CN111610191A - Road detection and repair system - Google Patents
Road detection and repair system Download PDFInfo
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- CN111610191A CN111610191A CN202010313111.3A CN202010313111A CN111610191A CN 111610191 A CN111610191 A CN 111610191A CN 202010313111 A CN202010313111 A CN 202010313111A CN 111610191 A CN111610191 A CN 111610191A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
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- E—FIXED CONSTRUCTIONS
- E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
- E01C—CONSTRUCTION OF, OR SURFACES FOR, ROADS, SPORTS GROUNDS, OR THE LIKE; MACHINES OR AUXILIARY TOOLS FOR CONSTRUCTION OR REPAIR
- E01C23/00—Auxiliary devices or arrangements for constructing, repairing, reconditioning, or taking-up road or like surfaces
- E01C23/01—Devices or auxiliary means for setting-out or checking the configuration of new surfacing, e.g. templates, screed or reference line supports; Applications of apparatus for measuring, indicating, or recording the surface configuration of existing surfacing, e.g. profilographs
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/30—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring roughness or irregularity of surfaces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
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Abstract
The invention relates to the technical field of automatic maintenance of roads and discloses a road detection and repair system which comprises a road side terminal, a vehicle-mounted terminal, a cloud platform and a repair terminal, wherein the vehicle-mounted terminal is connected with the road side terminal; the vehicle-mounted terminal is used for detecting real-time vehicle height data, acceleration data and vehicle positioning information of the vehicle, judging whether a driving road section is damaged or not according to the height data and the acceleration data, if so, calculating road surface unevenness, and sending the road surface unevenness and the vehicle positioning information to the road side terminal; the road side terminal is used for shooting a road surface picture of the road section to be detected, acquiring road side positioning information of the road section to be detected, judging whether the road section to be detected is damaged or not according to the road surface picture, if so, primarily delimiting a damage range according to the road side positioning information, taking the received vehicle positioning information located in the damage range as damage position information, and sending the damage position information and the corresponding road surface unevenness to the repair terminal through the cloud platform. The invention has the effect of high detection precision.
Description
Technical Field
The invention relates to the technical field of automatic road maintenance, in particular to a road detection and repair system.
Background
The traditional road surface detection is generally carried out by manpower directly, and the detection has many defects and is not high in precision. Normal transportation can not only be influenced at the testing process, and the manual work that needs is too much moreover, and the error also can be very big in the testing process, has consumed a large amount of manpower and materials. Therefore, automated detection means have been developed. At present, the road automatic detection means mainly adopts an image detection and identification technology, combines software and hardware, and can efficiently detect the pavement cracks in real time through the steps of image acquisition, crack extraction and the like. On one hand, the detection means has the problem of limited image recognition accuracy, on the other hand, the detection means depends on a special road detection vehicle, and for the limited road detection vehicle, a large amount of manpower and material resources are needed for detection on a road in a wide range.
Disclosure of Invention
The invention aims to overcome the technical defects and provide a road detection and repair system, which solves the technical problems that the road detection accuracy is not high and the detection can be realized only by special road detection vehicles in the prior art.
In order to achieve the technical purpose, the technical scheme of the invention provides a road detection and repair system, which comprises a road side terminal arranged on a road section to be detected, a vehicle-mounted terminal arranged on a vehicle, a cloud platform and a repair terminal;
the vehicle-mounted terminal is used for detecting real-time height data and acceleration data of a vehicle, acquiring vehicle positioning information of the vehicle, judging whether a driving road section is damaged or not according to the vehicle height data and the acceleration data, if so, calculating road surface unevenness according to the vehicle height data and the acceleration data, and sending the road surface unevenness and the corresponding vehicle positioning information to the road side terminal;
the road side terminal is used for shooting a road surface picture of a road section to be detected, acquiring road side positioning information of the road side terminal, judging whether the road section to be detected is damaged or not according to the road surface picture, if so, primarily delimiting a damage range according to the road side positioning information, taking the received vehicle positioning information located in the damage range as damage position information, and sending the damage position information and the corresponding road surface unevenness to the cloud platform;
the cloud platform is used for sending the damaged position information and the corresponding road surface unevenness to the repair terminal and informing the repair terminal to repair the road surface.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the vehicle-mounted terminal is mounted on the vehicle to detect the road surface damage condition, the roadside terminal is arranged at the roadside to photograph the road, and the detection and calculation results of the vehicle-mounted terminal are combined to further calculate and judge, so that the detection precision is improved. And the cloud platform sends a repairing instruction to the repairing terminal based on the two-stage detection result so that the repairing terminal can timely repair the road. The road detection combines the detection data of the vehicle sensor and the road surface picture, so the detection precision is high; meanwhile, the vehicle-mounted terminal is arranged on a common vehicle, and a special detection vehicle is not needed; and finally, the vehicle-mounted terminal and the road side terminal monitor the road surface state through edge calculation respectively, and the cloud platform integrates the edge calculation conclusion of the vehicle-mounted terminal and the road side terminal to judge the road surface state, so that the big data processing pressure of the cloud platform is reduced, and the faster network service response is generated.
Drawings
FIG. 1 is a schematic structural diagram of an embodiment of a road detection and repair system provided in the present invention;
FIG. 2 is a view of a detection scenario of an embodiment of a road detection and repair system provided in the present invention;
FIG. 3 is a flowchart illustrating operation of an embodiment of the vehicle-mounted terminal according to the present invention;
FIG. 4 is a flowchart illustrating operation of one embodiment of a roadside terminal provided by the present invention;
FIG. 5 is a flow chart illustrating the training of an embodiment of the present invention for calculating road surface irregularities using neural networks;
FIG. 6 is a flowchart illustrating operation of one embodiment of a roadside edge processor provided by the present invention;
fig. 7 is a flowchart of a work flow of an embodiment of the cloud platform provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
As shown in fig. 1 and fig. 2, embodiment 1 of the present invention provides a road detection and repair system, including a roadside terminal 20 disposed on a road segment to be detected, a vehicle-mounted terminal 10 mounted on a vehicle, a cloud platform 30, and a repair terminal 40;
the vehicle-mounted terminal 10 is configured to detect real-time height data and acceleration data of a vehicle, acquire vehicle positioning information of the vehicle, determine whether a driving road section is damaged according to the vehicle height data and the acceleration data, calculate road unevenness according to the vehicle height data and the acceleration data if the driving road section is damaged, and send the road unevenness and the corresponding vehicle positioning information to the roadside terminal 20;
the road side terminal 20 is configured to take a road surface picture of a road section to be detected, obtain road side positioning information of the road section, determine whether the road section to be detected is damaged according to the road surface picture, if yes, preliminarily define a damaged range according to the road side positioning information, use the received vehicle positioning information within the damaged range as damaged position information, and send the damaged position information and the corresponding road surface unevenness to the cloud platform 30;
the cloud platform 30 is configured to send the damaged position information and the corresponding road unevenness to the repair terminal 40, and notify the repair terminal 40 to perform road repair.
In this embodiment: the vehicle-mounted terminal 10 is used for acquiring height data and acceleration data when the vehicle passes through a damaged road surface, performing edge calculation to obtain the unevenness of the road surface passing through the damaged road surface, providing high-precision vehicle positioning information, and performing data interaction with a road test terminal, for example, the roadside terminal 20 on a driving road section can also directly send the data to the cloud platform 30; the roadside terminal 20 is used for acquiring a vehicle running track, providing high-precision roadside positioning information to assist the positioning of the vehicle, receiving data sent by the vehicle-mounted terminal 10 to further perform edge calculation and judgment on the damaged road surface range and the damaged unevenness condition, monitoring the road surface damage condition in real time, and sending the data to the cloud platform 30; the cloud platform 30 is used for big data analysis, marking the damaged position of the road surface by combining with a high-precision map, judging the damaged condition of the road surface according to data sent by road side equipment or vehicles, and sending the high-precision damaged position information to the road surface repairing terminal 40; the repair terminal 40 is used for repairing the road surface, can perform data interaction with the cloud platform 30, receives damaged position information of the damaged road surface, and feeds back repair data to the cloud platform 30 for updating after the road surface is repaired.
Specifically, edge computing is a technology developed in the context of high bandwidth, time sensitive, internet of things integration. The method is characterized in that a nearest-end service is provided nearby by adopting an open platform integrating network, computing, storage and application core capabilities on one side close to an object or a data source. The application program is initiated at the edge side, so that a faster network service response is generated, and the basic requirements of the industry in the aspects of real-time business, application intelligence and the like are met. The road surface unevenness is generally used to describe the degree of undulation of a road surface, and refers to the deviation of the road surface from an ideal plane, and is generally used to measure and evaluate the flatness of a road.
According to the invention, by combining the development of intelligent networking of automobiles, data acquisition of vehicles and roadside terminals 20 and cloud interaction, more abundant data support is provided for judging the road surface damage condition, the work of special road detection vehicles is omitted, the networking and intelligentization degree of road surface detection can be greatly improved, the real-time detection of the road surface damage condition becomes possible, further, the road surface repair work of the repair terminals 40 is managed through the cloud platform 30, and the efficiency of the repair work is improved.
In conclusion, the invention solves the problem of complex road surface detection by utilizing the technology in the field of intelligent traffic. By utilizing the real-time performance and reliability of the communication technology and the characteristics of the intelligent networked automobile, the abnormal condition of the road surface is known and reported to the cloud platform 30, the real-time learning and transmission of the road damage condition are realized, the actual difficulty in development of road detection and repair work is solved, the passing efficiency of the road is further ensured, the driving safety of passing vehicles is ensured, and the intelligent networked automobile is one of the key scenes of floor application in the field of intelligent transportation.
Preferably, as shown in fig. 1, the vehicle-mounted terminal 10 includes a sensor group 11, a vehicle-end positioning device 13, a vehicle-end communication device 12, and a vehicle-end edge processor 15;
the sensor group 11 is used for detecting real-time height data and acceleration data of the vehicle;
the vehicle end positioning device 13 is used for acquiring real-time vehicle positioning information of the vehicle-mounted terminal 10;
the vehicle end edge processor 15 is configured to determine whether a driving road section is damaged according to the vehicle height data and the acceleration data, and if so, calculate a road surface unevenness according to the vehicle height data and the acceleration data, and send the road surface unevenness and corresponding vehicle positioning information to the roadside terminal 20 through the vehicle end communication device 12.
As shown in fig. 3, the work flow of the in-vehicle terminal 10 is specifically as follows: when a vehicle runs on a road surface, real-time detection is carried out on vehicle body height data through the sensor group 11, whether the vehicle body height changes is judged, when the vehicle body height changes caused by the road surface damage condition is judged, real-time detection is carried out on sensor data and vehicle suspension data through the sensor group 11, the sensor data comprises vehicle body acceleration data and vehicle body height data, suspension parameters before and after the vehicle body height changes are combined, the suspension data comprises the type of a suspension, the damping of the suspension and the rigidity of the suspension, and for a semi-active suspension and an active suspension, a control strategy of the suspension needs to be provided for reverse calculation, the road surface unevenness of the vehicle running through the damaged road surface is calculated, and the damaged position is positioned by combining high-precision positioning information provided by the high-precision vehicle end positioning device 13; after the calculation is finished, the road unevenness of the driving damaged road and the corresponding vehicle positioning information are sent to the road side terminal 20; if the terminal 20 is not located on the road side of the driving road, the data is directly sent to the cloud platform 30 for further uniform processing. Specifically, the vehicle-mounted communication device can be realized by adopting GNSS and IMU, and the positioning precision is centimeter level.
Specifically, the present embodiment can implement high-precision road detection for two different application scenarios: firstly, when the vehicle runs to a road section without the road side terminal 20, the vehicle-mounted terminal 10 directly sends data to the cloud platform 30 for data processing; secondly, driving to a road section with road side equipment, depending on a V2I technology, the vehicle-mounted terminal 10 performs data interaction with the road side terminal 20 after detecting that the road side terminal 20 exists, and the road side terminal 20 performs data processing and then sends the data to the cloud platform 30 for further processing of the data, so that the defects of traditional cloud computing are overcome, and the real-time performance of the data processing process is improved.
Preferably, as shown in fig. 1, the sensor group 11 includes a vehicle height sensor, a vehicle body acceleration sensor, and a suspension acceleration sensor;
the vehicle body height sensor is used for detecting real-time height data of the vehicle;
the vehicle body acceleration sensor and the suspension acceleration sensor are used for detecting real-time acceleration data of a vehicle.
The sensor group 11 comprises a vehicle height sensor, a vehicle acceleration sensor and a suspension acceleration sensor, wherein the vehicle height sensor acquires real-time data of vehicle height change when passing through a convex hull or a concave pit, the vehicle acceleration sensor acquires vertical acceleration of a vehicle body, and the suspension acceleration sensor acquires suspension system acceleration signals when passing through the convex hull or the concave pit.
Preferably, as shown in fig. 1, the vehicle-mounted terminal 10 further includes an environment detection device 14;
the environment detection device 14 is used for detecting road surface environment information; and judging whether the driving road section has an obstacle or not according to the road surface environment information, if so, judging that the driving road section is not damaged, otherwise, judging whether the driving road section is damaged or not according to the vehicle body height data and the acceleration data.
Specifically, as shown in fig. 3, the environment detection device 14 is used for detecting the road surface condition, and between the determination of the road surface damage condition based on the vehicle height data and the acceleration data, the situation that the vehicle height sensor data changes due to obstacles (non-road surface damage reasons) such as speed bumps and road surface rubbish is eliminated from the road surface picture, and the environment detection device 14 may be implemented by using a millimeter wave radar, a laser radar, a camera, or the like.
Preferably, the roadside terminal 20 includes a camera, a roadside locating device 23, a roadside edge processor 24 and a roadside communication device 22;
the camera device 21 is used for shooting a road surface picture of a road section to be detected;
the roadside locating device 23 is configured to obtain roadside locating information of the roadside terminal 20;
the road side edge processor 24 is configured to determine whether the road section to be detected is damaged according to the road surface photograph, and if so, preliminarily define a damaged range according to the roadside positioning information, use vehicle positioning information within the damaged range as damaged position information, and send the damaged position information and the road surface unevenness to the cloud platform 30 through the roadside communication device 22.
Specifically, the work flow of the roadside terminal is as shown in fig. 4, the camera device 21 can monitor the vehicle driving track of the whole lane, the roadside communication device 22 provides a function of communicating with the vehicle-mounted terminal 10 and the cloud platform 30, the roadside positioning device 23 provides roadside positioning information of the roadside terminal 20 to assist the vehicle-mounted terminal 10 in positioning and receive data sent by the vehicle-mounted terminal 10, the roadside edge processor 24 calculates the expected range and the road damage condition within the range of the damaged road surface by calculating the road condition and the driving track monitored by the camera device 21 in real time in combination with road unevenness and corresponding vehicle positioning information sent by a plurality of vehicles driving through the damaged range, and sends the calculated data to the cloud platform 30.
Preferably, whether the driving road section is damaged or not is judged according to the vehicle height data and the acceleration data, and the method specifically comprises the following steps:
judging whether the change curve of the vehicle body height data accords with the convex hull height curve characteristic or the pit height curve characteristic, if not, judging that the road surface to be detected is not damaged, and if so, turning to the next step;
and further judging whether the change curve of the acceleration data accords with the convex hull acceleration curve characteristic or the pit acceleration curve characteristic, if not, judging that the road surface to be detected is not damaged, and if so, judging that the road surface to be detected is damaged.
The convex hull height profile is characterized by first rising and then falling, the pit height profile is characterized by first falling and then rising, the convex hull acceleration profile is characterized by first falling and then rising, and the pit acceleration profile is characterized by first rising and then falling.
Preferably, the road unevenness is calculated according to the vehicle height data and the acceleration data, and specifically:
collecting height data and acceleration data when a vehicle passes through different convex hulls or pits, and measuring the road surface unevenness of the convex hulls or the pits;
training a neural network by taking the vehicle body height data and the acceleration data as input and taking the road surface unevenness as output to obtain a road surface unevenness prediction model;
and calculating the road surface unevenness of the driving road section by using the road surface unevenness prediction model.
For the edge calculation of the vehicle-mounted terminal 10, the estimation of the road unevenness through the height data and the acceleration data may be implemented by a mechanical learning algorithm, and the algorithm for identifying the road unevenness includes, but is not limited to, a neural network, a support vector machine, a random forest and other mechanical learning algorithms. As shown in fig. 5, taking a neural network as an example, the neural network model parameters are trained by a training set, and the multiple models are compared by evaluation indexes after passing a test set test. The trained neural network model parameters can be obtained in advance and stored, data measured by the sensor group 11 is used as input in practical application, and recognized road unevenness is calculated according to the trained neural network model.
Preferably, as shown in fig. 2, there are a plurality of the in-vehicle terminals 10;
the roadside terminal 20 is configured to receive the road surface unevenness and the corresponding vehicle positioning information sent by the plurality of vehicle-mounted terminals 10 passing through the damaged range, and calculate the final damaged position information and the road surface unevenness by integrating the plurality of vehicle positioning information and the corresponding road surface unevenness.
After the road side terminal 20 determines that the road surface is a damaged road surface, the road surface unevenness is identified by the height data, acceleration data and basic parameters of the suspension which are acquired by the relevant sensors on the vehicle passing through the damaged area and detected in real time. And the calculated road unevenness is sent to the cloud platform 30 through the road side terminal 20, and when the road side terminal 20 does not exist, the data is directly sent to the cloud platform 30. The road side terminal 20 monitors the driving track of each vehicle in real time, after a plurality of vehicles run through the road unevenness and the corresponding vehicle positioning information sent by the vehicle-mounted terminal 10 within the damage range, the vehicle positioning information corresponding to the road unevenness at this time is the damage position information of the convex hull/pit, the road unevenness and the corresponding vehicle positioning information calculated by detecting the plurality of vehicles are combined, high-precision damage position information and road unevenness are calculated, the road unevenness can be averaged, the damage position information can be used for calculating the intersection range of the vehicle positioning information detected by each vehicle, and the damage position information and the road unevenness are sent to the cloud platform 30 after statistics.
Specifically, as shown in fig. 6, since the road unevenness transmitted by the vehicle-mounted terminal 10 is two-dimensional data, the roadside edge processor 24 may expand the road unevenness into three-dimensional data by edge calculation in combination with the positioning data, and the driving track is used to verify the coordinate data. Because the vehicle positioning information sent by the vehicle-mounted terminal 10 is difficult to be continuous, firstly, a continuous coordinate data set is generated according to the vehicle positioning information of a single vehicle; the method comprises the steps that a single vehicle generates a continuous coordinate data set which possibly generates certain errors, the continuous coordinate data set is verified according to a running track, whether the continuous coordinate data set is consistent with the track or not is judged, and if the continuous coordinate data set is not verified, no further processing is carried out; matching the road surface irregularity data of the single vehicle with the continuous coordinate data to generate the road surface irregularity data in the single vehicle track; the method comprises the steps of counting a plurality of vehicles, updating data of regions with repeated coordinate data, filling data of blank regions of the data, and further calculating the region range of the damaged road surface and the road surface unevenness in the range.
Preferably, the number of the roadside terminals 20 is plural;
the cloud platform 30 is configured to receive damaged position information and corresponding road surface unevenness sent by the roadside terminals 20, define a damaged level of each damaged position according to the road surface unevenness, and define a repair priority of each damaged position according to the damaged level;
the cloud platform 30 is further configured to send repair priorities of the damaged positions to the repair terminal 40, where the repair priorities sequentially send repair instructions of the corresponding damaged positions to the repair terminal 40, and notify the repair terminal 40 to perform pavement repair according to the repair priorities.
The roadside terminals 20 include a plurality of ones, which are sequentially disposed on one side of the road. Specifically, as shown in fig. 7, the cloud platform 30 receives data sent by the roadside terminals 20; the cloud platform 30 compares the road surface unevenness with the upper/lower threshold value of the preset range of each damaged level, so as to determine the damaged level of the road surface, when the damaged level of the road surface is judged to be very low and does not need to be repaired, the data are directly stored, when the damaged level of the road surface is judged to reach the level needing to be repaired, the setting of the repairing priority is carried out according to the damaged levels and the traffic flow conditions of a plurality of damaged positions, the repairing sequence is set according to the repairing priority, the plurality of damaged positions are sequentially repaired, the damaged position information needing to be repaired is sent to the repairing terminal 40 during repairing, so that the repairing terminal 40 carries out routine repairing, and the damaged data in the cloud platform 30 are updated after the repairing of the repairing terminal 40 is completed. Specifically, the cloud platform 30 identifies the damaged position by combining with the high-precision map, and sends the positioning information of the label position to the repair terminal 40.
Preferably, the repair terminal 40 is a manned repair vehicle, an unmanned repair vehicle or a remote repair vehicle.
The repair terminal 40 has a pavement repair function, and the type of the repair terminal may be manual repair, remote driving repair, or automatic repair. In this embodiment, the repair terminal 40 specifically refers to a repair vehicle, which may be a manned vehicle, a remote vehicle, or an unmanned vehicle, and after the pavement repair is completed, the repair terminal 40 needs to send repair data to the cloud platform 30 for updating the pavement information.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention. Any other corresponding changes and modifications made according to the technical idea of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A road detection and repair system is characterized by comprising a road side terminal arranged on a road section to be detected, a vehicle-mounted terminal arranged on a vehicle, a cloud platform and a repair terminal;
the vehicle-mounted terminal is used for detecting real-time vehicle height data and acceleration data of a vehicle, acquiring vehicle positioning information of the vehicle, judging whether a driving road section is damaged or not according to the vehicle height data and the acceleration data, if so, calculating road surface unevenness according to the vehicle height data and the acceleration data, and sending the road surface unevenness and the corresponding vehicle positioning information to the road side terminal;
the road side terminal is used for shooting a road surface picture of a road section to be detected, acquiring road side positioning information of the road side terminal, judging whether the road section to be detected is damaged or not according to the road surface picture, if so, primarily delimiting a damage range according to the road side positioning information, taking the received vehicle positioning information located in the damage range as damage position information, and sending the damage position information and the corresponding road surface unevenness to the cloud platform;
the cloud platform is used for sending the damaged position information and the corresponding road surface unevenness to the repair terminal and informing the repair terminal to repair the road surface.
2. The road detection and repair system of claim 1, wherein the vehicle-mounted terminal comprises a sensor group, a vehicle-end positioning device, a vehicle-end communication device and a vehicle-end edge processor;
the sensor group is used for detecting real-time height data and acceleration data of the vehicle;
the vehicle end positioning device is used for acquiring real-time vehicle positioning information of the vehicle-mounted terminal;
the vehicle end edge processor is used for judging whether a driving road section is damaged or not according to the vehicle body height data and the acceleration data, if so, calculating road surface unevenness according to the vehicle body height data and the acceleration data, and sending the road surface unevenness and corresponding vehicle positioning information to the road side terminal through the vehicle end communication device.
3. The road inspection and repair system of claim 2, wherein the set of sensors includes a body height sensor, a body acceleration sensor, and a suspension acceleration sensor;
the vehicle body height sensor is used for detecting real-time height data of the vehicle;
the vehicle body acceleration sensor and the suspension acceleration sensor are used for detecting real-time acceleration data of a vehicle.
4. The road detection and repair system of claim 2, wherein the vehicle-mounted terminal further comprises an environment detection device;
the environment detection device is used for detecting road surface environment information and judging whether an obstacle exists in a running road section according to the road surface environment information, if so, judging that the running road section is not damaged, otherwise, judging whether the running road section is damaged according to the vehicle body height data and the acceleration data.
5. The road detection and repair system of claim 1, wherein the roadside terminal comprises a camera, a roadside locator device, a roadside edge processor, and a roadside communicator;
the camera device is used for shooting a road surface picture of the road section to be detected;
the roadside positioning device is used for acquiring roadside positioning information of a roadside terminal;
the roadside edge processor is used for judging whether the road section to be detected is damaged or not according to the road surface picture, if so, preliminarily demarcating a damage range according to the roadside positioning information, taking vehicle positioning information within the damage range as damaged position information, and sending the damaged position information and the road surface unevenness to the cloud platform through the roadside communication device.
6. The road detection and repair system of claim 1, wherein the vehicle height data and the acceleration data are used to determine whether a damage exists on the driving road section, and specifically:
judging whether the change curve of the vehicle body height data accords with the convex hull height curve characteristic or the pit height curve characteristic, if not, judging that the road surface to be detected is not damaged, and if so, turning to the next step;
and further judging whether the change curve of the acceleration data accords with the convex hull acceleration curve characteristic or the pit acceleration curve characteristic, if not, judging that the road surface to be detected is not damaged, and if so, judging that the road surface to be detected is damaged.
7. The road detection and repair system of claim 1, wherein the road unevenness is calculated from the body height data and the acceleration data, in particular:
collecting height data and acceleration data when a vehicle passes through different convex hulls or pits, and measuring the road surface unevenness of the convex hulls or the pits;
training a neural network by taking the vehicle body height data and the acceleration data as input and taking the road surface unevenness as output to obtain a road surface unevenness prediction model;
and calculating the road surface unevenness of the driving road section by using the road surface unevenness prediction model.
8. The road inspection and repair system according to claim 1, wherein there are a plurality of the vehicle-mounted terminals;
and the road side terminal is used for receiving the road surface unevenness and the corresponding vehicle positioning information sent by the vehicle-mounted terminals within the damage range, and calculating the final damage position information and the road surface unevenness by integrating the vehicle positioning information and the corresponding road surface unevenness.
9. The road inspection and repair system of claim 1, wherein the number of roadside terminals is plural;
the cloud platform is used for receiving the damaged position information and the corresponding road surface unevenness sent by the road side terminals, defining the damaged level of each damaged position according to the road surface unevenness, and defining the repair priority of each damaged position according to the damaged level;
the cloud platform is further used for sending the repair priority of each damaged position to the repair terminal, the repair priority sends the repair instruction of the corresponding damaged position to the repair terminal in sequence, and the repair terminal is informed to repair the road surface according to the repair priority.
10. The road detection and repair system of claim 1, wherein the repair terminal is a manned repair vehicle, an unmanned repair vehicle, or a remotely driven repair vehicle.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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