156 results about "Road map" patented technology

The invention relates to the field of intelligent automatic driving, in particular to a multi-vehicle cooperative controllable confrontation test method based on a diffusion model. Comprising the following steps: S1, a diffusion model training stage: training a diffusion model based on real driving data, and learning vehicle behavior distribution through forward noise addition and reverse denoising to obtain fixed model parameters; s2, scene and multi-vehicle space-time modeling: fusing the road map, the lane topology and the vehicle state information, and constructing a space-time scene representation of multi-vehicle interaction as input of diffusion generation; s3, a diffusion generation mechanism based on adversarial guidance; s4, performing partial diffusion control and diversified confrontation generation; and S5, evaluating the authenticity and controllability of the multi-agent confrontation scene. Compared with the prior art, the method has the advantage that the authenticity, controllability and closed-loop consistency of multi-vehicle cooperative confrontation scene generation are obviously improved.

The invention provides a method and a device for determining an end-to-end perception decision regulation and control architecture, and belongs to the technical field of automatic driving. A first multi-modal data set is constructed based on a basic traffic signal image of an automatic driving scene, road map data and a basic driving rule; the second multi-modal data set is constructed based on dynamic traffic element image sequence data of an automatic driving scene, complex environment element image sequence data and complex driving rules, and the third multi-modal data set is constructed based on an automatic driving scene image, an automatic driving target and sensor time sequence data; and performing staged training on the multi-modal large model to obtain an end-to-end perception decision regulation and control architecture suitable for an automatic driving scene. A multi-modal large model is trained through a staged training strategy, basic element recognition, complex element recognition and decision training are gradually realized, the real-time performance of the model is enhanced, and the requirement of an automatic driving task for the real-time performance is met.

In various examples, a simulation platform generates a simulated driving environment by processing road map data to derive the location of wear-related visual artifacts for sections of a lane surface. Using map data, the simulation platform generates texture maps for aesthetic road rendering, which are used to apply textures to a 3D polygon topology mesh. The simulation platform generates visual artifacts representing the wear and tear of the road surface based on a calculation of one or more lane feature distances derived from the map data. The simulation platform calculates distances associated with reference line data derived from an image to render a texture of one or more lane features.The spacing is used to determine how the appearance of the texel is adjusted to include wear-related visual artifacts when displayed on a lane of the simulated driving environment.

The invention discloses a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation System) / map tightly integrated navigation positioning method and system based on road marking matching, and belongs to the technical field of navigation positioning, and the method comprises the following steps: acquiring priori road map data, foresight road image data, a GNSS original observation value and an INS original observation value; a semantic segmentation network is adopted to extract road marking semantic features in the foresight road image data, and a road marking feature instance is obtained; performing nearest neighbor search on the road marking feature instance and map elements in the prior road map data, and obtaining corresponding map matching observation based on a nearest neighbor search result; and coupling the GNSS original observation value, the INS original observation value and map matching observation to obtain a navigation positioning result. According to the method, a tight combination model based on GNSS / INS and map matching original observation values is provided, the positioning performance of a navigation system in a complex city scene is improved, and omni-directional pose constraint is provided for a vehicle.

The invention relates to the technical field of map making, in particular to a method and system for making a three-dimensional high-precision map containing road geometric elements, and the method comprises the steps: extracting original data from an original file through employing a user-defined analysis tool; preprocessing and checking the extracted original data to obtain core element data; and according to the core element data, generating a road three-dimensional model by adopting a space calculation model, and according to the core element data and a road design specification, performing derivative element calculation and generative three-dimensional element supplementation to form a three-dimensional lane-level road electronic map. According to the scheme, the three-dimensional high-precision map containing the road geometric elements can be manufactured, the map manufacturing efficiency is improved, the map precision is enhanced, and the cost is reduced.

Proximity-based surface texture generation for simulated environment systems and applications is disclosed. In various examples, a simulation platform generates a simulated driving environment by processing road map data to infer locations of wear-related visual artifacts for portions of a roadway surface. The simulation platform uses the map data to generate texture maps for aesthetic road rendering, which are used to apply texture to the 3D polygon topology mesh. The simulation platform generates visual artifacts representing use and wear of the roadway surface based on calculating one or more distances from roadway lane features derived from the map data. The simulation platform calculates a distance from the one or more roadway lane features associated with reference line data derived from the image to render the texture. The distances are used to determine how to adjust the appearance of texels to include wear-related visual artifacts when rendering wear-related virtual artifacts on the roadway of the simulated driving environment.

The invention relates to a method for determining at least one safety-critical peak region (R1, R2, R3) on the basis of an indicator value (Z) for statistical characterization of event descriptions detected by at least one vehicle in a location-related manner, wherein those inflow- and outflow-free road sections of which the section length is greater than or equal to a predetermined minimum section length are identified on the basis of a road map or navigation map. Identified road sections which adjoin one another are connected to form in each case a section chain (10) with a starting point (11) and an end point (12). Event descriptions comprising a geoposition (P1, P2) and at least one parameter of a vehicle environment model are detected by vehicles and transferred to an analysis system. The analysis system in each case assigns a nearest road network location (O1, O2) of a section chain (10) to a geoposition (P1, P2) of an event description and describes it by a longitudinal distance (L, L1, L2) in relation to the starting point (11) of the section chain (10). For at least one section chain (10), a profile of a density value (p) of event descriptions that is related to the longitudinal distance (L, L1, L2) from the starting point (11) is determined by means of a kernel density estimator of a predetermined bandwidth. The profile of the density value (p) is transformed, using local, bandwidth-related, Z standardization, into a Z profile (Z1, Z2) of a Z value (Z) which is mean-free in relation to bandwidth. In each case a region of road network locations (O1, O2) along the motorway-like road (100) which are connected along a section chain (10) between a peak beginning (Lmin) and a peak end (Lmax) and at which the Z value (Z) exceeds a predetermined threshold value (θ) is identified as a safety-critical peak region (R1, R2, R3).

The embodiment of the invention discloses a road element prediction method and device, equipment, a medium and a product, and the method comprises the steps: obtaining upstream and downstream roads adjacent to a target road, and constructing a road map with the target road as the center according to the topological relation between the target road and the upstream and downstream roads; taking roads in the road map as nodes, and obtaining static attribute information and track flow time sequence data of each node; generating node features in the road map according to the static attribute information of each node and the trajectory flow time sequence data to obtain a target road map; and carrying out spatial topology feature extraction on the target road map to obtain a representation vector of the target road map, and obtaining a prediction result of whether the road elements of the target road change or not according to the representation vector of the target road map. The technical scheme of the embodiment of the invention can be applied to the field of maps, the change of the road elements can be accurately predicted, and meanwhile, the timeliness and effectiveness of obtaining the change of the road elements are ensured.

An information processing apparatus comprises a processor configured to: acquire, from a first vehicle, lane topology information, estimated based on data acquired via a vehicle-mounted sensor of the first vehicle, indicating a lane topology of a road traveled by the first vehicle, and first information including position information corresponding to the lane topology information, associate, based on the first information, one or more pieces of the lane topology information acquired from a plurality of the first vehicles with each of a plurality of road segments included in a road map, and determine a lane topology for each of the plurality of road segments included in the road map, based on the one or more pieces of the lane topology information that is associated.

The invention provides a vegetable and fruit picking robot path planning method and system. The method comprises the following steps: firstly, constructing a global scene model represented by an octree; then collecting a quality path data packet of the risk local area, generating a local planner, generating a corresponding local area octree code for the risk local area, binding the local planner and the local area octree code as an experience record, and storing the experience record in a knowledge base; in the face of a new picking task scene, new local area octree codes are generated for the new local areas, and the most similar empirical records are retrieved from the knowledge base through recursive structure similarity calculation so as to determine a planning strategy of each new local area; and finally, constructing a discrete road map according to the starting point and the ending point of the new picking task, calculating a new local region sequence, forming a global planner, generating a collision-free continuous track from the starting point to the ending point by using the global planner, and delivering the collision-free continuous track to the robot for execution. The path planning efficiency, the success rate and the path quality of the robot in the complex picking environment can be effectively improved.

The present invention provides a safety distance warning method and system for a substation, which relates to the field of safety distance warning technology. The method includes using an equipment processing model to determine the substation high-voltage cable information and multiple live equipment information in the station based on the substation panoramic image information and the substation design drawing information; constructing an equipment map; processing the equipment map based on a first graph neural network to determine multiple electrical risk point information and multiple electrical safety point information; constructing a road map; processing the road map based on a second graph neural network to determine the operating route of the equipment to be operated; determining multiple line segments and the safe activity range of the boom of each line segment based on the crane boom information and the operating route of the equipment to be operated; and issuing an early warning to the equipment to be operated based on the operating route of the equipment to be operated and the safe activity range of the boom of each line segment. This method can accurately determine the safe activity range of the equipment operation.

To exactly recognize an object around a vehicle and to effectively reduce power consumption taken for recognition.SOLUTION: The present invention provides a vehicle control device which controls a vehicle to autonomously travel on a planned travel route. The device comprises: a space recognition data acquisition unit which acquires space recognition data from each of a plurality of sensors loaded on the vehicle; and a space recognition arithmetic unit which executes calculation for recognizing a surrounding space of the vehicle on the basis of the space recognition data. The space recognition arithmetic unit specifies each of a plurality of non-mobile objects associated with the travel route on the basis of the travel route and road map information, excludes non-mobile object data of a region concerning the non-mobile object from the acquired space recognition data, generates simplified space recognition data, and executes the calculation for recognizing the surrounding space of the vehicle on the basis of the simplified space recognition data.SELECTED DRAWING: Figure 1

The emergency braking area is estimated from the vehicle's position information. [Solution] A map providing server that estimates potential locations for sudden braking by acquiring vehicle information including the time progression of position information measured at predetermined time intervals from positioning sensors mounted on each of multiple vehicles traveling on a road or on portable terminals used by users in each vehicle, as well as vehicle speed information at the same time, and then calculates sudden braking areas by performing clustering processing on the potential locations for sudden braking and plots them on a road map.

A refuse vehicle includes an electric motor powered by a battery, a hydraulic pump driven by the electric motor, a hydraulic actuator powered by the hydraulic pump, and one or more processing circuits being configured to: determine a location of the refuse vehicle including a global position system coordinate, determine a position on a route map using the location, control the hydraulic actuator based on the position on the route map, determine a state of charge of the battery and a threshold for the state of charge below which operation of the electric motor, the hydraulic pump, or the hydraulic actuator is adjusted, and dynamically update the threshold based on the position on the route map or a weight of refuse in a refuse compartment.

The application discloses a kind of orchard inter-row road deviation identification method based on machine vision, belong to the technical field of agricultural machinery automation, comprising: carrying out orchard inter-row road segmentation;The image after segmentation is binarized, and road image processing coordinate system is established;In the segmented image of orchard inter-row road after binarization processing, select n rows, and obtain the y coordinate value of the left and right boundary points of the selected row in the orchard inter-row road;The center point of the selected n rows is calculated, and the average position of the road center point is calculated;The average position of the road center point calculated is added to the list;Judge the length of list D_List is equal to.Based on the segmented orchard inter-row road map, the road row is selected, and the road edge and road center point coordinate data of the selected road row are extracted, the Cox-Stuart trend detection algorithm is fused, and the path deviation problem of orchard operation mobile platform caused by orchard operation mobile platform equipment failure, GNSS signal loss and other reasons is solved.

The image relating to this design application is for monitoring the running status of an automated guided vehicle (AGV) in a transport facility, as well as various information such as abnormal conditions. The "Target Display Area" in the upper left of the image displays the AGV to be displayed, and the "Location Information Display Area" displays the route map and location information of the AGV as it moves. Furthermore, the route map displayed in the "Location Information Display Area" can be switched from a display of the entire route map, as shown in the "Image Diagram," to a display centered on the location of the AGV, as shown in the "Image Diagram Showing Changed State."

The invention provides an AR superposition method for a CAD road drawing and an unmanned aerial vehicle aerial video, and the method comprises the following steps: S1, converting the coordinates of the CAD road drawing into latitude and longitude data, and obtaining the elevation information of the drawing; s2, latitude and longitude data and elevation data are extracted from each frame of image of the unmanned aerial vehicle aerial video; s3, establishing connection between the CAD road drawing and the unmanned aerial vehicle aerial video by using the CAD road drawing, the unmanned aerial vehicle aerial video and common known information of the latitudes, longitudes and elevations of the CAD road drawing and the unmanned aerial vehicle aerial video, and realizing projection of the CAD road drawing on the unmanned aerial vehicle aerial video; and S4, finally, all the projected points are connected according to the previous connection mode on the CAD road drawing so as to restore the drawing. According to the AR superposition method of the CAD road drawing and the unmanned aerial vehicle aerial video, rapid and fully-automatic superposition is realized by using information contained in the CAD road drawing and the unmanned aerial vehicle aerial video, so that road construction progress supervision and progress reporting are facilitated.

The application provides a road map generation method, a road map annotation method, a computer device and a medium. The generation method comprises the following steps: acquiring lane line parameters output by a preset camera on a preset vehicle and dynamic parameters of nearby moving targets, and acquiring vehicle attitude parameters output by an inertial navigation device on the preset vehicle; determining a driving track of the preset vehicle based on the vehicle attitude parameters; determining a first lane center line of a road where the preset vehicle is located based on the driving track; generating road static data based on the lane line parameters, the vehicle attitude parameters and the first lane center line; and generating dynamic scene data based on the dynamic parameters of the nearby moving targets and the vehicle attitude parameters. According to the application, the lane line parameters output by the camera, the dynamic parameters of the nearby moving targets and the vehicle attitude parameters output by the inertial navigation device are used to determine the static road and the dynamic scene, so as to generate the road map, reduce the cost of generating the road map, and improve the efficiency.

Rating system (10) that determines a network connectivity performance road map (12), wherein the rating system (10) comprises: one or more back-end servers (20) in wireless communication with multiple vehicles (24) located in a geographical area (26) through a wireless communication network (28), wherein the multiple vehicles (24) collect multiple overall performance metrics of the wireless communication network (28); and one or more street map databases (54) in electronic communication with the one or more back-end servers (20), wherein the one or more street map databases (54) store a map data street graph of the geographic area (26) containing multiple nodes (60) connected by multiple edges (62), and one or more statistical measures corresponding to the multiple overall performance metrics of the wireless communication network (28) for each of the multiple nodes (60), and where one or more back-end servers (20) execute instructions to: Calculating one or more statistical measures corresponding to the multiple overall performance metrics of the wireless communications network (28) for each of the multiple edges (62) of the map data street graph of the geographic area (26); and Determining the network connectivity performance road map (12) of the geographical area (26) based on one or more statistical measures corresponding to the multiple overall performance metrics for each of the multiple nodes (60) and for each of the multiple edges (62), Receiving a route request containing a starting point and a final destination from one of the vehicles (24); Calculating distance costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12) in response to receiving the route request; Calculating time costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12), Combining the distance costs and the time costs together on the basis of a weight value assigned to the distance costs and a weight value assigned to the time costs to determine basic edge costs assigned to each of the edges (62) that are part of the network connectivity performance road map (12); and Determining one or more basic route plans by minimizing the basic edge costs assigned to each of the edges (62) located between the starting point and the final destination of the route requirement, characterized by the fact that the one or more back-end servers (20) further execute instructions to: Calculating relief costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12) in response to receiving the route request; and Calculating network live latency costs for each of the multiple edges (62) that are part of the network connectivity performance road map (12).

A device for evaluating road maps is proposed, wherein each road map has vertices and lines connecting the vertices, which represent the geometry of the roads. The device is configured to divide at least two road maps into respective tiles and to select a tile from each road map, wherein the geographical area of ​​the respectively selected tiles is identical. The device is further configured to compare the vertices and connecting lines in the selected tiles with one another and to determine a degree of discrimination between the road maps based on a result of the comparison.

The invention discloses a vehicle driving mode intelligent decision model construction method and system, and the method comprises the steps: obtaining sample data, which comprises the state and environment parameters of a vehicle during driving, a driving mode, an optimization target parameter and a dynamic constraint parameter; wherein the state and environment parameters comprise a geographic grid where the vehicle is located, and one or more of a loading interval, an environment temperature interval, a mileage interval, a maintenance record and a battery health state of the vehicle; the geographic grid is obtained by dividing the road map according to terrain based on preset terrain granularity; the optimization target parameter is obtained by counting a set target based on preset time or distance granularity; the intelligent decision-making model is obtained through training based on the training sample data, the intelligent decision-making model takes the state and environment parameters as input characteristics, the driving mode which enables the parameters of the target to be optimal and meets the dynamic constraint is output, and the optimal driving mode meeting the dynamic constraint can be automatically and individually decided for the vehicle according to the design target.

An information providing apparatus including a microprocessor and a memory storing a map information including a road map. The microprocessor is configured to perform: acquiring from an in-vehicle device, driving information including position information indicating the position of a vehicle detected by a first sensor and measurement error information indicating an occurrence of a measurement error output by a second sensor measuring an external environment of the vehicle, and further acquiring the map information from the memory; determining whether a snowfall has occurred in a predetermined region of the road map, based on the driving information and the map information; and outputting information in which a determination result is associated with the road map. The determining includes when recognizing that the measurement error has occurred while the vehicle is traveling in the predetermined region, determining that the snowfall has occurred in the predetermined region.

The invention relates to a four-dimensional road map imaging method and device, computer equipment and a computer readable storage medium. The method comprises the following steps: acquiring a current frame obtained by scanning an interventional instrument, and determining a candidate frame corresponding to the current frame; performing image reconstruction on a target frame in the candidate frames and the current frame to obtain a current reconstruction result; if it is determined that the interventional instrument is in an advancing state according to the current reconstruction result, fusing an increment part of the current reconstruction result with an original reconstruction result of the interventional instrument to obtain a target reconstruction result of the interventional instrument; and obtaining a four-dimensional road map of the interventional instrument according to the target reconstruction result. By adopting the method, the four-dimensional road diagram of the interventional instrument can be accurately reconstructed.

A vehicle driving control device is provided, which can continue automatic driving with excellent driving stability without hindering other vehicles even when the left and right dividing lines dividing the lane in which the vehicle is traveling cannot be identified. When traveling on a snowy road where the dividing lines cannot be identified, the driving lane of the vehicle M is estimated based on the vehicle position received by a GNSS receiver (14) and a high-precision road map (S1), the lateral position x_i of surrounding vehicles based on the vehicle M is calculated (S2), the driving lanes of the surrounding vehicles are estimated based on the lateral position x_i and the high-precision road map (S3), the offset amount i_offset of the surrounding vehicles is statistically calculated (S15), and when it is determined that the surrounding vehicles are offset toward the road shoulder (S16, S18), the offset amount d_offset for offsetting the vehicle M toward the road shoulder is calculated (S7), and the target travel path for automatic driving is reset (S9, S10).

The present invention belongs to the field of virtual reality redirection technology and provides a method and system for generating a virtual roadmap for a predictive redirection controller. The method comprises performing curved polygonal segmentation on a given virtual scene and calculating the shortest path tree for the user's current location in the scene using a shortest path tree algorithm. The given virtual scene is then skeletonized to obtain a polygonal skeleton. Based on the shortest path tree, the visible polygonal area of ​​the user's current location is calculated. Virtual waypoints are extracted based on the intersection of the visible polygonal area and the polygonal skeleton. A clothoid curve is used to fit the path between adjacent virtual waypoints. A determination is made as to whether the depth of the current waypoint meets a given depth. If not, the fitting is repeated using the next virtual waypoint as the user's current location until a virtual roadmap meeting the given depth is generated. The present invention can support virtual roadmap generation solutions for predictive redirection controllers in scenes with complex curved boundaries, addressing the limited applicability of existing predictive redirection controllers.

The application relates to the technical field of mobile robots, in particular to a traffic situation perception method and system, which comprises the following steps: in the process of a body-side roadside robot inspection, real-time acquisition of chassis encoder pulse data and multi-source perception data, construction of a traffic semantic vector based on the multi-source perception data and a global three-dimensional Gaussian road map; local incremental reconstruction updating of the global three-dimensional Gaussian road map based on the multi-source perception data, the chassis encoder pulse data and the traffic semantic vector, construction of a local perception blind area heat map based on the updated global three-dimensional Gaussian road map; construction of a semantic cost map based on the local perception blind area heat map, the multi-source perception data and the updated global three-dimensional Gaussian road map; construction of a local inspection path based on the local semantic cost map, movement along the local inspection path, and construction of a traffic situation perception result. The application improves the safety of robot autonomous movement and can output fine road perception information.

The application relates to a vehicle control method and device, an automatic driving equipment and a storage medium. The method comprises the following steps: acquiring vehicle positioning information of a target vehicle during driving, and querying road map information in front of the target vehicle according to the vehicle positioning information; identifying a damping mutation road surface in front of the target vehicle according to the road map information; acquiring steering torque compensation information corresponding to the damping mutation road surface; and performing steering control on the target vehicle on the damping mutation road surface according to the steering torque compensation information. The method can improve the steering control accuracy of the vehicle.

The application discloses a map updating method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: acquiring a road image collected by a roadside camera and detecting the road image to obtain a detection result of a motor vehicle area and an initial detection result of a non-motor vehicle parking area in the road image; determining a corrected detection result of the non-motor vehicle parking area in the road image according to the detection result of the motor vehicle area and the initial detection result of the non-motor vehicle parking area; performing boundary segmentation on the corrected detection result of the non-motor vehicle parking area to obtain an actual non-motor vehicle parking area in the road image; and updating a road map according to the actual non-motor vehicle parking area in the road image. The application updates the accurate area position of the non-motor vehicle parking area to the map based on the detection of the non-motor vehicle parking area by the roadside sensing device, so that the application can be used for navigation of the non-motor vehicle parking area and parking navigation of the automatic driving non-motor vehicle.

The invention relates to the technical field of artificial intelligence, and discloses a navigation method based on intelligent glasses. The method comprises the steps that a user starts navigation through a wake-up word and a voice instruction, after a destination is input, intelligent glasses automatically recognize and search a path result, the path result is broadcasted through voice for the user to select, the intelligent glasses obtain a high-precision virtual blind sidewalk map of a city where the user is located, and an optimal path is generated through a path planning algorithm. The intelligent glasses convert the path distance into the individualized step number of the user, start the environment perception and path correction functions, optimize the navigation route in real time, and enhance the direction perception and improve the navigation accuracy and accessibility by adopting a voice and vibration dual feedback mode. According to the method, high-precision positioning, intelligent path correction, multi-mode feedback and path presentation with the step number as the unit can be realized.

Navigation method, wherein a navigation device calculates a navigation route (20) from a starting location to a destination, wherein - a computing unit obtains information about at least one temporally and spatially variable event (1); - the computing unit estimates a temporal-spatial course of the event (1) for a future time horizon and stores it as a dynamic area of ​​interest (2); - the navigation device receives the dynamic area of ​​interest (2), determines a starting location and a starting time and calculates the navigation route (20) from the starting location to the destination, wherein the destination lies within the dynamic area of ​​interest (2) or an observation point (3) is set as the destination from which the event (1) is observable; - the computing unit divides a digital road map (6) into a plurality of polygons (7), wherein map information is assigned to each polygon (7), so that the polygons (7) represent the digital road map (6) in the form of a dynamic graph (8) and the computing unit maps the dynamic area of ​​interest (2) onto the dynamic graph (8), wherein the dynamic graph (8) comprises a plurality of nodes (9), wherein each polygon (7) is assigned a node (9), characterized in that - height information (10) is assigned to the nodes (9) of the graph (8) as map information, wherein the height information (10) describes the topographical height of the terrain and / or the geodetic height of an object located in the respective polygon (7), and the computing unit calculates a height difference to the respective neighboring nodes (11) for each node (9) of the graph (8), wherein a clear view to a neighboring node (11) exists if the height to the neighboring node (11) remains the same or decreases; and wherein - the computing unit determines a node chain (12) emanating from the dynamic area of ​​interest (2) with a clear view of the dynamic area of ​​interest (2) and defines a node (9) of the node chain (12) as an observation point (3).