484 results about "Road edge" patented technology

The invention relates to the technical field of image processing, in particular to a road area intelligent extraction system for unmanned aerial vehicle aerial images, and the system comprises an image noise filtering module which analyzes and inputs frequency domain information of the unmanned aerial vehicle aerial images, recognizes a target noise mode, and filters the unmanned aerial vehicle aerial images. According to the method, frequency domain noise analysis and notch filtering are combined, the sharpness of the road edge is reserved, meanwhile, high-frequency noise and periodic interference are restrained, and the visibility of a low-contrast road area is improved; local pixel spectrum dispersion calculation is introduced and is dynamically fused with morphological parameters, and direction consistency and length-width ratio constraints are combined, so that the connectivity perception capability of the fragmented non-paved road is enhanced, and the fracture misjudgment under the form-changeable terrain is reduced; a normalized vegetation index and multi-band reflectivity are combined for modeling, water reflection interference is eliminated through a blue light band standard deviation, and a space mask of a non-road surface feature interference area is constructed.

Disclosed herein are methods, devices, and systems for automatically detecting double parking violations. For example, one aspect of the disclosure concerns a method comprising determining a location of a road edge of a roadway from one or more video frames of a video captured by one or more video image sensors of an edge device; determining a layout of one or more lanes of the roadway, including a no-parking lane, based on the road edge; bounding the no-parking lane using a lane bounding polygon; bounding a vehicle detected from the one or more video frames using a vehicle bounding polygon; and detecting a potential double parking violation based in part on an overlap of at least part of the vehicle bounding polygon with at least part of the lane bounding polygon and a determination of whether the vehicle is static or moving.

A unified boundary machine learning model is capable of processing perception data received from various types of perception sensors on an autonomous vehicle to generate perceived boundaries of various semantic boundary types. Such perceived boundaries may then be used, for example, to control the autonomous vehicle, e.g., by generating a trajectory therefor. In some instances, the various semantic boundary types detectable by a unified boundary machine learning model may include at least a virtual construction semantic boundary type associated with a virtual boundary formed by multiple spaced apart construction elements, as well as an additional semantic boundary type associated with one or more other types of boundaries such as boundaries defined by physical barriers, painted or taped lines, road edges, etc.

The invention relates to the technical field of engineering construction, and discloses a concrete pavement paving device for engineering construction, which comprises a crawler machine, a rotating seat and a support plate, the rotating seat is fixedly mounted on the crawler machine, the upper end of the rotating seat is fixedly connected with a mounting plate, and the upper end of the mounting plate is transversely and movably provided with a telescopic arm; one side of the back plate is movably mounted at one end of the telescopic arm, two fixing seats are hinged to one side of the back plate, a first shell is jointly mounted on the two fixing seats, a second shell is arranged on one side of the first shell, a paving mechanism is jointly mounted between the first shell and the second shell, and the paving mechanism is used for uniformly paving concrete on the surface of a roadbed. And vibration trowelling can be realized after paving. According to the concrete pavement paving device for engineering construction, concrete of a curb and a pavement can be paved on the pavement, the paving thickness can be controlled, a template does not need to be paved on the surface of a roadbed, and the construction speed is increased.

The invention relates to the technical field of laser detection, in particular to laser detection equipment for pavement material thickness detection, which comprises a detection table, an arc-shaped hole is formed in one side of the top end of the detection table in a penetrating manner, a stop block is fixedly connected to the outer side, corresponding to the arc-shaped hole, of the top end of the detection table, and an arc-shaped road edge stone is arranged above the top end, corresponding to the arc-shaped hole, of the detection table. A positioning adjusting mechanism is arranged at the bottom end of the detection table, and a scraping cleaning mechanism and a detection mechanism are arranged at the top end of the detection table; the positioning adjusting mechanism comprises a first clamping plate and a second clamping plate which are arranged on the two sides of the inner wall of the arc-shaped hole, and the first clamping plate, the second clamping plate and the check block are matched to be used for positioning and adjusting the position of the arc-shaped road edge stone. Under the cooperation of the deflected first clamping plate, the deflected second clamping plate and the fixed stop block, the position of the arc-shaped road edge stone can be quickly adjusted, so that the adjustment time can be shortened, and the adjustment efficiency is improved.

A computer-implemented method for estimating a road geometry of a road upon which a vehicle is traveling and related aspects are disclosed. The disclosed embodiments provide a model-based technique for estimating a road model having an arbitrary number of lanes on a road as well as any entrance lanes (i.e. on-ramp or slip roads) and exit lanes (i.e. off ramps or off-slip roads). In more detail, the herein disclosed embodiments utilize a Bayesian approach to multi-lane tracking in various traffic scenarios, such as e.g. highway scenarios. The employed model-based algorithm estimates the lane center curves of multi-lane roads based on vehicle motion data (e.g. speed, angular velocity) and perception data (e.g. camera output, lidar output, radar output, etc.) that includes detected road features (e.g. lane markers, road edges, road barriers, guard rails, road markers, etc.) or other objects (e.g. other road users).

The invention discloses a road edge extraction method based on a vehicle-mounted millimeter wave radar and electronic equipment, and is applied to the technical field of millimeter wave radar data processing. The method comprises the following steps: acquiring driving information of a vehicle and trace point data of a millimeter wave radar; estimating a vehicle driving track according to the driving information and the trace point data; obtaining historical road edge trace points, and verifying the historical road edge trace points to eliminate invalid trace points; according to the vehicle driving track, screening and updating the current road edge trace points to obtain effective road edge points; and extracting the road edge through an RANSAC (Random Sample Consensus) algorithm under the condition that an effective road edge extraction result exists currently. According to the method, the track information of the vehicle and the trace point information detected by the millimeter wave radar are fully utilized, invalid points on the inner side and the outer side are removed through the historical road edge recognition result, the RASCAN calculation amount is reduced, meanwhile, the influence of non-road-edge obstacles on the result is avoided, the algorithm is stable, efficient and accurate, the method can well fit the road shape, and meanwhile the calculation amount is low.

A driving assistance control apparatus for a vehicle includes an acquiring unit and a control unit. The acquiring unit acquires a detected traveling environment of the vehicle. Using the acquired traveling environment, and in response to a preceding vehicle being present near a road edge and no obstacle being present between the road edge and the preceding vehicle, the control unit causes a driving assisting unit to perform driving assistance in which the preceding vehicle is tracked.

The invention provides a road network trajectory generation method and system based on pre-training, and a medium. The method comprises the following steps: S1, carrying out pre-training based on simulation data to obtain a pre-trained autoregression Transform model; step S2, based on real data, carrying out fine adjustment on the auto-regression Transform model after pre-training; and S3, generating a road edge trajectory through autoregressive reasoning by the finely adjusted model. According to the invention, a large amount of data generated by a simulator is used for training and generating a model, and then the model is aligned with observation results of the real world. The generative model provides a higher fidelity than a simulator. Different from a model which only depends on real world data, the method is more effectively popularized to the road network of the whole city range. Besides, as long as a simulator running on the urban road network can be accessed in the pre-training step, a trajectory generation model can be pre-trained for the city, and the trajectory generation model is used as a basic model further aligned with a real world observation result.

The invention discloses a road traffic detection control method based on a vehicle-mounted camera module, and belongs to the technical field of traffic detection, and the method specifically comprises the steps: collecting road image data in real time through the vehicle-mounted camera module; preprocessing the acquired road image data, and extracting a road area; performing edge extraction on the preprocessed road image data by using an edge detection algorithm to obtain road edge information; according to the road edge information, detecting straight-line segments in the road through Hough transform, and calculating an included angle between adjacent straight-line segments to determine the line type of the road; calculating the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road center line according to the line type of the road in combination with the speed and position information of the vehicle; according to the distance between the vehicle and the road boundary and the offset of the vehicle relative to the road center line, the driving direction and speed of the vehicle are adjusted through a preset control strategy; according to the invention, real-time safety detection of the vehicle in the driving state is realized.

Systems, methods, and other embodiments described herein relate to estimating lane boundaries using a slicing model with road data for generating maps. In one embodiment, a method includes computing three-dimensional (3D) representations that are discretized from acquired data about road edges associated with driving lanes. The method also includes deriving discrete and lateral slices of the road edges using a slicing model, the road edges are connected in a road graph that describes a mapped area. The method also includes extracting features from the lateral slices individually using a neural model for forming a histogram to estimate lane boundaries about the driving lanes. The method also includes generating a map by linking the lane boundaries individually along the road edges.

The invention relates to the technical field of road construction, in particular to a repairing and trimming device for road base paving construction, which comprises a trimming scraper, a first rotating shaft is rotatably arranged on the front side of the top of the trimming scraper, the bottom end of the first rotating shaft is connected with a second rotating shaft through a universal transmission assembly, and a material scattering assembly is arranged at one end, away from the universal transmission assembly, of the second rotating shaft. A shaking generation assembly is arranged on the trimming scraper and used for controlling the side, facing the road, of the material dredging assembly to incline and the front side of the material dredging assembly to tilt. The device has the beneficial effects that when the rotating disc rotates by a half circle, the multiple fixing columns not only knock lump materials in a shaking state, but also bring the materials located at the slope bottom to the position of the slope top, and when the rotating disc rotates by another half circle, the materials are uniformly spread downwards from the slope top, so that the materials are fully scattered and uniformly spread; and the problem that the thickness of the edge of a road is not uniform or the compactness is greatly different due to material caking or non-uniform thickness is avoided.

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 present invention belongs to the technical field of road construction, and discloses a paver and a paver. The paver includes a frame, a driving mechanism and a paving mechanism. The clutch limits the rotation of the third paving section relative to the sliding frame, and the first paving section rotates under the drive of the driving mechanism. Combined with the threaded cooperation between the first paving section and the second paving section, the sliding frame, the second paving section and the third paving section can all move in a direction away from the fixed frame to adjust the length of the paving mechanism, which is suitable for asphalt paving on roads of different widths. After the length of the paving mechanism is adjusted, the clutch releases the rotation restriction on the third paving section, so that the third paving section can rotate synchronously with the first paving section and the second paving section to pave the asphalt. At the same time, a heating fluid is introduced into the heating chamber enclosed between the second end of the first paving section and the slot to heat the asphalt at the edge of the road to ensure the uniformity of the asphalt paving at the edge.

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 invention belongs to the technical field of intelligent traffic, and provides a distributed optical fiber road sensor on-site manufacturing and road risk monitoring and early warning method. Comprising the steps of optical fiber unit manufacturing, concave shallow slot cutting, sensor construction, data acquisition, road surface state data conversion, scattered light time domain signal interval division, frequency domain conversion and filtering processing, multi-mode feature extraction and road surface condition recognition. According to the invention, the concave shallow slot is cut at the edge of the road, and the flat ribbon-shaped optical fiber unit is fixed in the shallow slot by using polyurea, so that the multifunctional distributed optical fiber road sensor which is integrated with the road surface, high in sensitivity, small in size, simple to install, convenient and rapid to maintain and repair and low in cost is constructed; through a zero crossing point and a noise threshold value, normal time domain signal interval judgment is optimized, and the effect of subsequent filtering processing is improved; a road surface condition identification data model is constructed through a multi-modal fusion technology, and the identification precision of multiple road surface abnormal conditions and the positioning precision of abnormal events are improved.

A method for creating a guidance trajectory for a first transportation vehicle which includes receiving swarm data for a route section that represent at least one motion trajectory of at least one second transportation vehicle traveling through this route section; determining a distance from the at least one motion trajectory represented by the swarm data to a determined roadway edge for the route section; and using an electronic computing device to apply the at least one motion trajectory to ascertain the guidance trajectory for the first transportation vehicle in response to the distance associated with the respective motion trajectory being greater than or equal to a predefined limit value for the route section, and to provide the guidance trajectory for the first transportation vehicle, as a result of which the first transportation vehicle is transversely controlled using the guidance trajectory.

The invention relates to a road information automatic extraction method based on a multi-modal remote sensing image, and the method comprises the steps: obtaining a multi-modal remote sensing image training sample set which comprises a plurality of groups of multi-modal remote sensing image training samples, and each group of multi-modal remote sensing image training samples comprises a multi-modal remote sensing image and a corresponding road label image; the multi-mode remote sensing image comprises an optical remote sensing image and an SAR image; the road label image comprises a road surface segmentation label and a road edge label; constructing an initial road extraction model, and training by using the multi-modal remote sensing image training sample set until a loss function converges to obtain a training road extraction model; and performing road extraction on the input multi-modal remote sensing image data based on the training road extraction model, and performing vectorization to obtain road data. According to the method and the device, the problem of insufficient road extraction precision in a road extraction task based on a remote sensing image in the prior art is solved, and the accuracy and connectivity of a road extraction result based on the remote sensing image are improved.

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.

The invention discloses a road surface point cloud extraction method and system based on facade point detection, and belongs to the technical field of point cloud processing, and the method comprises the steps: obtaining a road point cloud, and carrying out the preprocessing of the road point cloud based on a driving track; facade points in the road point cloud are detected and removed; screening the road point clouds with the facade points removed based on normal vector features to form preliminary road surface point clouds; and performing pavement point cloud and interference point separation on the preliminary pavement point cloud through density clustering, further optimizing the clustered pavement point cloud by applying a cloth simulation filtering algorithm, and outputting a clean pavement point cloud. According to the method, the road edge point cloud can be effectively reserved, the integrity and precision of the road point cloud are improved, and the requirements of applications such as road high-precision modeling and automatic driving are met.

The display system includes a lane line recognition unit configured to recognize a lane line of a traveling lane of the host vehicle based on a detection result of a camera of the host vehicle, a road edge structure recognition unit configured to recognize a road edge structure positioned outside the lane line based on a detection result of a sensor of the host vehicle, and a display control unit configured to control a display of the in-vehicle display based on recognition results of the lane line recognition unit and the road edge structure recognition unit. The display control unit is configured to display a road edge structure icon corresponding to the road edge structure on the in-vehicle display when the lane line is not recognized and the road edge structure is recognized.

The invention discloses a municipal road monitoring method and system based on an edge computing technology, and relates to the technical field of signal processing. The method comprises the steps that road edge nodes collect data through optical, vibration and infrared sensors, and the pavement crack index and the real-time traffic flow are calculated in parallel; fusing environment temperature and humidity data, weighting to generate a road health initial judgment value, and triggering a dynamic threshold alarm; exchanging initial judgment values at adjacent nodes through a low-power-consumption Mesh network, jointly calculating the regional-level traffic flow density and road surface damage association degree, and generating an encrypted regional road state feature vector; the central management platform aggregates the regional feature vectors, calculates a road comprehensive health score and an early warning weight coefficient in combination with a historical baseline, generates a self-adaptive dredging strategy and issues the self-adaptive dredging strategy to an edge node; according to node load and energy consumption data, the sampling frequency of the sensor is dynamically adjusted, and the crack recognition model is updated. According to the invention, the road state monitoring real-time performance and the early warning accuracy are obviously improved, and the data transmission energy consumption is reduced.

The invention provides a vehicle control method and device, electronic equipment and a vehicle, and the method comprises the steps: recognizing a road edge and / or an opposite coming vehicle through deploying a foresight all-in-one machine in the vehicle; the method comprises the following steps: deploying a millimeter wave radar in a vehicle to obtain a first transverse distance and a first estimated collision time between the vehicle and a road edge, and / or a second transverse distance and a second estimated collision time between the vehicle and an opposite vehicle; acquiring 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, acquiring a running state of an emergency lane keeping system in the vehicle according to the risk assessment level, and if the running state is an activated state, sending an early warning prompt according to the risk assessment level, or the vehicle is controlled by the electronic power-assisted steering system to move towards the edge of the road and / or in the transverse opposite direction of the coming vehicle. According to the application, the cost is reduced and the deployability is improved by deploying lightweight equipment.

The invention relates to a method for constructing a lane model, and the method comprises the steps: carrying out the processing of a detected lane line, and carrying out the parallelization processing of the lane line; adaptively determining a lane center line coefficient by using the processed lane line according to the identified lane scene; and sampling points on the lane center line according to the determined lane center line coefficient under the condition of keeping a safe distance from the road edge so as to construct the lane model. The application also relates to a computer program product and an electronic device.

The invention provides an expressway stake mark positioning method and equipment based on point cloud data element extraction, and the method comprises the steps: carrying out the preprocessing of original point cloud data through employing a slope method ground filtering and statistical outlier elimination filtering mode, and extracting a complete road surface; on the basis of the extracted complete road surface data, performing point cloud alignment, slicing and extracting road edges, and preliminarily solving a road center point by utilizing the geographic coordinate center of each point of the extracted road edges; skeleton points are randomly initialized, the positions of the skeleton points are iteratively optimized, then the skeleton points are subjected to sparse processing, and fitting is achieved through minimum spanning tree connection to generate a continuous center line of a road; and matching and positioning kilometer stake points to realize accurate assignment of stake numbers. According to the method, the expressway elements can be efficiently and accurately extracted from massive point cloud data and converted into stake number positioning information, the defects of a traditional method in efficiency and positioning precision are overcome, and the accuracy and working efficiency of expressway positioning are remarkably improved.

Lidar produces three-dimensional point clouds. From the point clouds, objects need to be detected and tracked. For example, from the point clouds, embodiments detect what kind of objects is detected, what shape the object is, and the objects current location and trajectory. Each lidar sensor on a vehicle produces a point cloud periodically. The point cloud is input into a deep learning neural network that outputs road geometry, such as road edges and lane dividers. In some embodiments, the other network can also output information about other objects in the environment, such as other vehicles and pedestrians.

The invention discloses a vehicle meeting control method, electronic equipment, a storage medium, a vehicle and a vehicle networking system, and the vehicle meeting control method comprises the steps: receiving a vehicle meeting control instruction which is generated by a cloud platform according to road side sensing information and vehicle sensing information; according to the meeting control instruction, at least one of the following items is executed: the position of an avoiding wheel of the vehicle in the vehicle width direction is adjusted, the relative position of a vehicle body of the vehicle and the road edge is controlled, the avoiding wheel is the wheel, close to the road edge, of the vehicle, and the avoiding wheel can move in the width direction of the vehicle; adjusting the height of the vehicle body; and alarming to prompt that vehicles cannot pass. According to the method, on a narrow road which does not meet normal meeting conditions, the meeting control instruction is generated through the cloud platform, the vehicle is controlled to realize automatic meeting, or an alarm is given to prompt that the vehicle cannot pass, the meeting intelligence of the automatic driving vehicle is ensured, the vehicle travel efficiency and safety are improved, and the traffic jam problem caused by meeting is avoided.

The invention discloses a ground pit detection method, device and equipment and a storage medium, and the method comprises the following steps: collecting ground 3D point cloud data through a laser radar, and obtaining the size and position information of an obstacle; road surface image information is collected through a binocular camera, the width and the position of a road edge are obtained, and current pit negative obstacle information is judged and output in combination with a point cloud negative obstacle recognition type; and ground pits are recognized through a YOLO target detection algorithm, when the pits are recognized, position and size information of the pits is calculated through a binocular positioning algorithm, and the position and size information and a negative obstacle judgment result are subjected to multi-modal fusion to obtain final pit information. Different pit sizes can be detected and distinguished, the vehicle body posture and the running speed of the aerial work platform vehicle can be adjusted in a diversified mode according to the different pit sizes, and the flexibility and safety of the aerial work platform for dealing with ground pit conditions are remarkably improved.

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 utility model relates to the technical field of asphalt pavement maintenance, in particular to an ultra-thin wearing layer asphalt pavement maintenance device which comprises a mobile vehicle body, a material storage box is fixed on one side of the mobile vehicle body, a lifting assembly is fixed on the mobile vehicle body, and a paving assembly used for pushing wearing layer materials is fixed at the lifting bottom end of the lifting assembly. A side frame is fixed to one side of the paving assembly, a cleaning assembly used for cleaning the surface of the paving assembly is fixed to one side of the side frame, and a height-adjustable material scraping assembly is fixed to the bottom of the side frame. And then the paving assembly is used for uniformly pushing the wearing layer paving material to the road edge direction, and the scraping assembly with the adjustable height is used for further leveling the wearing layer paving material leveled by the paving assembly, so that the paving thickness of the wearing layer paving material is kept uniform.