Road surface type prediction method and device, equipment, storage medium and product

Abstract

The invention discloses a road surface type prediction method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring a radial acceleration time-domain signal and a circumferential acceleration time-domain signal of a target vehicle in a rolling period of a preset number of tires; determining a radial non-grounding acceleration, a radial acceleration amplitude maximum value, a high-frequency amplitude integral value and a circumferential acceleration maximum value according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling period; and according to the radial non-grounding acceleration, the radial acceleration amplitude maximum value, the high-frequency amplitude integral value and the circumferential acceleration maximum value, determining the road surface type of the road to which the target vehicle belongs. According to the technical scheme of the embodiment of the invention, the road surface type prediction efficiency and prediction accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a road surface type prediction method, device, equipment, storage medium and product. Background Art

[0002] With the development of the automotive industry, people have higher and higher requirements for vehicle performance. Among them, road surface conditions have an important impact on vehicle driving and driving experience. During vehicle driving, the vehicle can make adaptive adjustments to roads with different road surface adhesion coefficients, so as to obtain a better driving experience.

[0003] However, it is difficult to obtain an accurate road surface type. The factors considered in the prior art during the determination of the road surface type are not comprehensive, resulting in a low accuracy in determining the road surface type. Moreover, since the process of determining the road surface type is usually carried out during vehicle driving, to a certain extent, it is necessary to improve the efficiency of determining the road surface type, so as to ensure vehicle driving safety and improve the driving experience. Summary of the Invention

[0004] The present invention provides a road surface type prediction method, device, equipment, storage medium and product to improve the prediction efficiency and accuracy of the road surface type.

[0005] According to one aspect of the present invention, there is provided a road surface type prediction method, the method comprising:

[0006] Obtaining the radial acceleration time domain signal and the circumferential acceleration time domain signal of a target vehicle under a preset number of tire rolling cycles;

[0007] Determining the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value and the maximum value of the circumferential acceleration according to the radial acceleration time domain signal and the circumferential acceleration time domain signal under each of the tire rolling cycles;

[0008] Determining the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value and the maximum value of the circumferential acceleration.

[0009] According to another aspect of the present invention, there is provided a road surface type prediction device, the device comprising:

[0010] A time domain signal acquisition module, configured to obtain the radial acceleration time domain signal and the circumferential acceleration time domain signal of a target vehicle under a preset number of tire rolling cycles;

[0011] An acceleration parameter determination module, configured to determine a radial non-ground acceleration, a maximum value of the radial acceleration amplitude, a high-frequency amplitude integral value, and a maximum value of the circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each of the tire rolling periods;

[0012] A road surface type prediction module, configured to determine the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration.

[0013] According to another aspect of the present invention, there is provided an electronic device, the electronic device including:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the road surface type prediction method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the road surface type prediction method according to any embodiment of the present invention when executed.

[0018] According to another aspect of the present invention, there is provided a computer program product including a computer program, and when the computer program is executed by a processor, the above-mentioned road surface type prediction method is implemented.

[0019] The technical solution of the embodiment of the present invention determines the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling period, and determines the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration. The above technical solution comprehensively considers various factors in the process of determining the road surface type, improves the comprehensiveness in the process of determining the road surface type, and improves the accuracy of determining the road surface type. In addition, the process of determining the road surface type of the present invention is determined in a model manner, which improves the efficiency of determining the road surface type to a certain extent, ensures the driving safety of the vehicle, and improves the driving experience.

[0020] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0022] Figure 1A is a flowchart of a road surface type prediction method provided according to Embodiment 1 of the present invention;

[0023] Figure 1B Schematic diagrams showing the representations of the radial acceleration in the time domain, the radial acceleration in the frequency domain, and the circumferential acceleration in the time domain provided according to an embodiment of the present invention;

[0024] Figure 2 is a schematic structural diagram of a road surface type prediction device provided according to Embodiment 2 of the present invention;

[0025] Figure 3 is a schematic structural diagram of an electronic device for implementing the road surface type prediction method of the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] In order to enable those skilled in the art to better understand the solution of the present invention, the following clearly and completely describes the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, rather than all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0028] Embodiment 1

[0029] Figure 1A As shown in the flowchart of a road surface type prediction method provided in Embodiment 1 of the present invention, this embodiment is applicable to the situation of predicting the road surface type during vehicle driving. This method can be executed by a road surface type prediction device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. As Figure 1A shown, the method includes:

[0030] S110. Obtain the radial acceleration time-domain signal and the circumferential acceleration time-domain signal of the target vehicle under a preset number of tire rolling cycles.

[0031] S120. Determine the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling cycle.

[0032] S130. Determine the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration.

[0033] Among them, the target vehicle can be a vehicle used for road surface type prediction during road driving. The prediction of the road surface type is helpful for the target vehicle to adjust vehicle performance parameters during vehicle driving, thereby improving the driving experience of the vehicle.

[0034] Among them, the road surface type can include smooth asphalt road, rough gravel road, ordinary cement road, ice and snow road surface, etc., and the road surface adhesion coefficient ranges of different road surface types are different.

[0035] Among them, the preset number of tire rolling cycles is the number of rolling cycles, which can be specifically preset by relevant technicians according to the actual vehicle driving conditions. During driving, the wheels rotate, and a tire rolling cycle is specifically the time for the wheel (tire) to rotate one circle.

[0036] Among them, the radial acceleration is the acceleration change in the vertical direction (i.e., the radial direction) caused by the rotation of the wheel during the contact of the tire with the ground, which is used to reflect the acceleration of the up and down movement of the tire. The circumferential acceleration is the acceleration of the tire along the circumferential direction of the wheel and is related to the lateral or surrounding deformation of the tire.

[0037] Among them, the time-domain signal is used to reflect the change of the accelerator signal over time, that is, the time axis and the corresponding acceleration in the signal. The radial acceleration time-domain signal and the circumferential acceleration time-domain signal under the tire rolling period can be detected by sensors deployed on the target vehicle, such as accelerometers.

[0038] Among them, the radial non-ground acceleration is the acceleration value when the radial signal is non-grounded; the acceleration value when non-grounded is the acceleration value in the radial direction when the tire is not in contact with the ground. The maximum value of the radial acceleration amplitude is the maximum value of the radial acceleration frequency-domain amplitude; the maximum value of the frequency-domain amplitude refers to the maximum amplitude value of the radial acceleration signal in the frequency-domain signal. The high-frequency amplitude integral value is the amplitude integral value of the high-frequency part (in the range of 600 to 1000 HZ); the amplitude integral value of the high-frequency part represents the sum of the amplitudes in the frequency domain within the frequency range between 600 Hz and 1000 Hz, and can represent the total energy or intensity of the signal in this frequency range. The maximum value of the circumferential acceleration is the maximum value of the circumferential signal acceleration; the circumferential signal represents the acceleration signal along the circumferential direction of the tire, characterizing the vibration characteristics of the tire in the circumferential direction. The maximum value of the circumferential acceleration is the maximum acceleration value of this signal in the time domain. Among them, the above amplitude represents the vibration amplitude, that is, the acceleration value.

[0039] Such as Figure 1B A schematic diagram showing the representation of the radial acceleration time domain, the radial acceleration frequency domain, and the circumferential acceleration time domain as shown. In an alternative embodiment, according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling period, determining the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration includes:

[0040] Step a1: Determine the mean time-domain signal according to the radial acceleration time-domain signal under each tire rolling period.

[0041] Specifically, perform a mean calculation on the radial acceleration time-domain signals under each tire rolling period to obtain the mean time-domain signal corresponding to the tire rolling period.

[0042] Step a2: Convert the mean time-domain signal into a radial acceleration frequency-domain signal through Fourier transform.

[0043] Specifically, the mean time-domain signal can be converted into a radial acceleration frequency-domain signal by using Fourier transform or fast Fourier transform (FFT). Among them, Fourier transform is used to convert the time-domain signal into the frequency-domain signal, which can characterize the intensity of different frequency components in the signal.

[0044] Step a3: Determine the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration according to the radial acceleration frequency-domain signal, the radial acceleration time-domain signal, and the circumferential acceleration time-domain signal.

[0045] Optionally, based on the radial acceleration frequency-domain signal, the radial acceleration time-domain signal, and the circumferential acceleration time-domain signal, determine the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the integral value of the high-frequency amplitude, and the maximum value of the circumferential acceleration, including:

[0046] Step b1: Determine the radial non-ground acceleration according to the radial acceleration time-domain signal.

[0047] Specifically, separate and filter the radial acceleration time-domain signal, identify the state of the tire in contact or not in contact with the ground, and then extract the acceleration data in the non-ground state as the radial non-ground acceleration.

[0048] Step b2: Determine the maximum value of the radial acceleration amplitude according to the radial acceleration frequency-domain signal.

[0049] Specifically, analyze the radial acceleration frequency-domain signal to determine the maximum acceleration amplitude value at each frequency, that is, the maximum value of the radial acceleration amplitude.

[0050] Step b3: Determine the integral value of the high-frequency amplitude according to the radial acceleration frequency-domain signal.

[0051] Specifically, integrate the frequency components of the radial acceleration frequency-domain signal between 600 Hz and 1000 Hz, calculate the sum of the amplitudes of all frequency components in this frequency band, and obtain the integral value of the high-frequency amplitude. It should be noted that the high-frequency components from 600 Hz to 1000 Hz are usually related to the high-frequency characteristics of the tire, such as local vibration, surface unevenness, noise, etc. This integral value can characterize the energy accumulation of high-frequency noise or vibration.

[0052] Step b4: Determine the maximum value of the circumferential acceleration according to the circumferential acceleration time-domain signal.

[0053] Specifically, analyze the circumferential acceleration time-domain signal to obtain the maximum acceleration value as the maximum value of the circumferential acceleration. Among them, the maximum value of the circumferential acceleration can characterize the maximum impact or vibration suffered by the tire during rotation.

[0054] Determine the road surface type of the target vehicle based on the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the integral value of the high-frequency amplitude, and the maximum value of the circumferential acceleration.

[0055] Exemplarily, a road surface type prediction model for road surface type prediction can be pre-trained, and the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the integral value of the high-frequency amplitude, and the maximum value of the circumferential acceleration are input into the road surface type prediction model to obtain the road surface type prediction result output by the model.

[0056] Among them, the road surface type prediction model can be pre-trained by relevant technical personnel. This embodiment also provides a model training method for the road surface type prediction model.

[0057] Specifically, obtain the historical acceleration signal features in the historical time period. Among them, the historical acceleration signal features include historical radial non-ground acceleration, historical maximum radial acceleration amplitude, historical high-frequency amplitude integral value, and historical maximum circumferential acceleration. The historical acceleration signal features correspond to their own true road surface types, which can be specifically pre-labeled by relevant technical personnel, and the true road surface types can be obtained from vehicle driving data.

[0058] Input the historical acceleration signal features and their corresponding true road surface types into a pre-constructed classification model to obtain the predicted road surface type output by the model; according to the true road surface type and the predicted road surface type of the historical acceleration signal features, train the classification model to obtain the road surface type prediction model. Among them, the classification model can be a linear classification model, support vector machine (SVM), multi-layer perceptron (MLP), convolutional neural network (CNN), or BP network model (backpropagation network).

[0059] The technical solution of this embodiment of the present invention determines the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal in each tire rolling period, and determines the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum circumferential acceleration. The above technical solution comprehensively considers various factors in the process of determining the road surface type, improves the comprehensiveness in the process of determining the road surface type, and improves the accuracy of determining the road surface type. In addition, the process of determining the road surface type in the present invention is determined by using a model, which improves the efficiency of determining the road surface type to a certain extent, ensures vehicle driving safety, and improves the driving experience.

[0060] Embodiment 2

[0061] Figure 2 It is a schematic structural diagram of a road surface type prediction device provided in Embodiment 2 of the present invention. A road surface type prediction device provided in an embodiment of the present invention is applicable to the situation of predicting the road surface type during vehicle driving. The road surface type prediction device can be implemented in the form of hardware and / or software, such as Figure 2As shown in the figure, the device specifically includes: a time-domain signal acquisition module 201, an acceleration parameter determination module 202, and a road surface type prediction module 203. Among them,

[0062] The time-domain signal acquisition module 201 is used to acquire the radial acceleration time-domain signal and the circumferential acceleration time-domain signal of the target vehicle under a preset number of tire rolling cycles;

[0063] The acceleration parameter determination module 202 is used to determine the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling cycle;

[0064] The road surface type prediction module 203 is used to determine the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration.

[0065] In the technical solution of the embodiment of the present invention, by determining the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration according to the radial acceleration time-domain signal and the circumferential acceleration time-domain signal under each tire rolling cycle, and determining the road surface type of the road to which the target vehicle belongs according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration. The above technical solution comprehensively considers various factors in the process of determining the road surface type, improves the comprehensiveness in the process of determining the road surface type, and improves the accuracy of determining the road surface type. In addition, in the process of determining the road surface type of the present invention, a model method is used for determination, which improves the determination efficiency of the road surface type to a certain extent, ensures the driving safety of the vehicle and improves the driving experience.

[0066] Optionally, the road surface type prediction module 203 includes:

[0067] The road surface type prediction unit is used to determine the road surface type of the road to which the target vehicle belongs based on the road surface type prediction model pre-trained according to the radial non-ground acceleration, the maximum value of the radial acceleration amplitude, the high-frequency amplitude integral value, and the maximum value of the circumferential acceleration.

[0068] Optionally, the acceleration parameter determination module 202 includes:

[0069] The mean line-of-sight signal determination unit is used to determine the mean time-domain signal according to the radial acceleration time-domain signal under each tire rolling cycle;

[0070] The time-domain signal conversion unit is used to convert the mean time-domain signal into a radial acceleration frequency-domain signal through Fourier transform;

[0071] An acceleration parameter determination unit, configured to determine a radial non-grounding acceleration, a maximum value of the radial acceleration amplitude, an integral value of the high-frequency amplitude, and a maximum value of the circumferential acceleration according to the radial acceleration frequency-domain signal, the radial acceleration time-domain signal, and the circumferential acceleration time-domain signal.

[0072] Optionally, the acceleration parameter determination unit is specifically configured to:

[0073] Determine the radial non-grounding acceleration according to the radial acceleration time-domain signal; and,

[0074] Determine the maximum value of the radial acceleration amplitude according to the radial acceleration frequency-domain signal; and,

[0075] Determine the integral value of the high-frequency amplitude according to the radial acceleration frequency-domain signal; and,

[0076] Determine the maximum value of the circumferential acceleration according to the circumferential acceleration time-domain signal.

[0077] The road surface type prediction device provided by the embodiments of the present invention can execute the road surface type prediction method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0078] Embodiment III

[0079] Figure 3 FIG. shows a schematic structural diagram of an electronic device 30 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0080] As Figure 3As shown, the electronic device 30 includes at least one processor 31 and a memory communicatively connected to the at least one processor 31, such as a read-only memory (ROM) 32, a random access memory (RAM) 33, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 31 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 32 or the computer program loaded from the storage unit 38 into the random access memory (RAM) 33. In the RAM 33, various programs and data required for the operation of the electronic device 30 can also be stored. The processor 31, the ROM 32, and the RAM 33 are connected to each other through a bus 34. The input / output (I / O) interface 35 is also connected to the bus 34.

[0081] Multiple components in the electronic device 30 are connected to the I / O interface 35, including: an input unit 36, such as a keyboard, a mouse, etc.; an output unit 37, such as various types of displays, speakers, etc.; a storage unit 38, such as a magnetic disk, an optical disc, etc.; and a communication unit 39, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 39 allows the electronic device 30 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0082] The processor 31 can be various general-purpose and / or dedicated processing components with processing and computing capabilities. Some examples of the processor 31 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 31 executes the various methods and processes described above, such as the road surface type prediction method.

[0083] In some embodiments, the road surface type prediction method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 38. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 30 via the ROM 32 and / or the communication unit 39. When the computer program is loaded into the RAM 33 and executed by the processor 31, one or more steps of the road surface type prediction method described above can be executed. Alternatively, in other embodiments, the processor 31 can be configured to execute the road surface type prediction method by any other appropriate means (e.g., by means of firmware).

[0084] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0085] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0086] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0088] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0089] A computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The relationship between the client and the server is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0090] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0091] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A road surface type prediction method, characterized in that: include: Acquire radial acceleration time domain signals and circumferential acceleration time domain signals of the target vehicle under a preset number of tire rolling cycles; Determine the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration according to the radial acceleration time domain signal and the circumferential acceleration time domain signal under each tire rolling cycle; The road surface type of the road to which the target vehicle belongs is determined according to the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration.

2. The method according to claim 1, characterized in that The determining, according to the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration, the road surface type of the road to which the target vehicle belongs includes: The road surface type of the road to which the target vehicle belongs is determined according to the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration based on a pre-trained road surface type prediction model.

3. The method according to claim 1, characterized in that Determining the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration according to the radial acceleration time domain signal and the circumferential acceleration time domain signal under each tire rolling cycle includes: Determining a mean time domain signal according to the radial acceleration time domain signal under each tire rolling cycle; Converting the mean time domain signal into a radial acceleration frequency domain signal through Fourier transform; The radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration are determined according to the radial acceleration frequency domain signal, the radial acceleration time domain signal and the circumferential acceleration time domain signal.

4. The method according to claim 3, characterized in that Determining the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration according to the radial acceleration frequency domain signal, the radial acceleration time domain signal and the circumferential acceleration time domain signal includes: Determining radial non-ground acceleration according to the radial acceleration time domain signal; and, Determining the maximum radial acceleration amplitude according to the radial acceleration frequency domain signal; and Determine a high-frequency amplitude integral value according to the radial acceleration frequency domain signal; the high-frequency amplitude integral value is the area enclosed by the time axis and the amplitude axis; and The maximum circumferential acceleration value is determined according to the circumferential acceleration time domain signal.

5. A road surface type prediction device, characterized in that: include: A time domain signal acquisition module, used to acquire a radial acceleration time domain signal and a circumferential acceleration time domain signal of a target vehicle under a preset number of tire rolling cycles; An acceleration parameter determination module, for determining radial non-ground acceleration, radial acceleration amplitude maximum value, high-frequency amplitude integral value and circumferential acceleration maximum value according to radial acceleration time domain signals and circumferential acceleration time domain signals under each tire rolling cycle; The road surface type prediction module is used to determine the road surface type of the road to which the target vehicle belongs based on the radial non-ground acceleration, the maximum radial acceleration amplitude, the high-frequency amplitude integral value and the maximum circumferential acceleration.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the road surface type prediction method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the road surface type prediction method according to any one of claims 1 to 4 when executed.

8. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the road surface type prediction method according to any one of claims 1 to 4.

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