Road settlement monitoring method based on GNSS, INS and laser ranging

Abstract

The invention discloses a road settlement monitoring method based on GNSS (Global Navigation Satellite System), INS (Inertial Navigation Satellite System) and laser ranging. GNSS equipment, IMU (Inertial Measurement Unit) equipment and laser ranging equipment are respectively mounted on a test vehicle; driving the test vehicle to run on the road to be tested according to a set mode, and collecting data in real time through the GNSS device, the IMU device and the laser ranging device; and determining an actual coordinate curve of a road surface measurement point of the to-be-measured road based on data acquired by the GNSS equipment, the IMU equipment and the laser ranging equipment, and observing settlement information of the road according to the actual coordinate curve. According to the invention, various devices are integrated on the test vehicle, so that continuous and dynamic monitoring can be realized, tiny settlement and sudden depression of the road can be found in time, and the problem of missing detection caused by large point spacing in a traditional method is avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of road settlement detection, and particularly relates to a road settlement monitoring method based on GNSS, INS, and laser ranging. Background Art

[0002] With the rapid development of social economy, to meet the development needs, the laying quantity of various urban roads, highways, and rural roads in transportation has increased. However, due to diverse geological conditions and climate changes in different regions, road settlement phenomena for different reasons will occur. For example, roads in coastal areas mostly have soft soil foundations, which are composed of loose sediments such as silt and silty soil. These soil layers are prone to compression and settlement under load. It is necessary to monitor the road settlement situation for subsequent repair to meet the traffic needs.

[0003] At present, leveling is a measurement method used to determine the height of each point on the ground relative to a certain reference plane (usually the sea level). This method is widely used in current road settlement detection and repair work. Leveling is based on the principle of a horizontal line of sight and determines the relative height by measuring the height difference between different points. Using a level or a total station for measurement, by comparing the measurement data at different time points, the settlement situation of the road is analyzed. The advantage of this method is high accuracy, but the disadvantage is that the distance between measurement points is relatively large, ranging from dozens of meters, which will result in the inability to capture sudden road depressions and is greatly affected by sudden depressions during linear recovery. And it requires surveyors to conduct on-site measurements, which requires road closure and a relatively long working time, resulting in a large cost. Summary of the Invention

[0004] The purpose of the present invention is to solve the deficiencies in the above background art and provide a road settlement monitoring method based on GNSS, INS, and laser ranging.

[0005] The technical solution adopted by the present invention is: a road settlement monitoring method based on GNSS, INS, and laser ranging, comprising the following steps:

[0006] Install a GNSS device, an IMU device, and a laser ranging device on a test vehicle respectively;

[0007] Drive the test vehicle to travel on the road to be measured in a set manner, and collect data in real time through the GNSS device, the IMU device, and the laser ranging device;

[0008] Determine the actual coordinate curve of the road surface measurement points of the road to be measured based on the data collected by the GNSS device, the IMU device, and the laser ranging device, and observe the settlement information of the road according to the actual coordinate curve.

[0009] Further, the GNSS device is set in an unobstructed area of the test vehicle, the IMU device has no relative displacement with the test vehicle, and the laser output by the laser ranging device is perpendicular to the ground plane.

[0010] Further, the test vehicle is driven on the road to be measured in a set manner, and data is collected in real time through the GNSS device, the IMU device, and the laser ranging device, including:

[0011] The test vehicle travels in a cycle in the order of standing still for a first set time, driving straight for a first set distance, and continuously driving for a second set time until the driving distance reaches a second set distance and then stops driving;

[0012] The GNSS device, the IMU device, and the laser ranging device collect data in real time during the driving of the test vehicle and continue to collect data for a third set time after the test vehicle stops driving.

[0013] Further, determining the actual coordinate curve of the road surface measurement points of the road to be measured based on the data collected by the GNSS device, the IMU device, and the laser ranging device includes:

[0014] Solving the GNSS data collected by the GNSS device to obtain the actual GNSS coordinate curve;

[0015] Solving the IMU data collected by the IMU device according to the actual GNSS coordinate curve to obtain the actual IMU coordinate curve;

[0016] Solving the actual IMU coordinate curve to obtain the theoretical coordinate curve of the road surface measurement points of the road to be measured;

[0017] Based on the theoretical coordinate curve of the road surface measurement points, correcting the data collected by the laser ranging device to obtain the actual coordinate curve of the road surface measurement points of the road to be measured.

[0018] Further, it also includes correcting the static data in all time periods of the actual GNSS coordinate curve, using the curve composed of the corrected static data and dynamic data as the corrected GNSS coordinate curve, and solving the IMU data collected by the IMU device according to the corrected GNSS coordinate curve to obtain the IMU coordinate curve.

[0019] Further, correcting the static data in all time periods of the actual GNSS coordinate curve includes:

[0020] Dividing the actual GNSS coordinate curve into several set time windows starting from the initial moment, judging the data displacement amount under each set time window, and if the data displacement amount under the set time window is less than or equal to the set displacement, then judging the data under the corresponding set time window as static data;

[0021] Take the total time period formed by several consecutive adjacent set time windows corresponding to the static data as the static time period, and correct all the static data in the static time period to be the same as the first data in the static time period.

[0022] Furthermore, it also includes correcting the data of all zero-speed time periods in the actual IMU coordinate curve, using the curve composed of the corrected data of the zero-speed time period and the non-zero-speed time period data as the corrected IMU coordinate curve, and performing resolution on the corrected IMU coordinate curve to obtain the theoretical coordinate curve of the measured points on the road surface to be measured.

[0023] Furthermore, the correction of the data of all zero-speed time periods in the actual IMU coordinate curve includes: judging whether each moment is a zero-speed moment, taking the total time period formed by several consecutive adjacent moments judged to be zero-speed moments as the zero-speed time period, and correcting all the data in the zero-speed time period to be the same as the first data in the zero-speed time period.

[0024] Furthermore, the judgment of whether each moment is a zero-speed moment includes:

[0025] Calculating T1 and T2 for each moment:

[0026]

[0027] If both T1 < thres_1 and T2 < thres_2 are satisfied, then judge the corresponding moment as a zero-speed moment;

[0028] wherein, T1 is the standard deviation of the acceleration; T2 is the standard deviation of the angular velocity; thres_1 and thres_2 are the first threshold and the second threshold respectively; N is the sampling number of the sliding window of the set time; k is the number of frames; Ω n is a sliding window of a certain set time; n is the total number of frames in the sliding window; and are respectively the vector means of the specific force and the angular rate within Ω n ; is the specific force at the k-th frame; is the angular rate at the k-th frame.

[0029] Even further, resolve the GNSS data, IMU data, and actual IMU coordinate curve respectively through the observation equation to obtain the corresponding coordinate curves.

[0030] The beneficial effects of the present invention are:

[0031] The present invention proposes a road settlement monitoring method that comprehensively utilizes GNSS (Global Navigation Satellite System), INS (Inertial Navigation System, where IMU is the Inertial Measurement Unit and is a key component of INS), and laser ranging technology. By integrating multiple devices onto a test vehicle, continuous and dynamic monitoring can be achieved, enabling the timely detection of minor road settlements and sudden depressions, and avoiding the problem of missed detections due to large point spacings in traditional methods. At the same time, the present invention does not require surveyors to measure point by point on site, reducing road closure time, minimizing the impact on traffic, shortening working hours, and reducing labor and time costs. Moreover, the present invention combines data from multiple devices, not only obtaining road surface height information, but also integrating data such as the vehicle's motion state to provide more comprehensive information for road settlement analysis, liberating productivity while ensuring accuracy, and providing a more rapid and accurate solution for road repair.

[0032] In the present invention, the GNSS device is placed in an unobstructed area to ensure good signal reception, reduce signal attenuation and errors caused by obstruction, and improve positioning accuracy. The IMU device has no relative displacement with the vehicle to ensure that the measured data accurately reflects the vehicle's motion. The laser ranging device emits laser perpendicular to the ground plane to ensure accurate measurement of the vertical distance, providing reliable vertical direction data for calculating the actual coordinate curve of the road surface measurement points and improving the accuracy of road settlement monitoring.

[0033] In the present invention, the test vehicle is driven in a specific manner, which can simulate different road usage scenarios, making the collected data more representative and comprehensive. For example, the reference data when the vehicle is stationary can be obtained in the stationary state, the data characteristics of the vehicle in a stable motion state can be analyzed during straight-line driving, and the road usage under actual traffic flow can be simulated during continuous driving. After the test vehicle stops, data is continuously collected for a second set time to ensure the integrity of the collected data, avoiding data loss or discontinuity caused by sudden vehicle stops, which is conducive to accurate subsequent data processing and analysis and improving the reliability of road settlement monitoring results.

[0034] In the present invention, through step-by-step calculation of the data collected by the GNSS device, IMU device, and laser ranging device, the fusion processing of multi-source data is achieved. The actual GNSS coordinate curve is calculated using GNSS data, providing a reference benchmark for IMU data calculation. Based on the actual GNSS coordinate curve, the actual IMU coordinate curve is calculated from IMU data, further improving the accuracy of IMU data. The theoretical coordinate curve of the road surface measurement points to be measured is calculated from the actual IMU coordinate curve, providing a basis for laser ranging data correction. Finally, based on the theoretical coordinate curve of the road surface measurement points, the data collected by the laser ranging device is corrected to obtain the actual coordinate curve of the road surface measurement points to be measured. Through the mutual correction and fusion of multi-source data, the accuracy and precision of road settlement monitoring are effectively improved.

[0035] The present invention corrects the static data in all time periods of the actual GNSS coordinate curve, eliminates the errors in the static data, and improves the accuracy of the GNSS coordinate curve. Using the curve composed of the corrected static data and dynamic data as the corrected GNSS coordinate curve, and then resolving the IMU data collected by the IMU device according to the corrected GNSS coordinate curve, a more accurate IMU coordinate curve can be obtained, providing more reliable data support for subsequent road settlement monitoring; by dividing a set time window and judging the data displacement to determine the static time period, all the static data in the static time period is corrected to be the same as the first data in the static time period. This correction method is simple and effective, can accurately identify and correct the errors in the static data, improve the accuracy and stability of the GNSS coordinate curve, and provide a more accurate basis for subsequent data processing and analysis.

[0036] The present invention corrects the zero-speed data in all time periods of the actual IMU coordinate curve, eliminates the errors in the zero-speed data, and improves the accuracy of the IMU coordinate curve. Using the curve composed of the corrected zero-speed data and non-zero-speed data as the corrected IMU coordinate curve, and resolving the corrected IMU coordinate curve to obtain the theoretical coordinate curve of the road surface measurement point to be measured, which can more accurately reflect the motion state of the vehicle and the position information of the road surface measurement point, improving the accuracy of road settlement monitoring; by judging whether each moment is a zero-speed moment and clarifying the judgment method, the total time period formed by the moments judged as zero-speed and having several consecutive adjacent moments is used as the zero-speed time period, and all the zero-speed data in the zero-speed time period is corrected to be the same as the first data in the zero-speed time period. This correction method can accurately identify and correct the errors in the zero-speed data, improve the accuracy and stability of the IMU coordinate curve, and provide more reliable data support for subsequent road settlement monitoring.

[0037] The present invention resolves the GNSS data, IMU data, and actual IMU coordinate curve through the observation equation to obtain the corresponding coordinate curves. This resolution method is universal and can adapt to different data types and monitoring requirements. At the same time, the observation equation resolution method has high accuracy and reliability, can accurately extract the coordinate information of the road surface measurement point from the original data, and provide accurate data support for road settlement monitoring. Description of the Drawings

[0038] Figure 1 It is the monitoring principle diagram of the present invention. Detailed Embodiment

[0039] The following further describes the specific embodiments of the present invention in conjunction with the accompanying drawings. It should be noted here that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation on the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] As Figure 1 shown, the present invention provides a road settlement monitoring method based on GNSS, INS, and laser ranging, including the following steps:

[0041] Step 1, Equipment installation

[0042] Install the GNSS (Global Navigation Satellite System) equipment, INS equipment (including IMU equipment), and laser ranging equipment (laser ranging sensor) at different fixed positions on the test vehicle. To ensure the accuracy and reliability of the collected data, the relative stability of the installation of the three devices should be ensured.

[0043] Among them, the GNSS equipment is a GNSS antenna, which is installed in an area without obstruction or an area with the least obstruction on the vehicle to achieve reliable reception of satellite signals. After the GNSS equipment is installed, the precise coordinates of the GNSS in the WGS84 coordinate system will be obtained from the CORS data stream accessed by the GNSS, which is convenient for subsequent data collection and data calculation; when installing the INS equipment, it is necessary to ensure that there is no relative displacement between the internal IMU equipment and the test vehicle; the laser ranging equipment is a laser ranging sensor, whose measurable range is 0.5 - 2m. When installing, it should be ensured that the laser output by it is perpendicular to the ground plane (or horizontal plane) to reduce measurement errors.

[0044] Step 2, Data collection

[0045] After the equipment installation is completed, when collecting data, drive the test vehicle to travel on the road to be measured according to the following steps:

[0046] ①. Control the test vehicle to be in a stationary state (i.e., the speed is 0), wait for the initialization of the above three devices, and after the device initialization, proceed to step ②.

[0047] ②. Control the test vehicle to be stationary for a first set time. During the time when the test vehicle is stationary, the above three devices collect data in real time.

[0048] ③. After the first set time is reached, control the test vehicle to first drive straight for a first set distance, and during the straight driving process, the above three devices collect data in real time.

[0049] ④ After the test vehicle travels in a straight line to reach the first set distance, immediately control the test vehicle to continuously travel without distinction for the second set time. During the non-distinctive continuous travel, the above three devices collect data in real time.

[0050] ⑤ After the second set time is reached, repeat steps ② - ④ until the total distance traveled by the test vehicle reaches the second set distance and then stop driving.

[0051] ⑥ After the test vehicle stops driving, the three devices continue to collect data until the collection time reaches the third set time and then stop data collection.

[0052] It should be noted that the first set time in step ② above is 3 - 5 minutes, that is, at the start of the vehicle's driving, data collection in a stationary state should be carried out first. The first set time is preferably 3 minutes or 4 minutes or 5 minutes.

[0053] It can be understood that the straight-line driving in step ③ above means that during the driving process, the distance by which the test vehicle deviates from the center line left and right shall not exceed 30 centimeters, and the amplitude of the steering wheel turning left and right shall not exceed 5 degrees. The first set distance is generally 50 - 100 m, preferably 50 m or 80 m.

[0054] It can be understood that the non-distinctive continuous driving in step ④ above means that the vehicle can be controlled to perform different operations without stopping, including but not limited to turning, lane changing, going straight, going uphill and downhill, etc. The second set time is set according to the accuracy requirements. The higher the accuracy, the shorter the continuous driving time. The second set time is generally 5 minutes. The speeds of the straight-line driving and the non-distinctive continuous driving are the set speeds, and the set speed is generally 5 km / h - 10 km / h.

[0055] It can be understood that in step ⑤ above, the second set distance is calibrated according to actual needs, generally 1 - 5 km, preferably 2 km.

[0056] It should be noted that the third set time in step ⑥ above is 3 - 5 minutes, that is, after the vehicle stops driving, the three devices need to continue to collect data for a period of time and then stop collecting data. The third set time is preferably 3 minutes or 4 minutes or 5 minutes.

[0057] It can be understood that since the IMU needs to be stationary for initialization during data collection and requires an initial coordinate with a relatively high accuracy (millimeter level), a stationary operation should be carried out at the start of driving. After data collection, the error of the IMU will gradually accumulate over time. Therefore, after driving for 3 - 5 minutes, it is necessary to be stationary to correct the IMU with the coordinates obtained by GNSS solution to ensure accuracy. Collect data in this way in a loop. At the end, in order to meet the need for smooth post-processing solution, it is necessary to be stationary. Thus, the above vehicle driving and data collection method is designed.

[0058] When the GNSS device, IMU device, and laser ranging device collect data, they collect data at a set time interval as a cycle. The data collection cycles of the three are the same, which is convenient for subsequent data calculation. The set time interval is 1 s.

[0059] Step 3: Data calculation

[0060] Data calculation refers to calculating the data collected by the GNSS device, IMU device, and laser ranging device to finally obtain the coordinates of the measurement points on the road surface to be measured. Through the coordinates, the road surface elevation information can be reflected, that is, it can be determined whether the road has settlement. The specific calculation process includes the following steps:

[0061] A. Calculate the GNSS data collected by the GNSS device to obtain the actual GNSS coordinate curve;

[0062] B. Calculate the IMU data collected by the IMU device according to the actual GNSS coordinate curve to obtain the actual IMU coordinate curve;

[0063] C. Calculate the actual IMU coordinate curve to obtain the theoretical coordinate curve of the measurement points on the road surface to be measured;

[0064] D. Correct the data collected by the laser ranging device based on the theoretical coordinate curve of the road surface measurement points, eliminate the error caused by the change in tire pressure when the vehicle is suspended, and obtain the actual coordinate curve of the road surface measurement points to be measured.

[0065] It should be noted that the coordinate curves in the above steps A - D are all sets of three-dimensional coordinates of the corresponding measurement points in time sequence. Due to different measurement principles or standards of different devices, the data forms obtained may be different, so a series of calculations are required. In the present invention, the corresponding data is specifically calculated through the observation equation. The detailed calculation steps are conventional techniques and will not be elaborated here. The observation equation taking GNSS data as an example is

[0066]

[0067] Among them, is the double-difference operator; is the pseudorange; is the distance; is the pseudorange noise; λ is the wavelength; is the phase; is the hardware delay error; is the carrier phase noise, i and j are the numbers of two measurement stations respectively, and p and q are the numbers of two satellites respectively.

[0068] In some embodiments, the GNSS data collected by the GNSS device is processed to obtain the geodetic coordinates with millimeter-level accuracy of the GNSS antenna. The actual GNSS coordinate curve obtained after processing contains static data (i.e., the data corresponding to the test vehicle when it is stationary) and dynamic data (the data corresponding to the test vehicle when it is moving). In theory, the static data should not have fluctuations, but the static data obtained from the actual processing has fluctuations, so the static data needs to be corrected.

[0069] Since the test vehicle cycles in the order of stationary - moving - stationary - moving, the GNSS data collected by the GNSS device and the data obtained after processing are both arranged in the order of static - dynamic - static - dynamic. When correcting the static data, it is necessary to correct the static data for all time periods. The curve composed of the corrected static data and dynamic data is used as the corrected GNSS coordinate curve, and the IMU data collected by the IMU device is processed according to the corrected GNSS coordinate curve to obtain the IMU coordinate curve.

[0070] To correct the static data for all time periods in the actual GNSS coordinate curve, it is necessary to first determine which time periods are static time periods. Only after determining the static time periods can the static data in the static time periods be corrected. The specific process is as follows:

[0071] The actual GNSS coordinate curve is divided into several set time windows starting from the initial moment, and the data displacement in each set time window is judged. If the data displacement in the set time window is less than or equal to the set displacement, the data in the corresponding set time window is judged as static data;

[0072] After judging the data in all set time windows, the total time period formed by several consecutive adjacent set time windows corresponding to the static data is used as the static time period, and all the static data in the static time period is corrected to be the same as the first data in the static time period.

[0073] It should be noted that the set time window is generally an integer multiple of the above-mentioned set time interval, preferably a 5s window. That is, there will be several coordinate data in the 5s window. Based on the data displacement (i.e., height) in the coordinate data, the difference between the maximum value and the minimum value of several data displacements is calculated. If the difference is less than or equal to the set displacement, and the set displacement is 10cm, it means that the data fluctuation in the 5s window is small, and the data in the 5s window is judged as static data; otherwise, the data in the 5s window is judged as dynamic data.

[0074] After judging the data of all windows, search for the set time windows corresponding to all static data. If there are N consecutive set time windows connected, and the data corresponding to the N set time windows are all static data, then the total time period formed by the N set time windows is taken as one of the static time periods, and several static time periods will be determined in the actual GNSS coordinate curve. The data of the actual static time periods may be the same or different. The above correction is to correct all the static data corresponding to the static time periods to the same data, that is, the static data of each static time period is the same, and the static data of different static time periods may be the same or different.

[0075] In some embodiments, to calculate the actual IMU coordinate curve from the IMU data collected by the IMU device according to the actual GNSS coordinate curve, first calibrate and perform attitude calculation on the IMU data, then perform inertial calculation, and then perform whole-second correction on the data after inertial calculation through the actual GNSS coordinate curve and Kalman filtering to obtain the coordinates of each IMU data point (i.e., the actual IMU coordinate curve), making the restoration points of the road linear denser and improving the accuracy of road repair.

[0076] After obtaining the actual IMU coordinate curve, zero-speed correction must be performed. Since there are certain differences between the zero biases of the accelerometer and gyroscope calibrated before the IMU leaves the factory and the actual ones, and affected by the earth's gravity, system error parts such as zero bias and gravitational acceleration can be eliminated through zero-speed correction.

[0077] Zero-speed correction is to correct the data of all zero-speed time periods in the actual IMU coordinate curve, and use the curve composed of the data of the corrected zero-speed time periods and the non-zero-speed time periods as the corrected IMU coordinate curve, and calculate the theoretical coordinate curve of the measurement points on the road surface to be measured from the corrected IMU coordinate curve.

[0078] To correct the data of all zero-speed time periods in the actual IMU coordinate curve, it is necessary to judge according to the actual data which data are the data at zero-speed moments (i.e., the data processed from the data collected when the test vehicle is stationary) and which are the data at non-zero-speed moments. The specific process is as follows: judge whether each moment is at zero speed, and take the total time period formed by the moments judged to be at zero speed and having several consecutive adjacent moments as the zero-speed time period, and correct all the data in the zero-speed time period to be the same as the first data in the zero-speed time period.

[0079] It should be noted that judging whether each moment is at zero speed includes: calculating T1 and T2 of each moment through the following formula. If T1 and T2 both satisfy: T1 < thres_1 and T2 < thres_2, then judge the corresponding moment as a zero-speed moment.

[0080]

[0081] Wherein, T1 is the standard deviation of acceleration; T2 is the standard deviation of angular velocity; thres_1 and thres_2 are the first threshold and the second threshold respectively, thres_1 = 0.00375 m / s 2 , thres_2 = 0.00375 * 180 / π rad, and the specific values can be adjusted according to the data quality of the IMU;; N is the number of samples in the sliding window of the set time; k is the number of frames; Ω n is a sliding window at a certain set time; n is the total number of frames in the sliding window; and are respectively the vector means of specific force and angular rate within Ω n ; is the specific force at the k-th frame; is the angular rate at the k-th frame.

[0082] After judging all moments, search for all moments. If there are M consecutive moments connected, and all M moments are zero-velocity moments, then the total time period formed by the M zero-velocity moments is used as the zero-velocity period. The actual IMU coordinate curve will determine several zero-velocity periods, and the data of each zero-velocity period may be the same or different. The above correction is to correct all data under the corresponding zero-velocity period to the same data, that is, the data of each zero-velocity period is the same, and the data of different zero-velocity periods may be the same or different.

[0083] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any change or replacement that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. The content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

Claims

1. A road settlement monitoring method based on GNSS, INS and laser ranging, characterized in that, Including the following steps: Install a GNSS device, an IMU device, and a laser ranging device on a test vehicle respectively; Drive the test vehicle to travel on the road to be measured in a set manner, and collect data in real time through the GNSS device, the IMU device, and the laser ranging device; Determine the actual coordinate curve of the pavement measurement points of the road to be measured based on the data collected by the GNSS device, the IMU device, and the laser ranging device, and observe the settlement information of the road according to the actual coordinate curve.

2. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 1, characterized in that: The GNSS device is set in an unobstructed area on the test vehicle, the IMU device has no relative displacement with the test vehicle, and the laser output by the laser ranging device is perpendicular to the ground plane.

3. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 1, wherein The driving the test vehicle to travel on the road to be measured in a set manner and collecting data in real time through the GNSS device, the IMU device, and the laser ranging device includes: Drive the test vehicle to travel in a cycle in the order of standing still for a first set time, traveling straight for a first set distance, and continuously traveling for a second set time until the traveled distance reaches a second set distance and then stop traveling; The GNSS device, the IMU device, and the laser ranging device collect data in real time during the driving process of the test vehicle, and continue to collect data for a third set time after the test vehicle stops traveling.

4. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 1, characterized in that The determining the actual coordinate curve of the pavement measurement points of the road to be measured based on the data collected by the GNSS device, the IMU device, and the laser ranging device includes: Solve the GNSS data collected by the GNSS device to obtain the actual GNSS coordinate curve; Solve the IMU data collected by the IMU device according to the actual GNSS coordinate curve to obtain the actual IMU coordinate curve; Solve the actual IMU coordinate curve to obtain the theoretical coordinate curve of the pavement measurement points of the road to be measured; Based on the theoretical coordinate curve of the pavement measurement points, correct the data collected by the laser ranging device to measure the actual coordinate curve of the pavement measurement points of the road to be measured.

5. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 4, wherein: It also includes correcting the static data of all time periods in the actual GNSS coordinate curve, using the curve composed of the corrected static data and dynamic data as the corrected GNSS coordinate curve, and solving the IMU data collected by the IMU device according to the corrected GNSS coordinate curve to obtain the IMU coordinate curve.

6. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 5, characterized in that: Correcting the static data of all time periods in the actual GNSS coordinate curve includes: Divide the actual GNSS coordinate curve into several set time windows starting from the initial moment, judge the data displacement amount under each set time window. If the data displacement amount under the set time window is less than or equal to the set displacement, then judge the data under the corresponding set time window as static data; Take the total time period formed by several consecutive adjacent set time windows corresponding to the static data as the static time period, and correct all the static data in the static time period to be the same as the first data in the static time period.

7. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 4, characterized in that: It also includes correcting the data of all zero-speed time periods in the actual IMU coordinate curve, using the curve composed of the corrected zero-speed time period data and non-zero-speed time period data as the corrected IMU coordinate curve, and solving the corrected IMU coordinate curve to obtain the theoretical coordinate curve of the pavement measurement points of the road to be measured.

8. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 7, characterized in that: The correction of the data in all zero-velocity periods in the actual IMU coordinate curve includes: judging whether each moment is a zero-velocity moment, taking the total period formed by the moments judged to be zero-velocity and having several consecutive adjacent moments as the zero-velocity period, and correcting all the data in the zero-velocity period to be the same as the first data in the zero-velocity period.

9. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 8, characterized in that: The judgment of whether each moment is a zero-velocity moment includes: Calculating T1 and T2 for each moment: If both T1 < thres_1 and T2 < thres_2 are satisfied simultaneously, it is judged that the corresponding moment is a zero-velocity moment; Among them, T1 is the standard deviation of acceleration; T2 is the standard deviation of angular velocity; thres_1 and thres_2 are the first threshold and the second threshold respectively; N is the number of samples in the sliding window of the set time; k is the number of frames; Ω n is the sliding window at a certain set time; n is the total number of frames in the sliding window; and are the vector means of specific force and angular rate within Ω n respectively; f k b is the specific force at the k-th frame; is the angular rate at the k-th frame.

10. The road settlement monitoring method based on GNSS, INS and laser ranging according to claim 4, wherein: The corresponding coordinate curves are obtained by resolving the GNSS data, IMU data, and actual IMU coordinate curve respectively through the observation equation.

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