11 results about "Road sign recognition" patented technology

The invention relates to the technical field of auxiliary driving, and discloses a deep learning-based road signboard recognition method, which comprises the following steps of: acquiring a road traffic video sequence stream in a vehicle driving process; inputting the road traffic video sequence stream into a deep learning detection framework based on improved YOLOv11 for initial positioning to obtain an initial positioning result of the road signboard; performing cross-frame target tracking on the initial positioning result of the road signboard through an improved Kalman algorithm to obtain a road signboard identification result with a motion track; and displaying the identification result of the road signboard on a vehicle-mounted head-up display of the vehicle. According to the road signboard identification method and system based on deep learning provided by the invention, a scheme based on deep learning and optimized Kalman filtering is adopted, traffic signboards in a complex road traffic environment are identified, and a perfect auxiliary driving system is established, so that key signboard information can be quickly and accurately found in the complex road environment; and a driver is assisted to make correct judgment.

A road sign recognition method and apparatus, a vehicle, and a storage medium. The method comprises: acquiring a road environment image, which is captured in real time by an image collection apparatus with respect of a road environment where a vehicle is located, and vehicle position information of the vehicle that is collected by a positioning sensor in real time (S101); extracting a road sign to be recognized that is contained in the road environment image, and determining whether the road sign to be recognized meets a preset determination condition (S102); if the road sign to be recognized meets the preset determination condition, using, as a target recognition result of the road sign to be recognized, the meaning and type of a known road sign matching the road sign to be recognized (S103); and if the road sign to be recognized does not meet the preset determination condition, on the basis of the road sign to be recognized and the vehicle position information combined with a pre-trained vision-language model, determining the target recognition result of the road sign to be recognized (S104).

The embodiment of the invention provides a road sign identification method, system and device based on point cloud data and a medium, and belongs to the technical field of road sign automatic identification. The method comprises the following steps: acquiring initial point cloud data and an initial laser image collected by a target vehicle under a target road; performing anomaly detection on the initial point cloud data by using the density distribution information to obtain target point cloud data of the target road; performing automatic clustering on the target point cloud data to obtain a target clustering center and associated point cloud data of the target clustering center; determining initial position information of the associated point cloud data in the initial laser image by using the associated point cloud data according to a mapping relationship between the target point cloud data and the initial laser image; determining a target feature corresponding to the initial road identifier, and performing edge recognition in the initial laser image according to the initial position information and the target feature to obtain target edge information of the initial laser image; and performing road identification identification according to the target edge information to obtain target identification information of the target road.

The application relates to the underground mine unmanned vehicle positioning technical field, in particular to an underground mine environment-based unmanned vehicle repositioning device and system based on road sign recognition, which comprises a bottom plate, the upper surface of the bottom plate is symmetrically provided with transport tracks, the upper surfaces of the two transport tracks are provided with sign position acquisition assemblies in a rolling mode, the sign position acquisition assembly comprises a plurality of roller wheels rolling installed on the upper surfaces of the transport tracks and L-shaped mounting plates fixedly sleeved on the outer surfaces of the roller wheels, the upper ends of the plurality of L-shaped mounting plates are fixedly connected with a machine seat, the upper surface of the machine seat is provided with an image processing module, and the surface of one end of the image processing module is provided with a controller, which is beneficial to the underground mine environment-based unmanned vehicle repositioning based on road sign recognition, can efficiently and accurately identify various traffic signs on the road, including text type traffic signs and other graphic signs, and can identify the approximate position of the vehicle in the mine.

The application discloses a roadside map construction method and device and electronic equipment. The method comprises the following steps: acquiring a current road image collected by a roadside camera, and identifying the current road image by using a preset image recognition model to obtain a road sign recognition result and a vehicle tracking result; determining first lane information of a road section where the roadside camera is located according to the road sign recognition result; determining second lane information of the road section where the roadside camera is located according to the vehicle tracking result; and constructing a roadside map of the road section where the roadside camera is located according to the first lane information of the road section where the roadside camera is located and the second lane information of the road section where the roadside camera is located. The application combines the road sign recognition result and the vehicle tracking result obtained based on roadside perception to determine the lane information of the road section where the roadside camera is located, thereby constructing a roadside map that is more in line with the use requirements of the roadside, and better assisting the perception tracking and path planning of the roadside.

This disclosure provides a road sign recognition method, system, train, and electronic device, which can be applied to the field of road sign recognition technology. The method includes: recognizing a road sign image acquired by a vehicle's image acquisition device using a first recognition model to obtain a first recognition result, the first recognition result including first location information; recognizing the road sign image using a second recognition model when at least one of the vehicle, the road sign image, and the first recognition result meets predetermined conditions, obtaining a second recognition result, the second recognition result including second location information; converting the second location information into estimated location information at the current time stamp based on the input timestamp of the road sign image input to the second recognition model and the current timestamp; and processing the first recognition result and the second recognition result according to the intersection-union ratio (IUU) between the estimated location information and the first location information to obtain a target recognition result for the road sign image.

The application provides a vehicle automatic driving navigation method and system based on road sign recognition, and relates to the field of automatic driving, which comprises the following steps: acquiring image data and point cloud data of road signs, performing alignment processing on the image data and the point cloud data to obtain fused sign features, and extracting preliminary position information; acquiring actual position information of the road signs, comparing the actual position information with the preliminary position information to obtain offset vector features; performing angle correction processing on the image data according to the visual features and the offset vector features to obtain sign posture information, and determining the change trend of the sign posture information; acquiring a vehicle driving track, adjusting the vehicle driving track according to the change trend and the offset vector features to obtain a predicted driving track, and performing vehicle navigation based on the predicted driving track. The application realizes real-time precision and dynamic updating of vehicle automatic driving.

The present disclosure relates to a system architecture, a transmission method, a vehicle, a medium and a chip for road sign recognition, belonging to the field of vehicle communication. The system architecture comprises: a whole vehicle central computing domain controller, a plurality of vehicle-mounted control devices connected with the whole vehicle central computing domain controller through Ethernet; a road sign recognition service providing a calling interface for calling; the whole vehicle central computing domain controller is used for checking the calling parameters sent by a first vehicle-mounted control device to the road sign recognition service, and forwarding the calling parameters to a road sign recognition domain controller if the checking is passed, and forwarding the return parameters sent by the road sign recognition service in response to the calling parameters to the first vehicle-mounted control device, so that the first vehicle-mounted control device obtains the road sign recognition result in the return parameters. The safety of the road sign recognition result transmission under the service-oriented architecture is effectively ensured, and the acquisition of illegal road sign recognition results is avoided.

The application discloses a traffic road sign recognition multi-task model inference optimization method based on operator optimization and related equipment thereof. The method comprises the following steps: acquiring a traffic road condition image and inputting the traffic road condition image into a traffic road sign multi-task recognition model; when a backbone network extracts features of the traffic road condition image, for each type of operator operated by the backbone network, an operator acceleration interface matched with the operator is called to execute the operation of the operator, and a traffic road sign global feature map is obtained; when tasks of each task branch are executed based on the traffic road sign global feature map, for each type of operator of each task branch, a task operator acceleration interface matched with the operator is called to execute the operation of the operator, and a task result of the task branch is output. As can be seen, when the multi-task model performs inference, the operator acceleration interface of the embedded microcontroller is called, so that the embedded microcontroller plays a role in accelerating the inference performance of the traffic road sign recognition multi-task, thereby improving the recognition efficiency of the multi-task model.

The embodiment of the invention provides a cross-language driving cooperative control method and device, a medium and a product, and relates to the technical field of intelligent driving. The method comprises the following steps: performing intention analysis on a multi-language instruction input by a user to generate a first driving instruction; loading a local traffic rule based on the position of the vehicle, and correcting the first driving instruction into a second driving instruction by using the local traffic rule and a preset multi-language road sign recognition model; and correcting the second driving instruction into a target driving instruction according to shared information sent by a motorcade to which the vehicle belongs. According to the scheme of the invention, through intention analysis, localization correction and motorcade cooperation, accurate conversion from a general instruction to a scenarized driving decision is realized, and the problem that an existing intelligent driving system based on a large language model lacks comprehensive adaptation capability to a multi-language environment, cross-cultural differences and dynamic localization rules is solved. And the driving requirement in a transnational scene cannot be met.

A driver assistance system is provided with an accelerator grip turnably operable by a rider to accelerate or decelerate a vehicle which is a saddle-type vehicle, an accelerator position sensor that detects a turning operation of the accelerator grip, an automated cruise controller that automatically controls a vehicle speed of the vehicle or a following distance on the basis of a set vehicle speed, a road sign recognizer that recognizes a regulation speed stipulated for a road on which the vehicle is traveling, and a vehicle speed specifier that, in response to the accelerator position sensor detecting a turning operation in a predetermined pattern while the automated cruise control based on the set vehicle speed is in progress, changes the set vehicle speed on the basis of a recognition result from the road sign recognizer.