Method and system for monitoring continuous road closure cone barrel in road closed area based on laser radar

Abstract

The invention discloses a laser radar-based continuous road closure cone barrel monitoring method and system for a road closed area, and the method comprises the steps: employing a laser radar and a bus steering engine, and assembling the laser radar on the bus steering engine to form laser radar cone barrel monitoring equipment; a laser radar cone barrel monitoring device scans environment point cloud data of a road closed area and transmits the environment point cloud data to an analysis server, and the analysis server obtains a road closure cone barrel point cloud data set continuously arranged in the road closed area through the environment point cloud data and identifies the number and position of each road closure cone barrel; and the analysis server calculates the distance between the adjacent channel sealing cone buckets through the channel sealing cone bucket point cloud data set, and performs compliance monitoring on the placement spacing of the continuously arranged channel sealing cone buckets. The method has the advantages that the cost is low, the arrangement is convenient, the influence of increase and decrease of the arrangement number of the road sealing conical barrels on the cost is avoided, the method can be used in closed areas of tunnels and bridge opening roads, and the environment application range is wide.

Description

Technical Field

[0001] The present invention relates to the field of road closure facilities, and in particular to a laser radar-based method and system for continuous road closure cone monitoring in a closed road area. Background Art

[0002] During road maintenance or traffic control, road-blocking cones need to be deployed to close the road. Since the road-blocking cones are placed continuously, the compliance of the continuously placed road-blocking cones needs to be monitored. The traditional monitoring method is manual inspection, which is inefficient and untimely. By installing GPS locators on the road-blocking cones, the more road-blocking cones are deployed, the higher the cost. In addition, the GPS locator has no signal in the underground space of the tunnel and cannot return data for monitoring. In addition, with the popularization of autonomous driving, the wrong order of collecting continuous road-blocking cones can easily cause misjudgment of vehicles, thereby causing traffic accidents. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for monitoring continuous road closure cones in closed road areas based on laser radar, so as to solve the problem of how to timely, safely and effectively manage and monitor the compliance of the placement of continuous road closure cones in closed road areas.

[0004] In order to solve the above technical problems, the present invention provides a method for monitoring continuous road closure cones in closed areas based on laser radar, comprising:

[0005] Step 110, using a laser radar and a bus servo, assembling the laser radar on the bus servo to form a laser radar cone barrel monitoring device;

[0006] Step 120, the environment point cloud data of the road closure area is scanned by the laser radar cone monitoring device and transmitted to the analysis server. The analysis server obtains the point cloud data set of the road closure cones arranged continuously in the road closure area through the environment point cloud data, and identifies the number and position of each road closure cone.

[0007] Step 130: The analysis server calculates the distance between adjacent road closure cones through the road closure cone point cloud data set, and performs compliance monitoring on the placement spacing of the consecutively arranged road closure cones.

[0008] Furthermore, the laser radar-based road closure area continuous road closure cone barrel monitoring method provided by the present invention also includes:

[0009] Step 140: The analysis server monitors the order of collecting the continuously arranged road-closing cones through the road-closing cone point cloud data set.

[0010] Furthermore, in the method for monitoring continuous road closure cones in a road closure area based on laser radar provided by the present invention, in step 140, the method for the analysis server to monitor the collection order of the continuously arranged road closure cones through the road closure cone point cloud data set includes:

[0011] Step 141, the analysis server identifies the position of the road closure cones at each time based on the road closure cone point cloud data set transmitted back by the laser radar cone monitoring device at different times in the road closure area;

[0012] Step 142, the analysis server determines whether the position and number of road closing cones in the road closing cone point cloud data set at the next moment match those at the previous moment. If they match, it is determined that the road closing cone has not been collected. If they do not match, it is determined that there is a missing cone at the next moment and the missing road closing cone is collected, and the time sequence of the collected road closing cones is recorded to monitor the collection order of the continuously arranged road closing cones.

[0013] Furthermore, in the laser radar-based road closure area continuous road closure cone monitoring method provided by the present invention, in the step 120, the environmental point cloud data of the road closure area scanned by the laser radar cone monitoring device is transmitted to the analysis server, and the analysis server obtains the point cloud data of the road closure cones arranged continuously in the road closure area through the environmental point cloud data, and the method for identifying the number and position of each road closure cone includes:

[0014] Step 121, placing the laser radar cone barrel monitoring device at the junction of the upstream transition zone and the buffer zone of the road closure area, and setting the initial viewing angle normal of the laser radar;

[0015] Step 122, controlling the laser radar scanning by the rotation of the bus servo to obtain the three-dimensional environmental point cloud data of the road closure area;

[0016] Step 123, transmitting the three-dimensional environment point cloud data to the analysis server;

[0017] Step 124, the three-dimensional environment point cloud data is processed by the analysis server to form an environment point cloud set and remove noise;

[0018] Step 125, the analysis server removes ground points from the denoised environmental point cloud set by using a random sampling consistent plane segmentation algorithm to obtain an environmental point cloud set after the ground is removed;

[0019] Step 126, the analysis server clusters the environment point cloud set after removing the ground through the Euclidean point cloud clustering method;

[0020] Step 127, analyzing the shape feature recognition of the road closure cones in the clustered environmental point cloud set by the server, obtaining a road closure cone point cloud data set, and identifying the number of road closure cones in the road closure cone point cloud data set;

[0021] Step 128: The analysis server calculates the centroid of each road closure cone in the road closure cone point cloud data set, and identifies the position of each road closure cone through the centroid position.

[0022] Furthermore, in the laser radar-based continuous road closure cone monitoring method for road closure areas provided by the present invention, in step 122, the method of obtaining three-dimensional environmental point cloud data of the road closure area by controlling the laser radar scanning through the rotation of the bus servo includes:

[0023] The laser radar transmits and receives laser pulses for scanning. Every time the bus servo rotates an angle, the laser radar scans and collects point cloud data once, which is recorded as a group of point cloud data. After the scanning is completed, multiple groups of point cloud data are obtained to form the three-dimensional environmental point cloud data of the closed road area.

[0024] Furthermore, in the laser radar-based road closure area continuous road closure cone monitoring method provided by the present invention, in step 124, the method of processing the three-dimensional environmental point cloud data by the analysis server to form an environmental point cloud set includes:

[0025] Step 1241, performing a rotation transformation on each group of point cloud data after the first group of point cloud data through a rotation matrix according to the rotation angle of the laser radar, to obtain each group of point cloud data corresponding to the rotation angle;

[0026] Step 1242, splicing the first set of point cloud data and the subsequent sets of point cloud data that have been rotated and transformed to form an environment point cloud set.

[0027] Furthermore, in the laser radar-based road closure area continuous road closure cone monitoring method provided by the present invention, in step 124, the method for denoising the environmental point cloud set includes:

[0028] Step 1243, filtering the environment point cloud set formed by splicing by using a voxel filtering algorithm, and setting the voxel grid size according to the specification size of the road closure cone barrel;

[0029] Step 1244, mapping the point cloud data in the stitched environment point cloud set into a voxel grid;

[0030] Step 1245, simplify and merge multiple point cloud data in the same voxel grid into one point, collect the merged points into a voxel set, calculate the centroid and number of each point in the voxel set, and form a denoised environmental point cloud set.

[0031] Furthermore, in the laser radar-based road closure area continuous road closure cone monitoring method provided by the present invention, in step 125, the analysis server removes ground points in the denoised environmental point cloud set by a random sampling consistent plane segmentation algorithm, and the environmental point cloud set after removing the ground includes:

[0032] By iteratively randomly sampling a set of point cloud data, fitting a plane equation, and finding all point cloud data close to the plane equation as ground point data, the identified ground point cloud data is removed from the environmental point cloud set to obtain the environmental point cloud set after removing the ground.

[0033] Furthermore, in the laser radar-based road closure area continuous road closure cone monitoring method provided by the present invention, in step 130, the method in which the analysis server calculates the distance between adjacent road closure cones through the road closure cone point cloud data set includes:

[0034] Step 131: the analysis server sorts the number of road closure cones and the set of their positions in the road closure cone point cloud data set according to the y coordinate, and sorts the road closure cones from near to far along the lane direction to obtain a sorted coordinate set of the road closure cones;

[0035] Step 132: The analysis server calculates the distance between adjacent road blocking cones according to the position coordinates of the front and rear adjacent road blocking cones in the sorted coordinate set of the road blocking cones.

[0036] In order to solve the above technical problems, the present invention also provides a laser radar-based road closure area continuous road closure cone barrel monitoring system, comprising:

[0037] A laser radar cone monitoring device, used to scan environmental point cloud data of a closed road area, wherein the laser radar cone monitoring device includes a bus servo and a laser radar mounted thereon;

[0038] The analysis server is used to obtain a point cloud data set of road closure cones arranged continuously in the road closure area based on the environmental point cloud data of the road closure area scanned by the lidar cone monitoring equipment, identify the number and position of each road closure cone based on the road closure cone point cloud data set, and calculate the distance between adjacent road closure cones. Through the distance calculation result, it is judged whether the placement spacing of the continuously arranged road closure cones is compliant.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The laser radar-based road closure area continuous road closure cone monitoring method and system provided by the present invention controls the laser radar to rotate and scan the environmental point cloud data of the road closure area through the bus servo to transmit it to the analysis server. The analysis server obtains the point cloud data set of the road closure cones arranged continuously in the road closure area through the environmental point cloud data, identifies the number and position of each road closure cone; calculates the distance between adjacent road closure cones by the position of adjacent road closure cones, so as to monitor whether the placement spacing of the continuously arranged road closure cones is compliant. Compared with the solution of setting GPS locator monitoring on each road closure cone, it has low cost and convenient deployment, is not affected by the increase or decrease in the number of road closure cones deployed, and can monitor whether the placement spacing of the continuously arranged road closure cones is compliant in the road closure area where the GPS locator cannot track the position in underground areas such as tunnels and bridge holes, and has the advantage of a wide range of environmental applicability. Compared with manual detection, it has the advantages of timeliness and safety. The laser radar cone monitoring device and the analysis server can remotely manage the continuously arranged road closure cones in the road closure area. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a method for continuous road closure cone monitoring in closed road areas based on LiDAR;

[0042] Figure 2 It is a schematic diagram of the block structure of the continuous road closure cone monitoring system based on laser radar;

[0043] Figure 3 It is a schematic diagram of the block structure of the laser radar cone barrel monitoring equipment;

[0044] Figure 4 It is a schematic diagram of the positional relationship of the laser radar cone monitoring equipment arranged at the road closure cones continuously arranged in the road closure area;

[0045] Figures 5 to 8 It is a schematic diagram of the scanning process of the laser radar cone monitoring equipment on the road closure cones continuously deployed in the road closure area;

[0046] As shown in the figure:

[0047] 200. A continuous road closure cone monitoring system based on laser radar in closed road areas; 210. A laser radar cone monitoring device; 220. An analysis server; 230. A monitoring terminal;

[0048] 300, Road;

[0049] 400. Road blocking cones. DETAILED DESCRIPTION

[0050] The present invention is described in detail below in conjunction with the accompanying drawings: The advantages and features of the present invention will become more apparent from the following description. It should be noted that the accompanying drawings are in very simplified form and in non-precise proportions, and are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention.

[0051] Please refer to Figure 1 The embodiment of the present invention provides a method for monitoring continuous road closure cones in a closed road area based on laser radar, which may include:

[0052] Step 110, using a laser radar 211 and a bus servo 212, assembling the laser radar 211 on the bus servo 212 to form a laser radar cone barrel monitoring device 210, such as Figures 2 to 4 The bus servo 212 is calibrated, and the initial viewing angle of the bus servo 212 is set. The bus servo 212 can read the current rotation angle of the bus servo 212 through the serial port as the scanning angle of the laser radar 211.

[0053] Step 120, the laser radar cone monitoring device 210 scans the environmental point cloud data of the road closure area and transmits it to the analysis server 220. The analysis server 220 obtains the point cloud data set of the road closure cones arranged continuously in the road closure area through the environmental point cloud data, and identifies the number and position of each road closure cone 400. The laser radar 211 and the bus servo 212 are both connected to the analysis server 220. Specifically, it may include:

[0054] Step 121, place the laser radar cone monitoring device 210 at the junction of the upstream transition zone and the buffer zone of the road closure area, and set the initial viewing angle normal l0 of the laser radar 211, where l0 is the opposite direction of the road 300 in the entire road closure area, such as Figure 4 After the laser radar 211 is started, it is necessary to collect the arrangement of the road blocking cones 400 in the entire closed area, and it is necessary to start the bus servo 212 to rotate and cover the range of all the road blocking cones 400 according to the FOV angle of the laser radar.

[0055] Step 122, the laser radar 211 is controlled to scan by rotating the bus servo 212, such as Figures 5 to 8 As shown, the three-dimensional environmental point cloud data of the road closed area can be obtained as:

[0056] D i ={(x i ,y i ,z i ,,reflect i )|i=1,2……N} (1);

[0057] Among them, (x i ,y i,z i ) represents the spatial coordinates of the point cloud data, reflect i It represents the reflectivity of the i-th point of the 3D environment point cloud data, and N is the number of point clouds obtained by a single scan.

[0058] The specific method for obtaining the three-dimensional environmental point cloud data of the road closure area can be: the laser radar 211 transmits and receives laser pulses for scanning, and the bus servo 212 rotates an angle each time the laser radar 211 scans and collects point cloud data once, which is recorded as a set of point cloud data. After the scanning is completed, multiple sets of point cloud data are obtained to form the three-dimensional environmental point cloud data of the road closure area. The rotation angle of the bus servo 212 is the scanning angle of the laser radar 211. The laser radar 211 scans an angle Δ α When collecting point cloud data once, the total number of angle scans of the laser radar 211, that is, the number of groups of point cloud data, is:

[0059] α k =α0+k×Δ α (2);

[0060] Among them, α k is the number of laser radar angle scans, α0 is the initial angle of the laser radar, k is the number of times, Δ α is the scanning angle.

[0061] In order to facilitate data transmission, the 3D environment point cloud data can be saved as a CSV file F.

[0062] Step 123, the three-dimensional environment point cloud data is transmitted to the analysis server 220. The three-dimensional environment point cloud data can be transmitted to the analysis server 220 in the form of a CSV file F through the http protocol.

[0063] Step 124: The three-dimensional environment point cloud data is processed by the analysis server 220 to form an environment point cloud set and remove noise. The specific steps may include:

[0064] Step 1241, according to the rotation angle of the laser radar 211, each group of point cloud data after the first group of point cloud data is rotated by a rotation matrix to obtain each group of point cloud data corresponding to the rotation angle. i (α k ), the rotation transformation can be performed by the following rotation matrix:

[0065]

[0066] Through the above rotation matrix (x i ,y i ,z i )The point cloud data obtained after rotation is:

[0067]

[0068] Among them, x i ,y i ,z i For each set of point cloud data D before rotation i (α k ) spatial coordinates, R(α k ) is the rotation value of the rotation matrix, x i’ ,y i’ ,z i’ After rotation, each set of point cloud data D i '(α k )’s spatial coordinates.

[0069] Step 1242: the first set of point cloud data and each set of point cloud data D after rotation transformation i (α k ) are spliced ​​to form an environmental point cloud set, which can be recorded as: Where K is the number of point cloud sets, Merge of point cloud collections.

[0070] Step 1243 , filtering the environment point cloud set formed by splicing by using a voxel filtering algorithm, and setting the voxel grid size according to the specification size of the road closure cone barrel 400 .

[0071] For the accuracy of data processing, the voxel grid is set in combination with the size of the road sealing cone barrel 400, for example, the voxel grid size is set to: lx=ly=lz=100mm, wherein lx, ly, lz are the sizes of the voxel grid.

[0072] Step 1244, mapping the point cloud data in the spliced ​​environment point cloud set to the voxel grid to obtain the voxel coordinates (v x ,v y ,v z ),Right now:

[0073]

[0074] Among them, x in formula (5) i ,y i , z i means x i’ ,y i’ , z i’ .

[0075] Step 1245, simplify and merge multiple point cloud data in the same voxel grid into one point, and collect the merged points into a voxel set Calculate the centroid (coordinate) and number of each point in the voxel set to form a denoised environmental point cloud. The centroid of each point is:

[0076]

[0077] in, is the centroid coordinate, M is the number of points. Here M refers to the merged points.

[0078] The average value of the emissivity is calculated by formula (6);

[0079]

[0080] in, is the average value of the emissivity, M is the number of points;

[0081] The new point cloud data D' is formed by the average value of the emissivity and the denoised environmental point cloud set, that is:

[0082] D'={(x i ,y i ,z i ,,reflect j )|j=1,2……M} (7);

[0083] Among them, x in formula (7) i ,y i ,z i , means reflect j Represents the reflectivity of the j-th point in the new point cloud data, M is the number of points, and j represents the j-th point in the new point cloud data.

[0084] The above steps 1243 to 1245 can filter out redundant points caused by stitching, so as to reduce the amount of point cloud data to be processed in subsequent steps and improve efficiency.

[0085] Step 125, the analysis server 220 removes the ground points in the denoised environment point cloud set by using the random sampling consistent Ransac plane segmentation algorithm to obtain the environment point cloud set after removing the ground. Specifically, it can be: by iteratively randomly sampling a set of point cloud data, fitting a plane equation, and finding all point cloud data close to the plane equation as ground points D ground , remove the identified ground point cloud data from the environmental point cloud set to obtain the environmental point cloud set after removing the ground. The plane equation can be:

[0086] Ax+By+Cz+E=0 (8);

[0087] Where A, B, C, E are constants, and x, y, z are coordinates in the Cartesian coordinate system;

[0088] At this point, the environment point cloud after removing the ground is:

[0089] D' no-ground =D'-D ground , (9);

[0090] D' no-ground is the environmental point cloud after removing the ground, D' is the environmental point cloud after denoising, and D ground is a ground point.

[0091] Step 126, the analysis server 220 clusters the environment point cloud set after removing the ground through the Euclidean point cloud clustering method to obtain a clustered environment point cloud set:

[0092] C j ={(x i ,y i ,z i ,,reflect i )|i=1,2……N j} (10);

[0093] Among them, C j The table shows the environment point cloud after clustering, x i ,y i ,z i Represents the spatial coordinates of point cloud data, reflect i Represents reflectivity, N j is the number of points in the clustered environment point cloud. The clustering threshold can be set as needed, for example, the threshold is set to 1000.

[0094] In step 127, the analysis server 220 recognizes the shape features of the road closure cones 400 in the clustered environmental point cloud set, obtains a road closure cone point cloud data set, and identifies the number of road closure cones 400 in the road closure cone point cloud data set. The following description takes a conical road closure cone 400 as an example.

[0095] By analyzing the shape of each cluster, we can identify whether it is a road closure cone 400 and analyze the height difference of the point cloud in each cluster:

[0096] h i =max (z i )-min(z i ) (11);

[0097] Among them, h i is the height difference of the point cloud in each cluster, max(z i) represents the point cloud with the largest height value in the clustered point cloud, min(z i ) represents the point cloud with the smallest height value in the clustered point cloud set;

[0098] Compare i The height standard value of the road closure cone barrel 400 is used to preliminarily screen the clustering results that meet the conditions, and then the reflectivity of the clustering results is reflected. i For further judgment, we finally fit a circle by identifying the projection of the clustering result on the (x, y) plane in the Cartesian coordinate system, and mark the identified cluster set of road closure cones as follows:

[0099] C cone ={(x i ,y i ,z i ,,reflect i )|i=1,2……N i} (12);

[0100] Among them, C cone To identify the cluster set of road closure cones, N i is the number of clustered road closure cones 400 points.

[0101] Step 128, the analysis server 220 calculates the centroid of each road closure cone 400 in the road closure cone point cloud data set, and identifies the position of each road closure cone 400 through the centroid position, that is, the centroid coordinates of the road closure cone 400

[0102] At this time, the set of centroid coordinates of the road blocking cone barrel 400 is:

[0103] Cone i ={(x i ,y i ,z i ,,reflect i )|i=1,2……N} (12);

[0104] Among them, Cone i A set of centroid coordinates of the road-closing cones 400, where N is the number of identified cones.

[0105] In step 130, the analysis server 220 calculates the distance between adjacent road-closing cones 400 through the road-closing cone point cloud data set, and performs compliance monitoring on the placement spacing of the continuously arranged road-closing cones 400.

[0106] Step 131: The analysis server 220 sorts the number and position of the road-closing cones 400 in the road-closing cone point cloud data set according to the y coordinate, and sorts the road-closing cones 400 from near to far along the lane direction to obtain a sorted centroid coordinate set of the road-closing cones 400, namely:

[0107] C sorted ={(x j1 ,y j1 ,z j1 ), (x j2 ,y j2 ,z j2 )…(x jN ,y jN ,z jN )} (13);

[0108] Among them, C sorted is the sorted centroid coordinate set of the road blocking cone barrel 400, y j1 ≤y j2 ≤…≤y jN The sorting only considers the y coordinate direction. When the sorting of the road-blocking cone barrels 400 is distributed in other coordinate directions, the sorting considers the layout direction of the road-blocking cone barrels 400.

[0109] Step 132: the analysis server 220 calculates the distance between adjacent road blocking cones 400 according to the position coordinates of the front and rear adjacent road blocking cones 400 in the sorted coordinate set of the road blocking cones 400, that is:

[0110]

[0111] Among them, d k is the distance between the kth road blocking cone 400 and the k+1th road blocking cone 400; x jk is the x coordinate of the kth road blocking cone 400, x jk+1 is the x coordinate of the k+1th road blocking cone 400; y jk is the y coordinate of the kth road blocking cone 400, y jk+1 is the y coordinate of the k+1th road blocking cone 400; jk is the z coordinate of the kth road blocking cone 400, z jk+1 is the z coordinate of the k+1th road-sealing cone 400.

[0112] In order to facilitate remote management and avoid traffic accidents, an alarm will be issued for road blocking cones 400 that are placed at spacings that do not meet regulatory requirements, providing a basis for subsequent improvement measures for safety management.

[0113] In step 140, the analysis server 220 may monitor the order of collecting the continuously arranged road closure cones 400 through the road closure cone point cloud data set. Specifically, it may include:

[0114] Step 141, the analysis server 220 analyzes the laser radar cone barrel monitoring device 210 at different times t n The point cloud data set of the road closure cones in the road closure area is transmitted back to identify the position of the road closure cones 400 at each time, that is, the set of centroid coordinates of the road closure cones 400 at each time is identified as:

[0115] Cone i (t n )={(x i ,y i ,z i ,,reflect i )|i=1,2……N(t n )} (15);

[0116] Among them, Cone i (t n ) is the set of centroid coordinates of the road blocking cone 400 at the nth moment, t n is the nth moment.

[0117] Step 142, the analysis server 220 determines the next time t n Compared with the previous moment t n-1 Check whether the positions and quantities of the road-closing cones 400 in the road-closing cone point cloud data set match. If they match, it is determined that the road-closing cones 400 have not been collected. If they do not match, it is determined that there is a missing cone at the next moment and the missing road-closing cones 400 are collected. The time sequence of the collected road-closing cones 400 is recorded to monitor the collection sequence of the continuously arranged road-closing cones 400. Specifically:

[0118] Formula (16) is used to determine whether the positions and quantities of the road closure cones 400 in the road closure cone point cloud data set at the previous and next moments match.

[0119]

[0120] Among them, x i (t n ), y i (t n ), z i (t n ) is the three-dimensional coordinate of the ith road blocking cone 400 at the nth moment, x i (t n-1 ), y i (t n-1 ), z i (t n-1) is the three-dimensional coordinate of the i-1th road-sealing cone barrel 400 at the n-1th moment.

[0121] Please refer to Figures 2 to 3 The embodiment of the present invention further provides a laser radar-based road closure area continuous road closure cone barrel monitoring system 200, which adopts the above method and includes:

[0122] The laser radar cone monitoring device 210 is used to scan the environmental point cloud data of the road closure area. The laser radar cone monitoring device 210 includes a bus servo 212 and a laser radar 211 mounted thereon.

[0123] The analysis server 220 is used to obtain a point cloud data set of road closure cones continuously arranged in the road closure area based on the environmental point cloud data of the road closure area scanned by the laser radar cone monitoring equipment 210, identify the number and position of each road closure cone 400 based on the road closure cone point cloud data set, and calculate the distance between adjacent road closure cones 400, and judge whether the placement spacing of the continuously arranged road closure cones 400 is compliant through the distance calculation result.

[0124] The method and system for monitoring continuous road closure cones 400 in a road closure area based on a laser radar 211 provided in an embodiment of the present invention controls the laser radar 211 to rotate and scan the environmental point cloud data of the road closure area through the bus servo 212, and transmits it to the analysis server 220. The analysis server 220 obtains the point cloud data set of road closure cones arranged continuously in the road closure area through the environmental point cloud data, identifies the number and position of each road closure cone 400; calculates the distance between adjacent road closure cones 400 by the position of adjacent road closure cones 400, and monitors whether the placement spacing of the continuously arranged road closure cones 400 is compliant. Compared with the solution of setting a GPS locator for monitoring on each road closure cone 400, it has low cost and convenient deployment, is not affected by the increase or decrease in the number of road closure cones 400, and can monitor whether the placement spacing of the continuously arranged road closure cones 400 is compliant in the road closure area where the GPS locator cannot track the position in underground areas such as tunnels and bridge holes, and has the advantage of a wide range of environmental applications. Compared with manual detection, it has the advantages of timeliness and safety. The laser radar cone monitoring device 210 and the analysis server 220 can remotely manage the road closure cones 400 that are continuously arranged in the road closure area.

[0125] The present invention is not limited to the above-mentioned specific implementation modes. Obviously, the above-mentioned embodiments are only some embodiments of the embodiments of the present invention, but not all embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention. Those skilled in the art can make other levels of modifications and changes to the present invention. In this way, if these modifications and changes of the present invention fall within the scope of the claims of the present invention, the present invention is also intended to include these changes and changes.

Claims

1. A method for monitoring continuous road closure cones in closed road areas based on laser radar, characterized in that: include: Step 110, using a laser radar and a bus servo, assembling the laser radar on the bus servo to form a laser radar cone barrel monitoring device; Step 120, the environment point cloud data of the road closure area is scanned by the laser radar cone monitoring device and transmitted to the analysis server. The analysis server obtains the point cloud data set of the road closure cones arranged continuously in the road closure area through the environment point cloud data, and identifies the number and position of each road closure cone. Step 130: The analysis server calculates the distance between adjacent road closure cones through the road closure cone point cloud data set, and performs compliance monitoring on the placement spacing of the consecutively arranged road closure cones.

2. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 1 is characterized in that: Also includes: Step 140: The analysis server monitors the order of collecting the continuously arranged road-closing cones through the road-closing cone point cloud data set.

3. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 2 is characterized in that: In step 140, the method for the analysis server to monitor the collection order of the continuously arranged road closure cones through the road closure cone point cloud data set includes: Step 141, the analysis server identifies the position of the road closure cones at each time based on the road closure cone point cloud data set transmitted back by the laser radar cone monitoring device at different times in the road closure area; Step 142, the analysis server determines whether the position and number of road closing cones in the road closing cone point cloud data set at the next moment match those at the previous moment. If they match, it is determined that the road closing cone has not been collected. If they do not match, it is determined that there is a missing cone at the next moment and the missing road closing cone is collected, and the time sequence of the collected road closing cones is recorded to monitor the collection order of the continuously arranged road closing cones.

4. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 1 is characterized in that: In step 120, the environmental point cloud data of the road closure area scanned by the laser radar cone monitoring device is transmitted to the analysis server, and the analysis server obtains the point cloud data of the road closure cones arranged continuously in the road closure area through the environmental point cloud data. The method for identifying the number and position of each road closure cone includes: Step 121, placing the laser radar cone barrel monitoring device at the junction of the upstream transition zone and the buffer zone of the road closure area, and setting the initial viewing angle normal of the laser radar; Step 122, controlling the laser radar scanning by the rotation of the bus servo to obtain the three-dimensional environmental point cloud data of the road closure area; Step 123, transmitting the three-dimensional environment point cloud data to the analysis server; Step 124, the three-dimensional environment point cloud data is processed by the analysis server to form an environment point cloud set and remove noise; Step 125, the analysis server removes ground points from the denoised environmental point cloud set by using a random sampling consistent plane segmentation algorithm to obtain an environmental point cloud set after the ground is removed; Step 126, the analysis server clusters the environment point cloud set after removing the ground through the Euclidean point cloud clustering method; Step 127, analyzing the shape feature recognition of the road closure cones in the clustered environmental point cloud set by the server, obtaining a road closure cone point cloud data set, and identifying the number of road closure cones in the road closure cone point cloud data set; Step 128: The analysis server calculates the centroid of each road closure cone in the road closure cone point cloud data set, and identifies the position of each road closure cone through the centroid position.

5. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 4 is characterized in that: In step 122, the method of obtaining three-dimensional environmental point cloud data of the road closure area by controlling the laser radar scanning through the rotation of the bus servo includes: The laser radar transmits and receives laser pulses for scanning. Every time the bus servo rotates an angle, the laser radar scans and collects point cloud data once, which is recorded as a group of point cloud data. After the scanning is completed, multiple groups of point cloud data are obtained to form the three-dimensional environmental point cloud data of the closed road area.

6. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 5 is characterized in that: In step 124, the method of processing the three-dimensional environment point cloud data by the analysis server to form an environment point cloud set includes: Step 1241, performing a rotation transformation on each group of point cloud data after the first group of point cloud data through a rotation matrix according to the rotation angle of the laser radar, to obtain each group of point cloud data corresponding to the rotation angle; Step 1242, splicing the first set of point cloud data and the subsequent sets of point cloud data that have been rotated and transformed to form an environment point cloud set.

7. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 6 is characterized in that: In step 124, the method for denoising the environment point cloud includes: Step 1243, filtering the environment point cloud set formed by splicing by using a voxel filtering algorithm, and setting the voxel grid size according to the specification size of the road closure cone barrel; Step 1244, mapping the point cloud data in the stitched environment point cloud set into a voxel grid; Step 1245, simplify and merge multiple point cloud data in the same voxel grid into one point, collect the merged points into a voxel set, calculate the centroid and number of each point in the voxel set, and form a denoised environmental point cloud set.

8. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 7 is characterized in that: In step 125, the analysis server removes ground points from the denoised environmental point cloud set by using a random sampling consistent plane segmentation algorithm, and the environmental point cloud set after removing the ground includes: By iteratively randomly sampling a set of point cloud data, fitting a plane equation, and finding all point cloud data close to the plane equation as ground point data, the identified ground point cloud data is removed from the environmental point cloud set to obtain the environmental point cloud set after removing the ground.

9. The method for monitoring continuous road closure cones in closed areas based on laser radar according to claim 4 is characterized in that: In step 130, the method in which the analysis server calculates the distance between adjacent road closure cones using the road closure cone point cloud data set includes: Step 131: the analysis server sorts the number of road closure cones and the set of their positions in the road closure cone point cloud data set according to the y coordinate, and sorts the road closure cones from near to far along the lane direction to obtain a sorted coordinate set of the road closure cones; Step 132: The analysis server calculates the distance between adjacent road blocking cones according to the position coordinates of the front and rear adjacent road blocking cones in the sorted coordinate set of the road blocking cones.

10. A laser radar-based road closure area continuous road closure cone barrel monitoring system, characterized in that: include: A laser radar cone monitoring device, used to scan environmental point cloud data of a closed road area, wherein the laser radar cone monitoring device includes a bus servo and a laser radar mounted thereon; The analysis server is used to obtain a point cloud data set of road closure cones arranged continuously in the road closure area based on the environmental point cloud data of the road closure area scanned by the lidar cone monitoring equipment, identify the number and position of each road closure cone based on the road closure cone point cloud data set, and calculate the distance between adjacent road closure cones. Through the distance calculation result, it is judged whether the placement spacing of the continuously arranged road closure cones is compliant.

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