BIM visualization modeling method for municipal road engineering based on vehicle positioning data

Abstract

The application discloses a BIM visual modeling method for municipal road engineering based on vehicle positioning data, wherein a vehicle equipped with a positioning device and a laser radar system is used to collect positioning and point cloud data when driving on a road with a preset length, so that the real-time positioning three-dimensional coordinates of the vehicle are calculated on a background server, so that the efficient modeling purpose of modeling while driving is achieved, and the simulation model is compared with the actual construction road to obtain the construction quality evaluation result.

Description

TECHNICAL FIELD

[0001] The present application relates to a BIM visualization modeling method for municipal road engineering, in particular to a BIM visualization modeling method for municipal road engineering based on vehicle positioning data, and belongs to the field of geographic mapping. BACKGROUND

[0002] The image obtained by scanning through a remote sensing satellite does not contain elevation data, so the point cloud technology gives a remedy. However, the problem is that the fusion technology of remote sensing images and point cloud images is usually needed to complete a real three-dimensional map. Such a map cannot be realistically simulated due to the blurred contours of the point cloud data, and such a fused map can only provide coordinate data in essence for human visual organs, and cannot realistically present the three-dimensional form of the road. The unmanned aerial vehicle surveying needs to additionally purchase high-cost unmanned aerial vehicles, and needs to fly at a fixed height and time, and the image processing speed is very slow, often requiring more advanced graphics cards. Therefore, the development of visualization modeling is limited, which is one of the problems.

[0003] On the other hand, the prior art is simply to convert design drawings into visualization, and to visualize for visualization, and does not specifically use visualization to do other work, such as evaluating road engineering quality. Even the evaluation is a post-construction evaluation. When the evaluation is unqualified, it is already impossible to save, which greatly wastes social resources. Therefore, how to timely discover construction quality problems, and real-time supervision, obtain evaluation data basis, and guide construction correction, is another problem to be solved. SUMMARY

[0004] In view of the above problems of the prior art, the present application will be redesigned in the following aspects: first, a positioning device carried by a vehicle is used to provide a map plane coordinate, second, the coordinates positioned during the vehicle driving are mapped to the corresponding point cloud to obtain the corresponding elevation, third, the positioning coordinates and the corresponding elevation are used to obtain real-time three-dimensional positioning during driving, so as to form a three-dimensional trajectory of the road while driving. Thus, a realistic road modeling can be formed through texture rendering or other methods.

[0005] Based on the above considerations, the present application provides a BIM visualization modeling method for municipal road engineering based on vehicle positioning data, which is completed by a modeling system. The modeling system comprises at least one vehicle, each of which is equipped with a laser radar for collecting point cloud data, a vehicle positioning system for collecting positioning coordinates, and a remote server installed with BIM software, and specifically comprises the following steps:

[0006] S1 constructs a road with a preset length, so that a vehicle travels along a route of the road with the preset length that has been constructed from a starting point of the construction, sends a positioning signal every predetermined time when the vehicle is traveling, and sends laser radar point cloud data to a remote server;

[0007] S2 the server pre-processes the point cloud data, analyzes corresponding coordinates according to the positioning signal at each time, and finds points near the corresponding coordinates in the point cloud data, calculates a point in the near points that is closest to the same horizontal plane projection of the corresponding coordinate on the horizontal plane projection as the calibration point at this time;

[0008] S3 a segmented model of a road with different widths is constructed by a BIM software, and a three-dimensional model of the road is continuously generated as the travel proceeds;

[0009] S4 the remote server constructs a simulation three-dimensional rectangular coordinate system in a design drawing file, extracts the coordinates and elevations of each simulation calibration point in the design drawing file using a visualization script program in the BIM software, the simulation calibration point refers to a simulation vehicle that continues to travel on a subsequent road that has not been constructed after the road with the preset length according to the manner of S2, and the coordinates and elevations are the coordinates and elevations of the corresponding calibration point (i.e., the corresponding simulation calibration point in the simulation travel process) in the corresponding drawing file, forming a simulation road point combination; a simulation segmented model of a road with different widths is created by the BIM software, and a simulation three-dimensional model of the road is continuously generated after the three-dimensional model of the road generated in S3 as the simulation travel proceeds;

[0010] S5 the road with the preset length is continuously constructed, and steps S1-S4 are performed, the three-dimensional model of the road generated by steps S1-S3 is compared with the simulation three-dimensional model of the road formed by step S4, so as to evaluate the actual construction quality of the road.

[0011] Optionally, the preset length is 100-500m, and the predetermined time is 1-5s.

[0012] Optionally, the route of the road includes a road route according to a vehicle form of the road, including a center line of a single lane, a same-direction multi-lane, a reverse double-lane, and a reverse multi-lane.

[0013] Optionally, the pre-processing includes noise processing, and the BIM software includes Revit.

[0014] Optionally, in the point cloud data, a plurality of points near the corresponding coordinates are found, and a point in the near points that is closest to the same horizontal plane projection of the corresponding coordinate on the horizontal plane projection is calculated as the calibration point at this time.

[0015] S2-1 constructs a geographic rectangular coordinate system, presets a preset radius of 0.2-0.5 m, and projects each of the corresponding coordinates , is the sequential number of the calibration point, and is projected in the XY plane of the geographic rectangular coordinate system ,

[0016] S2-2 projects the point cloud data in the preset radius of the circle center in the XY plane , , is the number of the point cloud in the circle domain, and then the points in the corresponding point cloud data are the points near the plurality of corresponding coordinates;

[0017] S2-3 then calibrates the point , is the time.

[0018] Optionally, the segmented model and the simulation segmented model are models between two adjacent calibration points.

[0019] It can be understood that by subsequent simulation modeling in the geographic coordinate system of the point cloud data after real modeling, construction problems such as road deviation, road size, and road elevation can be found in time in comparison with subsequent real construction, so as to avoid waste of resources in time.

[0020] Therefore, optionally, the evaluation of the actual construction quality of the road includes road deviation, road size, and road elevation.

[0021] Optionally, steps S1-S3 are used to generate a three-dimensional model of any constructed road on any constructed road.

[0022] A vehicle for implementing a municipal road engineering BIM visualization modeling method based on vehicle positioning data, comprising an intelligent vehicle machine, a laser radar arranged on a windshield for visualization modeling, and a vehicle-mounted positioning system on a roof, the intelligent vehicle machine being in communication with the remote server.

[0023] Preferably, the vehicle-mounted positioning system can be controlled to be closed by the intelligent vehicle machine, users can choose to open the vehicle-mounted positioning system for paid participation in modeling, and regardless of participation or not, users can choose to open the positioning signal after opening to be official confidential or willing to be public.

[0024] Preferably, the user can specify a public geographic range or specify other users or non-users to be public.

[0025] Optionally, users can obtain the notice of paid participation in modeling through the intelligent vehicle machine and apply online to participate.

[0026] Optionally, the method of specifying the other users or non-users that the disclosure is facing is facing the hand-held smart mobile devices of the other users or non-users.

[0027] Preferably, the hand-held smart mobile device is a smart phone.

[0028] It should be understood that the laser radar of the present application is not used for assisting driving, but for visualizing modeling. The vehicle with the above configuration can enable the cars running on the road to collect data and model quickly and efficiently.

[0029] The beneficial effects are that, through the form of building and simulation modeling, the real construction and simulation results are compared, the construction quality is evaluated, and engineering problems are found as early as possible. Through real-time data collection of road vehicles, low-cost and rapid background processing, simulation results and construction quality evaluation results are given. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 The schematic diagram of collecting positioning information and point cloud data in the process of vehicle driving in the construction of the reverse double-lane road with a preset length of 100m of embodiment 1 of the present application,

[0031] Figure 2 For Figure 1 The schematic diagram of the selected nearby points after the enlargement of the nearby circle domain of the midpoint D in the point cloud data at the end of the middle road, and the calibration point selection method,

[0032] Figure 3 The schematic diagram of the mutual connection of the road three-dimensional model and the simulation road three-dimensional model, wherein the comparison diagram of the actually constructed road and the simulation road three-dimensional model according to the drawing file is given,

[0033] Figure 4 The flow chart of step S4. DETAILED DESCRIPTION

[0034] Embodiment 1

[0035] As Figure 1 shown, a municipal road engineering BIM visual modeling method based on vehicle positioning data adopts a modeling system to complete, which comprises a vehicle and a laser radar arranged on the vehicle, a positioning device on the roof of the vehicle, and a remote server in communication with the vehicle.

[0036] The specific method comprises the following steps:

[0037] S1, a reverse double-lane road with a preset length of 100m is constructed, so that the vehicle drives from the construction starting point (such as Figure 1The vehicle begins to travel along the route of the 100m reverse two-way road that has been completed. When the vehicle is traveling, it sends a positioning signal to the remote server every 2 seconds as specified, and also sends the lidar point cloud data to the remote server. Figure 1 The text presents a local road segment with three adjacent points A, B, and C at 2-second intervals during the driving process, as well as point D at the end of 100m. The vehicle triggers the transmission of positioning signals and lidar point cloud data at these points.

[0038] The S2 server performs noise reduction on the point cloud data, analyzes the corresponding coordinates based on the positioning signal at each moment, finds multiple points near the corresponding coordinates in the point cloud data, calculates the point among these nearby points that is closest to the same horizontal projection of the corresponding coordinates on the horizontal plane, and uses it as the calibration point at that moment.

[0039] Specifically, such as Figure 2 As shown, with Figure 1 Taking the end of the circle as an example, point D is a circle with a radius of 50cm and has four point cloud data points a, b, c, and d that are outside the resolution limit.

[0040] like Figure 3 As shown, a simulated road model is constructed after the current preset length of 100m reverse two-way road.

[0041] Specifically, S2-1 involves constructing a geographic rectangular coordinate system XYZ-O, with a preset radius of 0.5m, and assigning each of the corresponding coordinates... , The calibration points are sequentially numbered and projected onto the XY plane of the geographic rectangular coordinate system. The circled area in the image is... Figure 1 The 100m section of the road contains three locations: A, B, and C.

[0042] S2-2 will Projecting point cloud data within a circular region of a predetermined radius centered on a circle onto the XY plane , Let the point cloud within the circular region be numbered, then The points in the corresponding point cloud data are points near multiple corresponding coordinates;

[0043] S2-3 is the calibration point. , Let's take the time as an example, specifically the time at site B.

[0044] S3 uses Revit to build segmented models of roads of different widths, and continuously generates 3D road models as driving progresses;

[0045] S4, as Figure 4As shown, the remote server constructs a simulation three-dimensional rectangular coordinate system 0-X'Y'Z' in the design drawing file, and uses the visualization script program in Revit to extract the coordinates and elevations of the corresponding calibration points of each simulation calibration point in the design drawing file. Figure 4 Examples of four simulation calibration points are given in

[0046] The simulation calibration point refers to following the method of S2. For example, Figure 1 after simulating the reverse two-way road with a preset length of 100m as shown, that is, after the end, continuing to simulate driving on the route of the subsequent road that has not been built, and its coordinates and elevation are the coordinates and elevation of the corresponding calibration point (that is, the calibration point corresponding to the simulation driving process) in the corresponding drawing file ( Figure 4 as shown), forming a combination of simulation road points; creating a simulation segmented model of roads with different widths (caused by the change in the number of lanes) through the Revit, and continuously connecting a simulation road three-dimensional model after the road three-dimensional model generated in S3 during the simulation driving (see Figure 4 );

[0047] S5 continues to build a road with a preset length and performs steps S1-S4, comparing the road three-dimensional model generated through steps S1-S3 and the simulation road three-dimensional model formed in the corresponding S4 step, so as to evaluate the actual construction quality of the road.

[0048] Specifically, to evaluate the actual construction quality of the road as Figure 3 shown, select a calibration point at random at the end of the actual construction, such as point D, draw a tangent line 1 to the driving route through D. Similarly, draw a tangent line 2 through the corresponding point D ( Figure 3 not shown in) in the simulation road three-dimensional model, and compare the orientations of the two in the geographical rectangular coordinate system XYZ-O. If it is within the preset angle range (for example, 0.01-0.08°), it is qualified; otherwise, it is unqualified. In Figure 3 for clarity, the actually constructed road is offset from its actual position so that the tangent line 1 and the tangent line 2 can be more intuitively distinguished. [[ID=​​​​​​​​​The vehicle-mounted positioning system can be turned off by the intelligent vehicle machine. The user can choose to participate in modeling for compensation and turn on the vehicle-mounted positioning system. Regardless of participation, the user can choose to open the positioning signal after the official secret or willingness to open.

[0052] The user can specify the non-user, such as family or friends, of the smartphone to be open. The user can also obtain the notice of participating in modeling for compensation through the intelligent vehicle machine and apply online. Thus, the user's vehicle driving position can be known, and the safety concern during the trip can be eliminated.

Claims

1. A municipal road engineering BIM visualization modeling method based on vehicle positioning data, characterized in that, The method is completed by a modeling system, the modeling system comprises at least one vehicle, the at least one vehicle is equipped with a laser radar for collecting point cloud data, a vehicle positioning system for collecting positioning coordinates, a remote server installed with BIM software, and specifically comprises the following steps: S1, a road with a preset length is constructed, so that the vehicle travels along the route of the road with the preset length which has been constructed from the construction starting point, and the positioning signal at every specified time is sent to the remote server and the laser radar point cloud data is sent to the remote server when the vehicle travels; S2, the server pre-processes the point cloud data, analyzes the corresponding coordinates according to the positioning signal at each time, and finds the points near the corresponding coordinates in the point cloud data, calculates the points in the same horizontal plane projection closest to the corresponding coordinates in the horizontal plane projection of these nearby points as the calibration point at this time; S3, a segmented model of the road with different widths is constructed by the BIM software, and the road three-dimensional model is continuously generated as the travel proceeds; S4, the remote server constructs a simulation three-dimensional rectangular coordinate system in the design drawing file, extracts the coordinates and elevations of the corresponding calibration points of each simulation calibration point in the design drawing file by using the visualization script program in the BIM software, the simulation calibration point refers to the simulation driving on the route of the subsequent road which has not been constructed after the road with the preset length according to the mode of S2, the coordinates and elevations are the coordinates and elevations of the corresponding calibration points in the corresponding drawing file, and a simulation road point combination is formed; the simulation segmented model of the road with different widths is created by the BIM software, and the simulation road three-dimensional model is continuously generated after the road three-dimensional model generated in S3 as the simulation driving proceeds; S5, the road with the preset length is continuously constructed, and steps S1-S4 are performed, so as to compare the road three-dimensional model generated by steps S1-S3 and the simulation road three-dimensional model formed in step S4, thereby evaluating the actual construction quality of the road.

2. The method of claim 1, wherein, The preset length is 100-500m, and the specified time is 1-5s; The route of the road comprises a vehicle driving road route according to the road, including a single lane, a same-direction multi-lane, a reverse double-lane, and a reverse multi-lane center line.

3. The method of claim 1, wherein, In the point cloud data, the points near the corresponding coordinates are found, the points in the same horizontal plane projection closest to the corresponding coordinates in the horizontal plane projection of these nearby points are calculated as the calibration point at this time, which comprises: S2-1 constructs a geographic rectangular coordinate system, presets a preset radius of 0.2-0.5m, and projects each of the corresponding coordinates , in the XY plane of the geographic rectangular coordinate system ; is the order number of the calibration point; S2-2 will project the point cloud data in the circle domain with a preset radius as the center in the XY plane , is the number of the point cloud in the circle domain, then the points in the corresponding point cloud data are the points near the multiple corresponding coordinates; S2-3 is a calibration point , is the time.

4. The method of claim 3, wherein, The segmented model and the simulation segmented model are the models between two adjacent calibration points; Evaluating the actual construction quality of the road comprises road deviation, road size, and road elevation.

5. The method of claim 3, wherein, The road deviation comprises that a tangent line of a driving route is made through an optional calibration point at the end of the actual construction, and another tangent line is made through the corresponding calibration point in the simulation road three-dimensional model, and the orientations of the two are compared in the geographic rectangular coordinate system XYZ-O.

6. The method according to any one of claims 1-5, characterized in that, The steps S1-S3 are used to generate the road three-dimensional model of any constructed road on any constructed road.

7. A vehicle for implementing the method of BIM visualization modeling based on vehicle positioning data for municipal road works according to any one of claims 1-6, characterized in that, The smart car machine, a laser radar on the windshield for visual modeling, and a car positioning system on the roof are included, and the smart car machine communicates with the remote server.

8. The vehicle of claim 7, wherein, The car positioning system can be closed by the smart car machine, the user can choose to participate in modeling for compensation and open the car positioning system, and the user can choose to open the positioning signal after the official secret or willing to be public.

9. The vehicle of claim 7, wherein, The user can specify the public geographical range or specify the public facing other users or non-users. The user can get the notice of participating in modeling for compensation through the smart car machine and apply online.

10. The vehicle of claim 9, wherein, The method of specifying the public facing other users or non-users is facing the smart mobile device of the other users or non-users.

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