174 results about "Road edge" patented technology

The invention discloses a multi-target road transportation path planning method and system based on multiple parameters A * and NSGA-II, and belongs to the technical field of road transportation path optimization. The method comprises the following steps: constructing a large-scale road network directed graph structure; establishing a satellite orbit model and a risk distribution model, calculating a dynamic risk value of a roadside, and forming dynamic road network data; a three-stage initialization strategy is adopted to generate an initial population, transportation time and reconnaissance risks are taken as double targets, evolutionary optimization is carried out through an NSGA-II algorithm, and a Pareto optimal path set is output. The system comprises a corresponding road network module, a risk module and a planning module. According to the method, the technical problems of multi-target conflict, low initial population quality and satellite risk avoidance of a traditional method are solved, and the timeliness, the concealment and the algorithm efficiency of path planning are remarkably improved.

The invention belongs to the field of urban traffic management, and provides a hierarchical dynamic routing system and method for a computing power-energy fusion network, and the method comprises the steps: dividing a fusion network graph into a plurality of region sub-graphs, and dividing a path table and a connection point path table based on each region sub-graph; monitoring the running states of the road, the edge computing node and the charging station in real time, and predicting the road congestion intensity, the edge computing node queuing estimation information and the charging constraint; and determining a candidate path set in the partition path table and the connection point path table according to an online request of the vehicle, screening each candidate path in the candidate path set based on the road congestion intensity, the edge computing node queuing estimation information and the charging constraint, and determining an optimal path. According to the method, online retrieval is converted into rapid combination and evaluation of small candidate sets from full-graph traversal; traffic, energy and computing power are incorporated into the same decision framework, and systematicness deviation caused by evaluation of the future at present is avoided.

The utility model relates to the technical field of expressway guardrails, in particular to an expressway anti-collision guardrail which comprises a fixed stand column, a movable stand column and an anti-collision device. The wave-shaped beam plates are continuously arranged along the edge of the road and are parallel to the fixed stand columns; and the horizontal connecting beam stretches across the corrugated beam plate and the fixed stand column, one end of the horizontal connecting beam is rotationally connected with the corrugated beam plate through a rotary connecting sleeve, and the other end of the horizontal connecting beam is rotationally connected with the fixed stand column through a buffer connecting sleeve. Through the arrangement of the rotary connecting sleeve and the buffer connecting sleeve, the wave-shaped beam plate can generate plastic deformation to absorb energy during collision and can also translate towards one side of the fixed stand column, and the translating motion drives the buffer connecting sleeve to rotate around the fixed stand column, so that the fixed limiting block sequentially collides with the limiting buffer plates; therefore, the energy absorption capability of the whole system is greatly enhanced.

Embodiments of the present disclosure relate to ground surface estimation using localized surface fitting. A three-dimensional (3D) surface structure (e.g., a road surface profile) may be estimated using a nonlinear optimization to fit height values to (e.g., accumulated, bias-corrected) LiDAR detections (e.g., sampled in localized regions along one or more predicted trajectories). For example, LiDAR data (e.g., detected 3D point clouds) may be ego-motion compensated, corrected for measurement bias, accumulated, and sampled along one or more predicted trajectories, and the height of each trajectory point may be fitted to the heights of the corresponding sampled points using a nonlinear optimization. As such, the resulting road surface profile (e.g., modeled along the wheel track(s)) may be provided to an adaptive suspension control system to modulate the damping characteristic of the suspension system to counteract indentations (e.g., potholes) or protrusions (e.g., speed bumps) represented in the road surface profile.

The application relates to a kind of road information automatic extraction methods based on multi-modal remote sensing image, comprising: obtaining multi-modal remote sensing image training sample set, including multiple groups of multi-modal remote sensing image training sample, each group of multi-modal remote sensing image training sample contains multi-modal remote sensing image and corresponding road label image;Multi-modal remote sensing image includes optical remote sensing image and SAR image;Road label image includes road surface segmentation label and road edge label;Initial road extraction model is constructed, and is trained using multi-modal remote sensing image training sample set until loss function converges, obtains training road extraction model;Based on training road extraction model, the input multi-modal remote sensing image data is extracted on road, and vectorization is carried out, and road data is obtained.The application solves the problem of insufficient road extraction precision in the prior art for remote sensing image road extraction task, improves the accuracy and connectivity of remote sensing image road extraction result.

The invention provides a municipal road BIM edge computing real-time control method and system based on an OPC UA protocol, and the method comprises the steps: monitoring the communication state of each node in an edge computing network and the continuity of sensor data, recognizing a data missing region, and determining the specific position of the data missing region; according to the position of the data missing area, a depth-first search algorithm is adopted to traverse the connection relation of adjacent nodes, and a fault boundary corresponding to the data missing area is constructed; and extracting redundant storage data from the fault boundary, analyzing whether the coverage capability of the redundant storage data meets the requirement or not, and if so, filling the data missing region to generate a preliminary repair result.

The invention discloses a system and method for adaptively controlling the hedging function of a sanitation cleaning vehicle, and the method comprises the steps: a vehicle-mounted intelligent terminal senses whether there is a pedestrian or a target distance of the type of a pedestrian at two sides of the vehicle through a visual sensor disposed on the vehicle; calculating the transverse distance and the longitudinal distance between the vehicle and the traveler, the rider, the road edge and the guardrail according to a visual algorithm; according to the transverse distance of the pedestrian or the riding pedestrian and the opposite-punching distance table corresponding to the rotating speed, a control message is sent to the uploading control screen, the uploading control screen issues a control instruction to the uploading controller, the uploading controller executes the control instruction, and the opposite-punching operation coverage distance and the opposite-punching function are automatically adjusted in real time. The hedging operation process of the cleaning vehicle is optimized, the intelligent level is improved, the loading controller receives a hedging self-adaptive control command of the vehicle-mounted intelligent terminal through the loading control screen, the left and right hedging electric control ball valves are controlled to be opened or closed in real time, and finally real-time dynamic control over the hedging distance is achieved.

The utility model relates to the technical field of road construction, in particular to a spraying mechanism of a line drawing robot, which comprises a frame, a running device, a main spraying device and a side spraying device, the running device comprises running wheel sets arranged on two sides of the frame, the main spraying device is arranged on the frame, and the side spraying device is positioned on the outer side of the running wheel sets. In practical application, spraying operation of road edges, narrow sidewalk boundaries or parking space lines in parking lots is often difficult to efficiently complete in a traditional mode due to space limitation. The side edge spraying device can be tightly attached to the road edge, so that the spraying range is flexible, and the spraying precision is precise. The side edge spraying device improves the operation efficiency and the spraying quality. And the time and cost consumption caused by manual adjustment or repeated spraying for covering the narrow edge area is reduced. According to the utility model, the limitation of the traditional spraying mode in narrow space operation is solved, and the spraying device has efficient and accurate spraying capability.

The tunnel pavement foreign matter intelligent detection early warning system comprises a processing terminal, the processing terminal is electrically connected with a clock circuit, the input end of the processing terminal is connected with a plurality of distance measuring terminals, and the output end of the processing terminal is connected with a plurality of alarm terminals; the distance measuring terminal comprises a distance measuring instrument and a reflecting plate which are oppositely arranged on the road edge in the tunnel, and a plurality of distance measuring terminals are arranged on the road edge at intervals in the length direction; the alarm terminal comprises an alarm lamp arranged at the top of the tunnel, and the alarm lamp is located on the side, close to the tunnel entrance, of the adjacent distance measuring terminal. According to the device, the distance measuring terminal is used for detection, when the reading of the distance measuring terminal is separated from a threshold value and the timing of the clock circuit exceeds a certain time period, the existence of a foreign matter can be judged, a driver can be reminded in an alarm mode, and the situation that the foreign matter does not exist in time and an alarm is caused by vehicle parking is avoided; and positive feedback can be generated, namely, a subsequent driver is reminded to slow down, and a negative effect cannot be caused.

The embodiment of the invention provides a road edge detection method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: segmenting original point cloud data collected by a laser radar according to a preset segmentation threshold value, and obtaining local point cloud data; performing sampling processing on the local point cloud data according to a preset three-dimensional voxel grid size to obtain sampling point cloud data; classifying three-dimensional points in the sampling point cloud data through a point cloud convolutional neural network model, and determining to obtain curb three-dimensional points; according to the curb three-dimensional points, curb marker facades are obtained; and determining curb position information according to the facade of the curb marker. In this way, the original point cloud data is segmented and sampled to obtain the sampling point cloud data, the point cloud convolutional neural network model is used to determine the facade of the road edge marker for the sampling point cloud data, and the position information of the road edge is determined according to the position information of the road edge marker, so that the stability and precision of the road edge detection result can be improved.

The application provides a remote sensing image road edge detection method and system, and the method comprises the following steps: extracting a predicted candidate vertex set Q from a road image; selecting a candidate vertex from the predicted candidate vertex set Q as a predicted starting vertex v i *, generating a local feature input agent model thereof, outputting a next predicted vertex v i+1 *, and updating a generated road edge graph g i+1 * based on the next predicted vertex v t *, continuing prediction until the road edge graph g t stops growing; and traversing each candidate vertex in the predicted candidate vertex set Q, performing prediction based on the agent model to obtain a road edge detection result. The method mainly adopts an end-to-end iterative graph generation method, can directly obtain linear object information, is less affected by segmentation performance, can solve the influence caused by partial occlusion, and can obtain vector data of the road edge without complicated post-processing operations.

The utility model belongs to the technical field of road traffic stone transportation, and particularly relates to road traffic stone transportation equipment which comprises a frame. The two ends of the vehicle frame are rotationally connected with walking wheels. The middle part of the frame is fixedly connected with a bearing rod; a pair of hanging cables is mounted at one end, close to the frame, of the bearing rod; a handrail is fixedly connected to one end, far away from the frame, of the bearing rod; the bottom ends of the pair of lifting cables are fixedly connected with a bearing plate; the middle part of the bearing plate is in sliding connection with a connecting seat; the two sides of the connecting base are rotationally connected with clamping plates through torsional springs. The bottoms of the opposite sides of the pair of clamping plates are rotationally connected with extrusion plates. Pulleys are rotationally connected to the two sides of the bearing plate; by means of the structure, the road edge stone can be lifted and transported and transferred in a lever mode, physical output of operators is reduced, and transportation convenience during construction of the road edge stone is improved.

The invention relates to the technical field of side pedals of vehicles, in particular to a high-performance telescopic electric side pedal control method and device. According to the method, within the preset time period after the vehicle door is opened, the distance measurement data of each measurement point on the side pedal connecting plate at each monitoring moment is obtained, all suspected obstacle influence time periods and obstacle influence parameters of each measurement point are obtained, and all obstacle influence time periods are screened out; and analyzing and acquiring an obstacle confidence coefficient at each measuring point in combination with a time interval between adjacent obstacle influence time periods at each measuring point in a time sequence, so as to control the extension and retraction of the electric side pedal. By monitoring the abnormal continuous condition of the distance measurement data at each measurement point, the possibility that the electric side pedal is influenced by a fixed obstacle such as a road edge is comprehensively evaluated, the influence of other random interference factors is reduced, the evaluation accuracy on the influence of the telescopic environment obstacle of the electric side pedal is improved, and then the control effect on the electric side pedal is improved.

The invention relates to a method for recognizing road categories and determining a speed zone for a motor vehicle (10) based thereon, comprising the steps of: acquiring data from an exterior area (50) of the motor vehicle (10) by means of a sensor device (40); analyzing a surface (60) of a roadway traveled on by the motor vehicle (10) and an adjacent roadway environment including the roadway boundary, based on the acquired data from the exterior area (50) by means of a control device (30), for a feature that is characteristic of the surface (60) and for the presence of road edge design elements (70) in the area of ​​the roadway environment;Rule-based determination of the speed zone by the control unit (30) based on the characteristic feature of the surface (60) and / or on the basis of existing roadside design elements (70), wherein the characteristic feature of the surface (60) includes at least the surface structure. The invention further relates to a device (20) comprising a control unit (30) and a sensor device (40) designed to carry out the method according to the invention or possible embodiments of the method according to the invention, as well as a motor vehicle (10) with such a device (20).

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 invention discloses a convergence point intelligent navigation function degradation judgment method, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining the current lane width at the current position of a target vehicle and the preview lane width at a preset preview distance in front of the target vehicle; determining width change information based on the current lane width and the preview lane width; acquiring a left side lane line variance and a right side lane line variance of the target vehicle in the current lane; determining variance information based on the left side lane line variance and the right side lane line variance; acquiring road edge information of a current lane; and when the width change information, the variance information and the road edge information meet a preset degradation condition, controlling an intelligent navigation function of the target vehicle to perform degradation operation. Accurate recognition and function degradation of the confluence point scene are realized, and the driving safety and the system robustness are improved.

The application is suitable for the field of intelligent traffic technology, and provides a positioning method, device and system based on a laser radar, a vehicle and a computer readable storage medium. The method comprises the following steps: obtaining coordinate values of at least two targets arranged on a second working vehicle, wherein the coordinate values of each target are the same as the coordinate values of a prism arranged on the target, and the coordinate values of the prism are obtained by tracking the prism with a total station; obtaining a first distance between a laser radar and the target, wherein the laser radar is arranged on a first working vehicle; and determining first pose information of the first working vehicle according to the first distance of at least two targets and the coordinate values of the targets. The application does not depend on GPS signals, and does not need to configure mobile base stations, laser range finders, infrared thermometers and electronic fences and other equipment, and does not need to refer to road ditches or road edges, and has high flexibility. The positioning accuracy of the automatic total station and the laser radar is high.

The application provides a method, device and equipment for safety protection of edge cleaning, and a readable storage medium. The method comprises the following steps: in the process of edge cleaning of a self vehicle, a time difference between a time point before a collision between the self vehicle and a road edge and a start time point of a current prediction period is calculated as an available operation duration of the current prediction period according to a self vehicle structure parameter and a self vehicle state parameter obtained at the start time point of the current prediction period; and a safety measure to be performed in the current prediction period is determined according to a size relationship between the available operation duration of the current prediction period and a preset threshold. Through the application, effective safety protection is provided for edge cleaning of an unmanned sanitation vehicle, so as to reduce the risk of collision between the unmanned sanitation vehicle and the road edge, improve the service life of a washing and cleaning disc device, and reduce the maintenance cost.

This invention provides a method for detecting road edges and drivable areas on closed roads based on lidar, comprising: acquiring lidar detection point cloud data; detecting point cloud data in groups based on voxel grids; voxel grids are obtained by dividing a predetermined detection space; a grid formed by projecting the combined voxel grids onto a ground plane as a raster image, and binarizing and marking the raster image according to the height distribution of the detected point cloud data within the voxel grids; and determining the road edge and drivable area based on the binarized and marked raster image. This invention improves the computational efficiency of road edge and drivable area detection by detecting point cloud data in groups using voxel grids, allowing point cloud data within each voxel grid to be processed in parallel. Simultaneously, binarizing and marking the detected point cloud data based on the height distribution within the voxel grids, and determining the road edge and drivable area using the binarized and marked raster image, further simplifies the computational steps and reduces the computational resource requirements.

The application provides a vehicle control method and device, electronic equipment and vehicle. The method comprises the following steps: deploying a front-view integrated machine in the vehicle to identify the road edge and / or oncoming vehicle; deploying a millimeter wave radar in the vehicle to obtain a first lateral distance and a first estimated collision time between the vehicle and the road edge, and / or a second lateral distance and a second estimated collision time between the vehicle and the oncoming vehicle; obtaining a vehicle risk assessment level according to the first lateral distance and the first estimated collision time, and / or the second lateral distance and the second estimated collision time; obtaining an operation state of an emergency lane keeping system in the vehicle according to the risk assessment level; if the operation state is an active state, sending a warning prompt according to the risk assessment level, or controlling the vehicle to move in a direction opposite to the lateral direction of the road edge and / or the oncoming vehicle through an electronic power steering system. The application reduces the cost and improves the deployability by deploying a light-weight device.

A procedure involves receiving map data with a plurality of map road edges and a plurality of perception road edges for a road segment. The procedure involves determining a probability value for orientations, each indicating whether at least one of the map road edges of the orientation should be the same road line as one of the perception road edges of the orientation. The procedure involves resolving ambiguity if no probability value of the road segment satisfies at least one orientation criterion, and determining a resolved orientation between the perception and map road edges. This involves applying multiple levels of ambiguity, each with a different ambiguity test, and determining whether a non-ambiguity count should be incremented depending on the magnitude of probabilities with respect to the orientations.The resolved alignment exists when the alignment between roadway edges has a highest non-ambiguity count.

The application discloses a kind of generation method, equipment and medium of automatic driving map, method includes: determining the target area of the automatic driving map to be generated, the area image of the target area under different frames is collected by the camera sensor arranged on positioning robot;By pre-trained image recognition model, the road edge curve in the area image is identified, and the starting point and key point in the road edge curve are determined to obtain the road edge point cloud data composed of starting point and key point;The starting point of different road edge curves is connected to generate the initial road edge corresponding to the target area, and whether there is breakpoint in the initial road edge is determined;If there is, then add several smoothing points to breakpoint, according to several smoothing points, the initial road edge is smoothed to obtain the road edge of the target area after processing.

This vehicle travel assistance method reduces the risk of collision with a moving object that exists in the vicinity of an edge of a road on which a vehicle is travelling. The method detects a moving object in a region in the vicinity of one road edge that is among left-right road edges of a road on which a vehicle is travelling and that is closer to the vehicle (S2); calculates the density of moving objects in the region in the vicinity of said one road edge (S3); and controls travel of the vehicle so as to further reduce the risk of collision with a moving object when the calculated density is high, as compared to a case where the calculated density is low (S4, S5).

The application provides a method and device for obtaining a peripheral road correction coefficient and an electronic device. The method comprises: generating a probe of a preset length perpendicular to the midpoint of each straight edge of the edge of the building site; identifying a target straight edge corresponding to the probe in contact with the road surface adjacent to the building site, and calculating the total length of the target straight edge; calculating a critical value of the number of road edges for comparison with the total length to determine whether the building site meets the urban and rural planning standards based on the optimal circumscribed ellipse of the building site; determining the number of road edges of the building site based on the total length and the critical value, and matching the number of road edges of the building site with the urban and rural planning standards to obtain the peripheral road correction coefficient of the building site. The application can quickly and accurately determine the peripheral road correction coefficient of the building site.

Aspects of the disclosure relate to generating map data. For instance, data generated by a perception system of a vehicle may be received. This data corresponds to a plurality of observations including observed positions of a passenger of the vehicle as the passenger approached the vehicle at a first location. The data may be used to determine an observed distance traveled by a passenger to reach a vehicle. A road edge distance between an observed position of an observation of the plurality of observations and a nearest road edge to the observed position may be determined. An inconvenience value for the first location may be determined using the observed distance and the road edge distance. The map data is then generated using the inconvenience value.

The invention discloses an automatic driving method, computer equipment, a storage medium, a program product and a mobile platform. The method comprises the following steps: determining a topological path and a road edge outer contour line in a sensing range according to environment sensing data; generating a road center line according to the topological path and the road edge outer contour line; and generating a driving track for automatic driving at least according to the road center line. The topological path and the along outer contour line are determined according to the environmental perception data of the vehicle, and the road center line is further generated according to the topological path and the along outer contour line for automatic driving. The method does not need to depend on the recognition of the lane line, and achieves the automatic driving on an unstructured road.

The present application relates to the technical field of data processing, and particularly provides a road edge detection method and device based on a non-repeating scanning laser radar, aiming at solving the problem of poor robustness and stability of the existing road edge detection method based on the non-repeating scanning laser radar. For this purpose, the road edge detection method comprises: obtaining initial point cloud data of the non-repeating scanning laser radar; first, candidate road edge line segments are screened out from the initial point cloud data of the non-repeating scanning laser radar, so as to facilitate subsequent extraction of road edge points and filtering out of the interference of non-road edge obstacles; then, first corner point cloud data and second corner point cloud data are determined through the elevation feature and gradient feature of each candidate point cloud data in the candidate road edge line segments; and further, road edge points are extracted from the candidate point cloud data based on the height difference of the first corner point cloud data and the second corner point cloud data, which is conducive to improving the effectiveness of the determined road edge points and improving the robustness and stability of the road edge detection method.