Vehicle control method, device and equipment and storage medium

Abstract

The invention discloses a vehicle control method, device and equipment and a storage medium, and the method comprises the steps: obtaining the environment information in front of a vehicle, and the environment information comprises laser radar data returned by a road section in front of the vehicle; determining front road information of the vehicle based on the laser radar data, wherein the front road information comprises a ground model corresponding to a front road; if the ground model represents that the front road comprises a low-lying road section, road surface information corresponding to the low-lying road section is determined based on the ground model, and the road surface information comprises gradient information and roughness information; and determining a control strategy of the vehicle based on the gradient information and the roughness information, and controlling the vehicle to run based on the control strategy. According to the technical scheme, the impact force can be reduced when the vehicle passes through the low-lying road section, and the comfort of users and passengers is greatly improved; and the safety performance can be greatly improved, and safety accidents are avoided.

Description

Technical Field

[0001] The present application relates to the field of vehicle intelligent driving technology, and specifically to a vehicle control method, device, equipment and storage medium. Background Art

[0002] At present, when an autonomous driving vehicle is driving on the road with the intelligent driving function turned on, the road surface condition will have a relatively large impact on the reliability of the intelligent driving vehicle. For example, when the road surface condition is poorly matched (low-lying road section), on the one hand, it will easily lead to relatively poor user comfort when the intelligent driving vehicle is driving, and on the other hand, it will easily lead to safety accidents when the intelligent driving vehicle is driving. Therefore, the comfort and safety of users during intelligent driving need to be improved. Summary of the invention

[0003] In view of the above problems, the present application provides a vehicle control method, device, equipment and storage medium, which can reduce the impact force when the vehicle passes through a low-lying section of road, greatly improve the comfort of users and passengers; it can also greatly improve safety performance and avoid the occurrence of safety accidents.

[0004] According to one aspect of an embodiment of the present application, a vehicle control method is provided, comprising: acquiring environmental information in front of the vehicle, the environmental information including laser radar data returned by a road section in front of the vehicle; determining road information in front of the vehicle based on the laser radar data, the road information including a ground model corresponding to the road in front; if the ground model represents that the road in front includes a low-lying section, determining road surface information corresponding to the low-lying section based on the ground model, the road surface information including slope information and roughness information; determining a control strategy for the vehicle based on the slope information and the roughness information, and controlling the vehicle's travel based on the control strategy.

[0005] In an optional manner, determining the road information ahead of the vehicle based on the lidar data includes: determining point cloud data of the road ahead of the vehicle based on the lidar data; obtaining height information and slope information of three-dimensional points corresponding to the point cloud data; eliminating three-dimensional points whose height information does not meet a preset ground height threshold and whose slope information does not meet a preset ground slope threshold to obtain target point cloud data; and constructing a ground model corresponding to the road ahead of the vehicle based on the target point cloud data.

[0006] In an optional manner, the method also includes: calculating the corresponding average height value of each three-dimensional point in the cloud data; binarizing the height information of each three-dimensional point based on the average height value to obtain non-ground point cloud and ground point cloud in the point cloud data; and using the point cloud data corresponding to the ground point cloud as target point cloud data.

[0007] In an optional manner, the method also includes: cutting the ground model into multiple ground sub-models according to a preset cutting model, the ground sub-model including at least two three-dimensional points; determining the lowest three-dimensional point in the ground sub-model, and determining candidate low-lying road sections based on the multiple lowest three-dimensional points; obtaining sensor data corresponding to the candidate low-lying road sections, and if the sensor data meets the preset low-lying road section data requirements, determining that the candidate low-lying road section is a low-lying road section.

[0008] In an optional manner, determining the control strategy of the vehicle based on the slope information and the roughness information includes: determining driving parameters of the vehicle based on the slope information and the roughness information, the driving parameters including at least one of suspension parameters of a suspension system and braking parameters of a braking system; determining the control strategy of the vehicle based on the driving parameters.

[0009] In an optional manner, the method further includes: if the slope information exceeds a preset slope threshold, obtaining the traffic condition of the current road section; determining the target driving path of the vehicle based on the traffic condition, and determining the control strategy of the vehicle based on the target driving path.

[0010] In an optional manner, the method also includes: when a vehicle passes through a low-lying road section, obtaining the lowest elevation point of the low-lying road section, current position information of the low-lying road section, and image information corresponding to the low-lying road section; generating low-lying road section information based on the lowest elevation point, current position information, and image information; and uploading the low-lying road section information to a corresponding cloud platform.

[0011] According to another aspect of an embodiment of the present application, a vehicle control device is provided, the device comprising: an acquisition module for acquiring environmental information in front of the vehicle, the environmental information comprising laser radar data returned by a road section in front of the vehicle; a first determination module for determining road information in front of the vehicle based on the laser radar data, the road information in front comprising a ground model corresponding to the road in front; a second determination module for determining road surface information corresponding to the low-lying section based on the ground model if the ground model characterizes that the road in front comprises a low-lying section, the road surface information comprising slope information and roughness information; a third determination module for determining a control strategy for the vehicle based on the slope information and the roughness information, and controlling the driving of the vehicle based on the control strategy.

[0012] According to another aspect of an embodiment of the present application, a computing device is provided, including: a controller; and a memory for storing one or more programs, which, when the one or more programs are executed by the controller, enables the controller to implement the above-mentioned vehicle control method.

[0013] According to another aspect of an embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored. The computer program includes executable instructions. When the executable instructions are executed on a vehicle control device / computing equipment, the vehicle control device / computing equipment executes the vehicle control method as described above.

[0014] In the technical solution of the present application, since the vehicle control method can determine the ground model corresponding to the road ahead by acquiring the laser radar data returned by the road section ahead of the vehicle, and can identify whether the road ahead includes a low-lying section through the ground model, and when the ground model characterizes that the road ahead includes a low-lying section, the slope information and roughness information corresponding to the low-lying section are determined through the ground model, and then the control strategy of the vehicle is determined according to the slope information and the roughness information, and finally the vehicle is controlled based on the control strategy.

[0015] Therefore, the vehicle control method of the present application can make predictive control strategies for the intelligent driving of the vehicle by identifying low-lying sections, so as to reduce the impact force of the vehicle when passing through low-lying sections, greatly improving the comfort of users and passengers; it can also greatly improve safety performance and avoid the occurrence of safety accidents.

[0016] The above description is only an overview of the technical solution of the embodiment of the present application. In order to more clearly understand the technical means of the embodiment of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiment of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present application. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:

[0018] Figure 1 A schematic block diagram of the process of steps S210-S240 of a vehicle control method provided in an embodiment of the present application is shown.

[0019] Figure 2 A schematic block diagram of the process of steps S221-S224 of a vehicle control method provided in an embodiment of the present application is shown.

[0020] Figure 3 A schematic block diagram of the process of steps S2231-S2233 of a vehicle control method provided in an embodiment of the present application is shown.

[0021] Figure 4 A schematic block diagram of the process of steps S231-S235 of a vehicle control method provided in an embodiment of the present application is shown.

[0022] Figure 5 A schematic block diagram of the process of steps S241 - S242 of a vehicle control method provided in an embodiment of the present application is shown.

[0023] Figure 6 A schematic block diagram of the process of steps S250 - S270 of a vehicle control method provided in an embodiment of the present application is shown.

[0024] Figure 7 A schematic structural diagram of a vehicle control device provided in an embodiment of the present application is shown.

[0025] Figure 8 A schematic diagram of the structure of an embodiment of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0026] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0027] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0028] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0029] The term "multiple" as used in this application refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0030] Figure 1 The following is a schematic flow chart of steps S210-S240 of a vehicle control method provided by an embodiment of the present application. Figure 1As shown, this embodiment provides a vehicle control method, which can make a predictive control strategy for the intelligent driving of the vehicle by identifying the low-lying road section, so that the impact force of the vehicle is reduced when the vehicle passes through the low-lying road section, greatly improving the comfort of users and passengers; it can also greatly improve the safety performance and avoid the occurrence of safety accidents. Among them, the method is executed by the vehicle terminal, and the method includes steps S210 to S240, which are described in detail as follows:

[0031] Step S210: Acquire environmental information in front of the vehicle, where the environmental information includes laser radar data returned by the road section in front of the vehicle.

[0032] For example, a lidar installed on a vehicle can emit laser pulses to the environment in front of the vehicle to obtain lidar data of the road section in front of the vehicle.

[0033] Step S220: Determine the road information ahead of the vehicle based on the laser radar data, where the road information ahead includes a ground model corresponding to the road ahead.

[0034] In an alternative approach, Figure 2 The following is a schematic flow chart of steps S221-S224 of a vehicle control method provided by an embodiment of the present application. Figure 2 As shown, the method for determining the road information ahead of the vehicle based on the laser radar data includes steps S221 to S224, which are described in detail as follows:

[0035] Step S221: Determine the point cloud data of the road ahead of the vehicle based on the laser radar data.

[0036] For example, when the lidar mounted on the top of a vehicle emits a laser pulse to the environment in front of the vehicle, the laser pulse will be reflected back when it encounters an object and then captured by the lidar receiver. Each reflection point is converted into a point in three-dimensional space, and these points are collected together to form a point cloud.

[0037] Step S222: Obtain height information and slope information of the three-dimensional points corresponding to the point cloud data.

[0038] It should be understood that the point cloud data includes multiple three-dimensional points, and obtaining the height information and slope information of the three-dimensional points corresponding to the point cloud data means: obtaining the height information and slope information of each three-dimensional point.

[0039] Step S223: Eliminate the three-dimensional points whose height information does not meet the preset ground height threshold and whose slope information does not meet the preset ground slope threshold, so as to obtain target point cloud data.

[0040] In an optional manner, the method for eliminating three-dimensional points whose slope information does not meet a preset ground slope threshold includes: calculating the slope value of each three-dimensional point, and converting the slope value result into a percentage or degree.

[0041] For example: define an analysis window, such as a 3×3 or 5×5 grid cell, and then calculate the vertical elevation difference between the corresponding 3D point in the grid cell and the adjacent point by simple difference, and then divide it by the horizontal distance between the two. The slope calculation formula is:

[0042]

[0043] Among them, S is the slope, Δz is the vertical elevation difference, Δx and Δy are the horizontal and vertical distances.

[0044] Furthermore, the slope value of the three-dimensional point is compared with a preset ground slope threshold, and the three-dimensional points whose slope value exceeds the preset ground slope threshold are eliminated.

[0045] Optionally, for plain areas, the preset ground slope threshold is 1%-3%, which can ensure the stability of the terrain and meet the basic needs of drainage and ventilation. For example, the open and gentle terrain space in garden design, such as a large lawn with a gentle slope, has a small slope, rich terrain changes, and a large site area, forming a large area of ​​activity "surface" for people to enter and carry out various activities.

[0046] Optionally, for hilly and mountainous areas, the preset ground slope threshold is 5%-20%. For slightly steep and closed terrain spaces and steep and closed terrain spaces, these terrains are mainly planted or mainly used for spatial separation. The slope can be relatively large, forming closed spaces separated by plants or terrain with large height differences and a strong sense of spatial territory.

[0047] Furthermore, after eliminating the 3D points whose slope values ​​exceed the preset ground slope threshold, it is necessary to check whether the slope of each 3D point is significantly different from the slopes of its adjacent 3D points. If so, remove them.

[0048] In an alternative approach, Figure 3 The flowchart of steps S2231-S2233 of a vehicle control method provided by an embodiment of the present application is shown. Figure 3 As shown, the method for removing three-dimensional points whose height information does not meet the preset ground height threshold includes steps S2231 to S2233, which are described in detail as follows:

[0049] Step S2231: Calculate the corresponding average height value of each three-dimensional point in the cloud data.

[0050] For example, the corresponding average height value of each 3D point is calculated using the height information of each 3D point.

[0051] Step S2232: Binarize the height information of each three-dimensional point based on the average height value to obtain non-ground point cloud and ground point cloud in the point cloud data.

[0052] For example, the calculated average height value is used as the preset ground height threshold, and a binarization operation is performed based on the height information of each three-dimensional point according to the preset ground height threshold. The grayscale of pixels greater than the preset ground height threshold is set to a maximum value of 255 (white), and the grayscale of pixels less than the preset ground height threshold is set to a minimum value of 0 (black). The white points are non-ground point clouds, and the black points are ground point clouds. In this way, data that is obviously not a ground point cloud can be separated to prepare for subsequent processing.

[0053] Step S2233: The point cloud data corresponding to the ground point cloud is used as the target point cloud data. At this point, since the data of non-ground points (such as traffic participants: vehicles, pedestrians, trees, buildings, etc.) in the original point cloud data have been removed, it is easy to obtain an accurate ground model.

[0054] Step S224: constructing a ground model corresponding to the road ahead of the vehicle based on the target point cloud data.

[0055] For example, the method of constructing the ground model corresponding to the road ahead of the vehicle based on the target point cloud data includes: first, importing the filtered target point cloud data into the geographic information system (GIS) or professional ground model (DTM, Digital Terrain Model) construction software, and then further processing the target point cloud data (including data cleaning, etc.), further removing outliers and isolated points, and if the data volume is very large, it is also necessary to simplify the data by gridding or clustering methods to reduce the amount of calculation. Then, through Del aunay triangulation, the target point cloud data is converted into an irregular triangulated network (TIN), and a suitable algorithm, such as the Bowyer-Watson algorithm, is selected for triangulation to ensure that the triangulated network meets the principle of maximizing the minimum angle to better simulate the terrain surface. On the basis of the triangulated network, the unknown elevation points in each triangle are calculated by the Kriging interpolation method, which usually can obtain more accurate results. The interpolated triangulated network is converted into regular grid data, usually a rectangular grid. The size of the grid is determined according to the needs. The higher the resolution, the finer the ground model, but the larger the amount of data. Then the ground model is optimized, smoothed and edge-refined to remove small outliers, smooth surface elevation changes and ensure that the edge of the ground model matches the actual terrain. Finally, the constructed ground model is saved in a common format for subsequent use.

[0056] Step S230: If the ground model indicates that the road ahead includes a low-lying section, road surface information corresponding to the low-lying section is determined based on the ground model, where the road surface information includes slope information and roughness information.

[0057] In an alternative approach, Figure 4 The following is a schematic flow chart of steps S231-S235 of a vehicle control method provided in an embodiment of the present application. Figure 4 As shown, the method for representing the front road including the low-lying road section by the ground model includes steps S231 to S235, which are described in detail as follows:

[0058] Step S231 : cutting the ground model into a plurality of ground sub-models according to a preset cutting model, wherein the ground sub-models include at least two three-dimensional points.

[0059] It should be understood that the preset cutting model can be set according to different ground models, as long as the ground model can be divided into a plurality of non-overlapping ground sub-models.

[0060] For example, the road segment in the ground model is cut along its length direction by using a preset cutting model to obtain a ground sub-model. Of course, the road segment in the ground model can also be divided into multiple lanes by using a preset cutting model, and then each lane is cut along the length direction of the road segment in the ground model to obtain a ground sub-model. The length of the road segment in each ground sub-model can be 50, 1m or 2m.

[0061] Step S232, determining the lowest three-dimensional point in the ground sub-model.

[0062] For example, local minimum points can be detected on the ground submodel using a terrain index method, which is determined by calculating the terrain characteristics of each point relative to its surrounding points.

[0063] Optionally, the negative topographic index (NTI) is used to determine the lowest three-dimensional point in the ground submodel. The calculation formula of NTI is as follows:

[0064] NTI = (elevation - average elevation) / (average elevation - minimum elevation)

[0065] Among them, the elevation is the elevation of the current 3D point, the average elevation is the average elevation of all 3D points within a certain range around the current 3D point, and the minimum elevation is the lowest elevation of all points within a certain range around the current 3D point.

[0066] It should be understood that if the NTI value of a 3D point is negative, it means that the 3D point is lower than the surrounding points and may be a local minimum point. The smaller the NTI value, the greater the possibility that the 3D point is a local minimum 3D point.

[0067] Optionally, a local pit index (LPI) is used to determine the lowest three-dimensional point in the ground submodel. The calculation formula of LPI is as follows:

[0068] LPI = (elevation - average elevation of surrounding points) / (maximum elevation of surrounding points - minimum elevation of surrounding points)

[0069] Among them, if the LPI value of a 3D point is greater than 1, it means that the 3D point is lower than the surrounding 3D points and may be the local lowest 3D point. The larger the LPI value, the greater the possibility that the 3D point is the local lowest 3D point.

[0070] Step S233: determining candidate low-lying road sections based on multiple lowest three-dimensional points.

[0071] It should be understood that adjacent three-dimensional points among the multiple lowest three-dimensional points are connected to obtain an area, and then the features of the low-lying road section are extracted through the width, depth and / or shape of the area to obtain a candidate low-lying road section.

[0072] For example, in the area surrounded by multiple lowest 3D points, there may be some non-lowest 3D points. In this case, the area surrounded by 3D points close to the average height value among the non-lowest 3D points is removed to obtain the remaining area, and then the features of the low-lying road section are extracted through the width, depth and / or shape of the remaining area to obtain the candidate low-lying road section.

[0073] Step S234, obtaining sensor data corresponding to the candidate low-lying road section.

[0074] For example, sensor data (such as image data, navigation data, etc.) corresponding to the candidate low-lying road sections are obtained through lidar and other sensors (such as cameras, ultrasonic radars, GPS, etc.).

[0075] Step S235 : if the sensor data meets the preset low-lying road section data requirement, the candidate low-lying road section is determined to be a low-lying road section.

[0076] For example, when the sensor data is image data, it may be possible to identify whether the candidate low-lying road section satisfies a preset low-lying road section by means of image recognition.

[0077] It should be understood that after confirming the candidate low-lying road section through the ground model, the low-lying road section can be identified more accurately by verifying it through the corresponding sensor data.

[0078] In an optional manner, the road surface information corresponding to the low-lying road section is determined based on the ground model, and the slope change can be identified through the ground model. The details are as follows:

[0079] First, in an analysis window, use the slope calculation formula to convert the slope calculation result into degrees. The following formula can be used:

[0080] S (degrees) = S (radians) × 180 / π

[0081] Secondly, create a slope grid and store the slope values ​​calculated in each analysis window in a grid dataset, with each grid cell corresponding to a slope value. For the slope grid, define the pane size again (for example, multiple grid cells are positioned as one pane), then sum the slope values ​​in each pane and calculate the average value. The change rate of each pane is calculated using the slope change rate formula, which is as follows:

[0082]

[0083] Where n is the number of points in the window, and the slope i is the slope value of each point in the pane, and the average slope is the average of the slopes of all points in the pane.

[0084] Finally, the calculated slope change rate value is stored in a new raster dataset, and the slope change rate can be used to understand the complexity of the terrain and the slope change space.

[0085] For example, by identifying the change in slope, the slope is graded and a slope grade map is created, and different colors are used to represent different slope grades. The slope grade can be set as gentle: 0-5 degrees; medium: 5-15 degrees; steep: 15-30 degrees; very steep: greater than 30 degrees.

[0086] In an optional manner, the road surface information corresponding to the low-lying road section is determined based on the ground model, and the roughness change can be identified through the ground model. The roughness corresponding to the low-lying road section refers to the microscopic irregularity of the surface of the low-lying road section.

[0087] For example: the standard deviation method is used to calculate the elevation standard deviation of all points in an analysis window, which can be used as an indicator of roughness. The larger the standard deviation, the higher the surface roughness, and vice versa.

[0088] Optionally, the standard deviation is divided into different levels, such as smooth (low standard deviation), medium, rough (high standard deviation); a roughness level map is created, with different shades representing different roughness levels.

[0089] Step S240: Determine a control strategy for the vehicle based on the slope information and the roughness information, and control the vehicle driving based on the control strategy.

[0090] In an alternative approach, Figure 5 The schematic flow chart of steps S241-S242 of a vehicle control method provided in an embodiment of the present application is shown. Figure 5 As shown, the method for determining the control strategy of the vehicle based on the slope information and the roughness information includes steps S241 to S242, which are described in detail as follows:

[0091] Step S241, determining the driving parameters of the vehicle based on the slope information and the roughness information, where the driving parameters include at least one of the suspension parameters of the suspension system and the braking parameters of the braking system.

[0092] Optionally, the suspension system can choose an air suspension system, which is more suitable for high-end models and vehicles with special requirements for comfort compared to traditional suspension systems. The air suspension system uses air springs instead of metal springs, and usually includes an air compressor, air tank, electronic control unit (ECU) and sensors. It can provide a smoother and more comfortable ride because the air spring can automatically adjust the hardness according to the road conditions. Secondly, its height can be adjusted, allowing users to adjust the height of the vehicle according to their own needs, and can also adapt to different load conditions to keep the level of their own vehicle. Therefore, the use of an air suspension system can improve the adaptability of the vehicle on various road surfaces, increase the vehicle's load capacity, and enhance the user's driving experience and comfort.

[0093] For example, when the slope information shows that the slope level of the current low-lying road section is gentle, and when the roughness information shows that the roughness of the current low-lying road section is small, the driving parameters of the ordinary road section can be used. When the slope information shows that the slope level of the current low-lying road section is steep; and / or, when the roughness information shows that the roughness of the current low-lying road section is large: the braking parameters in the driving parameters of the vehicle can be adjusted so that the braking system brakes and decelerates in advance; and / or, the suspension parameters in the driving parameters of the vehicle can be adjusted so that the suspension system responds in advance, so as to calculate the working parameters of the suspension system in advance, thereby improving the response time of the suspension system.

[0094] Furthermore, the method before or after determining the driving parameters of the vehicle based on the slope information and the roughness information also includes: comparing whether the slope value in the slope information exceeds a preset slope threshold, and if so, obtaining the traffic condition of the current road section; determining the target driving path of the vehicle based on the traffic status, and determining the control strategy of the vehicle based on the target driving path.

[0095] For example, when the slope value in the slope information exceeds the preset slope threshold, if the traffic status shows that there are many traffic participants, it is judged that it is difficult for the vehicle to bypass the low-lying road section, and the vehicle's driving path is not modified, that is, the target driving path of the vehicle is determined to be the original driving path, and then the vehicle's driving parameters are determined based on the target driving path, and then the vehicle's control strategy is determined. If the traffic status shows that there are few traffic participants, it is judged that the vehicle can bypass the low-lying road section. At this time, a smooth route can be planned as the target driving path to avoid the low-lying road section, such as changing lanes to bypass, and then the vehicle's driving parameters are determined based on the target driving path, and then the vehicle's control strategy is determined.

[0096] Step S242, determining the vehicle control strategy based on the driving parameters, ultimately reducing the impact force of the intelligent driving vehicle when passing through a low-lying road section, greatly improving the comfort of users and passengers.

[0097] In addition, after the vehicle passes through a detected low-lying section, the vehicle can automatically record relevant data and upload the relevant data to the cloud platform, so that when determining that a candidate low-lying section is a low-lying section, the relevant data on the cloud platform can be combined to determine whether the candidate low-lying section is a low-lying section.

[0098] It should be understood that when obtaining sensor data corresponding to a candidate low-lying road section, the sensor data includes historical relevant data of the low-lying road section automatically recorded by the vehicle and uploaded to the cloud platform.

[0099] In an alternative approach, Figure 6 The following is a schematic flow chart of steps S250-S270 of a vehicle control method provided by an embodiment of the present application. Figure 6 As shown, the method for automatically recording relevant data by the vehicle and uploading the relevant data to the cloud platform includes steps S250-S270, which are described in detail as follows:

[0100] Step S250: when the vehicle passes through a low-lying road section, the lowest elevation point of the low-lying road section, the current position information of the low-lying road section, and the image information corresponding to the low-lying road section are obtained.

[0101] Optionally, when a vehicle passes through a low-lying section, a lidar, ultrasonic sensor or other height measuring equipment can be used to obtain ground height information to determine the lowest elevation point of the low-lying section, and then the maximum wading depth value of the low-lying section and the chassis clearance parameters for safely passing through the low-lying section can be obtained.

[0102] Optionally, when a vehicle passes through a low-lying road section, the current position information of the low-lying road section may be recorded by the vehicle's positioning system, thereby recording the exact position of the low-lying road section.

[0103] Optionally, when a vehicle passes through a low-lying section of road, an image or video of the low-lying section may be captured by the vehicle's camera to obtain image information of the low-lying section for visual analysis and recording.

[0104] Step S260: Generate low-lying road section information based on the lowest elevation point, current location information and image information, so that after waiting for the end of driving, the user can be prompted through the in-vehicle infotainment system (IVI) interface to upload the data automatically recorded by the system to the cloud platform with one click.

[0105] Step S270: Upload the low-lying road section information to the corresponding cloud platform.

[0106] For example, the cloud platform will first pre-process the low-lying road section information to be uploaded. The purpose of data pre-processing is to ensure the accuracy and consistency of the uploaded data. At this stage, the cloud platform will perform data cleaning, format conversion, data fusion and data compression on the uploaded data.

[0107] It should be understood that the cloud platform performs data cleaning on uploaded low-lying road section information mainly to remove erroneous, redundant and inconsistent low-lying road section information data, and ensure that reliable and accurate low-lying road section information data can be used. The purpose of the cloud platform's format conversion of uploaded low-lying road section information is to convert data in different formats uploaded by users, such as current location information, low-lying road section characteristics, image information and lowest elevation points, into a unified format, such as JSON format or proprietary format, to facilitate subsequent comparison and processing. The cloud platform performs data fusion on uploaded low-lying road section information in order to combine different data sources and improve the completeness and accuracy of the data. The cloud platform compresses the uploaded low-lying road section information in order to save bandwidth and storage space, and the data needs to be compressed.

[0108] Furthermore, after data preprocessing of the low-lying road section information to be uploaded, one of the following methods can be used to establish a connection between the vehicle and the cloud platform: 1. Wi-Fi: If the device supports Wi-Fi, it can be used to upload data; 2. Mobile network: Use 4G / 5G network to connect to the cloud.

[0109] Furthermore, after establishing the connection between the vehicle and the cloud platform, data can be uploaded through a file transfer protocol, such as FTP (File Transfer Protocol), which is one of the protocols in the TCP / IP protocol suite. The FTP protocol consists of two components, one is the FTP server, and the other is the FTP client. The FTP server is used to store files, and users can use the FTP client to access resources located on the FTP server through the FTP protocol. When developing a website, the FTP protocol is usually used to upload web pages or programs to the Web server. In addition, since the FTP transmission efficiency is very high, this protocol is generally used when transferring large files on the network.

[0110] Furthermore, after the cloud platform receives the low-lying road section information, it is necessary to perform a data integrity check on the low-lying road section information to ensure that the data is not damaged during the upload process; and perform data verification on the low-lying road section information to check whether the data conforms to the predefined format and standards; finally, perform a data security check on the low-lying road section information to ensure the security of the data transmission process.

[0111] Furthermore, after preprocessing the low-lying road section information data to obtain the correct data, a relational database can be used to store and manage large-scale data, and the data can be partitioned and stored on multiple servers or storage nodes to improve access efficiency. After the data is stored, it can be further processed and analyzed to facilitate rapid decision support. In addition, data can be backed up regularly to prevent loss or shared with other systems or third parties, and the data upload process and cloud platform status can be monitored in real time to ensure stable operation of the system. Finally, based on actual usage and feedback information, the cloud platform will continuously update and optimize the uploaded data to improve its accuracy and practicality.

[0112] In summary, when the vehicle of the present application is driving, first, the laser radar installed on the roof can emit laser pulses to the road section in front of the vehicle to obtain laser radar data, and then remove the non-ground point cloud in the laser radar data to obtain the target point cloud data, and then establish the ground model corresponding to the road in front of the vehicle according to the target point cloud data. Secondly, the low-lying road section is identified through the ground model. When the ground model characterizes that the road ahead includes a low-lying road section, the slope information, roughness information and traffic status of the low-lying road section are determined, and then the target driving path and driving parameters of the vehicle are determined according to the slope information, roughness information and traffic status of the low-lying road section, and then a predictive control strategy is made for the intelligent driving of the vehicle, so that the impact force of the vehicle is reduced when the intelligent driving passes through the low-lying road section, which greatly improves the comfort of users and passengers; it can also greatly improve the safety performance and avoid the occurrence of safety accidents. Finally, the low-lying road section information of the low-lying road section that the vehicle has traveled is recorded and uploaded to the corresponding cloud platform, so that the uploaded low-lying road section information is continuously updated and optimized and iterated according to actual usage and feedback information to improve its accuracy and practicality, so that the vehicle can accurately identify the low-lying road section and the corresponding parameters of the low-lying road section when it passes through the same low-lying road section next time.

[0113] Figure 7 FIG. 1 is a schematic diagram showing the structure of a vehicle control device provided in an embodiment of the present application. Figure 7 As shown, in this embodiment, a vehicle control device is also provided for executing the vehicle control method in the above embodiment.

[0114] Furthermore, the vehicle control device 300 includes an acquisition module 310, which is used to acquire environmental information in front of the vehicle, and the environmental information includes laser radar data returned by the road section in front of the vehicle.

[0115] Furthermore, the vehicle control device 300 also includes a first determination module 320, which is used to determine the road information ahead of the vehicle based on the laser radar data, and the road information ahead includes a ground model corresponding to the road ahead.

[0116] Furthermore, the vehicle control device 300 also includes a second determination module 330, which is used to determine road surface information corresponding to the low-lying section based on the ground model if the ground model indicates that the road ahead includes a low-lying section, and the road surface information includes slope information and roughness information.

[0117] Furthermore, the vehicle control device 300 also includes a third determination module 340, which is used to determine a control strategy of the vehicle based on the slope information and the roughness information, and control the vehicle driving based on the control strategy.

[0118] It should be noted that the vehicle control device provided in the above embodiment and the vehicle control method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here.

[0119] Figure 8 A structural schematic diagram of an embodiment of a computing device of the present application is shown, which shows a structural schematic diagram of a computer system of a computing device suitable for implementing an embodiment of the present application. The specific embodiment of the present application does not limit the specific implementation of the computing device.

[0120] See also Figure 8 As shown, the computing device includes: a controller; and a memory for storing one or more programs. When the one or more programs are executed by the controller, the above-mentioned vehicle control method is executed.

[0121] Please continue reading Figure 8 As shown, the computer system of the computing device 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage part 508 to the random access memory (RAM) 503, such as executing the method in the above embodiment. In the RAM 503, various programs and data required for system operation are also stored. The CPU 501, the ROM 502 and the RAM 503 are connected to each other through a bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0122] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed so that a computer program read therefrom is installed into the storage section 508 as needed.

[0123] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 509, and / or installed from a removable medium 511. When the computer program is executed by a central processing unit (CPU) 501, various functions defined in the system of the present application are executed.

[0124] Another aspect of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the vehicle control method as described above is implemented. The computer-readable storage medium may be included in the computing device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0125] Another aspect of the present application also provides a computer program product or a computer program, which includes at least one executable instruction. When the executable instruction is run on a computing device / equipment, the computing device / equipment executes the above vehicle control method.

[0126] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with 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 (Erasable Programmable Read On l yMemory, EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as a part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0127] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the apparatus, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0128] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0129] According to one aspect of the embodiment of the present application, a computer system is also provided, including a central processing unit (CPU), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage portion to a random access memory (RAM), such as executing the method in the above embodiment. In RAM, various programs and data required for system operation are also stored. CPU, ROM and RAM are connected to each other via a bus. Input / output (I / O) interface is also connected to the bus.

[0130] The following components are connected to the I / O interface: an input part including a keyboard, a mouse, etc.; an output part including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage part including a hard disk, etc.; and a communication part including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication part performs communication processing via a network such as the Internet. A drive is also connected to the I / O interface as needed. Removable media, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., are installed on the drive as needed so that the computer program read therefrom is installed into the storage part as needed.

[0131] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0132] In the present application, the same or similar terminology concepts, technical solutions and / or application scenario descriptions are generally described in detail only the first time they appear. When they appear again later, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of the present application, for the same or similar terminology concepts, technical solutions and / or application scenario descriptions that are not described in detail later, reference can be made to the previous related detailed descriptions.

[0133] In the present application, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] The various technical features of the technical solution of the present application can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present application.

[0135] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. A person skilled in the art can easily make corresponding changes or modifications based on the main concept and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A vehicle control method, characterized in that: include: Acquiring environmental information ahead of the vehicle, the environmental information including laser radar data returned by the road ahead of the vehicle; Determine the road information ahead of the vehicle based on the laser radar data, wherein the road information ahead includes a ground model corresponding to the road ahead; If the ground model indicates that the road ahead includes a low-lying section, determining road surface information corresponding to the low-lying section based on the ground model, the road surface information including slope information and roughness information; A control strategy for the vehicle is determined based on the slope information and the roughness information, and the vehicle is controlled to travel based on the control strategy.

2. The method according to claim 1, characterized in that The determining the road information ahead of the vehicle based on the laser radar data comprises: Determine point cloud data of the road ahead of the vehicle based on the laser radar data; Obtaining height information and slope information of the three-dimensional point corresponding to the point cloud data; Eliminate the three-dimensional points whose height information does not meet a preset ground height threshold and whose slope information does not meet a preset ground slope threshold, so as to obtain target point cloud data; A ground model corresponding to the road ahead of the vehicle is constructed based on the target point cloud data.

3. The method according to claim 2, characterized in that The method further comprises: Calculate the corresponding average height value of each three-dimensional point in the cloud data; Binarize the height information of each three-dimensional point based on the average height value to obtain a non-ground point cloud and a ground point cloud in the point cloud data; The point cloud data corresponding to the ground point cloud is used as target point cloud data.

4. The method according to claim 1, characterized in that The method further comprises: Cutting the ground model into a plurality of ground sub-models according to a preset cutting model, wherein the ground sub-models include at least two three-dimensional points; Determining the lowest three-dimensional point in the ground sub-model, and determining a candidate low-lying road section based on a plurality of lowest three-dimensional points; The sensor data corresponding to the candidate low-lying road section is obtained, and if the sensor data meets the preset low-lying road section data requirements, the candidate low-lying road section is determined to be a low-lying road section.

5. The method according to claim 1, characterized in that The determining of the control strategy of the vehicle based on the slope information and the roughness information comprises: determining a driving parameter of the vehicle based on the slope information and the roughness information, the driving parameter comprising at least one of a suspension parameter of a suspension system and a braking parameter of a braking system; A control strategy for the vehicle is determined based on the driving parameters.

6. The method according to claim 5, characterized in that The method further comprises: If the slope information exceeds a preset slope threshold, the traffic condition of the current road section is obtained; A target driving path of the vehicle is determined based on the traffic state, and a control strategy of the vehicle is determined based on the target driving path.

7. The method according to claim 1, characterized in that The method further comprises: When the vehicle passes through the low-lying road section, obtaining the lowest elevation point of the low-lying road section, current position information of the low-lying road section, and image information corresponding to the low-lying road section; Generate low-lying road section information based on the lowest elevation point, current location information and the image information; The low-lying road section information is uploaded to the corresponding cloud platform.

8. A vehicle control device, characterized in that: The device comprises: An acquisition module, used to acquire environmental information in front of the vehicle, wherein the environmental information includes laser radar data returned by the road section in front of the vehicle; A first determination module, configured to determine the road information ahead of the vehicle based on the laser radar data, wherein the road information ahead includes a ground model corresponding to the road ahead; A second determination module is configured to determine road surface information corresponding to the low-lying section based on the ground model if the ground model indicates that the road ahead includes a low-lying section, wherein the road surface information includes slope information and roughness information; The third determination module is used to determine the control strategy of the vehicle based on the slope information and the roughness information, and control the vehicle to travel based on the control strategy.

9. A computing device, characterized in that include: Controller; A memory for storing one or more programs, which, when executed by the controller, enables the controller to implement the vehicle control method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which includes executable instructions. When the executable instructions are executed on the vehicle control device / computing equipment, the vehicle control device / computing equipment executes the vehicle control method as described in any one of claims 1 to 7.

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