A road condition research and judgment method and system based on GPS inertial navigation technology

Abstract

The application discloses a road condition research and judgment method and system based on GPS inertial navigation technology, obtains the vehicle driving speed corresponding to UTC time through the GPS inertial navigation technology, derives the road stake number or mileage stake number from the vehicle driving speed, loads the vehicle driving speed and the road stake number or mileage stake number to a video in real time through data fusion, and performs visual display, so that the research and judgment of the road condition are realized, and the defects that the prior art has time lag, insufficient picture coverage, and the position information and speed information of the road cannot be obtained from the video are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of road condition assessment technology, and in particular to a road condition assessment method and system based on GPS inertial navigation technology. Background Technology

[0002] When carrying out road-related work, such as road quality improvement, road safety assessment, and research on road speed limit schemes, a comprehensive understanding of the current road conditions is required. Video is generally the best medium for assessing the overall condition of a road. Currently, the assessment of road conditions is mainly achieved through panoramic maps, roadside cameras, and video recording tools such as dashcams. However, existing technologies for assessing road conditions have the following shortcomings:

[0003] (1) The video images of the panoramic map have a time lag. The road may undergo quality improvement and traffic safety facility optimization. The previous panoramic map cannot accurately reflect the current road conditions. The panoramic map can only serve as a reference. The actual road conditions must be reflected through on-site investigation.

[0004] (2) The roadside cameras can obtain road conditions in real time, but their coverage is not strong enough. At the same time, the video permissions of the cameras are controlled by the traffic police department, and the acquisition method is relatively cumbersome.

[0005] (3) The video obtained from the on-site survey of the vehicle can reflect the current road conditions in a true manner, but it is impossible to obtain the road location information (road marker, mileage marker), speed information, etc. from the video. Summary of the Invention

[0006] In view of this, the present invention proposes a road condition assessment method and system based on GPS inertial navigation technology, which can solve the defects of existing technologies in assessing road conditions.

[0007] The technical solution of this invention is implemented as follows:

[0008] A road condition assessment method based on GPS inertial navigation technology includes the following steps:

[0009] Install a dashcam and GPS inertial navigation system in the vehicle;

[0010] The vehicle travels from the beginning of the road to the end of the road, and obtains GPS time, vehicle speed data and video data in real time;

[0011] The road markers are calculated based on GPS time and vehicle speed data.

[0012] Road condition information is obtained by analyzing video data.

[0013] By fusing vehicle speed data, road markers, and road condition information with video data, a road condition assessment result is obtained.

[0014] The road condition assessment results are sent to a visualization terminal for display, thereby enabling the assessment of road conditions.

[0015] As a further optional solution to the road condition assessment method based on GPS inertial navigation technology, the method further includes:

[0016] The road condition assessment results are marked, and any abnormal conditions are noted.

[0017] As a further optional solution to the road condition assessment method based on GPS inertial navigation technology, the calculation of road markers based on GPS time and vehicle speed data specifically includes:

[0018] Convert the vehicle speed data to units to obtain the vehicle's speed per second;

[0019] The distance traveled by the vehicle is calculated based on the GPS time and the vehicle's speed per second.

[0020] Based on the vehicle's travel distance, the road markers are derived.

[0021] As a further optional solution to the road condition assessment method based on GPS inertial navigation technology, the step of analyzing road conditions based on video data to obtain road condition information specifically includes:

[0022] Construct a road condition analysis model;

[0023] The video data is split into individual seconds of image data.

[0024] Image data is sent every second to a road condition analysis model for analysis to obtain road condition information.

[0025] As a further optional solution to the road condition assessment method based on GPS inertial navigation technology, the step of fusing vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results specifically includes:

[0026] Compare the time data in the GPS time and video data;

[0027] By integrating vehicle speed data, road markers, and road condition information from GPS time and video data that are consistent with each other into the video, and then adding subtitles, a road condition assessment result can be obtained.

[0028] A road condition assessment system based on GPS inertial navigation technology includes:

[0029] The mounting module is used to install a dashcam and a GPS inertial navigation system on a vehicle.

[0030] The acquisition module is used to drive the vehicle from the starting point of the road to the end point of the road and acquire GPS time, vehicle speed data and video data in real time;

[0031] The calculation module is used to calculate the road marker number based on GPS time and vehicle speed data.

[0032] The analysis module is used to analyze road conditions based on video data and obtain road condition information;

[0033] The data fusion module is used to fuse vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results.

[0034] The visualization module is used to send the road condition assessment results to the visualization terminal for display, thereby realizing the assessment of road conditions.

[0035] As a further optional solution to the road condition assessment system based on GPS inertial navigation technology, the system also includes:

[0036] The annotation module is used to annotate the road condition assessment results and mark any abnormal conditions.

[0037] As a further optional solution to the road condition assessment system based on GPS inertial navigation technology, the calculation module includes:

[0038] The conversion module is used to convert vehicle speed data into units to obtain the vehicle's speed per second.

[0039] The processing module is used to calculate the distance traveled by the vehicle based on the GPS time and the vehicle's speed per second.

[0040] The derivation module is used to derive the road markers based on the vehicle's travel distance.

[0041] As a further optional solution to the road condition assessment system based on GPS inertial navigation technology, the analysis module includes:

[0042] Modules are used to build road condition analysis models;

[0043] The splitting module is used to split the video data to obtain image data for each second.

[0044] The determination module is used to send image data every second to the road condition analysis model for analysis to obtain road condition information.

[0045] As a further optional solution to the road condition assessment system based on GPS inertial navigation technology, the data fusion module includes:

[0046] The comparison module is used to compare the time data in GPS time and video data;

[0047] A module is added to integrate vehicle speed data, road markers, and road condition information that are consistent with the GPS time and video data into the video in the form of subtitles, so as to obtain the road condition assessment results.

[0048] The beneficial effects of this invention are as follows: by obtaining the vehicle speed corresponding to the UTC time through GPS inertial navigation technology, the road marker or mileage marker is derived from the vehicle speed. Through data fusion, the vehicle speed and road marker or mileage marker are loaded onto the video in real time for visualization, thereby realizing the assessment of road conditions. This effectively solves the defects of the existing technology, such as time lag, insufficient image coverage, and inability to obtain road location and speed information from the video. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a road condition assessment method based on GPS inertial navigation technology according to the present invention.

[0051] Figure 2 This is a schematic diagram of the road condition assessment system based on GPS inertial navigation technology according to the present invention. Detailed Implementation

[0052] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] refer to Figure 1-2 A road condition assessment method based on GPS inertial navigation technology includes the following steps:

[0054] Install a dashcam and GPS inertial navigation system in the vehicle;

[0055] The vehicle travels from the beginning of the road to the end of the road, and obtains GPS time, vehicle speed data and video data in real time;

[0056] The road markers are calculated based on GPS time and vehicle speed data.

[0057] Road condition information is obtained by analyzing video data.

[0058] By fusing vehicle speed data, road markers, and road condition information with video data, a road condition assessment result is obtained.

[0059] The road condition assessment results are sent to a visualization terminal for display, thereby enabling the assessment of road conditions.

[0060] In this embodiment, the vehicle speed corresponding to the UTC time is obtained through GPS inertial navigation technology. The road marker or mileage marker is derived from the vehicle speed. Through data fusion, the vehicle speed and road marker or mileage marker are loaded onto the video in real time for visualization, thereby realizing the assessment of road conditions. This effectively solves the defects of the existing technology, such as time lag, insufficient image coverage, and inability to obtain road location and speed information from the video.

[0061] It should be noted that the dashcam and GPS inertial navigation system are fixed to the vehicle, and the GPS inertial navigation system and video recording are turned on in advance. Since the world time is accurate, the start time of both does not need to be the same. The vehicle starts acquiring GPS time, speed, and video data as it travels from the starting point to the end point of the road. The GPS inertial navigation system fully utilizes the advantages of inertial navigation and satellite navigation systems, fusing the two navigation algorithms based on the optimal estimation algorithm and the Kalman filter algorithm to obtain the optimal navigation results. Especially when the satellite navigation system is not working (in tunnels and high-rise buildings), the inertial navigation system allows the navigation system to continue working, improving the stability and reliability of the system. The GPS inertial navigation system has an error of 1-2 meters per 100 meters, which is relatively small. The main data acquired by the GPS inertial navigation system are UTC time (hours / minutes / seconds) and ground velocity (vehicle speed). The UTC time can be accurately matched with the video time and is the basis for the fusion of GPS data and video data. The vehicle speed is used to estimate the vehicle's location (road marker).

[0062] Preferably, the method further includes:

[0063] The road condition assessment results are marked, and any abnormal conditions are noted.

[0064] In this embodiment, the road condition assessment results are marked, and the corresponding road facility condition evaluations are marked, such as damaged guardrails, greenery obscuring signs, and dim road markings. At the same time, vehicle speed can be used as the operating speed to evaluate road safety, and linear adjustments can be made to specific nodes or used as the basis for speed limit schemes.

[0065] Preferably, the calculation of the road marker based on GPS time and vehicle speed data specifically includes:

[0066] Convert the vehicle speed data to units to obtain the vehicle's speed per second;

[0067] The distance traveled by the vehicle is calculated based on the GPS time and the vehicle's speed per second.

[0068] Based on the vehicle's travel distance, the road markers are derived.

[0069] In this embodiment, the ground speed obtained by GPS is first converted to m / s, then the travel time per second is derived, and finally the road station number is derived. A station number is a coordinate of the road location. For example, a road station number is a number assigned to the foundation piles before construction; a mileage station number is a number set by the traffic management department after the road is completed and handed over. Taking the West Second Ring Road as an example, the starting station number is K164+452. If a vehicle departs from the starting point, video recording and GPS inertial navigation are activated. After one second, the vehicle's speed is 30 m / s. Therefore, the vehicle's position in the first second is K164+482. This process can be repeated to accurately obtain the road station number of the vehicle every second.

[0070] Preferably, the step of analyzing road conditions based on video data to obtain road condition information specifically includes:

[0071] Construct a road condition analysis model;

[0072] The video data is split into individual seconds of image data.

[0073] Image data is sent every second to a road condition analysis model for analysis to obtain road condition information.

[0074] In this embodiment, the road condition analysis model can be generated by training a neural network model, and no specific limitation is made here.

[0075] Preferably, the step of fusing vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results specifically includes:

[0076] Compare the time data in the GPS time and video data;

[0077] By integrating vehicle speed data, road markers, and road condition information from GPS time and video data that are consistent with each other into the video, and then adding subtitles, a road condition assessment result can be obtained.

[0078] In this embodiment, the GPS inertial navigation system primarily acquires UTC time (hours / minutes / seconds) and ground velocity (vehicle speed), while the video recording acquires Coordinated Universal Time (UTC) and video content. Data fusion between the two is based on accurate time. For example, if the video recording starts at time a, b, c, and ends at time d, e, f, the GPS inertial navigation system will process data within that UTC time period before data fusion. Data fusion involves integrating the acquired speed and station numbers into the video as subtitles. The added subtitles provide a set of station and speed information per second, allowing speed, station numbers, and video information to be displayed simultaneously in the same space, thus visualizing road condition information.

[0079] A road condition assessment system based on GPS inertial navigation technology includes:

[0080] The mounting module is used to install a dashcam and a GPS inertial navigation system on a vehicle.

[0081] The acquisition module is used to drive the vehicle from the starting point of the road to the end point of the road and acquire GPS time, vehicle speed data and video data in real time;

[0082] The calculation module is used to calculate the road marker number based on GPS time and vehicle speed data.

[0083] The analysis module is used to analyze road conditions based on video data and obtain road condition information;

[0084] The data fusion module is used to fuse vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results.

[0085] The visualization module is used to send the road condition assessment results to the visualization terminal for display, thereby realizing the assessment of road conditions.

[0086] In this embodiment, the vehicle speed corresponding to the UTC time is obtained through GPS inertial navigation technology. The road marker or mileage marker is derived from the vehicle speed. Through data fusion, the vehicle speed and road marker or mileage marker are loaded onto the video in real time for visualization, thereby realizing the assessment of road conditions. This effectively solves the defects of the existing technology, such as time lag, insufficient image coverage, and inability to obtain road location and speed information from the video.

[0087] It should be noted that the dashcam and GPS inertial navigation system are fixed to the vehicle, and the GPS inertial navigation system and video recording are turned on in advance. Since the world time is accurate, the start time of both does not need to be the same. The vehicle starts acquiring GPS time, speed, and video data as it travels from the starting point to the end point of the road. The GPS inertial navigation system fully utilizes the advantages of inertial navigation and satellite navigation systems, fusing the two navigation algorithms based on the optimal estimation algorithm and the Kalman filter algorithm to obtain the optimal navigation results. Especially when the satellite navigation system is not working (in tunnels and high-rise buildings), the inertial navigation system allows the navigation system to continue working, improving the stability and reliability of the system. The GPS inertial navigation system has an error of 1-2 meters per 100 meters, which is relatively small. The main data acquired by the GPS inertial navigation system are UTC time (hours / minutes / seconds) and ground velocity (vehicle speed). The UTC time can be accurately matched with the video time and is the basis for the fusion of GPS data and video data. The vehicle speed is used to estimate the vehicle's location (road marker).

[0088] Preferably, the system further includes:

[0089] The annotation module is used to annotate the road condition assessment results and mark any abnormal conditions.

[0090] In this embodiment, the road condition assessment results are marked, and the corresponding road facility condition evaluations are marked, such as damaged guardrails, greenery obscuring signs, and dim road markings. At the same time, vehicle speed can be used as the operating speed to evaluate road safety, and linear adjustments can be made to specific nodes or used as the basis for speed limit schemes.

[0091] Preferably, the computing module includes:

[0092] The conversion module is used to convert vehicle speed data into units to obtain the vehicle's speed per second.

[0093] The processing module is used to calculate the distance traveled by the vehicle based on the GPS time and the vehicle's speed per second.

[0094] The derivation module is used to derive the road markers based on the vehicle's travel distance.

[0095] In this embodiment, the ground speed obtained by GPS is first converted to m / s, then the travel time per second is derived, and finally the road station number is derived. A station number is a coordinate of the road location. For example, a road station number is a number assigned to the foundation piles before construction; a mileage station number is a number set by the traffic management department after the road is completed and handed over. Taking the West Second Ring Road as an example, the starting station number is K164+452. If a vehicle departs from the starting point, video recording and GPS inertial navigation are activated. After one second, the vehicle's speed is 30 m / s. Therefore, the vehicle's position in the first second is K164+482. This process can be repeated to accurately obtain the road station number of the vehicle every second.

[0096] Preferably, the analysis module includes:

[0097] Modules are used to build road condition analysis models;

[0098] The splitting module is used to split the video data to obtain image data for each second.

[0099] The determination module is used to send image data every second to the road condition analysis model for analysis to obtain road condition information.

[0100] In this embodiment, the road condition analysis model can be generated by training a neural network model, and no specific limitation is made here.

[0101] Preferably, the data fusion module includes:

[0102] The comparison module is used to compare the time data in GPS time and video data;

[0103] A module is added to integrate vehicle speed data, road markers, and road condition information that are consistent with the GPS time and video data into the video in the form of subtitles, so as to obtain the road condition assessment results.

[0104] In this embodiment, the GPS inertial navigation system primarily acquires UTC time (hours / minutes / seconds) and ground velocity (vehicle speed), while the video recording acquires Coordinated Universal Time (UTC) and video content. Data fusion between the two is based on accurate time. For example, if the video recording starts at time a, b, c, and ends at time d, e, f, the GPS inertial navigation system will process data within that UTC time period before data fusion. Data fusion involves integrating the acquired speed and station numbers into the video as subtitles. The added subtitles provide a set of station and speed information per second, allowing speed, station numbers, and video information to be displayed simultaneously in the same space, thus visualizing road condition information.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A road condition assessment method based on GPS inertial navigation technology, characterized in that, Specifically, the following steps are included: Install a dashcam and GPS inertial navigation system in the vehicle; The vehicle travels from the starting point to the ending point of the road, and GPS time, vehicle speed data, and video data are acquired in real time; the GPS time is in UTC time. The road markers are calculated based on GPS time and vehicle speed data. Road condition information is obtained by analyzing video data. By fusing vehicle speed data, road markers, and road condition information with video data, a road condition assessment result is obtained. The road condition assessment results are sent to a visualization terminal for display, thereby enabling the assessment of road conditions.

2. The road condition assessment method based on GPS inertial navigation technology according to claim 1, characterized in that, The method further includes: The road condition assessment results are marked, and any abnormal conditions are noted.

3. The road condition assessment method based on GPS inertial navigation technology according to claim 2, characterized in that, The calculation of road markers based on GPS time and vehicle speed data specifically includes: Convert the vehicle speed data to units to obtain the vehicle's speed per second; The distance traveled by the vehicle is calculated based on the GPS time and the vehicle's speed per second. Based on the vehicle's travel distance, the road markers are derived.

4. The road condition assessment method based on GPS inertial navigation technology according to claim 3, characterized in that, The road condition analysis based on video data to obtain road condition information specifically includes: Construct a road condition analysis model; The video data is split into individual seconds of image data. Image data is sent every second to a road condition analysis model for analysis to obtain road condition information.

5. The road condition assessment method based on GPS inertial navigation technology according to claim 4, characterized in that, The process of fusing vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results specifically includes: Compare the time data in the GPS time and video data; By integrating vehicle speed data, road markers, and road condition information from GPS time and video data that are consistent with each other into the video, and then adding subtitles, a road condition assessment result can be obtained.

6. A road condition assessment system based on GPS inertial navigation technology, characterized in that, include: The mounting module is used to install a dashcam and a GPS inertial navigation system on a vehicle. The acquisition module is used to drive the vehicle from the starting point of the road to the end point of the road and acquire GPS time, vehicle speed data and video data in real time; The GPS time is in UTC time. The calculation module is used to calculate the road marker number based on GPS time and vehicle speed data. The analysis module is used to analyze road conditions based on video data and obtain road condition information; The data fusion module is used to fuse vehicle speed data, road markers, and road condition information with video data to obtain road condition assessment results. The visualization module is used to send the road condition assessment results to the visualization terminal for display, thereby realizing the assessment of road conditions.

7. A road condition assessment system based on GPS inertial navigation technology according to claim 6, characterized in that, The system also includes: The annotation module is used to annotate the road condition assessment results and mark any abnormal conditions.

8. A road condition assessment system based on GPS inertial navigation technology according to claim 7, characterized in that, The computing module includes: The conversion module is used to convert vehicle speed data into units to obtain the vehicle's speed per second. The processing module is used to calculate the distance traveled by the vehicle based on the GPS time and the vehicle's speed per second. The derivation module is used to derive the road markers based on the vehicle's travel distance.

9. A road condition assessment system based on GPS inertial navigation technology according to claim 8, characterized in that, The analysis module includes: Modules are used to build road condition analysis models; The splitting module is used to split the video data to obtain image data for each second. The determination module is used to send image data every second to the road condition analysis model for analysis to obtain road condition information.

10. A road condition assessment system based on GPS inertial navigation technology according to claim 9, characterized in that, The data fusion module includes: The comparison module is used to compare the time data in GPS time and video data; A module is added to integrate vehicle speed data, road markers, and road condition information that are consistent with the GPS time and video data into the video in the form of subtitles, so as to obtain the road condition assessment results.

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