Automatic driving vehicle speed control method, device, equipment and storage medium

Abstract

The present invention relates to a method, device, equipment and storage medium for controlling the running speed of an autonomous driving vehicle, the method comprising: obtaining a road spectrum database model of the area to be driven based on the collected first road spectrum data of the area to be driven; obtaining vehicle information of the autonomous driving vehicle, and determining the first running speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information; and determining the speed control strategy corresponding to the autonomous driving vehicle based on the first running speed. The present invention collects the area to be driven, combines the obtained road spectrum information with the vehicle information, and performs precise control of the autonomous driving vehicle. For the autonomous driving vehicle, it is not only targeted, but also helps to improve the safety of the autonomous driving vehicle in service and realize refined coordinated speed regulation, and it can effectively reduce the consumption of manpower and material resources, and greatly improve the efficiency of the autonomous driving vehicle in service.

Description

Technical Field

[0001] The present invention relates to the field of control technology, and in particular to a method, device, equipment and storage medium for controlling the running speed of an autonomous driving vehicle. Background Art

[0002] With the rapid development and application of Internet technology, the logistics industry has developed rapidly. The traditional management model can no longer meet the needs of the logistics industry, and the logistics industry is developing towards intelligence. At present, the logistics industry is shifting towards unmanned, automated, and high-tech. Smart logistics will provide consumers with diversified and personalized products and services. Many companies at home and abroad have developed batches of intelligent self-driving cars, with the goal of continuously improving the timeliness and flexibility of logistics distribution.

[0003] However, as the field of autonomous driving has developed to date, existing technologies usually use the beyond-visual-range characteristics of high-precision maps to predict overall road traffic, traffic incidents, and road conditions, and serve as safety redundancy for the perception layer. However, road network information on narrow roads cannot be accurately collected, and thus cannot be accurately controlled. Changes cannot be predicted, and real-time updates are poor and do not meet operational requirements. Summary of the invention

[0004] In view of this, it is necessary to provide a method, device, equipment and storage medium for controlling the operating speed of an autonomous driving vehicle, so as to achieve the purpose of refined coordinated speed regulation during the autonomous driving process.

[0005] In order to achieve the above objectives, in a first aspect, the present invention provides a method for controlling the running speed of an autonomous driving vehicle:

[0006] Acquire a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven;

[0007] Acquire vehicle information of the autonomous driving vehicle, and determine a first operating speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information;

[0008] A speed control strategy corresponding to the automatic driving vehicle is determined according to the first operating speed.

[0009] Furthermore, the first road spectrum data of the area to be driven is collected, including:

[0010] Based on the vehicle body dynamics simulation analysis, the stiffness and damping ratio parameters of the autonomous driving vehicle system are obtained;

[0011] According to the stiffness and damping ratio parameters of the autonomous driving vehicle system, a test plan is formulated and sensors are installed to complete the collection of the road load spectrum;

[0012] The road analysis and processing target signal is edited according to the road load spectrum to complete the collection of the first road spectrum data.

[0013] Furthermore, after collecting the first road spectrum data of the area to be driven, the method further includes:

[0014] Acquire simulation data corresponding to the first spectrum data;

[0015] Based on the simulation data, the performance of the autonomous driving vehicle is tested and analyzed.

[0016] Furthermore, the vehicle body dynamics simulation analysis includes:

[0017] Use 3D drawing software to draw a 3D structural model of the vehicle body and obtain a 3D structural model of the simulated vehicle;

[0018] According to the relevant modules of the vehicle dynamics simulation software, the three-dimensional structural model of the simulated vehicle is established and simplified, and the construction of the virtual prototype is completed;

[0019] According to the virtual prototype, a road profile file is established, and a driving smoothness simulation analysis is completed;

[0020] Based on the ride smoothness simulation analysis, a ride smoothness evaluation result is obtained.

[0021] Furthermore, determining the first operating speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information includes:

[0022] Based on the vehicle information, obtaining a preset running speed corresponding to the autonomous driving vehicle;

[0023] Based on the preset running speed, determining whether there is a second running speed in the road spectrum database model whose degree of overlap with the preset running speed is within a first threshold range;

[0024] If there is a second running speed whose degree of overlap with the preset running speed is within the first threshold range, the second running speed is determined to be the first running speed of the automatic driving vehicle.

[0025] Furthermore, determining a speed control strategy corresponding to the autonomous driving vehicle according to the first operating speed includes:

[0026] Based on the first running speed, obtaining a first editing instruction for the first running speed;

[0027] Determining second road spectrum data of the reference point corresponding to the autonomous driving vehicle according to the reference point set at the first running speed through the first editing instruction;

[0028] Determine that the second road spectrum data is a speed control strategy corresponding to the autonomous driving vehicle.

[0029] Furthermore, the determining that the second road spectrum data is a speed control strategy corresponding to the autonomous driving vehicle includes:

[0030] Obtaining a first editing instruction from a user, and setting a reference point on the first operating speed range according to the first editing instruction;

[0031] Obtaining a second editing instruction from a user, and determining initial road spectrum data of the reference point corresponding to the autonomous driving vehicle according to the reference point and the second editing instruction;

[0032] Based on the initial road spectrum data, obtaining a control strategy for the reference point;

[0033] The first reference point corresponding to the control strategy that exceeds the second threshold is deleted, and the third road spectrum data after deleting the first reference point is determined to be the speed control strategy corresponding to the automatic driving vehicle.

[0034] In a second aspect, the present invention further provides an automatic driving vehicle running speed control device, comprising:

[0035] An acquisition module, used for acquiring a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven;

[0036] A first determination module, configured to obtain vehicle information of the autonomous driving vehicle, and determine a first operating speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information;

[0037] The second determination module is used to determine a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed.

[0038] In a third aspect, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above-mentioned method for controlling the operating speed of an autonomous driving vehicle when executing the computer program.

[0039] In a fourth aspect, the present invention further provides a computer storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method for controlling the operating speed of an autonomous driving vehicle are implemented.

[0040] Compared with the prior art, in the embodiments of the present invention, by collecting the driving area, the obtained road spectrum information data model is combined with the vehicle information to accurately control the speed of the autonomous driving vehicle. For autonomous driving vehicles, this is not only targeted, but also helps to improve the safety of autonomous driving vehicles and achieve refined coordinated speed regulation, and can effectively reduce the consumption of manpower and material resources, greatly improving the efficiency of autonomous driving vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of a flow chart of an embodiment of a method for controlling the speed of an automatic driving vehicle provided by the present invention;

[0042] Figure 2 A vehicle mathematical model diagram provided by an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a test site provided by an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of the structure of an embodiment of the automatic driving vehicle running speed control device provided by the present invention;

[0045] Figure 5 The present invention provides an electronic device. DETAILED DESCRIPTION

[0046] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0047] In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically limited. Reference to "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0048] In order to enable those skilled in the art to use the contents of the present invention, the following implementation methods are given in combination with the specific application scenario of "autonomous driving vehicle control". For those skilled in the art, the general principles defined here can be applied to other embodiments and application scenarios without departing from the spirit and scope of the present invention.

[0049] The method for controlling the running speed of an autonomous driving vehicle described in the embodiment of the present invention can be applied to any scenario of controlling the running speed of an autonomous driving vehicle. The embodiment of the present invention does not limit the specific application scenario. Any solution using the method and device for controlling the running speed of an autonomous driving vehicle provided by the embodiment of the present invention is within the protection scope of the present invention.

[0050] See also Figure 1 , Figure 1 The present invention is a flowchart of an embodiment of a method for controlling the speed of an autonomous driving vehicle provided by the present invention. A specific embodiment of the present invention discloses a method for controlling the speed of an autonomous driving vehicle, including:

[0051] Step S101: acquiring a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven;

[0052] Among them, the area to be driven includes multiple single route information, and each single route information can be regarded as an entity. The first road spectrum data collected in the area to be driven includes collecting each single route information. The specific information to be collected includes seven attributes such as route name, longitude, latitude, altitude, vehicle speed, time, and location data.

[0053] It is worth noting that before the present invention was proposed, there was still room for improvement in the existing sensor solutions, including the boundaries of sensor measurement and the operating conditions of sensor applications. The beyond-visual-range feature of high-precision maps can predict the overall road flow, traffic events, and road conditions, and can serve as a safety redundancy for the perception layer, but it cannot accurately collect road network information for narrow roads, and thus cannot accurately control them. Moreover, to a large extent, the driving speed is preset and calibrated on the map in advance, and changes cannot be predicted, and the real-time update is poor and does not meet operational requirements.

[0054] In response to the above problems, the embodiments of the present invention can provide a more accurate theoretical basis for test sites for the process of collecting road spectrum data by performing dynamic simulation analysis on the actual mechanical structure of the autonomous driving vehicle and establishing a vehicle mathematical model, making the results of road spectrum data collection more realistic and reliable. Furthermore, during the control process of the autonomous driving vehicle, it can operate under the most optimized working conditions, thereby improving service safety and achieving refined coordinated speed regulation.

[0055] See also Figure 2 , Figure 2 A vehicle mathematical model diagram is provided in an embodiment of the present invention. In the vehicle mathematical model diagram, when the mass distribution coefficient of the vibration model of the four degrees of freedom of a two-axle vehicle is close to 1, the front and rear vibrations of the suspension system are almost independent. So it is simplified as follows Figure 2 The two degrees of freedom vibration system shown. Figure 3Where M is the suspension (body) mass, m is the non-suspension (wheel) mass, K is the body stiffness, X is the damping coefficient of the damper, Kt is the tire stiffness, e(t), f(t) and g(t) are the longitudinal displacements of the body, tire and road surface respectively, where e and f are the independent coordinates of the system, and their respective equilibrium positions are defined as the coordinate origin.

[0056] See also Figure 3 , Figure 3 A schematic diagram of a test site provided by an embodiment of the present invention, such as Figure 3 As shown, the test site is located below the magnetic base of the vehicle suspension system.

[0057] Specifically, in one embodiment of the present invention, before collecting the first road spectrum data of the area to be driven, the method further includes:

[0058] Based on the vehicle body dynamics simulation analysis, the stiffness and damping ratio parameters of the autonomous driving vehicle system are obtained;

[0059] According to the stiffness and damping ratio parameters of the autonomous driving vehicle system, formulate a test plan and install sensors to complete the collection of road load spectra;

[0060] Editing the road analysis and processing target signal according to the road load spectrum to complete the collection of the first road spectrum data;

[0061] Complete the learning of the first spectrum data and speed regulation association machine, and conduct research on running speed control technology based on the learning results;

[0062] Based on the research on running speed control technology, road simulation tests are carried out to realize the regulation mechanism of autonomous operation.

[0063] In one embodiment of the present invention, the vehicle body dynamics simulation analysis includes:

[0064] Use 3D drawing software to draw a 3D structural model of the vehicle body and obtain a 3D structural model of the simulated vehicle;

[0065] According to the relevant modules of vehicle dynamics simulation software, the three-dimensional structural model of the simulated vehicle is established and simplified, and the construction of the virtual prototype is completed;

[0066] According to the virtual prototype, the road profile file is established and the driving smoothness simulation analysis is completed;

[0067] Based on the simulation analysis of ride smoothness, the ride smoothness evaluation results are obtained.

[0068] In one embodiment of the present invention, in order to combine the road spectrum data model with the vehicle information, the first road spectrum data information needs to be processed. Specifically, the processing method includes:

[0069] Collect vehicle body vibration acceleration data and pre-process the vehicle body vibration acceleration data;

[0070] Based on the pre-processed vehicle body vibration acceleration data, complete the coherent analysis of road surface geometric irregularities and vehicle body vibration acceleration;

[0071] Based on the coherent analysis of road geometry irregularities and vehicle body vibration acceleration, the diagnosis of road geometry irregularities based on wavelet analysis theory is completed.

[0072] In one embodiment of the present invention, a dynamic simulation analysis is performed on the actual mechanical structure of the autonomous driving vehicle and a vehicle mathematical model is established, including:

[0073] Collect and process vehicle body vibration information;

[0074] Based on the collected and processed vehicle vibration information, machine learning is performed to associate road spectrum information with speed regulation to complete the research on running speed control technology.

[0075] According to the research on running speed control technology, real-time vehicle status monitoring is carried out;

[0076] Based on the real-time status of the monitored vehicle body, a stability control mathematical model is established to form an autonomous operating speed control mechanism.

[0077] Step S102: Acquire vehicle information of the autonomous driving vehicle, and determine a first operating speed of the autonomous driving vehicle from a road spectrum database model based on the vehicle information;

[0078] Among them, due to the different vehicle types in the road map database, the corresponding driving speeds of the autonomous driving vehicles are different. This embodiment determines different types of operating speeds corresponding to different vehicle types according to different vehicle types, thereby ensuring the accuracy of the data and more specifically completing the regulation of the operating speed of the autonomous driving vehicle.

[0079] The vehicle information of an autonomous vehicle mainly includes a series of parameters and performance indicators such as vehicle weight, displacement, speed and mileage.

[0080] In one embodiment of the present invention, determining a first operating speed of the autonomous driving vehicle from a road spectrum database model based on vehicle information includes:

[0081] Based on the vehicle information, obtain a preset running speed corresponding to the autonomous driving vehicle;

[0082] Among them, for different types of autonomous driving vehicles, different preset driving speeds corresponding to the autonomous driving vehicles are obtained, so as to more specifically control the speed of the autonomous driving vehicles. And the preset driving speed mainly includes but is not limited to the historical driving speed of the autonomous driving vehicle.

[0083] Based on the preset running speed, determining whether there is a second running speed in the road spectrum database model whose degree of overlap with the preset running speed is within the first threshold range;

[0084] It can be understood that since a large amount of road spectrum data information is stored in the road spectrum database, the vehicle type that is the same as the autonomous driving vehicle type can be detected among all vehicle types in the road spectrum database model, and then it can be determined among the driving speeds corresponding to the vehicle type whether there is a second operating speed within the first threshold range whose degree of overlap with the preset driving speed.

[0085] If there is a second running speed whose degree of overlap with the preset running speed is within the first threshold range, the second running speed is determined to be the first running speed of the automatic driving vehicle.

[0086] In this step, if there is a second running speed whose degree of overlap with the preset running speed is within the first threshold range, the second running speed whose degree of overlap with the preset running speed is within the first threshold range is selected as the first running speed of the automatic driving vehicle.

[0087] Step S103: Determine a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed.

[0088] In this step, according to the first running speed, the user can customize the setting editing instructions, edit the first running speed according to the customized editing instructions, and determine the speed control strategy corresponding to the autonomous driving vehicle.

[0089] In one embodiment of the present invention, determining a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed includes:

[0090] Based on the first running speed, obtaining a first editing instruction for the first running speed;

[0091] In this step, a first editing instruction for editing the first operating speed is obtained, and the instruction attribute of the first editing instruction is extracted according to the first editing instruction, and the user's demand for the first operating speed is determined according to the instruction attribute. The instruction attribute specifically includes the setting of the first operating speed and the speed adjustment and planning of the first operating speed.

[0092] Determine second road spectrum data of a reference point corresponding to the autonomous driving vehicle according to the reference point set at the first operating speed by the first editing instruction;

[0093] The second road spectrum data is determined to be a speed control strategy corresponding to the autonomous driving vehicle.

[0094] In this step, the specific steps of setting the reference point are to perform dot processing within the preset speed of the first running speed, and determine the second road spectrum data corresponding to the reference point based on the reference point of the preset speed on the first running speed after the dot processing, and use the second road spectrum data as the speed control strategy corresponding to the autonomous driving vehicle.

[0095] The preset speed can be set accordingly according to different first running speeds, and the reference point is located at the middle position of the first running speed.

[0096] In one embodiment of the present invention, determining that the second road spectrum data is a speed control strategy corresponding to the autonomous driving vehicle includes:

[0097] Obtaining a first editing instruction from a user, and setting a reference point on a first operating speed range according to the first editing instruction;

[0098] Obtaining a second editing instruction from the user, and determining initial road spectrum data of the reference point corresponding to the autonomous driving vehicle according to the reference point and the second editing instruction;

[0099] In this step, the second editing instruction is an instruction issued after the user sets the reference point to connect the reference points into a line. The connection of the reference points into a line is used to generate initial road spectrum data of the reference points corresponding to the autonomous driving vehicle.

[0100] Based on the initial road spectrum data, obtain the control strategy of the benchmark point;

[0101] While determining the initial road spectrum data, the control strategy for each reference point is obtained and displayed in the initial road spectrum data.

[0102] The first reference point corresponding to the control strategy that exceeds the second threshold is deleted, and the third road spectrum data after deleting the first reference point is determined to be the speed control strategy corresponding to the autonomous driving vehicle.

[0103] In this step, a second threshold value of the control strategy of the reference point is set. When the reference point corresponding to the control strategy exceeds the second threshold value corresponding to the set control strategy, the first reference point corresponding to the control strategy exceeding the second threshold value is deleted, and the remaining reference points are used to generate third road spectrum data corresponding to the autonomous driving vehicle, and the third road spectrum data is determined as the speed control strategy corresponding to the autonomous driving vehicle.

[0104] Compared with the prior art, in the embodiments of the present invention, by collecting the driving area, the obtained road spectrum information data model is combined with the vehicle information to accurately control the speed of the autonomous driving vehicle. For autonomous driving vehicles, this is not only targeted, but also helps to improve the safety of autonomous driving vehicles and achieve refined coordinated speed regulation, and can effectively reduce the consumption of manpower and material resources, greatly improving the efficiency of autonomous driving vehicles.

[0105] In one embodiment of the present invention, after collecting the first road spectrum data of the area to be driven, the method further includes:

[0106] Acquire simulation data corresponding to the first spectrum data;

[0107] Based on the simulation data, the performance of the autonomous driving vehicle is tested and analyzed.

[0108] The first spectrum data can be obtained by importing the first spectrum data into a simulation software on the market to generate corresponding simulation data. The simulation software can be specifically AUL CRUIDE software.

[0109] Based on the data imported into the simulation software, the dynamic performance, economic performance and other indicators of different types of autonomous driving vehicles are tested and analyzed.

[0110] In order to better implement the automatic driving vehicle running speed control method in the embodiment of the present invention, based on the automatic driving vehicle running speed control method, correspondingly, please refer to Figure 4 , Figure 4 This is a schematic diagram of the structure of an embodiment of an automatic driving vehicle running speed control device provided by the present invention. The embodiment of the present invention provides an automatic driving vehicle running speed control device 400, including:

[0111] The acquisition module 401 is used to acquire a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven;

[0112] A first determination module 402 is used to obtain vehicle information of the autonomous driving vehicle and determine a first operating speed of the autonomous driving vehicle from a road spectrum database model based on the vehicle information;

[0113] The second determination module 403 is used to determine a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed.

[0114] It should be noted here that: the device 400 provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above method embodiments, which will not be repeated here.

[0115] Based on the above-mentioned method for controlling the running speed of an autonomous driving vehicle, an embodiment of the present invention also provides an electronic device accordingly, including: a processor and a memory, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the steps in the method for controlling the running speed of an autonomous driving vehicle in the above-mentioned embodiments are implemented.

[0116] Figure 5 , a schematic diagram of the structure of an electronic device 500 suitable for implementing the embodiment of the present invention is shown in FIG. The electronic device in the embodiment of the present invention may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0117] The electronic device includes: a memory and a processor, wherein the processor here may be referred to as a processing device 501 hereinafter, and the memory may include at least one of a read-only memory (ROM) 502, a random access memory (RAM) 503, and a storage device 508 hereinafter, as specifically shown below:

[0118] like Figure 5 As shown, the electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0119] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0120] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the ROM502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the method of the embodiment of the present invention are executed.

[0121] Based on the above-mentioned method for controlling the running speed of an autonomous driving vehicle, an embodiment of the present invention also provides a computer-readable storage medium accordingly, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the method for controlling the running speed of an autonomous driving vehicle as described in the above-mentioned embodiments.

[0122] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0123] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for controlling the speed of an automatic driving vehicle, characterized in that: include: Acquire a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven; Acquire vehicle information of the autonomous driving vehicle, and determine a first operating speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information, wherein determining the first operating speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information includes: Based on the vehicle information, obtaining a preset running speed corresponding to the autonomous driving vehicle; Based on the preset running speed, determining whether there is a second running speed in the road spectrum database model whose degree of overlap with the preset running speed is within a first threshold range; If there is a second running speed whose degree of overlap with the preset running speed is within the first threshold range, determining the second running speed as the first running speed of the automatic driving vehicle; A speed control strategy corresponding to the automatic driving vehicle is determined according to the first operating speed.

2. The method according to claim 1, characterized in that Before collecting the first road spectrum data of the area to be driven, the method further includes: Based on the vehicle body dynamics simulation analysis, the stiffness and damping ratio parameters of the autonomous driving vehicle system are obtained; According to the stiffness and damping ratio parameters of the autonomous driving vehicle system, a test plan is formulated and sensors are installed to complete the collection of the road load spectrum; Editing a road analysis and processing target signal according to the road load spectrum to complete the collection of the first road spectrum data; Complete the learning of the first spectrum data and speed regulation association machine, and conduct research on running speed control technology based on the learning results; Based on the research on running speed control technology, road simulation tests are carried out to realize the regulation mechanism of autonomous operation.

3. The method according to claim 2, characterized in that The vehicle body dynamics simulation analysis includes: Use 3D drawing software to draw a 3D structural model of the vehicle body and obtain a 3D structural model of the simulated vehicle; According to the relevant modules of the vehicle dynamics simulation software, the three-dimensional structural model of the simulated vehicle is established and simplified, and the construction of the virtual prototype is completed; According to the virtual prototype, a road profile file is established, and a driving smoothness simulation analysis is completed; Based on the ride smoothness simulation analysis, a ride smoothness evaluation result is obtained.

4. The method according to claim 3, characterized in that After collecting the first road spectrum data of the area to be driven, the method further includes: Acquire simulation data corresponding to the first spectrum data; Based on the simulation data, the performance of the autonomous driving vehicle is tested and analyzed.

5. The method according to claim 1, characterized in that Determining a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed includes: Based on the first running speed, obtaining a first editing instruction for the first running speed; Determining second road spectrum data of the reference point corresponding to the autonomous driving vehicle according to the reference point set at the first running speed through the first editing instruction; Determine that the second road spectrum data is a speed control strategy corresponding to the autonomous driving vehicle.

6. The method according to claim 5, characterized in that The determining that the second road spectrum data is a speed control strategy corresponding to the autonomous driving vehicle includes: Obtaining a first editing instruction from a user, and setting a reference point on the first operating speed range according to the first editing instruction; Obtaining a second editing instruction from a user, and determining initial road spectrum data of the reference point corresponding to the autonomous driving vehicle according to the reference point and the second editing instruction; Based on the initial road spectrum data, obtaining a control strategy for the reference point; The first reference point corresponding to the control strategy that exceeds the second threshold is deleted, and the third road spectrum data after deleting the first reference point is determined to be the speed control strategy corresponding to the automatic driving vehicle.

7. An automatic driving vehicle speed control device, characterized in that: include: An acquisition module, used for acquiring a road spectrum database model of the area to be driven according to the collected first road spectrum data of the area to be driven; The first determination module is used to obtain vehicle information of the autonomous driving vehicle, and determine a first running speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information, wherein the determining the first running speed of the autonomous driving vehicle from the road spectrum database model based on the vehicle information includes: Based on the vehicle information, obtaining a preset running speed corresponding to the autonomous driving vehicle; Based on the preset running speed, determining whether there is a second running speed in the road spectrum database model whose degree of overlap with the preset running speed is within a first threshold range; If there is a second running speed whose degree of overlap with the preset running speed is within the first threshold range, determining the second running speed as the first running speed of the automatic driving vehicle; The second determination module is used to determine a speed control strategy corresponding to the automatic driving vehicle according to the first operating speed.

8. An electronic device, characterized in that: It includes a memory and a processor, wherein the memory is used to store programs; the processor is coupled to the memory and is used to execute the programs stored in the memory to implement the steps in the method for controlling the operating speed of an autonomous driving vehicle as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the method for controlling the operating speed of an autonomous driving vehicle as described in any one of claims 1 to 6 above.

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