Road disease position identification method, electronic equipment, medium and product

Abstract

The invention discloses a road disease position identification method, electronic equipment, a medium and a product, and the method comprises the steps: obtaining road surface information reported by a plurality of terminals, each piece of road surface information comprising position information corresponding to a road surface abnormal point and a target vertical acceleration change value of a vehicle at the road surface abnormal point, the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; clustering analysis is conducted on the position information of all the road surface abnormal points, the clustering center of each clustering cluster is obtained, and each clustering center corresponds to one road disease position point.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of computer, in particular to a road disease position identification method, electronic device, medium and product. BACKGROUND

[0002] At present, with the passing of vehicles, the road may have defects such as cracks, pits, ruts, deep pits and collapse, which are collectively referred to as road diseases. Road diseases affect road capacity, road life and the probability of traffic accidents. In order to avoid the adverse effects of road diseases, it is necessary to discover road diseases in time and maintain the road. At present, road inspection vehicles or pre-embedded detection devices are usually used to detect road diseases, which has the problems of high cost and low efficiency. SUMMARY

[0003] Embodiments of the present application provide a road disease position identification method, electronic device, medium and product, which can at least improve the efficiency of road disease identification.

[0004] In order to at least solve the above technical problems, the present application is implemented as follows: In a first aspect, a road disease position identification method is provided, applied to a server, and the method comprises: acquiring road surface information reported by a plurality of terminals, wherein each road surface information comprises position information corresponding to a road surface anomaly point and a target vertical acceleration change value of a vehicle at the road surface anomaly point, and an absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; and obtaining a cluster center of each cluster by performing cluster analysis on position information of all road surface anomaly points, wherein each cluster center corresponds to a road disease position point.

[0005] In a second aspect, a road disease position identification method is provided, applied to a terminal, and the method comprises: determining a target position point as a road surface anomaly point in response to at least one vertical acceleration change value of a vehicle at the target position point being greater than a vertical acceleration change value detection threshold, and reporting road surface information corresponding to the road surface anomaly point to a server, wherein the road surface information comprises position information of the road surface anomaly point and a target vertical acceleration change value of the vehicle at the road surface anomaly point, and the target vertical acceleration change value is a maximum vertical acceleration change value in the at least one vertical acceleration change value.

[0006] In a third aspect, an electronic device is provided, comprising a processor, a memory and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions are executed by the processor to implement the steps of the method according to the first aspect, or to implement the steps of the method according to the second aspect.

[0007] In a fourth aspect, a readable storage medium is provided, and the readable storage medium has stored thereon a program or instructions, which, when executed by a processor, implement the steps of the method according to the first aspect or the steps of the method according to the second aspect.

[0008] In a fifth aspect, a computer program product is provided, and the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions, which, when executed by a computer, cause the computer to implement the steps of the method according to the first aspect or the steps of the method according to the second aspect.

[0009] In the embodiments of the present application, the road surface information reported by a plurality of terminals is acquired, wherein each road surface information includes position information corresponding to a road surface abnormal point and a target vertical acceleration change value of a vehicle at the road surface abnormal point, and the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; and clustering centers of each cluster are obtained by performing clustering analysis on the position information of all the road surface abnormal points, wherein each clustering center corresponds to a road disease position point. In this way, based on the road surface information reported by the terminals, the positions of the vertical acceleration abnormal value points are found, and a plurality of road disease positions can be identified at the same time, so as to improve the efficiency of road disease position identification, and further effectively improve the service level of the traffic road.

[0010] It should be understood that the foregoing general description and the following detailed description are only exemplary and explanatory, and are not limiting to the present application. BRIEF DESCRIPTION OF DRAWINGS

[0011] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments consistent with the present application and serve to explain the principles of the present application together with the specification.

[0012] Figure 1 FIG. 1 shows a flow diagram of a road disease position identification method according to an exemplary embodiment of the present application; Figure 2 FIG. 2 shows another flow diagram of a road disease position identification method according to an exemplary embodiment of the present application; Figure 3 FIG. 3 shows an interaction diagram of a terminal and a server according to an exemplary embodiment of the present application; Figure 4 FIG. 4 shows another flow diagram of a road disease position identification method according to an exemplary embodiment of the present application; Figure 5 FIG. 5 shows an interaction diagram of a road disease position identification system according to an exemplary embodiment of the present application; Figure 6 Fig. 1 shows a schematic diagram of a processing flow provided by an example embodiment of the present application; Figure 7 Fig. 2 shows a schematic diagram of an electronic device provided by an example embodiment of the present application. DETAILED DESCRIPTION

[0013] The example embodiments will be described in detail herein with reference to the attached drawings. The following description is made with reference to the accompanying drawings in which like reference numerals refer to like elements, unless otherwise indicated. The following description of example embodiments is not representative of all embodiments consistent with the present application. Rather, it is merely intended to be illustrative of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0014] Figure 1 Fig. 1 shows a schematic diagram of a processing flow provided by an example embodiment of the present application; S110: Obtain road surface information reported by a plurality of terminals.

[0015] Each road surface information includes position information corresponding to a road surface anomaly point and a target vertical acceleration change value of a vehicle at the road surface anomaly point, and the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold.

[0016] It can be understood that when a vehicle travels on a flat road surface, the contact between the tire and the road surface is stable, and the acceleration in the vertical direction will remain in a stable and small range. When there is an obstacle, foreign matter or pothole, damage or other abnormal conditions on the road surface, the vehicle will experience a significant bump when passing through the position, and at this time, the acceleration change value of the vehicle in the vertical direction will exceed the vertical acceleration change value detection threshold. Therefore, the acceleration change of the vehicle in the vertical direction, i.e., the vertical acceleration change value, can be used to determine whether an abnormal condition exists at a certain road surface position passed by the vehicle. Therefore, in the present embodiment, when the terminal determines that the absolute value of the vertical acceleration change value of the vehicle at the road surface anomaly point is greater than the vertical acceleration change value detection threshold, the terminal reports the position information corresponding to the road surface anomaly point and the target vertical acceleration change value of the vehicle at the road surface anomaly point to the server.

[0017] In an example embodiment, the terminal can be a vehicle-mounted terminal or a mobile phone, a tablet computer or other terminal located inside a vehicle. For example, the vehicle-mounted terminal establishes a communication connection with the server, the vehicle-mounted terminal has a positioning function or a function of obtaining a position, and the vehicle-mounted terminal has an acceleration sensing function or a function of obtaining a vehicle acceleration, that is, the vehicle-mounted terminal can directly obtain the position information of the vehicle and the acceleration of the vehicle, or indirectly obtain the position information of the vehicle and the acceleration of the vehicle through a positioning device and an acceleration sensor on the vehicle, and then determine the vertical acceleration change value based on the obtained acceleration. When the vehicle-mounted terminal determines that the vertical acceleration change value of the vehicle at a certain road abnormal point exceeds the vertical acceleration change value detection threshold, the server is notified of the position information of the road abnormal point and the vertical acceleration change value of the vehicle at the road abnormal point. For example, the mobile phone or an application (Application, App) installed in the mobile phone can obtain the position information of the vehicle and the vertical acceleration change value of the vehicle, wherein the position information can be obtained based on the positioning function of the mobile phone, and the vertical acceleration change value of the vehicle can be determined based on the acceleration sensing function of the mobile phone, that is, the acceleration sensing function of the mobile phone is used to perceive the acceleration of the vehicle, and then the vertical acceleration change value is determined based on the acceleration; or the mobile phone establishes a connection with a positioning device and an acceleration sensor installed in the vehicle, so that the position information of the vehicle and the vertical acceleration change value of the vehicle can be obtained in real time.

[0018] In the embodiments of the present application, road disease detection does not need to be performed on the road by using a road inspection vehicle or a pre-buried detection device, and the reporting of road surface information can be realized for any vehicle. Thus, the server can receive road surface information reported by multiple terminals at the same time, and the difficulty and cost of obtaining road surface information are reduced.

[0019] S120: Obtain a cluster center of each cluster by performing clustering analysis on the position information of all road abnormal points.

[0020] Each cluster center corresponds to a road disease position point.

[0021] It can be understood that the embodiments of the present application can obtain road surface information reported by multiple terminals, and simultaneously perform clustering analysis on multiple road surface information, so that at least one cluster can be obtained, each cluster has a cluster center, and the cluster center corresponds to a road disease position point.

[0022] In an exemplary embodiment, the Mean-Shift algorithm can be used to perform cluster analysis on the location information of all road surface anomalies to obtain the cluster centers of each cluster. The Mean-Shift algorithm is a non-parametric clustering and target tracking method based on kernel density estimation, which achieves cluster analysis by iteratively finding local maxima or density peaks in the data distribution. Exemplarily, S120 above may include the following steps: S121: Determine at least one initial point from the data. and initialize its position as The dataset includes location information for each road surface anomaly point, which can be latitude and longitude coordinates, meaning the location of each initial point is its corresponding latitude and longitude coordinates.

[0023] S122: For each initial point, perform a loop iteration to obtain the convergence point corresponding to each initial point.

[0024] Understandably, for each data point In the t The position in the next iteration can be updated using the following formula:

[0025] This formula is used to divide the points Move to its local weighted average position, i.e., the mean of the points within the sliding window. It's a kernel function. It's a bandwidth parameter. It is the first point in the set. The position vectors of the points.

[0026] S123: After each iteration, check the distance between the center points before and after the iteration. Check if the distance is less than a preset threshold. If the condition is met, the point is considered to have converged; otherwise, continue iterating.

[0027] S124: When all initial points converge to their respective density maxima, convergence points that converge to the same point or whose density peak difference is less than a preset difference threshold are merged to form the final cluster.

[0028] S124 may include the following steps: Step 1: Collect all convergence points.

[0029]

[0030] Step 2: Remove duplicate or nearly identical convergence points.

[0031] for Each convergence point in if there is another convergence point such that wherein, is a difference threshold value for judging whether the density peaks of and can be merged into one density peak, if less than the second threshold value, it is determined that and belong to the same cluster.

[0032] In another exemplary embodiment, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm can be used to cluster analyze the position information of all road surface anomaly points, that is, the DBSCAN algorithm is used to cluster analyze the position information of all road surface anomaly points first, and then the weighted average is used to obtain the cluster center position information as the estimation of the road disease position.

[0033] In the embodiment of the present application, the road surface information reported by a plurality of terminals is obtained, wherein each road surface information includes position information corresponding to a road surface anomaly point and a target vertical acceleration change value of a vehicle at the road surface anomaly point, and the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; the position information of all road surface anomaly points is cluster analyzed to obtain cluster centers of each cluster, wherein each cluster center corresponds to a road disease position point. In this way, based on the road surface information reported by the terminal, the position center of the vertical acceleration anomaly value point is found, and multiple road disease positions can be identified at the same time, thereby improving the efficiency of road disease position identification, and further effectively improving the service level of the traffic road.

[0034] Figure 2 Another flowchart of the road disease position identification method provided by the embodiment of the present application is shown, as shown in Figure 2 the method can include the following steps: S210: Obtain road surface information reported by a plurality of terminals.

[0035] Each road surface information includes position information corresponding to a road surface anomaly point and a target vertical acceleration change value of a vehicle at the road surface anomaly point, and the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold.

[0036] S220: Cluster analyze the position information of all road surface anomaly points to obtain cluster centers of each cluster, wherein each cluster center corresponds to a road disease position point.

[0037] The specific content of S210 and S220 described above can be referred to the aboveFigure 1 The related description of S110 and S120 in the illustrated embodiment will not be repeated here.

[0038] S230: For each road disease location point, a second vertical acceleration change value corresponding to the road disease location point is obtained by performing weighted average processing on each first vertical acceleration change value corresponding to the road disease location point.

[0039] Each first vertical acceleration change value is a target vertical acceleration change value in road surface information corresponding to each target road surface anomaly point, and each target road surface anomaly point is a road surface anomaly point in a neighborhood range of the road disease location point.

[0040] S240: The disease degree of each road disease location point is evaluated according to the second vertical acceleration change value corresponding to each road disease location point.

[0041] It can be understood that the extracted clustering center is used as the road disease location point, for each road disease location point, the position information thereof is used as the center, and a range is determined according to a preset radius, wherein the preset radius can be a bandwidth, that is, the neighborhood range refers to a range or area formed by the road surface anomaly points around the clustering center and divided into the clustering center. The target vertical acceleration change values of the road surface anomaly points in the neighborhood range are weighted and averaged to obtain the second vertical acceleration change value corresponding to the road disease location point, and then the disease degree of each road disease location point is evaluated based on the second vertical acceleration change value corresponding to each road disease location point.

[0042] For example, if the second vertical acceleration change value corresponding to a certain road disease location point is less than a first threshold, the disease degree of the road disease location point is determined to be a first degree; if the second vertical acceleration change value corresponding to a certain road disease location point is greater than or equal to the first threshold and less than a second threshold, the disease degree of the road disease location point is determined to be a second degree, wherein the second degree is greater than the first degree; if the second vertical acceleration change value corresponding to a certain road disease location point is greater than or equal to the second threshold, the disease degree of the road disease location point is determined to be a third degree, wherein the third degree is greater than the second degree.

[0043] In the embodiment of the present application, the road surface information reported by a plurality of terminals is acquired, wherein each road surface information comprises position information corresponding to a road surface abnormal point and a target vertical acceleration change value of a vehicle at the road surface abnormal point, and the absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; clustering analysis is performed on the position information of all road surface abnormal points to obtain clustering centers of each cluster, wherein each clustering center corresponds to a road disease position point. In this way, based on the road surface information reported by the terminal, the position center of the vertical acceleration abnormal value point is found, and a plurality of road disease positions can be identified at the same time, thereby improving the efficiency of road disease position identification, and further effectively improving the service level of the traffic road. In addition, for each road disease position point, a weighted average processing is performed on each first vertical acceleration change value corresponding to the road disease position point to obtain a second vertical acceleration change value corresponding to the road disease position point, wherein each first vertical acceleration change value is a target vertical acceleration change value in the road surface information corresponding to each target road surface abnormal point, and each target road surface abnormal point is a road surface abnormal point in the neighborhood range of the road disease position point. According to the second vertical acceleration change value corresponding to each road disease position point, the disease degree of each road disease position point is evaluated, so as to realize accurate quantification of the road disease degree.

[0044] In an exemplary embodiment, the method further comprises: based on the position information and the second vertical acceleration change value corresponding to each road disease position point, constructing road disease information corresponding to each road disease position point; and adding the road disease information to a road disease information dataset.

[0045] It can be understood that, based on the position information and the second vertical acceleration change value corresponding to each road disease position point, road disease information corresponding to each road disease position point is constructed, the road disease information comprises the position information, the second vertical acceleration change value and the road disease degree of the road disease position point, and is added to the road disease information dataset, which is used to support road disease treatment and road disease avoidance in the driving process, thereby reducing the road disease positioning cost and improving the data timeliness.

[0046] In an exemplary embodiment, before acquiring the road surface information reported by a plurality of terminals, the method further comprises: sending a registration instruction to each terminal, wherein the registration instruction is used to instruct the terminal to register a vertical acceleration change value abnormal reporting event, the vertical acceleration change value abnormal reporting event is used to trigger the terminal to determine a target position point as a road surface abnormal point and report road surface information corresponding to the road surface abnormal point in response to that the absolute value of at least one vertical acceleration change value of the vehicle at the target position point collected by the terminal is greater than a vertical acceleration change value detection threshold, and the target vertical acceleration change value included in the road surface information is the maximum vertical acceleration change value in the at least one vertical acceleration change value.

[0047] The following is an example, as shown in Figure 3 The embodiment is exemplarily illustrated, as Figure 3 shown, an interaction schematic diagram of a service end and a terminal provided by the embodiment of the application can include the following steps: S310: a communication connection is established between the service end and the terminal through a transmission control protocol (TCP).

[0048] S320: Reg mechanism registration.

[0049] That is, the Reg mechanism is used to register the vertical acceleration change value abnormal reporting event to each terminal.

[0050] S320 can include: S322: sending a registration instruction to each terminal.

[0051] The registration instruction is used to instruct the terminal to register the vertical acceleration change value abnormal reporting event.

[0052] S324: a vertical acceleration change value detection threshold is issued to each terminal.

[0053] S325: receiving the registration confirmation information returned by the terminal.

[0054] S330: Notify mechanism triggering.

[0055] That is, the terminal continuously detects the vertical acceleration value, and when the absolute value of the vertical acceleration change value is greater than the vertical acceleration change value detection threshold, the abnormal acceleration value and the position information of the abnormal point are reported to the service end through the Notify mechanism, and the position information can be the latitude and longitude value.

[0056] S340: when both parties are in an idle state, the connection is maintained through a heartbeat data packet.

[0057] The idle state means that the terminal or the service end is currently not executing any valid task, and is in a waiting or low-power consumption mode.

[0058] In the embodiment, only the vertical acceleration change value abnormal reporting event is registered to the terminal, the terminal reports the position information of the road abnormal point and the vertical acceleration change value of the vehicle at the road abnormal point in response to the triggering of the event, and any terminal can upload the road information corresponding to the road abnormal point after registering the vertical acceleration change value abnormal reporting event. In this way, the service end can receive the road information reported by multiple terminals at the same time, which reduces the difficulty and cost of obtaining the road information. Figure 4Another flowchart of the method for identifying road disease position provided by an example embodiment of the present application is shown, which can be executed by a terminal. In other words, the method can be executed by software or hardware installed on the terminal, and the method can include the following steps: S410: in response to the at least one vertical acceleration change value of the vehicle at the target position point being greater than the vertical acceleration change value detection threshold, determining that the target position point is a road abnormal point, and reporting road information corresponding to the road abnormal point to a server.

[0059] The road information includes position information of the road abnormal point and a target vertical acceleration change value of the vehicle at the road abnormal point, and the target vertical acceleration change value is a maximum vertical acceleration change value in the at least one vertical acceleration change value.

[0060] It can be understood that when the vehicle is driving on a flat road, the tire is in stable contact with the road, and the vertical acceleration will remain in a stable and small range. When there is an obstacle, foreign matter or a pit, damage or other abnormal conditions on the road, the vehicle will experience a significant bump when passing through the position, and at this time, the vertical acceleration change value of the vehicle will exceed the vertical acceleration change value detection threshold. Therefore, the vertical acceleration change of the vehicle, i.e., the vertical acceleration change value, can be used to determine whether an abnormal condition exists at a certain road position passed by the vehicle. Therefore, in the embodiment of the present application, when the terminal determines that the absolute value of the vertical acceleration change value of the vehicle at the road abnormal point is greater than the vertical acceleration change value detection threshold, the terminal reports the position information corresponding to the road abnormal point and the target vertical acceleration change value of the vehicle at the road abnormal point to the server.

[0061] In addition, in the embodiment of the present application, the terminal reports the target vertical acceleration change value of the vehicle at the road abnormal point, and the target vertical acceleration change value is a maximum vertical acceleration change value in the at least one vertical acceleration change value. That is, at a certain moment, when the vertical acceleration change value of the vehicle at a certain position point is greater than the vertical acceleration change value detection threshold, the vertical acceleration change value after the moment is continuously collected until a moment when the vertical acceleration change value of the vehicle is less than the vertical acceleration change value detection threshold, and the collection is stopped. Therefore, the maximum vertical acceleration change value in the at least one vertical acceleration change value is selected as the target vertical acceleration change value.

[0062] In an example embodiment, the terminal can be a vehicle-mounted terminal or a mobile phone, a tablet computer or other terminal located inside the vehicle. Exemplarily, taking the vehicle-mounted terminal as an example, the vehicle-mounted terminal establishes a communication connection with the server, the vehicle-mounted terminal has a positioning function or a function of obtaining a position, and the vehicle-mounted terminal has an acceleration sensing function or a function of obtaining a vehicle acceleration, that is, the vehicle-mounted terminal can directly obtain the position information of the vehicle and the acceleration of the vehicle, or indirectly obtain the position information of the vehicle and the acceleration of the vehicle through a positioning device and an acceleration sensor on the vehicle, and then determine the vertical acceleration change value based on the obtained acceleration. When the vehicle-mounted terminal determines that the vertical acceleration change value of the vehicle at a certain road surface abnormal point exceeds the vertical acceleration change value detection threshold, the position information of the road surface abnormal point and the vertical acceleration change value of the vehicle at the road surface abnormal point are reported to the server. Taking the mobile phone as an example, the mobile phone or the application (Application, App) installed in the mobile phone can obtain the position information of the vehicle and the vertical acceleration change value of the vehicle, wherein the position information can be obtained based on the positioning function of the mobile phone, and the vertical acceleration change value of the vehicle can be determined based on the acceleration sensing function of the mobile phone, that is, the acceleration sensing function of the mobile phone is used to perceive the acceleration of the vehicle, and then the vertical acceleration change value is determined based on the acceleration; or the mobile phone establishes a connection with the positioning device and the acceleration sensor installed in the vehicle respectively, so that the position information of the vehicle and the vertical acceleration change value of the vehicle can be obtained in real time.

[0063] In the embodiments of the present application, by responding to the fact that at least one vertical acceleration change value of the vehicle at the target position point is greater than the vertical acceleration change value detection threshold, the target position point is determined to be a road surface abnormal point, and the road surface information corresponding to the road surface abnormal point is reported to the server, wherein the road surface information includes the position information of the road surface abnormal point and the target vertical acceleration change value of the vehicle at the road surface abnormal point, and the target vertical acceleration change value is the maximum vertical acceleration change value in the at least one vertical acceleration change value, so that the server can quickly identify multiple road disease positions based on the road surface information reported by the terminal by finding the position center of the vertical acceleration abnormal value point, thereby improving the efficiency of road disease position identification, and further effectively improving the service level of the traffic road.

[0064] In an example embodiment, before responding to the fact that at least one vertical acceleration change value of the vehicle at the target position point is greater than the vertical acceleration change value detection threshold, determining that the target position point is a road surface abnormal point, and reporting the road surface information corresponding to the road surface abnormal point to the server, the method further includes the following steps: obtaining acceleration data collected by the acceleration sensor; obtaining converted acceleration data by converting the acceleration data to a unified coordinate system; and calculating the vertical acceleration change value based on the converted acceleration data.

[0065] It can be understood that the motion data of each vehicle is relative to the vehicle itself, and the motion data measured by the vehicle itself sensor is converted to a unified coordinate system, so that each vertical acceleration change value received by the server is in the same coordinate system, avoiding re-conversion. In an exemplary embodiment, the unified coordinate system can be the earth coordinate system.

[0066] Exemplarily, the conversion of coordinates can be implemented based on the following formula (1): (1) wherein, is the acceleration vector in the earth coordinate system, and the last member is the vertical acceleration component, denoted as , is the acceleration vector in the current coordinate system, is the coordinate transformation matrix, used to convert to the earth coordinate system. The construction of the coordinate transformation matrix can be implemented using a static construction algorithm. In the coordinate conversion process, first define the acceleration vector , which represents the gravity vector when the terminal is stationary. Define the magnetometer vector , which is used to reflect the direction of the geomagnetic field. Then calculate the gravity direction according to the following formula (2), calculate the east axis according to the following formula (3), calculate the north axis according to the following formula (4), and determine the coordinate transformation matrix R based on the gravity direction, the east axis and the north axis, wherein the coordinate transformation matrix is .

[0067] , (2) (3) (4) Based on the above formulas (1)-(4), the value of can be obtained, and since the gravitational acceleration is contained in , the gravitational acceleration ( ) can be directly subtracted to obtain the vertical acceleration change value during vehicle driving.

[0068] In an example embodiment, before the target position point is determined as a road abnormal point and the road information corresponding to the road abnormal point is reported to the server in response to the at least one vertical acceleration change value of the vehicle at the target position point being greater than the vertical acceleration change value detection threshold, the method further comprises: receiving a registration instruction issued by the server, wherein the registration instruction is used to instruct the terminal to register a vertical acceleration change value abnormal reporting event, and the vertical acceleration change value abnormal reporting event is used to trigger the terminal to determine the target position point as the road abnormal point and report the road information corresponding to the road abnormal point in response to the absolute value of the at least one vertical acceleration change value of the vehicle at the target position point collected being greater than the vertical acceleration change value detection threshold.

[0069] For specific details about this embodiment, please refer to the related description in the above Figure 3 embodiment, which will not be repeated here.

[0070] The application embodiment also provides an interactive schematic diagram of a road disease position identification system, as shown in Figure 5 The road disease position identification system includes a data collection layer, a data processing layer, and an application layer. The data collection layer is composed of distributed terminals, and the processing procedure of the data collection layer includes the following steps: S510: The terminal monitors the vertical acceleration change value in real time according to a preset vertical acceleration change value detection threshold.

[0071] S520: Determine whether the vertical acceleration change value of the vehicle at the road abnormal point exceeds the vertical acceleration change value detection threshold.

[0072] If it exceeds, go to S530; if it does not exceed, go to S510.

[0073] S530: Report the road information to the server.

[0074] The road information includes the position information corresponding to the road abnormal point and the target vertical acceleration change value of the vehicle at the road abnormal point.

[0075] The data processing layer includes a server, and the processing procedure of the data processing layer includes the following steps: S540: Receive the road information reported by the terminal.

[0076] S550: Construct an abnormal data set based on the reported road information.

[0077] S560: Cluster analysis of the abnormal data set.

[0078] S570: Construct a road disease information data set.

[0079] wherein the road disease information dataset comprises position information of each cluster center and a vertical acceleration change value of a vehicle at the cluster center, and each cluster center corresponds to a road disease position point.

[0080] S575: sending the road disease information dataset to an application layer.

[0081] The processing flow of the application layer comprises the following steps: S580: receiving the road disease information dataset constructed by the server.

[0082] S590: optimizing a road maintenance system by using the road disease information dataset.

[0083] S595: optimizing an automatic driving road risk avoidance system by using the road disease information dataset.

[0084] wherein, as shown in Figure 6 The application embodiment further provides another processing flow diagram of the application layer, wherein the cloud road disease data center constructs a road network disease database according to the previous road disease information dataset and makes a comprehensive risk assessment by AI research and judgment to generate disease avoidance instructions and a maintenance priority list. The maintenance priority list is decided according to the disease position and disease intensity information in the disease database and is issued to the road maintenance system. After receiving the maintenance priority list, the maintenance work order system of the road maintenance system arranges and dispatches the construction team to repair the road disease. After the repair, the road disease repair condition is fed back to the road network disease database of the cloud road disease data center. In the automatic driving application scenario, the cloud road disease data center can send the disease avoidance instructions containing the road disease level and position information to the automatic driving system at the vehicle end. Although the current vehicle end automatic driving system has laser radar, vision, millimeter wave radar and other perception measures, heavy rain and snow weather and heavy fog weather make the accuracy of these sensors decrease, which leads to the risk of misjudgment of the automatic driving system. Therefore, after introducing the disease avoidance instructions given by the cloud road disease server, the vehicle end automatic driving module makes a comprehensive research and judgment, and the collaborative decision-making layer can provide a more conservative automatic driving strategy in bad weather, thereby providing a safer driving experience.

[0085] As shown in Figure 7 The application embodiment further provides an electronic device 700, comprising a processor 710 and a memory 720, wherein the memory 720 stores a program or instruction which can be run on the processor 710, and the program or instruction is executed by the processor 710 to realize the various processes of the above-mentioned Figures 1 to 6 The embodiments shown in the above-mentioned

[0086] The embodiment of the present application further provides a readable storage medium, wherein the readable storage medium stores a program or instructions, and the program or instructions are executed by a processor to implement the above-mentioned Figures 1 to 6 The various processes of the above-mentioned embodiments and the same technical effects can be achieved, and thus details are not described herein again.

[0087] The processor is the processor in the terminal in the above-mentioned embodiments. The readable storage medium can include a computer readable only memory (ROM), a random access memory (RAM), a magnetic disc or an optical disc, etc. In some examples, the readable storage medium can be a non-transient computer readable storage medium.

[0088] The embodiment of the present application further provides a chip, which comprises a processor and a communication interface, wherein the communication interface is coupled with the processor, and the processor is used to run a program or instructions to implement the above-mentioned Figures 1 to 6 The various processes of the above-mentioned embodiments and the same technical effects can be achieved, and thus details are not described herein again.

[0089] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system chip, a system chip, a chip system or a system on chip, etc.

[0090] The embodiment of the present application further provides a computer program / program product, which comprises a computer program stored on a non-transient computer readable storage medium, and the computer program comprises program instructions, and the program instructions are executed by a computer to implement the above-mentioned Figures 1 to 6 The various processes of the above-mentioned embodiments and the same technical effects can be achieved, and thus details are not described herein again.

[0091] It should be understood that, in this paper, the term "including", "containing" or any other variant thereof is intended to cover non-exclusive containing, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the method and device in the embodiment of the present application is not limited to the order of functions shown or discussed, and can also include the execution of functions in a substantially simultaneous manner or in a reverse order, for example, the described method can be executed in a different order from the described order, and various steps can also be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0092] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned example methods can be realized by means of a computer software product and a general hardware platform as necessary, and of course can also be realized by hardware. The computer software product is stored in a storage medium (such as a ROM, a RAM, a magnetic disc, an optical disc, etc.), and includes a plurality of instructions for enabling a terminal or a network side device to execute the method described in each embodiment of the present application.

[0093] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the specific embodiments described above, and the specific embodiments described above are merely illustrative rather than limiting. Those skilled in the art can make many forms of embodiments under the inspiration of the present application without departing from the scope of the present application and the scope protected by the claims, and these embodiments all belong to the protection of the present application.

Claims

1. A method of identifying a location of a road disease, characterized by, Applied to a server, comprising: Obtaining road surface information reported by a plurality of terminals, wherein each road surface information comprises position information corresponding to a road surface anomaly point and a target vertical acceleration change value of a vehicle at the road surface anomaly point, and an absolute value of the target vertical acceleration change value is greater than a vertical acceleration change value detection threshold; Obtaining a cluster center of each cluster by performing clustering analysis on position information of all road surface anomaly points, wherein each cluster center corresponds to a road disease position point.

2. The method of claim 1, wherein, After the cluster center of each cluster is obtained by performing clustering analysis on the position information of all road surface anomaly points, the method further comprises: For each road disease position point, a second vertical acceleration change value corresponding to the road disease position point is obtained by performing weighted average processing on first vertical acceleration change values corresponding to the road disease position point, wherein each first vertical acceleration change value is the target vertical acceleration change value in the road surface information corresponding to each target road surface anomaly point, and each target road surface anomaly point is the road surface anomaly point within a neighborhood range of the road disease position point; According to the second vertical acceleration change value corresponding to each road disease position point, the disease degree of each road disease position point is evaluated.

3. The method of claim 2, wherein, The method further comprises: Based on the position information and the second vertical acceleration change value corresponding to each road disease position point, road disease information corresponding to each road disease position point is constructed; The road disease information is added to a road disease information data set.

4. The method of claim 1, wherein, Before the road surface information reported by a plurality of terminals is obtained, the method further comprises: Sending a registration instruction to each terminal, wherein the registration instruction is used to instruct the terminal to register a vertical acceleration change value abnormal reporting event, the vertical acceleration change value abnormal reporting event is used to trigger the terminal to determine that a target position point is a road surface anomaly point in response to an absolute value of at least one vertical acceleration change value of a vehicle at the target position point collected being greater than the vertical acceleration change value detection threshold, and to report road surface information corresponding to the road surface anomaly point, wherein the target vertical acceleration change value included in the road surface information is the maximum vertical acceleration change value in the at least one vertical acceleration change value.

5. A method of identifying a location of a road disease, characterized by, Applied to a terminal, comprising: In response to at least one vertical acceleration change value of a vehicle at a target position point being greater than a vertical acceleration change value detection threshold, determining that the target position point is a road surface anomaly point, and reporting road surface information corresponding to the road surface anomaly point to a server, wherein the road surface information comprises position information of the road surface anomaly point and a target vertical acceleration change value of the vehicle at the road surface anomaly point, and the target vertical acceleration change value is the maximum vertical acceleration change value in the at least one vertical acceleration change value.

6. The method of claim 5, wherein, Before the method of determining the target position point as a road abnormal point and reporting road information corresponding to the road abnormal point to a server in response to at least one vertical acceleration change value of a vehicle at the target position point being greater than a vertical acceleration change value detection threshold, the method further comprises: obtaining acceleration data collected by an acceleration sensor; obtaining converted acceleration data by converting the acceleration data to a unified coordinate system; calculating the vertical acceleration change value based on the converted acceleration data.

7. The method of claim 5, wherein, Before the method of determining the target position point as a road abnormal point and reporting road information corresponding to the road abnormal point to a server in response to at least one vertical acceleration change value of a vehicle at the target position point being greater than a vertical acceleration change value detection threshold, the method further comprises: receiving a registration instruction issued by the server, wherein the registration instruction is used to instruct the terminal to register a vertical acceleration change value exception reporting event, and the vertical acceleration change value exception reporting event is used to trigger the terminal to determine the target position point as the road abnormal point and report the road information corresponding to the road abnormal point in response to an absolute value of at least one vertical acceleration change value of a vehicle at the target position point collected by the terminal being greater than the vertical acceleration change value detection threshold.

8. An electronic device, comprising: The processor, the memory, and the program or instructions stored on the memory and executable on the processor are included, and the program or instructions are executed by the processor to implement the steps of the road disease position identification method according to any one of claims 1-7.

9. A readable storage medium, characterized by, The program or instructions are stored on the readable storage medium, and the program or instructions are executed by the processor to implement the steps of the road disease position identification method according to any one of claims 1-7.

10. A computer program product, characterised in that, The computer program product includes program instructions, and when the program instructions are executed by the computer, the computer implements the steps of the road disease position identification method according to any one of claims 1-7.

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