146 results about "Trafficability" patented technology

The invention belongs to the technical field of path planning, and discloses a path planning method and system fusing multi-modal terrain perception and vehicle dynamics, and the method comprises the steps: obtaining and fusing multi-modal geographic data to generate a terrain physical representation, and calculating the terrain complexity based on the terrain physical representation; predicting an overturning index and a stability margin of the vehicle based on the terrain physical representation, and generating a trafficability cost function; taking the trafficability cost function as a constraint condition, selecting a motion element according to terrain complexity to perform trajectory fitting, and generating a vehicle path; executing the vehicle path to obtain a vehicle state, correcting the trafficability cost function by using the vehicle state, and optimizing the vehicle path; and constructing a loss function, training the path planning model, and performing path planning by using the trained model. According to the invention, by establishing a terrain vehicle bidirectional coupling mechanism, safe and adaptive local path planning under a complex unstructured terrain is realized, and the traffic capacity and safety of the system in a dynamic environment are significantly improved.

The invention discloses a vehicle trajectory planning method and device and a vehicle, and relates to the technical field of intelligent driving. The method comprises the following steps: obtaining vehicle state information of a target vehicle, a reference trajectory and environment perception data containing available traffic width, and performing trajectory optimization processing according to the vehicle state information, the reference trajectory and the environment perception data to obtain a trajectory optimization result of the reference trajectory; in the trajectory optimization processing process, taking a first passing cost required for minimizing a trajectory optimization result as a target; a passing width cost item in the first passing cost is a power function taking the residual passing width as an independent variable, and the passing width cost item is increased along with the reduction of the residual passing width; the remaining passing width is the difference between the available passing width and the vehicle width of the target vehicle. Therefore, in a narrow traffic scene, the traffic width cost item is increased in a super-linear manner, the constraint strength on the transverse position of the track is enhanced, the generation of a high-risk track excessively close to an obstacle is effectively avoided, the planning interruption frequency is reduced, and the trafficability of the vehicle in the narrow scene is remarkably improved.

The invention discloses an intelligent road surface recognition method based on force perception and image analysis. The method comprises the following steps: S1, acquiring image data and contact force data in the advancing process of a mobile robot; s2, inputting the image into a two-channel feature network, and extracting structural features and fuzzy region information; s3, processing through an unwrapping model to form an image semantic vector; s4, constructing a contact time sequence, extracting behavior characteristics, and generating a contact event code; s5, performing alignment and weighted fusion on the image semantic vector and the contact code, and outputting a combined pavement state vector; s6, inputting a trafficability scoring model, identifying a ground type and generating a trafficability score; and S7, transmitting the result to a navigation module for path planning and motion control. Visual and force sense information is combined, and the complex terrain recognition accuracy and the robot traffic capacity are improved.

The invention provides a vehicle path planning method and device. The method comprises the following steps: acquiring vehicle parameters, environment sensing data, a path starting point and a path ending point; generating an upper-layer obstacle grid map and a lower-layer obstacle grid map based on the vehicle parameters and the environment perception data; performing collision detection based on the vehicle parameters in the upper-layer obstacle grid map and the lower-layer obstacle grid map to obtain an upper-layer collision detection result and a lower-layer collision detection result; combining the upper-layer collision detection result with the lower-layer collision detection result to generate a planned path from the path starting point to the path ending point; the planned path comprises obstacle-avoiding nodes for bypassing the upper-layer obstacle and obstacle-crossing nodes for crossing the lower-layer obstacle. Therefore, efficient path searching in the multi-obstacle complex scene is realized, and the vehicle has better trafficability in the multi-obstacle complex scene.

The invention relates to the technical field of vehicle control, and provides a vehicle tire pressure adjusting method and a vehicle. Vehicle running data and a road topographic image in front of the vehicle are obtained, so that the vehicle trapping risk of the vehicle is predicted, and vehicle trapping probability information of the vehicle is obtained; according to the method, the vehicle trapping risk of the vehicle can be predicted in advance, the accuracy of vehicle trapping risk prediction is ensured through environmental perception and operation data, and the vehicle trapping risk prediction accuracy is improved. The tire pressure adjusting quantity is determined in time according to the vehicle sinking probability information and the vehicle operation data, so that the tire pressure adjusting accuracy is ensured, the purpose of timely intervention before the vehicle sinking is achieved, the vehicle sinking caused by mismatching of the tire pressure under the complex road conditions such as sand and mud is avoided, the vehicle escaping capability is improved, and the vehicle safety is improved. And the trafficability of the vehicle under various complex road conditions is improved.

The invention relates to the technical field of geographic information systems, in particular to an incomplete road network repairing and reconstructing method based on AI recognition. Comprising the following steps: S1, road surface data geometric restoration and road width calculation; s2, reconstructing a target road network topology; s3, road attribute matching; and S4, topology simplification and output. According to the method, through the dynamic distance threshold value and topology verification, broken roads are intelligently connected, the disconnection phenomenon is eliminated, a topology connected road network is constructed, and a reliable data basis is provided for path planning. The width is calculated through correlation between the road surface and the center line, and the external road network attributes are fused, so that the output road network has key information such as the road width and grade, and the trafficability evaluation requirement in mechanical construction is met.

The invention discloses a visual analysis method and equipment for the trafficability of a grain transport vehicle tractor track and a storage medium. According to the method, images are collected through a vehicle-mounted binocular vision system, and multi-dimensional geometric attributes of the terrain and obstacles are automatically extracted through semantic segmentation, three-dimensional reconstruction and voxel modeling. And on the basis of the extracted multi-dimensional attributes, constructing a hierarchical evaluation system containing terrain and obstacle criteria. A local weight of each attribute index is determined by adopting an analytic hierarchy process, and a fuzzy membership degree vector of each index on different passage evaluation grades is constructed according to dynamic judgment parameters adaptively set with the current grain transport vehicle model number and the terrain, so that a membership degree matrix is formed. And finally, through hierarchical fuzzy comprehensive evaluation, calculating to obtain a comprehensive trafficability score. The accuracy, reliability and automation level of tractor track trafficability evaluation are improved.

The invention provides a vehicle remote control driving system and method integrating AR virtual path projection, and relates to the technical field of vehicle remote control. The system constructs a high-precision three-dimensional environment model through cooperative work of an environment sensing module and a data processing and decision module; the AR path generation unit generates a collision-free virtual path and a vehicle dynamic rehearsal picture, and the collision-free virtual path and the vehicle dynamic rehearsal picture are visually presented in an augmented reality mode through the remote control terminal outside the vehicle, so that a driver can obtain comprehensive situation awareness beyond a physical visual field outside the vehicle; and after the virtual path is confirmed or adjusted in combination with the interaction control, the vehicle control strategy unit automatically generates a cooperative control command adapting to the road condition, and an execution mechanism is driven to perform accurate execution. According to the system, the safety and operation confidence of remote control driving are improved, the blind area collision risk is effectively avoided, the trafficability of the vehicle in a complex environment is enhanced, meanwhile, the operation difficulty is greatly reduced through AR visual interaction, and intelligent and user-friendly vehicle exterior remote control driving experience is achieved.

The invention belongs to the technical field of data processing, and discloses a Mars rover non-contact trafficability estimation method and system based on thermal inertia, and the method comprises the steps: obtaining a ground surface temperature time sequence and environment parameters of a target region; constructing a thermal inertia estimation model, and inputting the earth surface temperature time sequence and the environmental parameters into the thermal inertia estimation model to obtain a thermal inertia estimation value of the fire soil; constructing a thermal inertia and trafficability index relation model, inputting the thermal inertia estimation value of the fire soil into the thermal inertia and trafficability index relation model, and outputting a predicted trafficability index; and determining a trafficability state grade according to the predicted trafficability index, and generating a navigation control suggestion, so that the Mars rover passes through the target area according to the Mars rover navigation control suggestion. According to the method, the trafficability index of the Mars rover is predicted by extracting the thermal inertia estimation value of the fire soil in the target area, the evaluation precision of the Mars rover passing through the target area can be effectively improved, and the driving safety of the Mars rover is ensured.

The invention relates to the technical field of unmanned vehicle path planning, and provides a path planning method suitable for an unmanned vehicle in a field scene, and the method comprises the steps: carrying out the evaluation of a trafficable terrain, and obtaining the trafficability of the current ground; a global reference path is generated in combination with the trafficability and an improved Inform-RRT * algorithm; performing trajectory fitting on the global reference path by adopting a Bezier curve to generate a smooth path; and local planning and tracking control are performed based on a kinematic model in combination with the smooth path and obstacle information. According to the path planning framework provided by the invention, the trafficability of the terrain and the dynamic characteristics of the robot are considered, so that the method better meets the actual application requirements, and the operation efficiency and reliability of the unmanned vehicle in the complex terrain are improved.

The invention provides an air-ground collaborative navigation method based on a hierarchical visual language action model, which comprises the following steps that: a ground robot and an air unmanned aerial vehicle respectively acquire relevant data and send the relevant data to a central processing system for processing; a global path planning module of the central processing system generates a coarse-grained global path key point sequence, namely a sparse path point sequence, based on the processed and aligned aerial top view image, and then a local path planning module of the central processing system generates dense local path points between adjacent sparse path points based on the ground view image; and a capability perception evaluation module of the central processing system evaluates the trafficability of each output candidate path according to the physical capability of the ground robot so as to provide a basis for final path selection. The method effectively solves the problems that a traditional air-ground collaborative framework lacks quantitative evaluation and closed-loop feedback mechanisms for physical capabilities of ground robots and does not make full use of global environment information to carry out robot passage planning and the like.

The invention discloses an unmanned engineering machinery steer-by-wire system and a control method in the technical field of vehicle chassis and steering systems. The unmanned engineering machinery steer-by-wire system comprises four wheels and steering modules, wherein the steering modules are in one-to-one correspondence with the four wheels, are completely independent and have the same structure; the corner deflection of the four wheels is cooperatively controlled through a distributed electronic control system; and each wheel is driven by a hub motor. Through four-wheel steering, the minimum turning radius can be 0 m, the trafficability in narrow roadways, sidewalks and obstacle dense areas is improved, meanwhile, four-wheel steering is independently controlled, special movement forms such as transverse translation and oblique advancing are supported, and the four-wheel steering robot is particularly suitable for high-precision operation requirements such as urban road edge stone attaching and sweeping; four-wheel independent main pin steering is combined with a hub motor and distributed redundancy control, so that the reliability, the function safety and the maintainability of the system are remarkably improved, and the system is particularly suitable for unmanned engineering machinery to work for a long time in narrow, complex and severe environments.

The utility model relates to an aerial work platform which comprises a main platform unit, the main platform unit comprises a main work platform and a first guardrail assembly, the first guardrail assembly is arranged on the edge of the main work platform in a surrounding mode, and the first guardrail assembly extends in the height direction; the anti-collision unit comprises an anti-collision rod assembly, and the anti-collision rod assembly is assembled on the first guardrail assembly; the anti-collision rod assembly comprises an upper structure, a lower structure and an induction piece, one end of the upper structure is rotationally connected with the lower structure, and the induction piece is installed at the other end of the upper structure. During working, the induction piece is driven by the upper structure to move to a high point. According to the anti-collision structure, the lifting action of the working platform can be stopped in time after a top obstacle is detected, safety accidents are effectively avoided, good top anti-collision protection measures are provided for operators, the anti-collision structure can be folded and stored conveniently in a non-working state, and therefore the trafficability of the whole machine in a stored state cannot be affected.

This invention provides a vision-based self-supervised off-road terrain accessibility estimation method. This method utilizes measurement data from an onboard inertial measurement unit to generate self-supervised access cost labels, enabling the predicted terrain cost to reflect the dynamic response characteristics of the vehicle during driving. Furthermore, these labels do not require manual annotation, saving the cost of training data labeling. Images containing rich terrain features are used as input perceptual information for the prediction network, and a contrastive learning method is used to pre-train the backbone network that extracts multi-scale features from the images, improving the reliability and accuracy of off-road terrain accessibility estimation.

The invention provides a lane center line generation method and device, electronic equipment and a vehicle, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining a single communication path according to a lane topology network, carrying out the aggregation of segmented lanes in the single communication path, obtaining at least one aggregated lane in the single communication path, and carrying out the aggregation of the at least one aggregated lane in the single communication path; determining passing points of each aggregation lane, connecting the passing points of each aggregation lane, generating a lane center line of each aggregation lane, and splicing and fitting the lane center line of each aggregation lane to obtain a target lane center line; according to the method, the lane center line of each aggregation lane is spliced and fitted to obtain the target lane center line, so that the continuity, smoothness and trafficability of the finally generated target lane center line are ensured, and the intelligent driving safety and the user driving experience are improved.

The invention discloses a path planning method based on a city engine and an unreal engine. The method comprises the following steps: completing basic data preparation, rule definition, model generation and visual presentation and analysis, and establishing a city model; secondly, constructing a vehicle motion model in an unreal engine, and simulating weather; the three-dimensional static model and a dynamic model in an unreal engine are fused to generate an urban environment; carrying out geographical gridding on the urban area; introducing a trafficability map and physical restrictions of the vehicle, and setting the trafficability map of the vehicle; an improved A * algorithm based on geographic gridding is introduced, path planning is conducted, the improved A * algorithm is used, and path optimization is achieved through a heuristic function and a penalty function; and outputting the generated path plan.

The utility model relates to the technical field of security and protection equipment, in particular to all-weather security and protection patrol equipment which can avoid obstacles in the moving process, push and clean sundries such as stones on a walking road, avoid influence on equipment walking, improve trafficability and safety, facilitate adjustment of monitoring directions and improve the safety of the equipment. The patrol area is increased; comprising an equipment body, an equipment box, two patrol cameras, a face recognition camera, an adjusting assembly, an avoiding assembly, a pushing assembly and a control assembly, walking wheels are arranged at the bottom of the equipment body, the equipment box is installed at the right end of the top of the equipment body, the adjusting assembly is installed in the equipment box, and the two patrol cameras are installed at the output end of the top of the adjusting assembly; an avoiding assembly is installed on the outer wall of the equipment body, pushing assemblies are installed at the left and right ends of the bottom of the equipment body, a control assembly is installed in the equipment body, and the face recognition camera is installed at the left end of the top of the equipment body.

The invention discloses a small general intelligent control chassis for hilly and mountainous areas, which belongs to the technical field of agricultural mechanical equipment and comprises a telescopic support, a lifting walking system, a central transfer steering system and a control and navigation system. The telescopic support adjusts the wheel track of the whole vehicle through a front frame body and a rear frame body which are connected in a sliding mode. The four lifting walking systems are independently installed below the four corners of the support. Each lifting walking system comprises wheels, an electric push cylinder driving the wheels to ascend and descend and a pressure sensor monitoring grounding pressure. The central transfer steering system is installed on the support and used for controlling synchronous steering of four wheels. The control and navigation system receives signals of the sensors and controls the systems to act cooperatively, so that self-adaptive driving and operation of the chassis under complex terrains are achieved. The trafficability, stability and operation safety of the agricultural machine in hilly and mountainous areas are improved.

The invention discloses an amphibious unmanned vehicle walking mechanism with a wheel-track interchange function, and mainly relates to the field of amphibious vehicles. The traveling mechanism adopts a modular design relatively independent of a vehicle body, and mainly consists of a turnover lifting piece and an interchangeable tire / crawler traveling piece. The overturning and lifting part drives the walking part to be wholly overturned upwards or downwards through the cooperative action of the overturning oil cylinder and the lifting oil cylinder, so that when the amphibious vehicle runs in water, the walking mechanism can be overturned out of the water surface, the streamline of the vehicle body is kept, and the water resistance is reduced; and the ground can be reliably grounded when the vehicle runs on land. The hydraulic motor is used for driving and providing power, and the pin shaft is used for quick connection and separation, so that the tire walking part and the crawler walking part can be integrally and quickly interchanged to adapt to different application scenes such as hard road surfaces or sand beaches, sludge and the like. According to the amphibious vehicle, the overwater high speed performance and the land complex terrain trafficability of the amphibious vehicle are effectively considered, the application range of the amphibious vehicle is widened, and the use efficiency is improved.

The application discloses a complex road boundary detection method and device based on point cloud voxel processing and belongs to the field of road detection. The method comprises the following steps: acquiring point cloud image data of articles around a road vehicle driving area, and performing voxel segmentation; adding a fixed point in the voxel to expand the voxel features; inputting a single-layer full connection layer to obtain a high-dimensional feature vector matrix; performing global feature transformation on all point cloud high-dimensional feature vector matrices in the voxel; selecting the global features corresponding to the k nearest point clouds as the center to aggregate; taking different values of k to obtain voxel features at different scales, and performing fusion; performing regression on the fused features to obtain related information of the articles around the vehicle driving area; calculating the boundary position of the vehicle driving area to obtain the width of the vehicle driving area, and determining whether the vehicle driving area is passable. The complex road boundary is accurately detected.

The invention discloses a control method for high-altitude operation equipment and a related device. The control method comprises the steps that the type of a road surface where the high-altitude operation equipment is located, chassis attitude parameters and equipment state parameters are obtained; based on at least one of the road surface type, the chassis attitude parameter and the equipment state parameter, selecting a target control mode from a plurality of preset chassis control modes; and according to the target control mode, torque distribution and / or rotating speeds of a plurality of driving units of the high-altitude operation equipment are / is adjusted. According to the invention, effective balance between good trafficability and efficient energy utilization can be realized.

The utility model discloses a suspension system and a vehicle. The suspension system comprises a first end cover and a first spring piece, the first end cover is used for being connected with one of the vehicle body and the wheel assembly, and the first spring piece is used for being connected with the other one of the vehicle body and the wheel assembly; the second end cover is arranged between the first end cover and the first spring piece, and the second end cover is connected with the end, close to the first end cover, of the spring piece; and the second spring piece is arranged between the second end cover and the first end cover. According to the embodiment of the utility model, through the matching of the first end cover, the second end cover and the second spring piece, the distance between the vehicle body and the wheel assembly is increased in an extreme driving environment, so that the wheel assembly is always in contact with the ground, the probability that the first spring piece is disengaged is reduced, the trafficability is improved, the conditions of abnormal sound and impact feeling are improved, and the service life of the vehicle is prolonged. And the comfort is improved.

The invention relates to a control device for a vehicle. The present invention addresses the problem of providing a control device for a vehicle that can use a learned model to give consideration to both the protection of a drive system and the trafficability. Provided is a vehicle control device. The apparatus includes a prediction unit that predicts a feature amount by inputting travel data of a vehicle into a first learned model obtained by machine learning, and an estimation unit that estimates whether the vehicle can pass through a road surface by inputting the feature amount into a second learned model obtained by machine learning. A setting unit that determines a limit value for limiting the driving force or braking force of the vehicle on the basis of the estimation by the estimation unit; and a control unit that controls the limit value on the basis of the estimation and the result of whether the vehicle can pass.

The embodiment of the invention is suitable for the technical field of computers, and provides a road section trafficability judgment method and device, electronic equipment and a computer program product, and the method comprises the steps: obtaining road section information of a to-be-detected road section and a first coordinate of at least one detection point on an obstacle; determining a longitudinal deviation value and a transverse deviation value of the detection point in the to-be-detected road section according to the second coordinate, the third coordinate and the coordinate of the detection point; the longitudinal deviation value is used for representing a deviation value between the detection point and the starting point in the direction of the center line; the transverse deviation value is used for representing the vertical distance between the detection point and the center line; and generating a trafficability judgment result corresponding to the road section to be detected based on the longitudinal deviation value and the transverse deviation value corresponding to the at least one detection point. According to the embodiment, the accuracy of road section trafficability judgment can be improved, so that the driving safety is improved.

The utility model discloses a tunnel foldable walkway plate, and relates to the technical field of shield tunneling machine corollary equipment, the tunnel foldable walkway plate comprises a main body plate and an extension plate, at least part of the main body plate is used for being arranged between a rear corollary trolley and a tunnel wall, and the main body plate is used for being connected with the rear corollary trolley; the extension plate is hinged to the main body plate, the included angle between a hinge shaft of the extension plate and the main body plate and the length direction of the rear matched trolley is smaller than 10 degrees, the extension plate has two states, one state is a folded state, the other state is an unfolded state, and the included angle between the extension plate in the folded state and the main body plate is smaller than 90 degrees; and the included angle between the extension plate in the unfolded state and the main body plate is greater than 90 degrees. The extension plate has the folded state and the unfolded state, the extension plate in the unfolded state can shield the gap between the main body plate and the tunnel wall, then the safety is improved, the extension plate in the folded state can reduce the size of the walkway plate in the width direction, and then the trafficability is improved.

The invention belongs to the technical field of mobile robots, and discloses an intelligent passing method and system for a mobile robot in a narrow channel environment, and the method comprises the steps: setting sampling points at the two normal sides of each path point along a forward window of a reference path of the mobile robot, and judging the trafficability of the sampling points based on the connectivity of a local map. Generating a narrow lane point set only when the sampling points on the two sides are impassable; when the continuous point number of the narrow lane point set reaches a preset continuous point number threshold value, the narrow lane section is judged; calculating an average displacement vector from the continuous path points in front of the narrow road section to obtain a narrow road passing direction; reversely shifting the outer side of the narrow road starting point by a preset distance in the narrow road passing direction to generate an entrance posture adjusting point; taking the entrance attitude adjustment point as a relay, selecting a forward reference point, positioning an index position at the starting point of the narrow lane, and generating two sections of sub-paths from the forward reference point to the entrance attitude adjustment point and from the entrance attitude adjustment point to the starting point of the narrow lane through graph search; and the passing efficiency and stability of the mobile robot in a complex narrow road environment are improved.

The invention belongs to the technical field of grid map construction, and discloses a multi-semantic grid map construction method fusing structured road topology. The method comprises the following steps: extracting a structured road region from a remote sensing image, constructing a topological network of the structured road region, and generating a road topology containing a center line and key road points; performing multi-category semantic segmentation on the same image, and endowing each semantic category with a weight according to the traffic capacity; rasterizing the weighted semantic segmentation result to form a multi-semantic grid map; and finally, projecting the road topology to a grid map, and performing weight enhancement on grids covering the topology to generate a grid map fused with topology guide information. According to the method, map support containing semantic trafficability and a road topological structure at the same time can be provided for an unmanned platform in a complex cross-country environment, and the efficiency and reliability of path planning are remarkably improved.

The logistics transport vehicle comprises a cargo box body and a vehicle frame box, a first variable-diameter wheel is arranged on the outer side of the vehicle frame box, a second variable-diameter wheel is arranged on the outer side of the vehicle frame box, a third variable-diameter wheel is arranged on the outer side of the vehicle frame box, and a fourth variable-diameter wheel is arranged on the outer side of the vehicle frame box. The first variable-diameter wheel and the second variable-diameter wheel are rotationally connected to the two sides of the front end of the frame box respectively. The first to fourth variable-diameter wheels are arranged, and each variable-diameter wheel adopts a single-drive variable-diameter mechanism formed by matching a shear fork rod group with a middle rod group, so that the diameter of the wheel can be changed in real time, the wheel diameter can be increased to increase the obstacle crossing height when the vehicle encounters a higher obstacle, and the wheel diameter can be reduced to reduce the height of the whole vehicle when the vehicle needs to pass through a narrow space; and the trafficability and maneuverability of the logistics transport vehicle in complicated terrains such as warehouse thresholds, stairs and uneven road surfaces are obviously enhanced.

The invention provides a differential device which can maintain turning performance and improve trafficability. A differential device (1) is provided with: a differential case (7) rotatably disposed; a pinion (11) that is rotatably supported within the differential case and revolves by the rotation of the differential case; and a pair of side gears (13, 15) that mesh with the pinion gear and are rotatable relative to each other, in which the pinion gear and the side gears are configured from a bevel gear set, and a first planar portion (39) that is orthogonal to the rotation axis is provided on the rear surface side of the gear portion of the side gears. The differential case is provided with a second planar portion (41) which is orthogonal to the rotating shaft and is disposed so as to face the first planar portion (39) so as to be able to abut against the first planar portion (39), and a first abutting force is applied between the first planar portion (39) and the second planar portion (41) by a biasing member (43). The meshing reaction force between the pinion gear and the side gear imparts a second abutting force between the first planar portion (39) and the second planar portion (41).

This invention relates to the field of autonomous driving technology, and particularly to a method and apparatus for single-frame and multi-frame collaborative drivable point cloud segmentation based on LiDAR. The method includes: inputting raw LiDAR data into a single-frame point cloud segmentation algorithm to obtain a single-frame point cloud segmentation result; inputting the raw LiDAR data into a preset real-time localization and mapping algorithm to obtain a downsampled point cloud map; performing drivability segmentation on the downsampled point cloud map to obtain a grid-based drivability analysis result; and fusing the single-frame point cloud segmentation result and the grid-based drivability analysis result to obtain a point cloud map with semantic information. This solves the problems of existing point cloud segmentation and roadside detection methods in autonomous driving, such as lack of labeled point cloud data, difficulty in interpretability and deployment in real vehicles, and poor segmentation results.