Road surface measurement method and device, electronic equipment and storage medium

Abstract

This application provides a road surface measurement method, apparatus, electronic device, and storage medium. The method includes: acquiring the relative height of at least four wheels of a vehicle traveling on a target road; the relative height is relative to a preset reference ground, and the at least four wheels are not all located on the same side of the vehicle; constructing a plane containing at least three of the at least four wheels based on their relative heights, the at least three wheels not all located on the same side of the vehicle; acquiring the distance between the remaining wheels and the plane based on their relative heights; and determining the road surface unevenness of the target road based on the distance between the remaining wheels and the plane. This method improves the accuracy of measuring the unevenness of the road surface when a vehicle is traveling.

Description

Technical Field

[0001] This application relates to pavement measurement technology, and more particularly to a pavement measurement method, apparatus, electronic device and storage medium. Background Technology

[0002] With the development of vehicle electrification and intelligence, the development of autonomous driving is accelerating, and the comfort requirements of advanced autonomous driving functions are correspondingly increasing. Differences in road surface unevenness have a significant impact on the comfort of autonomous vehicles during operation. Determining the road surface unevenness during vehicle operation is crucial for improving the operational comfort of autonomous vehicles.

[0003] However, existing methods for measuring road surface unevenness have limitations, such as being unsuitable for use in autonomous driving or having low detection accuracy. Summary of the Invention

[0004] This application provides a road surface measurement method, device, electronic equipment, and storage medium to solve the problem of low accuracy in measuring road surface unevenness during vehicle operation.

[0005] In a first aspect, this application provides a road surface measurement method, the method comprising:

[0006] The relative height of at least four wheels of the vehicle is obtained when the vehicle is traveling on the target road; the relative height is the height relative to a preset reference ground, and the at least four wheels are not all located on the same side of the vehicle;

[0007] Based on the relative height of at least three of the at least four wheels, a plane is constructed in which the at least three wheels are located, and the at least three wheels are not all located on the same side of the vehicle;

[0008] Based on the relative height of the remaining wheels among the at least four wheels, the distance between the remaining wheels and the plane is obtained;

[0009] The road surface unevenness of the target road is determined based on the distance between the remaining wheels and the plane.

[0010] Optionally, determining the road surface unevenness of the target road based on the distance between the remaining wheels and the plane includes:

[0011] The road surface type of the target road is determined based on the distance between the remaining wheels and the plane, and the mapping relationship between the distance and the road surface type;

[0012] The road surface unevenness of the target road is obtained based on the road surface type of the target road and the mapping relationship between the road surface type and the unevenness.

[0013] Optionally, constructing the plane containing the at least three wheels based on the relative height of the at least three of the at least four wheels includes:

[0014] The at least four wheels are sorted according to their relative heights;

[0015] Select the preset number of wheels in ascending order of their number;

[0016] The plane is constructed using the relative heights of a selected preset number of wheels.

[0017] Optionally, obtaining the relative height of at least four wheels of the vehicle while it is traveling on the target road includes:

[0018] Acquire sensor data corresponding to the wheel; the sensor includes: a first sensor installed between the vehicle body and the suspension corresponding to the wheel and / or a second sensor installed on the wheel;

[0019] The relative height of the wheel is obtained based on the sensor data, and the mapping relationship between the sensor coefficients, sensor data, and relative height constructed based on a preset reference ground.

[0020] Optionally, the sensor includes: the first sensor and the second sensor;

[0021] The step of obtaining the relative height of the wheel based on the sensor data, and the mapping relationship between sensor coefficients, sensor data, and relative height constructed based on a preset reference ground, includes:

[0022] The first relative initial height of the wheel is obtained based on the first sensor data, the sensor coefficients constructed based on a preset reference ground, the first sensor data, and the mapping relationship between relative height.

[0023] The second relative initial height of the wheel is obtained based on the second sensor data, and the mapping relationship between the sensor coefficients constructed based on the preset reference ground, the second sensor data, and the relative height.

[0024] The relative height of the wheel is obtained based on the first relative initial height and the second relative initial height.

[0025] Optionally, the sensor includes: a first sensor and a second sensor, and the step of determining the road surface unevenness of the target road based on the distance between the remaining wheel and the plane includes:

[0026] Obtain a first initial unevenness of a first plane constructed based on the relative height obtained by the first sensor, and a second initial unevenness of a second plane constructed based on the relative height obtained by the second sensor;

[0027] The road surface unevenness of the target road is determined based on the first initial unevenness and the second initial unevenness.

[0028] Optionally, the method further includes:

[0029] The vehicle is controlled intelligently based on the unevenness of the target road surface.

[0030] Secondly, this application provides a road surface measuring device, the device comprising:

[0031] The first acquisition module is used to acquire the relative height of at least four wheels of the vehicle when it is traveling on the target road; the relative height is the height relative to a preset reference ground.

[0032] A construction module is used to construct the plane containing at least three of the at least four wheels based on the relative height of at least three of the at least four wheels;

[0033] The second acquisition module is used to acquire the distance between the remaining wheels and the plane based on the relative height of the remaining wheels among the at least four wheels;

[0034] The determination module is used to determine the road surface unevenness of the target road based on the distance between the remaining wheels and the plane.

[0035] Thirdly, this application provides a controller, including: a processor, and a memory communicatively connected to the processor;

[0036] The memory stores computer-executed instructions;

[0037] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of the first aspects.

[0038] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any of the first aspects.

[0039] Fifthly, this application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the learning transition state prediction method described in any of the first aspects.

[0040] The road surface measurement method, apparatus, electronic device, and storage medium provided in this application involve a controller acquiring the relative height of at least four wheels of a vehicle traveling on a target road; then, constructing a plane containing at least three of the four wheels based on their relative heights; next, acquiring the distance between the remaining wheels and the plane based on their relative heights; and finally, determining the road surface unevenness of the target road accordingly. Since the relative height of the wheels changes depending on the unevenness of the road surface, the relative height of the wheels can reflect the unevenness of the road surface where the vehicle is currently located. Furthermore, the above method is unaffected by the environment and is not limited by many influencing factors; it only requires the measured relative height of the wheels to accurately obtain the road surface unevenness, improving the accuracy of road surface unevenness measurement and contributing to improving the comfort and stability of autonomous vehicles during driving. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0042] Figure 1 A flowchart illustrating the first road surface measurement method provided in this application:

[0043] Figure 2 This is a schematic diagram of the installation location of a first sensor;

[0044] Figure 3 A flowchart illustrating the second road surface measurement method provided in this application;

[0045] Figure 4 A flowchart illustrating the third road surface measurement method provided in this application;

[0046] Figure 5 A flowchart illustrating the fourth road surface measurement method provided in this application;

[0047] Figure 6 A flowchart illustrating the fifth road surface measurement method provided in this application;

[0048] Figure 7 A flowchart illustrating the sixth road surface measurement method provided in this application;

[0049] Figure 8 A schematic diagram of the structure of a road surface measuring device provided in this application;

[0050] Figure 9 This is a schematic diagram of the structure of a controller 900 provided in this application.

[0051] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0052] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0053] During operation, autonomous vehicles can adjust their autonomous driving parameters based on varying road surface unevenness. For example, if the road surface is uneven, the vehicle can appropriately increase its shock absorption performance to ensure a comfortable ride; conversely, when the road surface is relatively smooth, the shock absorption performance can be reduced. Therefore, real-time acquisition of road surface unevenness data is crucial for the stability and comfort of autonomous vehicles.

[0054] There are various existing methods for detecting road surface unevenness.

[0055] Existing technology 1: Contact measurement

[0056] This measurement method primarily refers to using road profile measuring equipment that maintains constant contact with the road surface for road measurement. Examples include longitudinal unevenness analyzers and multi-wheel leveling instruments. Because this method allows direct contact with the road surface, it offers high measurement accuracy. However, since this method requires contact with the road surface to perform the measurement, it cannot be practically installed on vehicles, meaning it cannot be applied to real-time measurement of road unevenness during vehicle movement.

[0057] Existing technology 2: Non-contact measurement

[0058] Non-contact measurement mainly refers to the use of vehicle-mounted laser, ultrasonic, and camera sensors to collect road surface information through images, sound waves, and laser feedback signals of varying lengths, and then using algorithms to measure road surface unevenness. However, this method is often affected by many factors such as environment, lighting, and driving habits, which limits its use and makes the measurement accuracy highly dependent on the environment.

[0059] For example, when measuring road surface unevenness by taking pictures with a camera, only a partial angle of the road surface can be captured, which cannot accurately reflect the actual condition of the road surface; moreover, when the light is dim, this method of measuring road surface unevenness by taking pictures has low accuracy.

[0060] Existing technology 3: Suspension response recognition

[0061] This method primarily involves acquiring relevant vibration transmission characteristic parameters of the road surface through the suspension to the vehicle body, and then using algorithms to analyze and calculate the specific road surface unevenness based on these parameters. However, this type of calculation involves too many related theoretical parameters, requiring accurate determination of numerous parameters such as suspension stiffness, tire pressure, driving speed, driving habits, and vehicle load weight to accurately calculate road surface unevenness. However, in practical applications, it is impossible to obtain accurate data for these parameters, thus failing to yield precise road surface unevenness results.

[0062] In summary, existing road surface unevenness measurement methods cannot meet the requirement of accurately acquiring road surface unevenness information during vehicle operation. The inventors considered that the relative height between the wheels directly affects the operational comfort of autonomous vehicles during operation. Furthermore, the greater the road surface unevenness, the greater the difference in relative wheel height; that is, wheel height directly reflects road surface unevenness. Therefore, if the wheel height can be accurately acquired during vehicle operation, the necessary road surface unevenness information can be accurately obtained.

[0063] In view of this, this application provides a road surface measurement method. This method measures the relative height of the wheels during vehicle operation to obtain the actual road surface unevenness during the operation of an autonomous vehicle. It can be applied to the real-time measurement of road surface unevenness during vehicle operation and meets the actual usage needs of the vehicle. It is not affected by environmental factors and other rigidities, thus achieving accurate acquisition of road surface unevenness and improving the measurement accuracy of road surface unevenness during vehicle operation.

[0064] The entity executing the road surface measurement method provided in this application can be any controller of the vehicle, such as the Vehicle Control Unit (VCU) or the Electronic Stability Program (ESP); it can also be an electronic device, such as a computer or a back-end server of an autonomous vehicle. This electronic device can acquire relevant data during the vehicle's operation to execute the road surface measurement method provided in this application. For example, the electronic device can wirelessly connect to the vehicle's controller to acquire relevant data during the vehicle's operation from the controller.

[0065] The following uses a controller as the executing entity as an example to illustrate the technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems in detail through specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0066] Figure 1 A flowchart illustrating the first road surface measurement method provided in this application is shown below. Figure 1 As shown, it includes the following steps:

[0067] S101. Obtain the relative height of at least four wheels of the vehicle when it is traveling on the target road.

[0068] The aforementioned at least four wheels are not all located on the same side of the vehicle. Regarding the selection of the at least four wheels, when the vehicle includes only four wheels, then the at least four wheels refer to all four wheels of the vehicle; when the vehicle includes more than four wheels, provided that the at least four wheels are not all located on the same side of the vehicle, this application does not limit the specific selection method of the at least four wheels, and it can be some of the wheels or all of the wheels of the vehicle, and this application does not limit it. For example, when the vehicle includes six wheels, the at least four wheels can be, for example, the two frontmost wheels on both sides and the two rearmost wheels on both sides; or it can be the two frontmost wheels on both sides and the two middle wheels on both sides.

[0069] The target road mentioned above can be any road that is traversable by vehicles, and this application does not limit it. The relative height mentioned above is the height relative to a preset reference ground. This application does not limit the way the preset reference ground is set; for example, the ground when the vehicle is on a level road surface with zero load can be used as the preset reference ground.

[0070] In this step, the controller acquires the relative height of at least four wheels that are not all located on the same side of the vehicle when driving on the target road. Based on this relative height, the controller determines the actual road surface unevenness during the vehicle's autonomous driving process. It should be understood that if the vehicle has more than four wheels, the controller can acquire the relative height of the corresponding number of wheels.

[0071] One possible implementation is that the controller can obtain the relative height of at least four wheels of the vehicle while it is traveling on the target road using sensors. The type and number of sensors used to obtain the relative height of the different wheels can be the same or different.

[0072] The sensors mentioned here can be sensors capable of acquiring height data, and / or whose acquired data has a mapping relationship with relative height. Therefore, based on the sensors, the relative height of at least four wheels of a vehicle traveling on a target road can be obtained. Furthermore, the sensor's installation location is related to the type of data it acquires. Examples include height sensors (e.g., Hall effect sensors) installed between the vehicle body and the suspension corresponding to the wheels, pressure sensors inside the wheels, and infrared sensors on the sides of the wheels.

[0073] S102. Construct the plane containing at least three of the at least four wheels based on the relative height of the three wheels.

[0074] This application does not limit the specific number of at least three wheels out of at least four wheels; for example, it could be three, four, or even more. The specific number of at least three wheels here can be preset. These at least three wheels are not all located on the same side of the vehicle.

[0075] This application does not limit the method by which the controller determines the at least three wheels for constructing the plane from at least four wheels. For example, it can select at least three wheels to construct the plane in ascending order; it can also select at least three wheels to construct the plane in descending order; it can also select at least three wheels at fixed positions; or it can randomly select at least three wheels to construct the plane. The specific method can be set according to actual needs. Optionally, when the controller constructs the plane based on the relative height of the three wheels, the controller can, for example, determine the actual positions of the three wheels based on their relative height. Then, the controller constructs the corresponding plane by connecting these three actual positions. The actual positions mentioned here can, for example, be represented using 3D coordinates. This application does not limit the construction method of the 3D coordinate system; it can be any coordinate system that can characterize the aforementioned three actual positions.

[0076] Optionally, when the controller constructs a plane based on the relative heights of three or more wheels, the controller can, for example, determine the actual positions of the three or more wheels based on their relative heights. Then, the controller constructs the plane containing the three or more wheels based on their actual positions using a plane fitting method. This application does not limit the specific implementation of the plane fitting; it can be any plane fitting method in the prior art.

[0077] S103. Based on the relative height of the remaining wheels among at least 4 wheels, obtain the distance between the remaining wheels and the plane.

[0078] Since the distance between the remaining wheels and the plane reflects the relative positional relationship of at least four wheels of the vehicle, and the relative positional relationship of at least four wheels reflects the unevenness of the road surface where the vehicle is located, in this step, the controller obtains the distance between the remaining wheels and the plane based on the relative height of the remaining wheels among the at least four wheels, and uses this obtained distance to determine the actual unevenness of the road surface where the vehicle is located.

[0079] For example, the controller can determine the actual position of the remaining wheels out of at least four wheels based on their relative heights. The controller can then calculate the distance from the remaining wheels to the constructed plane based on this actual position. Specifically, any method for calculating the distance from a point to a plane can be used, which will not be elaborated upon here.

[0080] S104. Determine the road surface unevenness of the target road based on the distance between the remaining wheels and the plane.

[0081] Since the distance between the remaining wheels and the plane can characterize the road surface unevenness of the target road where the vehicle is currently located, in this step, the controller determines the road surface unevenness of the target road based on the distance between the remaining wheels and the plane.

[0082] This application does not limit the method of characterizing road surface unevenness; it can be a custom method or any existing method for characterizing unevenness. For example, road surface unevenness can be characterized by terms such as flat, relatively flat, relatively rough, and rough.

[0083] The controller determines the road surface unevenness of the target road based on the distance between the remaining wheels and the surface, and this determination is related to the number of remaining wheels.

[0084] For example, if only one wheel remains, the controller can pre-store the mapping relationship between the distance between the remaining wheel and the plane and the road surface unevenness of the target road. The controller can determine the road surface unevenness of the target road based on the distance between the remaining wheel and the plane, and the mapping relationship.

[0085] Alternatively, the controller can store the mapping relationship between distance and road surface type, as well as the mapping relationship between road surface type and unevenness. The controller determines the road surface type of the target road based on the distance between the remaining wheels and the road surface, and the mapping relationship between distance and road surface type; then, based on the road surface type of the target road, and the mapping relationship between road surface type and unevenness, it obtains the road surface unevenness of the target road. The aforementioned road surface type can be, for example, a custom road surface type, such as A-type, B-type, C-type, D-type, etc.

[0086] If multiple wheels remain, the controller determines the road surface unevenness of the target road based on the distances between these remaining wheels and the plane. For example, the controller could average the distances between the remaining wheels and the plane, and then determine the road surface unevenness based on this average. Alternatively, the controller could perform statistical analysis on the distances between the remaining wheels and the plane, and then determine the road surface unevenness based on the statistical analysis results.

[0087] For example, the controller stores a mapping relationship between the number of distances exceeding a preset distance threshold and the road surface unevenness. This application does not limit the specific value of the preset distance threshold; those skilled in the art can determine it based on actual conditions. The controller determines the number of distances exceeding the preset distance threshold, and then, based on this number and the mapping relationship between the number and the road surface unevenness, determines the road surface unevenness of the target road.

[0088] In this embodiment, the controller acquires the relative heights of at least four wheels of the vehicle while it is traveling on the target road. Then, based on the relative heights of at least three of the four wheels, a plane is constructed containing those three wheels. Next, based on the relative heights of the remaining wheels, the distance between the remaining wheels and the plane is acquired. Finally, the road surface unevenness of the target road is determined accordingly. Since the relative heights of the wheels change depending on the unevenness of the road surface, the relative heights of the wheels can reflect the unevenness of the road surface where the vehicle is currently located. Furthermore, the above method is unaffected by the environment and is not limited by many influencing factors. It only requires the measured relative heights of the wheels to accurately acquire the road surface unevenness, improving the accuracy of road surface unevenness measurement and contributing to the subsequent improvement of the comfort and stability of autonomous vehicles during driving.

[0089] As mentioned earlier, the controller can obtain the relative height of at least four wheels of the vehicle when it is traveling on the target road using sensors.

[0090] For example, the controller can acquire sensor data corresponding to the wheel; then, based on the sensor data, and a mapping relationship between sensor coefficients, sensor data, and relative height constructed based on a preset reference ground, the relative height of the wheel can be obtained. The sensor data mentioned here can be, for example, current or voltage data, depending on the type of sensor.

[0091] Regarding the sensor coefficients constructed based on the preset reference ground, they can be obtained, for example, through pre-experimentation. Taking an electronic device (e.g., a computer or server) as the executing entity, the electronic device fits and derives accurate sensor coefficients based on multiple sets of sensor data recorded during the experiment, and the corresponding measured relative height of the wheels. For example, the mapping relationship among the above three can be: Ha = Ka * A, where Ha is the relative height, Ka is the sensor coefficient, and A is the sensor data.

[0092] It should be understood that the type and number of sensors used to obtain the relative height of different wheels can be the same or different. For example, the aforementioned sensors may include a first sensor installed between the vehicle body and the suspension corresponding to the wheel, and / or a second sensor installed on the wheel.

[0093] The first sensor mentioned here may be, for example, a height sensor (e.g., a Hall sensor), and the second sensor mentioned above may be, for example, a pressure sensor (also known as a tire pressure sensor), which may be installed inside the tires of a vehicle. Figure 2 This is a schematic diagram of the installation location of a first sensor, such as... Figure 2 As shown, the first sensor is installed between the vehicle body and the suspension corresponding to the wheel. It should be understood that in practical applications, this application does not limit the specific location of the first sensor between the vehicle body and the suspension corresponding to the wheel. For example, the first sensor can be installed on the upper suspension arm or the lower suspension arm, depending on the actual usage requirements.

[0094] Taking the acquisition of the relative height of at least four wheels of a vehicle traveling on a target road using multiple sensors as an example, in this case, the relative height of the corresponding wheel can be obtained from the data collected by each sensor. Based on this relative height, the road surface unevenness corresponding to each sensor is obtained using the methods described in steps S102-S104 above. Then, the road surface unevenness corresponding to each sensor is combined to obtain the final road surface unevenness of the target road. In this case, the relative height corresponding to each wheel of the vehicle is not unique.

[0095] Alternatively, the final relative height of the corresponding wheel can be obtained from the data collected by each sensor. Using this final relative height, steps S102-S104 above can be performed to obtain the final road surface unevenness of the target road. In this case, the relative height corresponding to each wheel of the vehicle is unique.

[0096] In other words, the road surface unevenness of the target road can be calculated separately based on the data of each sensor, and then the final road surface unevenness of the target road can be obtained based on the multiple road surface unevennesses corresponding to multiple sensors; alternatively, when obtaining the relative height, the final relative height of the wheel can be obtained based on the relative height determined by each sensor, and then the road surface unevenness of the target road can be determined based on the final relative height.

[0097] The following example illustrates two implementation methods, using the example of each wheel equipped with two types of sensors, namely the first sensor and the second sensor.

[0098] Implementation Method 1: The relative height of each wheel of the vehicle is unique.

[0099] Figure 3 A flowchart illustrating the second road surface measurement method provided in this application is shown below. Figure 3 As shown, in this implementation, the controller can acquire the road surface unevenness of the target road using the following steps. Contents in this implementation that are the same as or similar to those in the above embodiments can be referred to the above embodiments, and will not be repeated here:

[0100] S201. Based on the first sensor data, and the mapping relationship between the sensor coefficients constructed based on the preset reference ground, the first sensor data, and the relative height, obtain the first relative initial height of the wheel.

[0101] S202. Based on the second sensor data, and the mapping relationship between the sensor coefficients constructed based on the preset reference ground, the second sensor data, and the relative height, the second relative initial height of the wheel is obtained.

[0102] The first relative initial height mentioned in step S201 above refers to the relative height of the wheel corresponding to the first sensor; the second relative initial height mentioned in step S202 refers to the relative height of the wheel corresponding to the second sensor. The specific implementation method can be found in the foregoing content and will not be repeated here.

[0103] S203. Obtain the relative height of the wheel based on the first relative initial height and the second relative initial height.

[0104] One possible implementation is that the controller can, for example, add the first relative initial height and the second relative initial height corresponding to each wheel and take the average to obtain the relative height of the wheel; or, the controller can pre-store the weights of the first relative initial height and the second relative initial height, and obtain the relative height of the wheel based on the weights, as well as the first relative initial height and the second relative initial height.

[0105] For example, for a certain wheel, the controller multiplies the first relative initial height of the wheel by the corresponding weight, multiplies the corresponding second relative initial height by the corresponding weight, and then adds the two together to obtain the relative height of the wheel.

[0106] Another possible implementation involves storing a mapping between driving scenarios and relative heights determined by different types of sensors in the controller. This application does not limit the way driving scenarios are divided; for example, it may include high-temperature driving scenarios and low-temperature driving scenarios. The controller, for example, can acquire the current actual driving scenario and then, based on the driving scenario and the aforementioned mapping, determine which type of sensor's relative height will be used as the final wheel relative height.

[0107] Since the performance of different types of sensors may vary under different driving scenarios, experiments can be conducted to determine which type of sensor is more accurate in determining relative height under different driving scenarios. A mapping relationship can then be established between driving scenarios and the relative height determined by the corresponding type of sensor with higher accuracy. Based on this, the relative height of the vehicle's wheels when traveling on a target road can be determined. This approach better aligns with actual driving scenarios, expands the application scenarios of road surface measurement methods, and improves the accuracy of road surface unevenness measurement.

[0108] S204. Construct a plane containing at least three of the at least four wheels, based on the relative height of the three wheels.

[0109] S205. Based on the relative height of the remaining wheels out of at least four wheels, obtain the distance between the remaining wheels and the plane.

[0110] S206. Determine the road surface unevenness of the target road based on the distance between the remaining wheels and the plane.

[0111] In this implementation, after acquiring the sensor data corresponding to the wheel, the controller can obtain the relative height of the wheel based on the sensor data, the sensor coefficients constructed based on a preset reference ground, and the mapping relationship between the sensor data, the relative height, and the sensor height. This method allows for accurate determination of the wheel's relative height based on the sensor data, thereby characterizing road surface unevenness and improving the accuracy of the road surface measurement method provided in this application.

[0112] Furthermore, the above implementation method uses two types of sensors to obtain the relative height of the wheels, thus obtaining a more accurate relative height of the wheels, which further improves the accuracy of the road surface unevenness of the target road determined accordingly.

[0113] Implementation Method 2: The relative height of each wheel of the vehicle is not unique.

[0114] Figure 4 A flowchart illustrating the third road surface measurement method provided in this application is shown below. Figure 4 As shown, in this implementation, the controller can obtain the first initial unevenness of the first plane constructed based on the relative height obtained by the first sensor, and the second initial unevenness of the second plane constructed based on the relative height obtained by the second sensor.

[0115] For details, please refer to... Figure 4 The controller can obtain the first initial unevenness of the first plane constructed based on the relative height obtained by the first sensor through the following steps. The contents that are the same as or similar to those in the above embodiments can be referred to the above embodiments, and will not be repeated here:

[0116] S301. Obtain the relative height of at least four wheels of the vehicle when it is traveling on the target road, based on the information obtained from the first sensor.

[0117] S302. Based on the relative height of at least three of the at least four wheels obtained from the first sensor, construct the first plane in which the at least three wheels are located.

[0118] S303. Based on the relative height of the remaining wheels among at least four wheels obtained from the first sensor, obtain the distance between the remaining wheels and the first plane.

[0119] S304. Determine the first initial unevenness of the target road based on the distance between the remaining wheels of at least four wheels and the first plane obtained from the first sensor.

[0120] The aforementioned first initial unevenness refers to the road surface unevenness of the target road determined based on the data from the first sensor.

[0121] Continue to refer to Figure 4 The controller can obtain the second initial unevenness of the second plane constructed based on the relative height obtained by the second sensor through the following steps. The contents that are the same as or similar to those in the above embodiments can be referred to the above embodiments, and will not be repeated here:

[0122] S305. Obtain the relative height of at least four wheels of the vehicle when it is traveling on the target road, based on the information obtained from the second sensor.

[0123] S306. Based on the relative height of at least three of the at least four wheels obtained from the second sensor, construct the second plane in which the at least three wheels are located.

[0124] S307. Based on the relative height of the remaining wheels among at least four wheels obtained from the second sensor, obtain the distance between the remaining wheels and the second plane.

[0125] S308. Determine the second initial unevenness of the target road based on the distance between the remaining wheels of at least four wheels and the second plane obtained from the second sensor.

[0126] The aforementioned second initial unevenness refers to the road surface unevenness of the target road determined based on the data from the second sensor.

[0127] It should be understood that this application is not limited to the execution order of obtaining the first initial unevenness based on the first sensor and obtaining the second initial unevenness based on the second sensor; they can be executed in parallel or sequentially; when executed sequentially, this application does not limit the order in which the two are executed.

[0128] After obtaining the first initial unevenness and the second initial unevenness, the controller can execute step S309.

[0129] S309. Determine the road surface unevenness of the target road based on the first initial unevenness and the second initial unevenness.

[0130] For example, if the first initial roughness and the second initial roughness represent the same level of road roughness, the controller can use either the first initial roughness or the second initial roughness as the road roughness of the target road. If the first initial roughness and the second initial roughness represent different levels of road roughness, the controller can select the one representing the higher level of road roughness as the road roughness of the target road.

[0131] In this implementation, the controller acquires the final road surface roughness based on road surface roughness data obtained from two types of sensors. This approach expands the application scenarios of the road surface measurement method provided in this application, and further improves the accuracy of the final acquired road surface roughness by using road surface roughness data obtained from two types of sensors.

[0132] Optionally, after acquiring the road surface unevenness, the controller can perform intelligent driving control of the vehicle based on the road surface unevenness of the target road.

[0133] The intelligent driving control mentioned here can be, for example, adjusting the intelligent driving control parameters of the vehicle during driving based on the unevenness of the target road surface. This could include adjusting the vehicle's autonomous driving mode or the parameters of the shock absorption system, thereby enabling the vehicle's autonomous driving state to adapt to the unevenness of the current road surface, improving the vehicle's stability and comfort during driving, while also reducing vehicle wear and tear and protecting the vehicle.

[0134] One possible implementation is that after acquiring the road surface unevenness, the controller directly performs intelligent driving control of the vehicle based on the road surface unevenness.

[0135] Another possible implementation is that the controller can send the road surface unevenness to electronic devices, such as computers or vehicle back-end servers, so that the electronic devices can generate corresponding intelligent driving control parameters and then send them to the vehicle for intelligent driving control.

[0136] The following describes how to construct the plane containing at least three of the at least four wheels based on the relative height of at least three of the four wheels, i.e., step S102 in the above embodiment. Figure 5 A flowchart illustrating the fourth road surface measurement method provided in this application is shown below. Figure 5 The step S102 may include the following steps:

[0137] S401. Sort at least four wheels according to their relative heights.

[0138] In this step, the controller sorts at least four wheels according to their relative heights to construct a plane based on that sorting.

[0139] S402. Select the preset number of wheels according to the sorting order from low to high.

[0140] This application does not limit the specific value of the preset number; it can be any number greater than 3 and less than the aforementioned minimum of 4 wheels. In this step, the controller selects the preset number of wheels in ascending order to construct the plane accordingly.

[0141] S403. Construct a plane using the relative heights of the selected preset number of wheels.

[0142] For example, the controller can first determine the actual position of the wheels using the relative heights of a selected preset number of wheels. Taking an initial relative height of 0 as an example, if the relative height of the wheels changes to 5cm during vehicle movement, the z-coordinate value of the wheel increases by 5, thus determining the wheel's position. After determining the actual positions of the selected preset number of wheels, the controller can construct a plane based on these actual positions. The specific construction method can be referred to the above embodiment, and will not be repeated here.

[0143] In this embodiment, the controller sorts at least four wheels based on their relative heights. Then, it selects a preset number of wheels in ascending order and uses the relative heights of these selected wheels to construct a plane. In this way, the controller can construct a plane corresponding to wheels with lower relative heights, thereby reflecting the road conditions at the lower position of the vehicle and representing the actual road conditions.

[0144] The following is a specific embodiment of a road surface measurement method provided in this application. Figure 6 This is a flowchart illustrating the fifth road surface measurement method provided in this application. Figure 7 A flowchart illustrating the sixth road surface measurement method provided in this application is shown below. Figure 6 and Figure 7 As shown, the method includes the following steps:

[0145] S501. Acquire sensor data corresponding to at least 4 wheels.

[0146] Reference Figure 7 The sensors include: a height sensor mounted between the vehicle body and the corresponding suspension components of the wheels, and tire pressure sensors mounted on the wheels. It should be understood that... Figure 7 This is a schematic diagram illustrating how the controller acquires sensor data from four height sensors and four tire pressure sensors.

[0147] S502. Based on the height sensor data, and the mapping relationship between the sensor coefficients constructed based on the preset reference ground, the height sensor data, and the relative height, obtain the first relative initial height of the wheel.

[0148] S503. Based on the tire pressure sensor data, and the mapping relationship between the sensor coefficient constructed based on the preset reference ground, the tire pressure sensor data, and the relative height, the second relative initial height of the wheel is obtained.

[0149] S504. Obtain the relative height of the wheel based on the first relative initial height and the second relative initial height.

[0150] S505. Sort at least four wheels according to their relative heights.

[0151] S506. Select the preset number of wheels according to the sorting order from low to high.

[0152] S507. Construct a plane using the relative heights of the selected preset number of wheels.

[0153] S508. Based on the relative height of the remaining wheels out of at least four wheels, obtain the distance between the remaining wheels and the plane.

[0154] S509. Determine the road surface type of the target road based on the distance between the remaining wheels and the plane, and the mapping relationship between the distance and the road surface type.

[0155] S510. Based on the road surface type of the target road and the mapping relationship between road surface type and unevenness, obtain the road surface unevenness of the target road.

[0156] S511. Intelligent driving control of the vehicle based on the unevenness of the target road surface.

[0157] Figure 8 This application provides a schematic diagram of the structure of a road surface measuring device, as shown below. Figure 8 As shown, the road surface measuring device includes: a first acquisition module 11, a construction module 12, a second acquisition module 13, and a determination module 14. Optionally, the road surface measuring device may also include, for example, the following module: a control module 15.

[0158] The first acquisition module 11 is used to acquire the relative height of at least four wheels of the vehicle when it is traveling on the target road; the relative height is the height relative to a preset reference ground, and the at least four wheels are not all located on the same side of the vehicle;

[0159] The construction module 12 is used to construct a plane containing at least three of the at least four wheels based on the relative height of at least three of the at least four wheels, wherein not all three wheels are located on the same side of the vehicle.

[0160] The second acquisition module 13 is used to acquire the distance between the remaining wheel and the plane based on the relative height of the remaining wheel among the at least four wheels;

[0161] The determination module 14 determines the road surface unevenness of the target road based on the distance between the remaining wheels and the plane.

[0162] Optionally, the determining module 14 is specifically used to determine the road surface type of the target road based on the distance between the remaining wheels and the plane, and the mapping relationship between the distance and the road surface type; and to obtain the road surface unevenness of the target road based on the road surface type of the target road, and the mapping relationship between the road surface type and the unevenness.

[0163] Optionally, the construction module 12 is specifically used to sort the at least four wheels according to their relative heights; select a preset number of wheels in ascending order; and construct the plane using the relative heights of the selected preset number of wheels.

[0164] Optionally, the first acquisition module 11 is specifically used to acquire sensor data corresponding to the wheel; the sensor includes: a first sensor installed between the vehicle body and the suspension corresponding to the wheel and / or a second sensor installed on the wheel; based on the sensor data, and the mapping relationship between sensor coefficients, sensor data, and relative height constructed based on a preset reference ground, the relative height of the wheel is acquired.

[0165] For example, the sensor includes: a first sensor and a second sensor; a first acquisition module 11, specifically configured to acquire a first relative initial height of the wheel based on the first sensor data and a mapping relationship between sensor coefficients constructed based on a preset reference ground, the first sensor data, and relative height; acquire a second relative initial height of the wheel based on the second sensor data and a mapping relationship between sensor coefficients constructed based on a preset reference ground, the second sensor data, and relative height; and acquire the relative height of the wheel based on the first relative initial height and the second relative initial height.

[0166] Optionally, the sensor includes: a first sensor and a second sensor; a determining module 14 is specifically used to obtain a first initial unevenness obtained by constructing a first plane based on the relative height obtained by the first sensor, and a second initial unevenness obtained by constructing a second plane based on the relative height obtained by the second sensor; and to determine the road surface unevenness of the target road based on the first initial unevenness and the second initial unevenness.

[0167] Optionally, the control module 15 is used to perform intelligent driving control on the vehicle based on the road surface unevenness of the target road.

[0168] The road surface measurement device provided in this application can perform the road surface measurement method in the above-described method embodiments. Its implementation principle and technical effects are similar, and will not be repeated here. It should be noted that the above... Figure 8 The division of modules shown is merely illustrative. This application does not limit the division of modules or the naming of modules.

[0169] Figure 9 This is a schematic diagram of the structure of a controller 900 provided in this application. Figure 9 As shown, the controller may include at least one processor 901 and a memory 902.

[0170] The memory 902 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0171] The memory 902 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0172] The processor 901 is used to execute computer execution instructions stored in the memory 902 to implement the road surface measurement method described in the foregoing method embodiments. The processor 901 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0173] The controller 900 may also include a communication interface 903, through which it can communicate and interact with external devices, such as terminal devices (e.g., mobile phones, tablets). In specific implementations, if the communication interface 903, memory 902, and processor 901 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0174] Optionally, in a specific implementation, if the communication interface 903, memory 902, and processor 901 are integrated on a single chip, then the communication interface 903, memory 902, and processor 901 can communicate through an internal interface.

[0175] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used for the road surface measurement method in the above embodiments.

[0176] This application also provides a computer program product including executable instructions stored in a readable storage medium. At least one processor of an electronic device can read the executable instructions from the readable storage medium, and the processor executes the executable instructions to cause the electronic device to implement the road surface measurement methods provided in the various embodiments described above.

[0177] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0178] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method of measuring a road surface, characterized by, The method comprises: acquiring relative heights of at least four wheels of a vehicle when the vehicle is driving on a target road; the relative heights are heights relative to a preset reference ground, and the at least four wheels are not all located on the same side of the vehicle; constructing a plane in which at least three wheels of the at least four wheels are located according to the relative heights of the at least three wheels, and the at least three wheels are not all located on the same side of the vehicle; acquiring distances between the remaining wheels and the plane according to the relative heights of the remaining wheels of the at least four wheels; determining a road surface unevenness of the target road according to the distances between the remaining wheels and the plane; the determining of the road surface unevenness of the target road according to the distances between the remaining wheels and the plane comprises: when the number of the remaining wheels is one, determining a road surface type of the target road according to the distance between the remaining wheel and the plane and a mapping relationship between the distance and the road surface type; acquiring the road surface unevenness of the target road according to the road surface type of the target road and a mapping relationship between the road surface type and the unevenness; when the number of the remaining wheels is multiple, determining the road surface unevenness of the target road according to an average value of the distances between the multiple remaining wheels and the plane, or according to a mapping relationship between the number of the distances exceeding a preset distance threshold and the road surface unevenness.

2. The method of claim 1, wherein, the constructing of the plane in which the at least three wheels are located according to the relative heights of the at least three wheels comprises: sorting the at least four wheels according to the relative heights of the at least four wheels; selecting a preset number of wheels in a sorting order from low to high; constructing the plane using the relative heights of the selected preset number of wheels.

3. The method according to claim 1 or 2, characterized in that, the acquiring of the relative heights of the at least four wheels of the vehicle when the vehicle is driving on the target road comprises: acquiring sensor data corresponding to the wheels; the sensors comprise first sensors installed between a vehicle body and suspensions corresponding to the wheels and / or second sensors installed on the wheels; acquiring the relative heights of the wheels according to the sensor data and a mapping relationship among sensor coefficients, sensor data and relative heights constructed based on a preset reference ground.

4. The method of claim 3, wherein, the sensors comprise the first sensors and the second sensors; the acquiring of the relative heights of the wheels according to the sensor data and the mapping relationship among the sensor coefficients, the sensor data and the relative heights constructed based on the preset reference ground comprises: acquiring first relative initial heights of the wheels according to the first sensor data and a mapping relationship among sensor coefficients, the first sensor data and the relative heights constructed based on the preset reference ground; acquiring second relative initial heights of the wheels according to the second sensor data and a mapping relationship among sensor coefficients, the second sensor data and the relative heights constructed based on the preset reference ground; According to the first relative initial height and the second relative initial height, a relative height of the wheel is obtained.

5. The method of claim 3, wherein, The sensor comprises the first sensor and the second sensor, and the method further comprises: a first initial unevenness obtained based on a first plane constructed based on the relative height obtained by the first sensor, and a second initial unevenness obtained based on a second plane constructed based on the relative height obtained by the second sensor; According to the first initial unevenness and the second initial unevenness, a road unevenness of the target road is determined.

6. The method of claim 1 or 2, wherein, The method further comprises: According to the road unevenness of the target road, intelligent driving control is performed on the vehicle.

7. A road surface measuring device, characterized by comprising: The device comprises: A first obtaining module is configured to obtain relative heights of at least four wheels of a vehicle when the vehicle is driving on a target road; the relative height is a height relative to a preset reference ground; A constructing module is configured to construct a plane in which at least three wheels of the at least four wheels are located according to the relative heights of the at least three wheels; A second obtaining module is configured to obtain distances between remaining wheels of the at least four wheels and the plane according to the relative heights of the remaining wheels; A determining module is configured to determine a road unevenness of the target road according to the distances between the remaining wheels and the plane; The determining module is specifically configured to, when the number of the remaining wheels is one, determine a road type of the target road according to the distance between the remaining wheel and the plane, and a mapping relationship between the distance and the road type; and determine the road unevenness of the target road according to the road type of the target road and a mapping relationship between the road type and the unevenness. When the number of the remaining wheels is more than one, the road unevenness of the target road is determined according to an average value of the distances between the remaining wheels and the plane, or according to a mapping relationship between the number of the distances exceeding a preset distance threshold and the road unevenness.

8. A controller characterized by, Comprise: A processor and a memory connected to the processor in communication; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the method according to any one of claims 1-6.

Images