244 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.

The invention discloses a road scene space rapid investigation system combining RTK and image reconstruction, relates to the technical field of road scene space investigation, and is used for solving the problem of poor road mapping splicing effect. According to the method, an RTK track in road inspection is collected and synchronized with an image frame, after abnormal points are removed, continuous control points are extracted to construct a road topology skeleton, a space is divided into a plurality of mapping units based on the control points and direction vectors, redundant overlapping areas are set, and a mapping task package with structural continuity is generated; a road structure area in an image is extracted through semantic segmentation and edge detection, a structure mask is constructed and projected to a three-dimensional space, and point cloud density enhancement and reconstruction optimization are guided, so that block boundary structure anchor points are further identified, local rigid body registration is completed, and a global error minimization model is constructed. The posture consistency and the space continuous splicing of all the image blocks are realized, and the exploration efficiency of the road scene space is improved.

Various embodiments include a backend for an object updating system for removing objects present in a digital road map comprising: a memory storing a set of instructions; and a processor in communication with the memory. The digital road map is stored in the memory. The set of instructions, when loaded and executed by the processor, cause the processor to: receive a path and environmental data captured along this path from a vehicle; recognize objects in the environmental data; and remove an object from the digital road map if the object is not recognized in the environmental data.

The invention belongs to the technical field of virtual reality redirection, and provides a method and system for generating a virtual road map of a predictive redirection controller, and the method comprises the steps: carrying out the curve polygon subdivision of a given virtual scene, and calculating a shortest path tree of a current position of a user in the scene through a shortest path tree algorithm; performing skeleton processing on the given virtual scene to obtain a polygonal skeleton; calculating a visible polygonal area of the current position of the user based on the shortest path tree; extracting virtual road points according to the intersection points of the visible polygonal area and the polygonal skeleton; fitting a path between adjacent virtual road points by using a clothoid; and judging whether the current road point depth meets the given depth or not, and if not, repeatedly fitting the next virtual road point as the current position of the user until a virtual road map meeting the given depth is generated. According to the method, a prediction redirection controller virtual road map generation scheme of a curve boundary complex scene can be supported, and the problem that the application range of a prediction redirection controller in the prior art is small is solved.

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.

A vehicle traveling information analysis device comprises: a reception unit that receives, from a plurality of vehicles, traveling information which includes location information and time information; a traveling information recording unit that stores, in a traveling information storage unit, the traveling information received from the reception unit together with identification information of vehicles; an analysis condition input unit that accepts, from a user, designation of an analysis condition which includes information pertaining to an analysis target road; an extraction region setting unit that sets extraction regions each having a predetermined area to a respective plurality of locations on a road map on the basis of the designated analysis condition; and a vehicle identification information extraction unit that extracts identification information of a vehicle having a record of traveling information in all the extraction regions which have been respectively set to the plurality of locations on the road map.

A method of constructing a map based on a large model, a vehicle control method, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence technology, in particular to fields of computer vision, deep learning, large model and generative model technologies. The method includes: acquiring an associated-region lane attribute and an image to be detected, which is collected by an onboard sensor and represents a road region to be detected; constructing a target prompt information based on the associated-region lane attribute; and processing the target prompt information and the image to be detected by using the large model to obtain a regional road map for the road region to be detected. The associated-region lane attribute corresponds to an associated road region, and the associated road region and the road region to be detected meet a predetermined similarity condition.

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.

A computer-implemented method is provided for determining a navigation route between a start point and a target point. The method includes setting the start and target points, and then generating a road map with a road graph having plural edges between the star and target points representing traversable route portions. The generated road map also has nodes that interconnect the adjacent edges. The road map is generated from geospatial data retrievably stored in a database. The method proceeds by generating an emotion map layer by a machine learning model that is trained to predict, based on static and / or dynamic contextual input data for each of the edges, the likely emotions of a driver as they traverse the relevant edge and generate emotion weightings in the emotion map layer. The method then calculates the navigation route by the emotion map layer with the emotion weightings obtained in the previous step.

The invention discloses an automatic driving online vectorization map construction method, model and equipment combined with high-precision positioning, and the method comprises the steps: constructing a high-quality beyond-visual-range online vectorization road map through the mutual enabling of multi-modal information of a vehicle-end around-view camera, a cloud low-orbit satellite and the like; the problem of vehicle end sensing failure in complex scenes such as large crossroads, high-speed confluence areas and canyon tall buildings is solved. The method comprises the following steps: firstly, fusing a streaming strategy and a stacking strategy to improve the time sequence modeling capability, and enhancing the characterization capability by using global information of a height dimension and a width dimension; secondly, cloud information and vehicle end information are deeply fused based on an attention mechanism, and the perception performance is improved. And finally, the fusion features of different scales of the cloud end and the vehicle end are efficiently decoded based on hierarchical perception aggregation of adaptive query, and according to different scales of map instances, adaptive query dynamically interacts with the fusion features of different resolutions and focuses on key target instances, so that the convergence efficiency and the construction effect of map elements of different scales are improved.

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).

To provide a driving evaluation apparatus for appropriately evaluating the driving skill of a driver.SOLUTION: A driving evaluation apparatus includes: an error information generation section 12 that generates steering error information, which is information on an error of an actual measured value with respect to a predicted value of steering, on an evaluation target road identified by road map information on the basis of traveling information of a plurality of vehicles acquired by an information acquisition section 11; and a driving evaluation section 13 that evaluates a driving skill of a driver of an evaluation target vehicle on the basis of a difference between a reference error value determined by the generated steering error information of the plurality of vehicles for the evaluation target road within a predetermined period and a target error value determined by the steering error information, which is generated by the error information generation section, of the evaluation target vehicle for the evaluation target road within the predetermined period.SELECTED DRAWING: Figure 4

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.

The invention provides a vehicle trajectory planning method and device, a vehicle and a storage medium, and the method comprises the steps: obtaining an image of a surrounding environment of a target vehicle, historical trajectory information of an object in the surrounding environment, and a road map, carrying out the fusion coding according to the historical trajectory features of the object, the map features of the road map, and the image features of the image, and obtaining a target trajectory; the method comprises the steps of obtaining a fusion feature according to current positioning information of a target vehicle, the position of each pixel point in an image, a set position in a road map and the fusion feature, decoding according to the current positioning information of the target vehicle, the position of each pixel point in the image, the set position in the road map and the fusion feature to obtain a target decoding feature, and predicting a trajectory according to the target decoding feature to obtain a trajectory planning result of the target vehicle. Fusion coding is carried out based on the trajectory features, the map features and the image features, so that association relationships among different types of features are extracted by fusion coding, trajectory prediction is carried out based on fusion coding, and the accuracy of trajectory prediction is improved.

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 utility model discloses a cultural and creative entity ticket which comprises a token main body, one side surface of the token main body is provided with a groove, the groove is buckled with a cover plate, the interior of the groove is divided into two placing grooves through a partition plate, and one placing groove is provided with an electronic ticket; the other placing groove is provided with a power supply module, a radio frequency tag identification module, a control processing module and a voice broadcast module, and the power supply module supplies power to the radio frequency tag identification module, the control processing module and the voice broadcast module; a sinking groove is formed in the other side surface of the token main body; and a scenic spot route map or a scenic spot marker embossment is arranged in the sinking groove. The electronic ticket and the scenic spot explanation voice function are integrated on the token, in addition, the token body is further provided with the scenic spot route map or the scenic spot marker embossment, the token can be tied on the waist or held by a hand, the token is different from an existing paper ticket, the touring experience feeling, the use feeling and the emotional value of tourists are improved, and the tokens can be collected for dwell.

Aspects of the present disclosure provide for the identification of parkable areas. In one example, observations of parked vehicles can be identified from stored data. The observations can be used to determine whether a subpart of an edge of a road map corresponds to a parkable area. In some examples, the edge can define a drivable area in the road map. Additionally, map information is generated based on a determination of whether a subpart of the edge corresponds to a parkable area.

An evaluation system for determining a network connectivity performance road map includes one or more backend servers in wireless communication with a plurality of vehicles located in a geographic area by a wireless communication network and one or more road map databases in electronic communication with the one or more backend servers. One or more road map databases store a map data road map of a geographic area, the map data road map comprising a plurality of nodes connected by a plurality of edges, and one or more statistics of a plurality of overall performance metrics of the wireless communication network corresponding to each of the plurality of nodes. The one or more backend servers determine a network connectivity performance road map for the geographic area based on statistics of the plurality of overall performance metrics corresponding to each of the plurality of nodes and each of the plurality of edges.

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.

To improve a technique for recommending a traveling lane to a driver of a vehicle.SOLUTION: A navigation device is mounted on a vehicle and guides a route to be traveled by the vehicle. The navigation device includes a position information acquisition section, a storage section, a display section, and a control section. The position information acquisition section acquires current position information on the vehicle. The storage section stores road map information including information on a lane. The display section is configured to display one or more lanes of a road on which the vehicle travels, on the basis of the road map information. The control section determines a recommended lane in which traveling of the vehicle is recommended on the basis of the road map information and the route, determines a traveling lane in which the vehicle is traveling on the basis of the road map information and the current position information, and causes the display section to display the recommended lane and the traveling lane in different manners.SELECTED DRAWING: Figure 1