned vehicle.

[0017] 2. Use the marking robot to draw geometric figures on both sides of the road according to the preset mode as digital markings. These figures include not only basic shapes such as straight lines and curves, but also complex patterns in the form of QR codes, which are used to convey more information. The information is conveyed through simple geometric figures or QR codes, which enhances the flexibility and scalability of the system.

[0018] 3. Through the binocular camera collection, a binocular camera is installed on the unmanned vehicle, and the digital road marking image on the road is captured and analyzed through pixel positioning technology to determine the position of the vehicle relative to the marking, thereby improving the adaptability and positioning accuracy of the unmanned vehicle in complex environments.

[0019] 4. Through the set map database and positioning and navigation system, all known digital marking position information is stored in the map database. When the unmanned vehicle detects a specific marking through the binocular camera, it can quickly locate its own position by comparing the data in the database. The positioning and navigation system combines the real-time position information provided by the binocular camera and the records in the map database, so that the unmanned vehicle can maintain good navigation performance even in the absence of satellite signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the overall structure of the present invention; Figure 2 This is a working schematic diagram of the road marking robot of the present invention; Figure 3 The figure is a schematic flow chart of the operation of the unmanned vehicle of the present invention. DETAILED DESCRIPTION

[0021] The present invention will be further described and illustrated below in conjunction with specific embodiments and accompanying drawings: See also Figure 1-3 The present invention provides a road digital marking system, including a marking robot and an unmanned vehicle. The marking robot is used to draw digital markings of a specific pattern on the road, receive task instructions from a control center, including information such as the position, type and style of the markings, drive to a designated location along a predetermined path, draw digital markings on the ground using special paint, and use the marking robot to draw geometric figures as digital markings on both sides of the road according to a preset pattern. The figures include not only basic shapes such as straight lines and curves, but also complex patterns in the form of QR codes, etc., which are used to convey more information. The information is conveyed by simple geometric figures or QR codes, etc., which enhances the flexibility and scalability of the system. The marking robot includes a driving component, an image acquisition component, a measurement component, a data processing component, a storage component, a marking component and a communication component. Image acquisition component: The image acquisition device acquires images of the road markings completed on both sides of the road; Measurement component: The measurement component measures and counts the distance of the acquired image; Data processing component: digitizes the data obtained by the image acquisition component and the measurement component; Road marking component: The road marking component uses a robot to draw geometric figures as digital road markings on both sides of the road according to a preset pattern; Communication component: transmits both collected data and produced data to the control center; The unmanned vehicle includes a binocular camera component, a map database, a data processing system, a positioning and navigation system, a communication component and a feedback system. Binocular camera assembly: The binocular camera is installed on the unmanned vehicle to capture and analyze the digital road marking images on the road; it takes real-time road images and uses pixel positioning technology to determine the exact position of the digital road markings. The binocular camera uses pixel positioning technology to accurately measure the relative distance between the vehicle and the digital road markings. It takes real-time road images and uses pixel positioning technology to determine the exact position of the digital road markings. Data processing system: processes the acquired data and extracts the characteristic information of the road markings. The communication component connects the unmanned vehicle to the control center through network wireless communication. The control center monitors the status of the unmanned vehicle and imports the road marking label data into the unmanned vehicle in advance to call for comparison and positioning. In the case of partial wear of the graphics, the road marking patterns on both sides are used to detect and calculate which lane the vehicle is in on the road. Map database: stores all information about digital road markings for query by unmanned vehicles. The map database matches the extracted information with the records in the map database to determine the current location of the vehicle. Positioning and navigation system: Combining the real-time position information provided by the binocular camera and the records in the map database, the driving component makes the road marking robot move, receives task instructions from the control center, including information such as the location, type and style of the marking, drives to the designated location according to the predetermined path, and uses special paint to draw digital markings on the ground. The storage component stores the obtained data; Feedback system: The recognized digital identification information and data are transmitted to the control center so that the robot can adjust the digital markings later to ensure the safe and normal driving of the unmanned vehicle.

[0022] The unmanned vehicle is also equipped with active safety components, which include: identification module, decision module, power limiting module and brake control module. The identification module identifies whether there is a person within a certain threshold in front of the retrieval movement, and whether it exceeds the lane and road edge it should be in. If so, the decision module activates the power limit to the minimum and activates the brake control module to ensure safety.

[0023] A method for identifying digital road markings, wherein an unmanned vehicle uses the positioning method of the above system without satellite positioning, comprising the following steps: S1: The unmanned vehicle positioning and navigation system is initialized and calibrated by recognizing the target with a binocular camera, and verified by comparing the known distance and width of the road markings; S2: Use a binocular camera to capture the digital road marking image on the road, and use pixel positioning technology to detect whether the road marking pattern meets the calculation requirements based on the known lane and road marking width. If so, calculate the exact position coordinates of the unmanned vehicle through the digital road marking; S3: Process the acquired data, analyze the image data, extract the feature information of the markings, and store all known digital marking position information in the map database. When the unmanned vehicle detects a specific marking through the binocular camera, it can quickly locate its own position by comparing the data in the database; S4: All known digital road marking location information is stored in the map database. When the unmanned vehicle detects a specific road marking through the binocular camera, it can quickly locate its own position by comparing the data in the database. The identified information is compared with the records in the map database to determine the current position of the vehicle. The operation reports of all road marking robots are collected to ensure that the location information of each digital road marking is accurately recorded. S5: Combining the real-time location information provided by the binocular camera and the records in the map database, the unmanned vehicle can maintain good navigation performance even in the absence of satellite signals, improving the adaptability and positioning accuracy of the unmanned vehicle in complex environments; S6: Feedback the recognized digital identification information and data to the control center, which will regularly check the validity and accuracy of the data in the database, update or delete invalid records in a timely manner, and support external import of new road marking data to adapt to the changes and development of urban roads.

[0024] The working principle of the present invention is as follows: the road marking robot receives task instructions from the control center, including information such as the position, type and style of the markings, moves the road marking robot through the driving component, drives to the designated location along a predetermined path, starts the image acquisition component on the road marking robot, acquires images of the markings completed on both sides of the road through the image acquisition device, measures and counts the distance of the acquired images through the measuring component, digitizes the data obtained by the image acquisition component and the measuring component, and then draws geometric figures as digital markings on both sides of the road according to a preset mode through the road marking component, draws digital markings on the ground with special paint, and after completion, feeds back the task completion status to the control center, and uploads the specific position of the markings to the map database.

[0025] When the unmanned vehicle is driving, a binocular camera component is used to capture road images in real time, and pixel positioning technology is used to determine the exact position of the digital markings. The acquired data is processed to extract the characteristic information of the markings, and the extracted information is matched with the records in the map database to determine the current position of the vehicle. At the same time, the operation reports of all marking robots are collected to ensure that the position information of each digital marking is accurately recorded, the validity and accuracy of the data in the database are checked regularly, and invalid records are updated or deleted in a timely manner. External import of new marking data is supported to adapt to the changes and development of urban roads. At the same time, combined with the real-time position information provided by the binocular camera and the records in the map database, the unmanned vehicle can maintain good navigation performance even in the absence of satellite signals.

[0026] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. A road digital marking system, comprising a road marking robot and an unmanned vehicle, characterized in that: The marking robot includes a driving component, an image acquisition component, a measuring component, a data processing component, a storage component, a marking component and a communication component. Image acquisition component: The image acquisition device acquires images from both sides of the road; Measurement component: The measurement component measures and counts the distance of the acquired image; Data processing component: digitizes the data obtained by the image acquisition component and the measurement component; Road marking component: The road marking component draws geometric figures as digital road markings on both sides of the road according to the preset mode. The unmanned vehicle includes a binocular camera component, a map database, a data processing system, a positioning and navigation system, a communication component and a feedback system. Binocular camera assembly: The binocular camera is installed on the unmanned vehicle to capture and analyze the digital road marking images on the road; it takes real-time road images and uses pixel positioning technology to determine the exact position of the digital road markings; Map database: stores all information about digital road markings for query by unmanned vehicles; Positioning and navigation system: combines the real-time location information provided by the binocular camera and the records in the map database.

2. A road digital marking system according to claim 1, characterized in that: At least one or more of the road marking robots are used to draw digital road markings of a specific pattern on the road, receive task instructions from a control center, including information such as the location, type and style of the road markings, drive to a designated location along a predetermined path, and draw digital road markings on the ground using special paint.

3. A road digital marking system according to claim 1, characterized in that: The binocular camera uses pixel positioning technology to accurately measure the relative distance between the vehicle and the digital marking, captures road surface images in real time, and uses pixel positioning technology to determine the exact position of the digital marking.

4. A road digital marking system according to claim 1, characterized in that: The map database matches the extracted information with records in the map database to determine the current position of the vehicle.

5. A road digital marking system according to claim 1, characterized in that: The driving component enables the line marking robot to move, and the storage component stores the obtained data.

6. A road digital marking system according to claim 1, characterized in that: The communication component in the road marking robot transmits both the collected data and the produced data to the control center.

7. A road digital marking system according to claim 1, characterized in that: The road marking robot is used to draw geometric figures as digital road markings on both sides of the road according to a preset pattern. The figures include not only basic shapes such as straight lines and curves, but also complex patterns in the form of QR codes, etc., which are used to convey more information.

8. A road digital marking system according to claim 1, characterized in that: The data processing system in the unmanned vehicle processes the acquired data, extracts characteristic information of the markings, imports the marking label data into the unmanned vehicle in advance, calls for comparison and positioning, and uses the marking patterns on both sides to detect and calculate which lane the vehicle is in on the road when the graphics are partially worn.

9. A method for recognizing digital road markings, comprising a digital road marking system according to any one of claims 1 to 8, characterized in that: The following steps are involved: S1: Use a binocular camera to capture the digital road marking image and use pixel positioning technology to determine the exact position of the digital road marking; S2: Process the acquired data, analyze the image data, and extract the characteristic information of the marking line; S3: Compare with the records in the map database to determine the current position of the vehicle, collect the operation reports of all road marking robots, and ensure that the position information of each digital road marking is accurately recorded; S4: Combining the real-time location information provided by the binocular camera and the records in the map database, the unmanned vehicle can maintain good navigation performance even when there is no satellite signal; S5: Feedback the recognized digital identification information and data to the control center, which will regularly check the validity and accuracy of the data in the database, update or delete invalid records in a timely manner, and support external import of new road marking data to adapt to the changes and development of urban roads.

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