Road bump detection method and system, storage medium and vehicle

Abstract

The invention provides a road bump detection method and system, a storage medium and a vehicle, and the method comprises the steps: obtaining the vertical acceleration of a target vehicle when the target vehicle runs on a bumpy road surface; acquiring pit slot characteristic data of the bumpy road surface; acquiring a bumpy danger index of the bumpy road surface according to the vertical acceleration and the pit slot characteristic data; judging the jolting grade of the jolting road surface according to the jolting danger index; the judgment result of the jolting level is uploaded to a sharing platform for jolting information sharing; the technical problems that according to an existing road bumping detection method, the road surface condition is generally obtained through a single vehicle-mounted sensor, only the bumping condition of the road surface where a vehicle is located currently can be detected, and the bumping condition of the road beyond the sight cannot be pre-judged are solved. Therefore, a driver or a vehicle system can sense that the vehicle runs into a bumpy road section and cannot decelerate or adjust the driving posture in advance, and the safety and comfort of the driver in the driving process are influenced.

Description

Technical Field

[0001] The present application relates to the technical field of road detection, and in particular to a road bump detection method, a detection system, a storage medium, and a vehicle. Background Art

[0002] With the continuous advancement of sensor technology and the rapid development of computers, computer vision and image processing technologies have also made great progress. Driven by this technological wave, the concepts of "smart transportation" and "smart cities" have emerged.

[0003] Bumpy roads pose numerous hazards to vehicle driving, including tire damage and blowouts, deformation and fracture of the suspension system and shock absorbers, resulting in reduced comfort, mechanical damage and deformation of the chassis and body, and poor contact and malfunction of electronic equipment. Therefore, using computer vision and sensors to detect bumpy roads is a core process, with the primary goal of improving vehicle safety and comfort during driving.

[0004] However, there is at least one of the following problems in the related technology: the existing road bump detection method usually obtains the road condition by a single vehicle-mounted sensor, and can only detect the bumpy condition of the road where the vehicle is currently located, and cannot predict the bumpy condition of the road out of sight. As a result, the driver or vehicle system can only perceive it when the vehicle enters a bumpy section, and cannot slow down or adjust the driving posture in advance, affecting the driver's safety and comfort during driving. Summary of the Invention

[0005] The technical problem to be solved by this application is that the existing road bump detection method usually obtains the road condition by the on-board sensor of a single vehicle, and can only detect the bump condition of the road where the vehicle is currently located, but cannot predict the bump condition of the road outside the field of vision. As a result, the driver or vehicle system can only perceive it when the vehicle enters a bumpy section, and cannot slow down or adjust the driving posture in advance, affecting the driver's safety and comfort during driving.

[0006] To solve the above technical problems, in a first aspect, the present application provides a road bump detection method, which includes: When the target vehicle is traveling on a bumpy road, obtaining the vertical acceleration of the target vehicle; Acquiring pothole characteristic data of a bumpy road surface, the pothole characteristic data including one or more of a pothole sinking depth, a pothole area, and a pothole density; The vertical acceleration and pothole characteristic data are sent as input to the bump calculation model in the cloud to obtain the bump hazard index of the bumpy road surface; Determine the bumpiness level of the bumpy road surface based on the bumpiness hazard index; The determination results of the turbulence level are uploaded to the cloud-based sharing platform for sharing turbulence information.

[0007] Compared with the existing technology, the technical effect achieved by adopting this technical solution is as follows: this solution obtains the vertical acceleration of the target vehicle and the pothole characteristic data of the bumpy road surface when the target vehicle is traveling on the bumpy road surface, and determines the bumpiness level of the bumpy road surface based on the vertical acceleration and the pothole characteristic data. Finally, the determination result of the bumpiness level is uploaded to the cloud-based sharing platform for sharing the bumpiness information, so that when the subsequent vehicle is about to travel on the bumpy road surface, the bumpiness condition of the road ahead can be predicted in advance through the bumpiness information shared on the sharing platform, and sufficient time and driving distance can be reserved to slow down or adjust the driving posture in advance, thereby improving the safety and comfort of the driver during driving.

[0008] In one embodiment of the present application, obtaining a bumpy road hazard index based on vertical acceleration and pothole characteristic data includes: Calculate the geometric feature weight of the pit according to the sinking depth and pit area; The dynamic weight of the pit is calculated based on the vertical acceleration and the pit density; The turbulence hazard index is calculated based on the geometric feature weight and the dynamic weight.

[0009] Compared with existing technologies, this solution achieves the following technical benefits: By calculating the bumpiness hazard index based on pothole depth, area, and density, as well as the vertical acceleration of the target vehicle, this solution can more comprehensively and accurately reflect the actual road bumpiness and potential risks. This avoids the misjudgment that can occur in existing technologies that rely solely on vertical acceleration to determine the bumpiness level.

[0010] In one example of the present application, the calculation formula for calculating the geometric feature weight of the pit according to the sinking depth and the pit area is: ; The calculation formula for the dynamic weight of the pit is calculated based on the vertical acceleration and the pit density: ; The calculation formula for the turbulence hazard index based on the geometric feature weight and dynamic weight is: ; Among them, G is the geometric feature weight, D is the dynamic weight, P is the bumpy hazard index, d is the sinking depth, s is the pothole density, a z is the vertical acceleration, ω is the pit density, b1, b2, b3, b4, b5, b6 are constants, and b1+b2=1, b3+b4=1, b5+b6=1, tanh is the hyperbolic tangent function, σ is the sigmoid logic function, represents the product of b5 and G, Represents the product of b6 and D.

[0011] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: this solution makes the calculation result of the bumpy hazard index more scientific, so as to more accurately reflect the bumpy condition of the bumpy road surface.

[0012] In one example of the present application, the road bump detection system includes a camera device provided on a target vehicle, the bump risk index includes a first bump risk index at a bridge joint, and the road bump detection method further includes: Determining whether the bumpy road surface is a bridge joint based on the road surface image acquired by the camera device; If the bumpy road surface is at a bridge joint, the first bump hazard index is recorded as zero.

[0013] Compared with the existing technology, the technical effect achieved by adopting this technical solution is as follows: this solution records the first bump hazard index as zero when the bumpy road surface is a bridge joint, so as to eliminate the interference of the fixed structure at the bridge joint on the bumpy condition detection result of the road surface, and further improve the accuracy of the actual bumpy condition detection result of the road.

[0014] In one example of the present application, the road bump detection method further includes: Determine whether the weather condition in the area where the target vehicle is located is rainy based on the road image; If the weather condition is rainy, the turbulence risk index for rainy days is: Pr=b7·P; Among them, Pr is the turbulence hazard index on rainy days, and b7 is a constant.

[0015] Compared with the existing technology, the technical effect achieved by adopting this technical solution is as follows: this solution overcomes the interference of the road bump condition detection result caused by the effect of reducing the friction coefficient of the road surface on rainy days by recording the bump hazard index on rainy days as: Pr=b7·P, and further improves the accuracy of the actual road bump condition detection result.

[0016] In one example of the present application, a road section with a bumpy road surface is defined as an abnormal road section, and a vehicle about to travel on the abnormal road section is defined as a first vehicle; The turbulence levels include level one, level two and level three. The turbulence risk index of level one is defined as P1, the turbulence risk index of level two is defined as P2 and the turbulence risk index of level three is defined as P3. <P2<P3; When the bumpiness level is level one, the first vehicle continues to move forward in the current driving posture; When the bump level is level 2, the first vehicle triggers a vehicle suspension stiffness adjustment mode; When the bumpiness level is level two, the first vehicle enters a forced speed reduction mode.

[0017] Compared with existing technologies, this technical solution achieves the following technical benefits: By distinguishing between level one, level two, and level three bumps, this solution enables refined control of the first vehicle about to enter an abnormal road section, further improving driver safety and comfort. Specifically, for level one bumps, the first vehicle maintains normal driving to ensure efficiency; for level two bumps, suspension stiffness is adjusted to enhance comfort or protect the suspension system; and for level three bumps, forced speed reduction is implemented, prioritizing driver safety.

[0018] In a second aspect, the present application further provides a road bump detection system, which is configured to execute the road bump detection method in any of the above examples. The road bump detection system includes: a first acquisition module, the first acquisition module being used to acquire the vertical acceleration of the target vehicle when the target vehicle is traveling on a bumpy road; A second acquisition module, the second acquisition module is used to obtain pothole characteristic data of the bumpy road surface; A data input module is used to send vertical acceleration and pothole characteristic data as input to a bump calculation model in the cloud to obtain a bump hazard index for the bumpy road surface; A level determination module is used to determine the bumpiness level of the bumpy road surface according to the bumpiness risk index; The sharing module is used to upload the determination results of the turbulence level to the cloud-based sharing platform for sharing turbulence information.

[0019] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: the road bump detection system provided by this solution can achieve the technical effect corresponding to any of the above examples, which will not be repeated here.

[0020] In one embodiment of the present application, a road bump detection system includes: a road-end data fusion module, the road-end data fusion module being used to fuse the bump information of the abnormal road section and send the fused bump information and the positioning information of the abnormal road section to the first vehicle; The communication module is used to connect the target vehicle, the cloud, the first vehicle, and the road-side detection module to communicate and share bump information.

[0021] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: this solution connects the target vehicle, cloud, first vehicle, and road-side detection module through the road-side data fusion module and the communication module, so that the target vehicle, cloud, first vehicle, and road-side detection module can share bumpy information.

[0022] On the third aspect, the present application also provides a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by a processor corresponding to the road bump detection system in any of the above examples, the road bump detection system can implement the road bump detection method in any of the above examples.

[0023] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: the computer-readable storage medium provided by this solution can achieve the technical effect corresponding to any of the above examples, which will not be repeated here.

[0024] In a fourth aspect, the present application also provides a vehicle, comprising: a road bump detection system as in any of the above examples.

[0025] Compared with the existing technology, the technical effect achieved by adopting this technical solution is: the vehicle provided by this solution can achieve the technical effect corresponding to any of the above examples, which will not be repeated here.

[0026] By adopting the technical solution of this application, the following technical effects can be achieved: The present application obtains the vertical acceleration of the target vehicle and the characteristic data of potholes on the bumpy road surface when the target vehicle is traveling on the bumpy road surface, and determines the bumpiness level of the bumpy road surface based on the vertical acceleration and the pothole characteristic data. Finally, the determination result of the bumpiness level is uploaded to a cloud-based sharing platform for sharing the bumpiness information. When a subsequent vehicle is about to travel on the bumpy road surface, the bumpiness condition of the road ahead can be predicted in advance through the bumpiness information shared on the sharing platform, and sufficient time and driving distance can be reserved to slow down or adjust the driving posture in advance, thereby improving the safety and comfort of the driver during driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] To more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings to be used in describing the embodiments. Obviously, the drawings described below are only some embodiments of the present application, and those skilled in the art can derive other drawings based on these drawings without inventive effort. Figure 1 One of the flow charts of a road bump detection method provided in an embodiment of the present application; Figure 2 This is a second flow chart of a road bump detection method provided in an embodiment of the present application; Figure 3 This is one of the module diagrams of a road bump detection system provided in an embodiment of the present application; Figure 4 This is the second module diagram of a road bump detection system provided in an embodiment of the present application.

[0028] Description of reference numerals: 100, first acquisition module; 200, second acquisition module; 300, data input module; 400, level determination module; 500, sharing module; 600, road-side data fusion module; 700, communication module. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0030] like Figure 1 As shown, in a first aspect, the present application provides a road bump detection method, which includes: S100: When the target vehicle is traveling on a bumpy road, obtaining a vertical acceleration of the target vehicle; S200: Acquiring pothole characteristic data of a bumpy road surface; S300: Sending the vertical acceleration and pothole characteristic data as input to a bump calculation model in the cloud to obtain a bump hazard index for the bumpy road surface; S400: determining a bumpiness level of the bumpy road surface according to a bumpiness risk index; S500: uploading the determination result of the turbulence level to a cloud-based sharing platform for sharing turbulence information; The pit characteristic data includes one or more of the pit sinking depth, the pit area, and the pit density.

[0031] Specifically, this solution obtains the vertical acceleration of the target vehicle and the pothole characteristic data of the bumpy road surface when the target vehicle is traveling on the bumpy road surface, and determines the bumpiness level of the bumpy road surface based on the vertical acceleration and pothole characteristic data. Finally, the determination result of the bumpiness level is uploaded to a cloud-based sharing platform for sharing the bumpiness information. When a subsequent vehicle is about to travel on the bumpy road surface, the bumpiness condition of the road ahead can be predicted in advance through the bumpiness information shared on the sharing platform, and sufficient time and driving distance can be reserved to slow down or adjust the driving posture in advance, thereby improving the safety and comfort of the driver during driving.

[0032] like Figure 2 As shown, in one embodiment provided by the present application, obtaining a bumpy road hazard index based on vertical acceleration and pothole characteristic data includes: S310: Calculating the geometric feature weight of the pit according to the sinking depth and the pit area; S320: Calculating the dynamic weight of the pit according to the vertical acceleration and the pit density; S330: Calculate a turbulence risk index based on the geometric feature weight and the dynamic weight.

[0033] Specifically, this solution calculates the bumpiness hazard index by combining pothole depth, area, and density with the target vehicle's vertical acceleration. This provides a more comprehensive and accurate reflection of the actual road bumpiness and potential risks. This avoids the misjudgment that can occur in existing technologies that rely solely on vertical acceleration to determine bumpiness levels.

[0034] In one embodiment provided in the present application, S310: the calculation formula for calculating the geometric feature weight of the pit according to the sinking depth and the pit area is: ; S320: The formula for calculating the dynamic weight of the pit based on the vertical acceleration and the pit density is: ; S330: The formula for calculating the bump hazard index based on the geometric feature weight and the dynamic weight is: ; Among them, G is the geometric feature weight, D is the dynamic weight, P is the bumpy hazard index, d is the sinking depth, s is the pothole density, a z is the vertical acceleration, ω is the pit density, b1, b2, b3, b4, b5, b6 are constants, and b1+b2=1, b3+b4=1, b5+b6=1, tanh is the hyperbolic tangent function, σ is the sigmoid logic function, represents the product of b5 and G, Represents the product of b6 and D.

[0035] Specifically, this solution makes the calculation results of the bumpy hazard index more scientific so as to more accurately reflect the bumpy conditions of the bumpy road surface.

[0036] In a specific embodiment provided in this application, the value of b1 is 0.6, the value of b2 is 0.4, the value of b3 is 0.7, the value of b4 is 0.3, the value of b5 is 0.4, and the value of b6 is 0.6; That is, the calculation formula for the geometric feature weight of the pit is calculated based on the subsidence depth and pit area: ; The calculation formula for the dynamic weight of the pit is calculated based on the vertical acceleration and the pit density: ; The calculation formula for the turbulence hazard index based on the geometric feature weight and dynamic weight is: .

[0037] In one embodiment provided herein, a road bump detection system includes a camera device disposed on a target vehicle, a bump risk index includes a first bump risk index at a bridge joint, and a road bump detection method further includes: Determining whether the bumpy road surface is a bridge joint based on the road surface image acquired by the camera device; If the bumpy road surface is at a bridge joint, the first bump hazard index is recorded as zero.

[0038] Specifically, this solution records the first bump hazard index as zero when the bumpy road surface is a bridge joint, so as to eliminate the interference of the fixed structure at the bridge joint on the bumpy condition detection result of the road surface, and further improve the accuracy of the actual bumpy condition detection result of the road.

[0039] In one embodiment provided in this application, the road bump detection method further includes: Determine whether the weather condition in the area where the target vehicle is located is rainy based on the road image; If the weather condition is rainy, the turbulence risk index for rainy days is: Pr=b7·P; Among them, Pr is the turbulence hazard index on rainy days, and b7 is a constant.

[0040] Specifically, this solution records the bumpy hazard index on rainy days as: Pr=b7·P, so as to overcome the interference of the reduced friction coefficient of the road surface on the bumpy condition detection results in rainy days, and further improve the accuracy of the actual bumpy condition detection results of the road.

[0041] In a specific embodiment provided in the present application, the value of b7 is 1.2, that is, the turbulence risk index when the weather condition is rainy is: Pr=1.2P.

[0042] In one embodiment provided by the present application, a road section with a bumpy road surface is defined as an abnormal road section, and a vehicle about to travel on the abnormal road section is defined as a first vehicle; The turbulence levels include level one, level two and level three. The turbulence risk index of level one is defined as P1, the turbulence risk index of level two is defined as P2 and the turbulence risk index of level three is defined as P3. <P2<P3; When the bumpiness level is level one, the first vehicle continues to move forward in the current driving posture; When the bump level is level 2, the first vehicle triggers a vehicle suspension stiffness adjustment mode; When the bumpiness level is level two, the first vehicle enters a forced speed reduction mode.

[0043] In a specific embodiment provided in the present application, setting P=30-60 is level one bump, setting P=60-85 is level two bump, at this time the first vehicle triggers the vehicle suspension stiffness adjustment mode, setting P>85 is level three bump, at this time, the first vehicle enters the forced deceleration mode and will be forced to decelerate to below 30km / h.

[0044] Specifically, this solution distinguishes between level one, level two, and level three bumps, enabling refined control of the first vehicle approaching an abnormal road section, further improving driver safety and comfort. Specifically, for level one bumps, the first vehicle maintains normal driving to ensure efficiency; for level two bumps, suspension stiffness is adjusted to enhance comfort or protect the suspension system; and for level three bumps, forced speed reduction is implemented, prioritizing driver safety.

[0045] Second, as Figure 3 As shown, the present application also provides a road bump detection system, which is used to perform the road bump detection method as described in any of the above embodiments. The road bump detection system includes a first acquisition module 100, a second acquisition module 200, a data input module 300, a level determination module 400, and a sharing module 500. Specifically, the first acquisition module 100 is used to obtain the vertical acceleration of the target vehicle when the target vehicle is traveling on a bumpy road surface. The second acquisition module 200 is used to obtain pothole characteristic data on the bumpy road surface. The data input module 300 is used to send the vertical acceleration and pothole characteristic data as input to a cloud-based bump calculation model to obtain a bump hazard index for the bumpy road surface. The level determination module 400 is used to determine the bump level of the bumpy road surface based on the bump hazard index. The sharing module 500 is used to upload the bump level determination result to a cloud-based sharing platform for bump information sharing.

[0046] In one embodiment provided in this application, Figure 4 As shown, the road bump detection system includes a road-side data fusion module 600 and a communication module 700. The road-side data fusion module 600 is used to fuse the bump information of abnormal road sections and send the fused bump information and the positioning information of the abnormal road sections to the first vehicle. The communication module 700 is used to communicate with the target vehicle, the cloud, the first vehicle, and the road-side detection module to share the bump information.

[0047] Specifically, this solution connects the target vehicle, the cloud, the first vehicle, and the road-side detection module through the road-side data fusion module 600 and the communication module 700, so that the target vehicle, the cloud, the first vehicle, and the road-side detection module can share bumpy information.

[0048] On the third aspect, the present application also provides a computer-readable storage medium. When the instructions in the computer-readable storage medium are executed by a processor corresponding to the road bump detection system in any of the above embodiments, the road bump detection system can implement the road bump detection method in any of the above embodiments.

[0049] In a fourth aspect, the present application also provides a vehicle, comprising: a road bump detection system as in any of the above embodiments.

[0050] Although the present application is disclosed as above, the present application is not limited thereto. Any person skilled in the art may make various changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims.

Claims

1. A road bump detection method, characterized in that: The road bump detection method comprises: When the target vehicle is traveling on a bumpy road, obtaining a vertical acceleration of the target vehicle; Acquiring pothole characteristic data of the bumpy road surface, the pothole characteristic data including one or more of a pothole sinking depth, a pothole area, and a pothole density; sending the vertical acceleration and the pothole characteristic data as input to a bump calculation model in the cloud to obtain a bump hazard index of the bumpy road surface; determining a bumpiness level of the bumpy road surface according to the bumpiness risk index; The determination result of the turbulence level is uploaded to the cloud sharing platform for sharing turbulence information.

2. The road bump detection method according to claim 1, characterized in that: The obtaining of the bumpy road hazard index according to the vertical acceleration and the pothole characteristic data includes: Calculating a geometric feature weight of the pit according to the sinking depth and the pit area; Calculating a dynamic weight of the pit according to the vertical acceleration and the pit density; The turbulence risk index is calculated according to the geometric feature weight and the dynamic weight.

3. The road bump detection method according to claim 2, characterized in that: The calculation formula for calculating the geometric feature weight of the pit according to the sinking depth and the pit area is: ； The calculation formula for calculating the dynamic weight of the pit according to the vertical acceleration and the pit density is: ； The calculation formula for calculating the bump risk index based on the geometric feature weight and the dynamic weight is: ； Wherein, G is the geometric feature weight, D is the dynamic weight, P is the bump risk index, d is the sinking depth, s is the pothole density, a z is the vertical acceleration, ω is the pit density, b1, b2, b3, b4, b5, and b6 are constants, and b1+b2=1, b3+b4=1, and b5+b6=1. tanh is the hyperbolic tangent function, and σ is the sigmoid logic function. represents the product of b5 and G, Represents the product of b6 and D.

4. The road bump detection method according to claim 3, characterized in that: The road bump detection system includes a camera device provided on the target vehicle, the bump risk index includes a first bump risk index at a bridge joint, and the road bump detection method further includes: determining, based on the road surface image acquired by the camera device, whether the bumpy road surface is the bridge joint; If the bumpy road surface is the bridge joint, the first bumpy risk index is recorded as zero.

5. The road bump detection method according to claim 4, characterized in that: The road bump detection method further includes: Determining whether the weather condition in the area where the target vehicle is located is rainy based on the road surface image; If the weather condition is rainy, the turbulence risk index for rainy days is: Pr=b7·P; Wherein, Pr is the bumpy hazard index on rainy days, and b7 is a constant.

6. The road bump detection method according to any one of claims 1 to 5, characterized in that: defining a road section with the bumpy road surface as an abnormal road section, and defining a vehicle about to travel on the abnormal road section as a first vehicle; The turbulence levels include level one turbulence, level two turbulence, and level three turbulence. The turbulence risk index of level one turbulence is defined as P1, the turbulence risk index of level two turbulence is defined as P2, and the turbulence risk index of level three turbulence is defined as P3. <P2<P3; When the bumpiness level is the first level bumpiness, the first vehicle continues to move forward in the current driving posture; When the bump level is the second level bump, the first vehicle triggers a vehicle suspension stiffness adjustment mode; When the bump level is the second-level bump, the first vehicle enters a forced speed reduction mode.

7. A road bump detection system, characterized in that: The road bump detection system is used to perform the road bump detection method according to any one of claims 1 to 6, and the road bump detection system includes: A first acquisition module (100), the first acquisition module (100) is used to acquire the vertical acceleration of the target vehicle when the target vehicle is traveling on a bumpy road; A second acquisition module (200), the second acquisition module (200) is used to acquire pothole characteristic data of the bumpy road surface; A data input module (300), the data input module (300) is used to send the vertical acceleration and the pothole characteristic data as input to a bump calculation model in the cloud to obtain a bump hazard index of the bumpy road surface; a level determination module (400), the level determination module (400) being used to determine the bumpiness level of the bumpy road surface according to the bumpiness risk index; A sharing module (500) is used to upload the determination result of the turbulence level to the cloud sharing platform for sharing turbulence information.

8. The road bump detection system according to claim 7, characterized in that: The road bump detection system includes: A roadside data fusion module (600), the roadside data fusion module (600) is used to fuse the bump information of the abnormal road section, and send the fused bump information and the positioning information of the abnormal road section to the first vehicle; A communication module (700) is used to establish a communication connection between the target vehicle, the cloud, the first vehicle, and the roadside detection module to share the bump information.

9. A computer-readable storage medium, characterized in that When the instructions in the computer-readable storage medium are executed by a processor corresponding to the road bump detection system according to claim 7 or 8, the road bump detection system can implement the road bump detection method according to any one of claims 1 to 7.

10. A vehicle, characterized in that: The vehicle comprises: a road bump detection system as claimed in claim 7 or 8.

Images