Vehicle driving mileage obtaining method, device, equipment and medium
By obtaining the time interval, coordinates and driving offset angle of the vehicle, combined with the Kalman filtering algorithm, the vehicle's mileage is calculated, and the mileage calculation error problem caused by GPS positioning error is solved, and the calculation accuracy is improved.
Patent Information
- Application Number
- CN202510291710.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-12
- Publication Date
- 2025-06-13
AI Technical Summary
When calculating the mileage based on the GPS positioning system, the GPS positioning error of mine cars located in remote areas is large, resulting in large errors in the calculated mileage.
By obtaining the time interval between the current time and the previous time, the vehicle coordinates and the driving offset angle, and obtaining the observed state variable matrix of the current time, the predicted state variable matrix of the current time is determined based on this information, and then the estimated state variable matrix is calculated through the Kalman filtering algorithm to obtain more accurate vehicle coordinates, thereby calculating the vehicle mileage.
By improving the estimation accuracy of vehicle coordinates, the calculation accuracy of vehicle mileage is improved and errors are reduced.
Smart Images
Figure CN120141527A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of vehicle control, and in particular, to a method, device, equipment and medium for obtaining the driving mileage of a vehicle. Background Art
[0002] In recent years, with the continuous development of artificial intelligence and driverless vehicle technology, driverless mining vehicles have also been applied to various mining areas. The driving mileage of driverless mining vehicles has important reference significance for the scheduling of driverless mining vehicles.
[0003] In the related art, the driving mileage is calculated based on the GPS positioning system, that is, the positioning information of the GPS at adjacent sampling moments is obtained, and the driving mileage of the vehicle is calculated based on the adjacent positioning information.
[0004] However, in the above method of calculating the driving mileage based on the GPS positioning system, the fact that the mining vehicle works almost in remote areas and the GPS positioning error in remote areas is large is not considered. Therefore, the calculated driving mileage has a large error. Summary of the Invention
[0005] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a method, device, equipment and medium for obtaining the driving mileage of a vehicle.
[0006] An embodiment of the present disclosure provides a method for obtaining the driving mileage of a vehicle. The method includes: obtaining the time interval from the current moment to the previous moment of the vehicle, obtaining the vehicle coordinates and the driving offset angle of the vehicle at the previous moment, and obtaining the observed state variable matrix at the current moment, where the driving offset angle is the sum of the heading angle and the wheel deflection angle of the vehicle; determining the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates and the driving offset angle; calculating the predicted state variable matrix and the observed state variable matrix at the current moment according to a preset first formula to determine the estimated state variable matrix at the current moment, where the estimated state variable matrix includes the estimated vehicle coordinates at the current moment; and obtaining the driving mileage of the vehicle according to the previously obtained estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment.
[0007] An embodiment of the present disclosure also provides a device for obtaining vehicle driving mileage. The device includes: a data acquisition module, configured to acquire the time interval of the vehicle from the previous moment to the current moment, acquire the vehicle coordinates and driving offset angle of the vehicle at the previous moment, and acquire the observation state variable matrix at the current moment, where the driving offset angle is the sum of the vehicle's heading angle and wheel deflection angle; a first determination module, configured to determine the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates, and the driving offset angle; a second determination module, configured to calculate the predicted state variable matrix and the observation state variable matrix at the current moment according to a preset first formula to determine the estimated state variable matrix at the current moment, where the estimated state variable matrix includes the estimated vehicle coordinates at the current moment; and a third determination module, configured to acquire the vehicle driving mileage according to the previously acquired estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment.
[0008] An embodiment of the present disclosure also provides an electronic device. The electronic device includes: a processor; a memory for storing executable instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method for obtaining vehicle driving mileage provided by the embodiment of the present disclosure.
[0009] An embodiment of the present disclosure also provides a computer-readable storage medium. The storage medium stores a computer program, and the computer program is used to execute the method for obtaining vehicle driving mileage provided by the embodiment of the present disclosure.
[0010] The technical solution provided by the embodiment of the present disclosure has the following advantages compared with the prior art:
[0011] The solution for obtaining vehicle driving mileage provided by the embodiment of the present disclosure acquires the time interval of the vehicle from the previous moment to the current moment, acquires the vehicle coordinates and driving offset angle of the vehicle at the previous moment, and acquires the observation state variable matrix at the current moment. The driving offset angle is the sum of the vehicle's heading angle and wheel deflection angle. The predicted state variable matrix at the current moment is determined according to the time interval, vehicle coordinates, and driving offset angle. Further, the predicted state variable matrix and the observation state variable matrix at the current moment are calculated according to a preset first formula to determine the estimated state variable matrix at the current moment. The estimated state variable matrix includes the estimated vehicle coordinates at the current moment. The vehicle driving mileage is acquired according to the previously acquired estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment. In this technical solution, the estimation progress of vehicle coordinates is improved, and the vehicle driving mileage is calculated based on the estimated vehicle coordinates, thereby improving the calculation accuracy of vehicle driving mileage. Description of the Drawings
[0012] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages, and aspects of the embodiments of the present disclosure will become more apparent. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the original components and elements are not necessarily drawn to scale.
[0013] Figure 1 It is a schematic flowchart of a method for obtaining the driving mileage of a vehicle provided by an embodiment of the present disclosure;
[0014] Figure 2 It is a schematic diagram of a vehicle architecture provided by an embodiment of the present disclosure;
[0015] Figure 3 It is a schematic structural diagram of a device for obtaining the driving mileage of a vehicle provided by an embodiment of the present disclosure;
[0016] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure. Specific Embodiments
[0017] The embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Instead, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.
[0018] It should be understood that the various steps recorded in the method embodiments of the present disclosure can be executed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.
[0019] As used herein, the term "including" and its variants are open-ended, that is, "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.
[0020] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules, or units, and are not used to limit the order of the functions executed by these devices, modules, or units or their interdependent relationships.
[0021] It should be noted that the modifications of "one" and "multiple" mentioned in this disclosure are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise clearly specified in the context, it should be understood as "one or more".
[0022] The names of the messages or information exchanged between multiple devices in the embodiments of this disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.
[0023] To solve the above problems, the embodiments of this disclosure provide a method for obtaining the driving mileage of a vehicle. The method will be introduced below in combination with specific embodiments.
[0024] Figure 1 As shown in the flowchart of a method for obtaining the driving mileage of a vehicle provided by the embodiments of this disclosure, this method can be executed by a device for obtaining the driving mileage of a vehicle, where the device can be implemented by software and / or hardware and is generally integrated in an electronic device. As Figure 1 shown, the method includes:
[0025] Step 101, obtain the time interval from the current moment to the previous moment of the vehicle, obtain the vehicle coordinates and the driving offset angle of the vehicle at the previous moment, and obtain the observation state variable matrix at the current moment, where the driving offset angle is the sum of the vehicle's heading angle and the wheel deflection angle.
[0026] Among them, referring to Figure 2 the simplified architecture diagram of the vehicle shown, the wheels are in the gray rectangular frame area, L is the distance between the middle of the wheels, the vehicle's heading angle is ψ, the wheel deflection angle can be understood as the transverse deflection angle α of the vehicle body relative to the middle line of the two wheels due to the wheel deflection action. Among them, the driving offset angle θ = α + ψ. Among them, based on the geometric relation theorem, δ is the deflection angle of the deflected wheel relative to the opposite wheel.
[0027] In an embodiment of this disclosure, the current moment and the previous moment can be determined according to a preset sampling time interval. In this embodiment, obtain the time interval Δt from the current moment to the previous moment of the vehicle, and obtain the vehicle coordinates and the driving offset angle of the vehicle at the previous moment, where the vehicle coordinates can include the estimated coordinate points of the vehicle on the x-axis and y-axis.
[0028] In this embodiment, the observation state variable matrix at the current moment is also obtained. Among them, the observation state variable matrix can include the current state variables of the vehicle actually measured, and the current state variables can include vehicle coordinates and / or vehicle speed, etc. The observation state variables can be obtained based on the vehicle speed sensor and GPS positioning information in the vehicle. Among them, in some possible embodiments, let Z = [x, y, v] TDenote the observation variable matrix. Here, \(x\) and \(y\) represent the vehicle coordinates, and \(v\) represents the vehicle speed. Then the observation variable matrix can be expressed as \(Z\). k =H k X k +w k , where \(Z\) k is the said observation variable matrix. X k =[x k ,y k ,v k T , \(x\) and \(y\) are vehicle coordinates, \(k\) is the current moment, \(v\) is the vehicle speed. Here, \(X\) k can be regarded as the estimated state variable matrix. That is, in this embodiment, it is considered that there is an observation error \(w\) between the observation variable matrix and the estimated state variable matrix. k .
[0029] Step 102: Determine the predicted state variable matrix at the current moment according to the time interval, vehicle coordinates, and driving offset angle.
[0030] In an embodiment of the present disclosure, the predicted state variable matrix at the current moment is determined according to the time interval, vehicle coordinates, and driving offset angle of the previous moment. Among them, the predicted state variable matrix may include the predicted vehicle coordinates and vehicle speed at the current moment, etc. In this embodiment, the estimated state variable matrix at the current moment is not directly used as the predicted state variable matrix at the current moment because the estimated state variable matrix at the current moment has an estimation error. Therefore, in this embodiment, according to the driving offset angle, time interval, etc., the predicted state variable matrix at the current moment is determined.
[0031] It should be noted that any method of determining the predicted state variable matrix at the current moment according to the vehicle coordinates and driving offset angle of the previous moment should fall within the scope protected by the present disclosure. In some possible embodiments, the state transition matrix at the previous moment is determined according to the time interval, vehicle coordinates, and driving offset angle, and the state transition matrix at the current moment is predicted according to the state transition matrix at the previous moment.
[0032] In this example, determining the state transition matrix at the previous moment according to the time interval, vehicle coordinates, and driving offset angle may include: constructing the estimated state variable matrix at the previous moment according to the time interval, vehicle coordinates, and driving offset angle. For example, the estimated state variable matrix at the previous moment can be expressed as: Furthermore, according to the estimated state variable matrix at the previous moment, time interval, and driving offset angle, construct the estimated state variable matrix at the current moment. In this example, the movement of the vehicle can be regarded as two-dimensional movement in a plane, and the vehicle can be approximately regarded as moving in a uniform straight line. Then, combining Figure 2 The estimated state variable matrix at the current moment constructed is as follows: is the estimated state variable matrix at the previous moment, Δt is the time interval, and θ is the driving offset angle.
[0033] Furthermore, according to the preset second formula, the state transition matrix at the current moment and the previously obtained estimated state variable matrix at the previous moment are calculated to obtain the predicted state variable matrix at the current moment.
[0034] That is, assuming the estimated state variable matrix at time k - 1 then the estimated state variable matrix at time K is the following formula (1):
[0035]
[0036] Further, based on formula (1), formula (2) can be sorted out:
[0037]
[0038] Based on formula (2), formula (3) can be sorted out, where formula (3) is the above-mentioned preset second formula:
[0039]
[0040] Among them, is the predicted state variable matrix at the current moment, Φ k,k-1 is the state transition matrix at the current moment, and the state transition matrix at the previous moment is according to The state transition matrix at the current moment can be obtained by one-step prediction, V k-1 is the system estimation noise at time k - 1, that is, the noise when estimating the state matrix. This noise can be calibrated according to experimental data or can be regarded as Gaussian noise, etc. Among them, the method of one-step prediction is not limited here. For example, it can be predicted according to the moving average model, etc.
[0041] Step 103: Calculate the predicted state variable matrix and the observed state variable matrix at the current moment according to the preset first formula to determine the estimated state variable matrix at the current moment, where the estimated state variable matrix includes the estimated vehicle coordinates at the current moment.
[0042] Among them, in different application scenarios, the preset first formula is different. In some possible embodiments, the preset first formula is the following formula (4):
[0043]
[0044] Among them, K k can be regarded as the filtering gain matrix at the current moment, K k = Pk,k-1 H k-1 T (H k-1 P k,k-1 H k-1 T +R k-1 ) -1 ,Z k is the observation state variable matrix at the current moment, is the estimated state variable matrix at the previous moment, K k = P k,k-1 H k-1 T (H k-1 P k,k-1 H k-1 T +R k-1 ) -1 ,R k-1 is the observation noise error variance matrix corresponding to the observation state variable at the previous moment, R k-1 can be calibrated according to experimental data, or can be Gaussian noise, the prediction error variance matrix at the current moment, etc., P k,k-1 is the P predicted one-step from the estimated error variance matrix at the previous moment k,k-1 = Φ k,k-1 P k-1 Φ k,k-1 T +Q k-1 ,Q k-1 is the system estimation noise error variance matrix at the previous moment, Q k-1 can be calibrated according to experimental data, or can be Gaussian noise, etc., P k = (I - K k H k-1 )P k,k-1 ,I is the unit vector, in some possible embodiments, Φ k,k-1 is the state transition matrix predicted according to the state transition matrix at the previous moment, for example, Φ predicted one-step from the state transition matrix at the previous moment k,k-1 The one-step prediction method is not limited here. For example, it can be predicted according to the moving average model. For example, a corresponding preset value can be directly superimposed on each matrix element in the state transition matrix at the previous moment to obtain Φ k,k-1 etc., where the state transition matrix at the previous moment is Δt is the time interval, θ is the driving offset angle, where,
[0045] That is, in this embodiment, the current wheel angle and the current vehicle speed are used in combination with the Kalman filtering algorithm to correct the GPS position, thereby obtaining more accurate positioning information. This positioning information can be the estimated vehicle coordinates at the current moment included in the estimated state variable matrix. The positioning accuracy of the estimated vehicle coordinates is relatively high.
[0046] Step 104: Obtain the vehicle driving mileage according to the estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment obtained in advance.
[0047] Among them, the method for obtaining the estimated vehicle coordinates at the previous moment can refer to the method for obtaining the estimated vehicle coordinates at the current moment, which will not be elaborated here. Among them, the estimated vehicle coordinates at the initial moment can be estimated with reference to the vehicle coordinates observed by GPS, etc. For example, it can be obtained by superimposing noise errors on the measured coordinates. Among them, the noise error can be calibrated according to the scenario requirements, or can be randomly generated Gaussian noise, etc.
[0048] In an embodiment of the present disclosure, when the estimated state variable matrix is as shown in the above formula (4), the vehicle driving mileage can refer to the following formula (5). Among them, in formula (5), the estimated state variable matrix at the previous moment is is the first matrix vector x of the estimated state variable matrix at the previous moment k-1 , is the second matrix vector y of the estimated state variable matrix at the previous moment k-1 , and the estimated state variable matrix at the current moment is is the first matrix vector x of the estimated state variable matrix at the previous moment k , is the second matrix vector y of the estimated state variable matrix at the previous moment k :
[0049]
[0050] In summary, for the method for obtaining the vehicle driving mileage according to the embodiments of the present disclosure, the time interval of the vehicle from the current moment to the previous moment is obtained, the vehicle coordinates and the driving offset angle of the vehicle at the previous moment are obtained, and the observation state variable matrix at the current moment is obtained. The driving offset angle is the sum of the vehicle's heading angle and the wheel steering angle. According to the time interval, the vehicle coordinates and the driving offset angle, the predicted state variable matrix at the current moment is determined. Furthermore, according to a preset first formula, the predicted state variable matrix and the observation state variable matrix at the current moment are calculated to determine the estimated state variable matrix at the current moment. The estimated state variable matrix includes the estimated vehicle coordinates at the current moment. According to the previously obtained estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment, the vehicle driving mileage is obtained. In this technical solution, the estimation progress of the vehicle coordinates is improved, and the vehicle driving mileage is calculated based on the estimated vehicle coordinates, thereby improving the calculation accuracy of the vehicle driving mileage.
[0051] To implement the above embodiments, the present disclosure also proposes an apparatus for obtaining the vehicle driving mileage.
[0052] Figure 3 As shown in the structural schematic diagram of an apparatus for obtaining the vehicle driving mileage provided by the embodiments of the present disclosure, the apparatus can be implemented by software and / or hardware, and is generally integrated in an electronic device. The electronic device can be regarded as a server device with computing capabilities, etc. The electronic device can be set independently of the vehicle or integrated in the vehicle. As Figure 3 shown, the apparatus includes: a data acquisition module 310, a first determination module 320, a second determination module 330, and a third determination module 340, where
[0053] The data acquisition module 310 is configured to obtain the time interval of the vehicle from the current moment to the previous moment, obtain the vehicle coordinates and the driving offset angle of the vehicle at the previous moment, and obtain the observation state variable matrix at the current moment. The driving offset angle is the sum of the vehicle's heading angle and the wheel steering angle;
[0054] The first determination module 320 is configured to determine the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates, and the driving offset angle;
[0055] The second determination module 330 is configured to calculate the predicted state variable matrix and the observation state variable matrix at the current moment according to a preset first formula to determine the estimated state variable matrix at the current moment. The estimated state variable matrix includes the estimated vehicle coordinates at the current moment;
[0056] The third determination module 340 is configured to obtain the vehicle driving mileage according to the previously obtained estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment.
[0057] The vehicle driving mileage acquisition device provided by the embodiments of the present disclosure can execute the vehicle driving mileage acquisition method provided by any embodiment of the present disclosure, and has the corresponding functional modules and beneficial effects for executing the method.
[0058] To implement the above embodiments, the present disclosure also proposes a computer program product, including a computer program / instructions, which, when executed by a processor, implement the vehicle driving mileage acquisition method in the above embodiments.
[0059] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.
[0060] Specifically refer to Figure 4 , which shows a schematic structural diagram of the electronic device 400 suitable for implementing the embodiments of the present disclosure. The electronic device 400 in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The electronic device shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.
[0061] As Figure 4 shown, the electronic device 400 may include a processor (such as a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the memory 408 into the random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other through a bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.
[0062] Generally, the following devices may be connected to the I / O interface 405: an input device 406 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a memory 408 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 409. The communication device 409 can allow the electronic device 400 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 4 shows the electronic device 400 with various devices, it should be understood that it is not required to implement or have all the shown devices. More or fewer devices may be alternatively implemented or had.
[0063] In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present disclosure includes a computer program product that includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network via the communication device 409, or installed from the memory 408, or installed from the ROM 402. When the computer program is executed by the processor 401, the above-described functions defined in the method for obtaining the vehicle driving mileage according to the embodiments of the present disclosure are performed.
[0064] It should be noted that the above-mentioned computer-readable medium in the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, in which computer-readable program code is carried. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable signal medium can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.
[0065] In some embodiments, the client and the server can communicate using any currently known or future-developed network protocol such as HTTP (HyperText Transfer Protocol), and can be interconnected with digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet (e.g., the Internet), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.
[0066] The above computer-readable medium can be included in the above electronic device; or can exist separately without being assembled into the electronic device.
[0067] The above computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device is caused to execute the method for obtaining the vehicle driving mileage in the above embodiments.
[0068] The electronic device can write computer program code for performing the operations of the present disclosure in one or more programming languages or combinations thereof. The above programming languages include, but are not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., by using an Internet service provider to connect through the Internet).
[0069] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or by a combination of dedicated hardware and computer instructions.
[0070] The units involved in the embodiments described in the present disclosure can be implemented in software or in hardware. In some cases, the name of the unit does not constitute a limitation on the unit itself.
[0071] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. By way of example, and without limitation, the types of hardware logic components that may be used include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and the like.
[0072] In the context of the present disclosure, a machine-readable medium may be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a 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.
[0073] The above description is only a preferred embodiment of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present disclosure.
[0074] In addition, although the operations are depicted in a particular order, this should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although a number of specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments.
[0075] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are merely example forms for implementing the claims.
Claims
1. A method for obtaining vehicle mileage, characterized in that: The following steps are involved: Obtaining the time interval from the current moment to the previous moment of the vehicle, obtaining the vehicle coordinates and the driving offset angle of the vehicle at the previous moment, and obtaining the observation state variable matrix at the current moment, wherein the driving offset angle is the sum of the heading angle and the wheel deflection angle of the vehicle; Determine the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates and the driving offset angle; Calculating the predicted state variable matrix and the observed state variable matrix at the current moment according to a preset first formula to determine the estimated state variable matrix at the current moment, wherein the estimated state variable matrix includes the estimated vehicle coordinates at the current moment; The vehicle mileage is obtained according to the pre-acquired estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment.
2. The method according to claim 1, characterized in that The observed variable matrix is: Z k =H k X k +w k Among them, Z k is the observed variable matrix, X k =[x k ,y k ,v k ] T , x and y are the vehicle coordinates, k is the current moment, v is the speed of the vehicle, w k is the observation error.
3. The method according to claim 1, characterized in that The step of determining the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates and the driving offset angle includes: Determine the state transfer matrix at the previous moment according to the time interval, the vehicle coordinates and the driving offset angle; Predicting the state transfer matrix at the current moment according to the state transfer matrix at the previous moment; The state transfer matrix at the current moment and the estimated state variable matrix at the previous moment obtained in advance are calculated according to a preset second formula to obtain the predicted state variable matrix at the current moment.
4. The method according to claim 3, characterized in that The determining the state transfer matrix at the previous moment according to the time interval, the vehicle coordinates and the driving offset angle comprises: Constructing the estimated state variable matrix of the previous moment according to the time interval, the vehicle coordinates and the driving offset angle; Constructing the estimated state variable matrix at the current moment according to the estimated state variable matrix at the previous moment, the time interval and the driving deviation angle; The state transfer matrix at the previous moment is determined according to the relationship between the estimated state variable matrix at the current moment and the estimated state variable matrix at the previous moment.
5. The method according to claim 4, characterized in that The estimated state variable matrix at the current moment constructed according to the estimated state variable matrix at the previous moment, the time interval and the driving offset angle is: in, is the estimated state variable matrix at the current moment, is the estimated state variable matrix of the previous moment, t is the time interval, and θ is the driving deviation angle.
6. The method according to any one of claims 3 to 5, characterized in that: The preset second formula includes: in, is the predicted state variable matrix at the current moment, Φ k,k-1 is the state transfer matrix at the current moment, and the state transfer matrix at the previous moment is Δt is the time interval, θ is the driving deviation angle, x and y are vehicle coordinates, k-1 is the previous moment, v is the vehicle speed, V is the system estimated noise, 7. The method according to claim 1, characterized in that The preset first formula includes: in, Z k is the observed state variable matrix at the current moment, is the estimated state variable matrix of the previous moment, K k =P k,k- 1H k-1 T (H k-1 P k,k-1 H k-1 T +R k-1 ) -1 , R k-1 is the observation noise error variance matrix corresponding to the observed state variable at the previous moment, P k,k-1 =Φ k,k-1 P k-1 Φ k,k-1 T +Q k-1 , Q k-1 is the system estimation noise error variance matrix at the previous moment, P k =(IK k H k-1 ) k,k-1 , I is a unit vector, the Φ k,k-1 is the state transfer matrix at the current moment, Δt is the time interval, and θ is the driving deviation angle.
8. A device for obtaining vehicle mileage, characterized in that: include: A data acquisition module, used to acquire the time interval from the current moment to the previous moment of the vehicle, acquire the vehicle coordinates and driving offset angle of the vehicle at the previous moment, and acquire the observation state variable matrix at the current moment, wherein the driving offset angle is the sum of the heading angle and the wheel deflection angle of the vehicle; A first determination module, used to determine the predicted state variable matrix at the current moment according to the time interval, the vehicle coordinates and the driving offset angle; A second determination module is used to calculate the predicted state variable matrix and the observed state variable matrix at the current moment according to a preset first formula to determine the estimated state variable matrix at the current moment, wherein the estimated state variable matrix includes the estimated vehicle coordinates at the current moment; The third determination module is used to obtain the vehicle mileage based on the pre-acquired estimated vehicle coordinates at the previous moment and the estimated vehicle coordinates at the current moment.
9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is used to execute the vehicle mileage acquisition method described in any one of claims 1 to 7.
10. An electronic device, comprising: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the vehicle mileage acquisition method as described in any one of claims 1-7 above.