Vehicle driving assistance method and device, electronic equipment and storage medium

Abstract

This application provides a vehicle driving assistance method, device, electronic device, and storage medium. The method includes: acquiring the current operating status data of a target vehicle and identifying multiple surrounding vehicles adjacent to the target vehicle; acquiring operating data collected by each surrounding vehicle, the operating data including the surrounding vehicle itself and the operating status data of multiple adjacent vehicles; constructing a three-dimensional road model centered on the target vehicle based on the operating data and the current operating status data; and distributing the three-dimensional road model centered on the target vehicle to the target vehicle, enabling the target vehicle to determine its operating status data for the next moment based on the three-dimensional road model centered on the target vehicle, and to drive according to the operating status data for the next moment. Using the method of this application can further improve vehicle driving safety.

Description

Technical Field

[0001] This application relates to automotive intelligent cockpit technology, and more particularly to a vehicle driving assistance method, device, electronic device, and storage medium. Background Technology

[0002] With the development of intelligent cockpit technology in automobiles, vehicle driving assistance methods have emerged to help vehicles drive better and improve their safety and intelligence.

[0003] Currently, automotive driver assistance algorithms are all based on data detected by the vehicle itself, calculated by the vehicle's local intelligent driving domain controller to determine the driving environment around the target vehicle, thereby assisting the target vehicle to drive more safely.

[0004] However, the data collected by the vehicle itself is limited, making it difficult to further improve the driving safety of the target vehicle. Summary of the Invention

[0005] This application provides a vehicle driving assistance method, device, electronic device, and storage medium to solve the technical problem in the prior art that it is difficult to further improve the driving safety of the target vehicle.

[0006] In a first aspect, this application provides a vehicle driving assistance method, including:

[0007] The system acquires the current operating status data of the target vehicle and identifies multiple surrounding vehicles adjacent to the target vehicle, which are vehicles scanned by the target vehicle's image acquisition device and radar.

[0008] The operation data collected by each of the surrounding vehicles is obtained. The operation data includes the surrounding vehicles and the operation status data of multiple neighboring vehicles adjacent to the surrounding vehicles. The neighboring vehicles are the vehicles scanned by the image acquisition device and radar of the surrounding vehicles.

[0009] Based on the aforementioned operational data and the operational status data at the current moment, a three-dimensional road model centered on the target vehicle is constructed.

[0010] The three-dimensional road model centered on the target vehicle is sent to the target vehicle so that the target vehicle can determine the operating status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the operating status data of the next moment.

[0011] In one embodiment, determining the plurality of surrounding vehicles adjacent to the target vehicle includes:

[0012] Acquire images of the target vehicle from multiple directions obtained by the image acquisition device;

[0013] Image recognition algorithms are used to identify images from the multiple directions to obtain multiple license plate numbers;

[0014] The vehicles corresponding to each of the aforementioned license plate numbers are identified as multiple surrounding vehicles adjacent to the target vehicle.

[0015] In one embodiment, adjacent vehicles are surrounding vehicles or vehicles next to each other; the operating status data includes at least: throttle acceleration, vehicle speed, steering wheel angle, and driving distance to each adjacent vehicle.

[0016] In one embodiment, when the adjacent vehicle is a surrounding vehicle, the driving distance to each adjacent vehicle is measured by the ranging device of the target vehicle; when the adjacent vehicle is a neighboring vehicle, the driving distance to each adjacent vehicle is measured by the ranging device of the surrounding vehicle.

[0017] In one embodiment, the operating status data for the next moment includes: the target vehicle's driving direction and speed at the next moment.

[0018] In one embodiment, the method further includes: acquiring real-time operating status data uploaded by each vehicle within a preset range, wherein the vehicles include the target vehicle and other vehicles besides the target vehicle.

[0019] Secondly, this application provides a vehicle driving assistance device, comprising:

[0020] The operation status data acquisition module is used to acquire the current operation status data of the target vehicle and identify multiple surrounding vehicles adjacent to the target vehicle. The surrounding vehicles are vehicles scanned by the image acquisition device and radar of the target vehicle.

[0021] The operation data acquisition module is used to acquire the operation data collected by each of the surrounding vehicles. The operation data includes the surrounding vehicles and the operation status data of multiple neighboring vehicles adjacent to the surrounding vehicles. The neighboring vehicles are the vehicles scanned by the image acquisition device and radar of the surrounding vehicles.

[0022] The three-dimensional model construction module is used to construct a three-dimensional road model centered on the target vehicle based on the aforementioned operational data and the operational status data at the current moment.

[0023] The running status sending module is used to send the three-dimensional road model centered on the target vehicle to the target vehicle, so that the target vehicle can determine the running status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the running status data of the next moment.

[0024] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0025] The memory stores computer-executed instructions;

[0026] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0027] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0028] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0029] The vehicle driving assistance method, device, electronic device, and storage medium provided in this application acquire the current operating status data of a target vehicle, as well as the operating status data of multiple surrounding vehicles adjacent to the target vehicle; acquire the operating data collected by each of the surrounding vehicles, including the operating status data of the surrounding vehicles and multiple adjacent vehicles; and construct a three-dimensional road model centered on the target vehicle based on the operating data collected by the surrounding vehicles and the current operating status data. This three-dimensional road model directly reflects the driving conditions or road surface conditions around the target vehicle. Thus, the data acquired by the electronic device includes not only the current operating status data collected by the target vehicle itself, but also the operating status data of multiple surrounding vehicles and adjacent vehicles. This operating status data has more dimensions than the original data, and constructing a three-dimensional road model centered on the target vehicle based on this operating status data can expand the target vehicle's perception range of the surrounding traffic conditions. Finally, a 3D road model centered on the target vehicle is sent to the target vehicle, enabling the target vehicle to determine its operating status data for the next moment based on the 3D road model centered on the target vehicle, and drive according to the operating status data for the next moment, thereby further improving the safety of vehicle driving. Attached Figure Description

[0030] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0031] Figure 1 This is an application scenario diagram illustrating the vehicle driving assistance method according to an embodiment of this application.

[0032] Figure 2This is a flowchart illustrating an embodiment of a vehicle driving assistance method according to this application;

[0033] Figure 3 This is a schematic diagram showing the distribution of the target vehicle, surrounding vehicles, and adjacent vehicles according to an embodiment of this application;

[0034] Figure 4 This is a flowchart illustrating another embodiment of the vehicle driving assistance method of this application;

[0035] Figure 5 This is a schematic diagram of the structure for implementing the vehicle driving assistance method of this application;

[0036] Figure 6 This is a schematic diagram of the structure of an electronic device used to implement a vehicle driving assistance method.

[0037] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0038] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0039] To clearly understand the technical solution of this application, the solutions of the prior art will be described in detail first.

[0040] In traditional methods, automotive driver assistance algorithms rely on the vehicle's local intelligent driving domain controller to calculate the surrounding driving environment based on data detected by the vehicle itself, thereby assisting in safer driving. However, the data collected by the vehicle itself is limited (only including the distances between the vehicle and surrounding vehicles), making it difficult to further improve the driving safety of the target vehicle.

[0041] Therefore, when faced with the technical problems of existing technologies, the inventors, through creative research, discovered a way to further improve vehicle driving safety. Instead of relying solely on data detected by the target vehicle itself, they acquired more multi-dimensional data. This involved obtaining the target vehicle's current operational status data, as well as operational data collected by surrounding vehicles and their adjacent neighboring vehicles. Based on this combined data, a three-dimensional road model centered on the target vehicle was constructed. This model directly reflects the surrounding traffic and road conditions. Thus, the electronic device acquires data including the target vehicle's current operational status data, as well as the operational status data of multiple surrounding and adjacent vehicles. This increased the dimensionality of the operational status data compared to previous methods, and constructing a three-dimensional road model based on this data expands the target vehicle's perception range of its surrounding traffic conditions. Finally, a 3D road model centered on the target vehicle is sent to the target vehicle, enabling the target vehicle to determine its operating status data for the next moment based on the 3D road model centered on the target vehicle, and drive according to the operating status data for the next moment, thereby further improving the safety of vehicle driving.

[0042] like Figure 1 As shown in the embodiment of this application, the application scenario of the vehicle driving assistance method includes an electronic device 10 and multiple vehicle controllers in the corresponding network architecture. The electronic device 10 communicates with the multiple vehicle controllers. The multiple vehicle controllers include a controller 20 for the target vehicle and controllers for vehicles other than the target vehicle controller 20, referred to as non-target vehicle controllers 30. The non-target vehicle controllers 30 include at least controllers for surrounding vehicles and controllers for adjacent vehicles. The target vehicle controller 20 uploads its operating status data to the electronic device 10 in real time, so that the electronic device 10 can obtain the current operating status data of the target vehicle. At the same time, the electronic device 10 also determines multiple surrounding vehicles adjacent to the target vehicle at the current time and obtains the operating data collected by each surrounding vehicle. Then, based on the operating data collected by each surrounding vehicle and the current operating status data, a three-dimensional road model centered on the target vehicle is constructed. Finally, the three-dimensional road model is sent to the target vehicle so that the target vehicle can determine the operating status data for the next moment based on the three-dimensional road model and drive according to the operating status data for the next moment.

[0043] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0044] Figure 2 This application provides a vehicle driving assistance method according to an embodiment, such as... Figure 2 As shown, the vehicle driving assistance method provided in this embodiment uses an electronic device as the execution subject. Therefore, the vehicle driving assistance method provided in this embodiment includes the following steps:

[0045] Step 101: Obtain the current operating status data of the target vehicle and identify multiple surrounding vehicles adjacent to the target vehicle.

[0046] Among them, operational status data refers to data related to the vehicle's operational status, which can characterize the vehicle's operating condition. The operational status data of the target vehicle at the current moment may include the target vehicle's throttle acceleration, vehicle speed, steering wheel angle, and driving distance from surrounding vehicles.

[0047] Surrounding vehicles refer to vehicles adjacent to the target vehicle. This can be understood as vehicles detected by image acquisition devices and radar scans of the target vehicle. Image acquisition devices are typically installed around the target vehicle, for example, at the front, rear, left, and right. Therefore, surrounding vehicles refer to vehicles captured by image acquisition devices in these four directions. Image acquisition devices can be cameras.

[0048] Step 102: Obtain the operating data collected by each of the surrounding vehicles.

[0049] The operational data includes the surrounding vehicles and the operational status data of multiple adjacent vehicles. Adjacent vehicles refer to vehicles that are next to the surrounding vehicles; that is, adjacent vehicles are those detected by the image acquisition device and radar of the surrounding vehicles. As mentioned above, adjacent vehicles can be understood as vehicles captured by the image acquisition device in the four directions of front, rear, left, and right of the surrounding vehicles.

[0050] After obtaining the operational data collected by the surrounding vehicles, the electronic device essentially obtains not only the current operational status data of the target vehicle, but also the operational status data of multiple surrounding vehicles and multiple adjacent vehicles.

[0051] like Figure 3 The diagram shows the distribution of the target vehicle, surrounding vehicles, and adjacent vehicles. Vehicle 1 is the target vehicle, multiple vehicles 2 are surrounding vehicles, and multiple vehicles 3 are adjacent vehicles.

[0052] Step 103: Based on the aforementioned operational data and the operational status data at the current moment, construct a three-dimensional road model centered on the target vehicle.

[0053] The electronic device can construct a three-dimensional road model centered on the target vehicle based on the target vehicle's current operating status data, the operating status data of multiple surrounding vehicles, and the operating status data of multiple neighboring vehicles.

[0054] Step 104: The three-dimensional road model centered on the target vehicle is sent to the target vehicle so that the target vehicle can determine the operating status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the operating status data of the next moment.

[0055] In this process, after a three-dimensional road model centered on the target vehicle is sent to the target vehicle, the target vehicle can determine the current driving conditions around it and the operating status data for the next moment based on the three-dimensional road model centered on the target vehicle. The operating status data for the next moment determined by the three-dimensional road model centered on the target vehicle can effectively improve the driving safety of the target vehicle.

[0056] Optionally, the operational status data for the next moment includes the target vehicle's direction of travel and speed at the next moment.

[0057] Taking a rear-end collision as an example, suppose there are three vehicles, A, B, and C, positioned in front and behind each other in the same lane. When A brakes suddenly, according to traditional methods, B would typically begin braking when it detects a distance of 50 meters from A, and C would begin braking when it detects a distance of 50 meters from B. This short braking time easily leads to chain-reaction rear-end collisions. In this embodiment, when A brakes suddenly, C can use electronic devices to determine in advance that A is braking suddenly, based on B's operational status data and the operational status data of A collected by B. Furthermore, based on B's operational status data, the operational status data of A collected by B, and C's current operational status data, combined with a three-dimensional road model centered on the target vehicle, C can determine the target vehicle's operational status data for the next moment, facilitating timely avoidance of danger.

[0058] In this application, the current operating status data of the target vehicle and multiple surrounding vehicles adjacent to the target vehicle are acquired; operating data collected by each of the surrounding vehicles is acquired, including the operating status data of the surrounding vehicles and multiple adjacent vehicles; based on the operating data collected by each of the surrounding vehicles, the current operating status data, and a preset driving assistance algorithm, the operating status data of the target vehicle at the next moment is determined; and the operating status data at the next moment is sent to the target vehicle so that the target vehicle drives according to the operating status data at the next moment. The data obtained by the electronic device includes both the current operating status data collected by the target vehicle itself and the operating status data of multiple surrounding vehicles and adjacent vehicles. This operating status data has more dimensions than the original data, and a three-dimensional road model centered on the target vehicle can be constructed based on this operating status data, which can expand the target vehicle's perception range of the surrounding traffic conditions. Finally, a 3D road model centered on the target vehicle is sent to the target vehicle, enabling the target vehicle to determine its operating status data for the next moment based on the 3D road model centered on the target vehicle, and drive according to the operating status data for the next moment, thereby further improving the safety of vehicle driving.

[0059] As an alternative implementation method, such as Figure 4 As shown, in this embodiment, step 101, determining multiple surrounding vehicles adjacent to the target vehicle, includes the following steps:

[0060] Step 201: Acquire images of the target vehicle from multiple directions obtained by the image acquisition device.

[0061] The target vehicle is equipped with multiple image acquisition devices. For example, one image acquisition device can be installed in each of the four directions of the target vehicle: front, rear, left, and right. Therefore, after the target vehicle is started, images from multiple directions can be acquired through the image acquisition devices, and the image acquisition is done in real time.

[0062] The target vehicle uploads images from multiple directions captured by the image acquisition device to electronic devices in real time.

[0063] Step 202: Use an image recognition algorithm to identify the images from the multiple directions and obtain multiple license plate numbers.

[0064] After acquiring images of the target vehicle from multiple directions, the electronic device can use a pre-trained image recognition algorithm to perform image recognition on these images, thereby identifying multiple license plate numbers. To enable the image acquisition device to acquire images containing license plate numbers from the left and right sides of the target vehicle, the installation position of the image acquisition device can be adjusted so that it can capture images containing license plate numbers from both the left and right sides.

[0065] The specific process of using image recognition algorithms to identify license plate numbers is existing technology and will not be elaborated upon.

[0066] Step 203: Identify the vehicles corresponding to each license plate number as multiple surrounding vehicles adjacent to the target vehicle.

[0067] Among them, the vehicles corresponding to each license plate number are identified as multiple surrounding vehicles adjacent to the target vehicle.

[0068] In this embodiment, images of the target vehicle from multiple directions are acquired by an image acquisition device; an image recognition algorithm is used to identify the images from multiple directions to obtain multiple license plate numbers; and the vehicles corresponding to each license plate number are identified as multiple surrounding vehicles adjacent to the target vehicle. Because the electronic device uses an image recognition algorithm to identify license plate numbers to determine multiple surrounding vehicles, the accuracy of the electronic device in identifying multiple surrounding vehicles adjacent to the target vehicle can be improved.

[0069] In one embodiment, when the electronic device acquires multiple surrounding vehicles adjacent to the target vehicle, the target vehicle may also use a locally preset image recognition algorithm to perform image recognition on images from multiple directions acquired by each image acquisition device to obtain multiple license plate numbers; upload the multiple license plate numbers to the electronic device; after the electronic device receives them, it determines the corresponding vehicle based on each license plate number as multiple surrounding vehicles adjacent to the target vehicle.

[0070] In this embodiment, the target vehicle itself identifies the license plate number, which reduces the computing power burden on electronic devices.

[0071] As an optional implementation, in this embodiment, step 103 includes the following steps:

[0072] Step 301: Obtain the point cloud data of the target vehicle, the point cloud data of each of the surrounding vehicles, and the point cloud data of each of the neighboring vehicles to construct an initial three-dimensional road model.

[0073] At least one radar is installed on the target vehicle, surrounding vehicles, and adjacent vehicles. The point cloud data of the target vehicle, surrounding vehicles, and adjacent vehicles are obtained through radar scanning. The point cloud data carries three-dimensional coordinates. The initial three-dimensional road model constructed based on this point cloud data can be understood as constructing a three-dimensional map model centered on the target vehicle, including surrounding and adjacent vehicles.

[0074] Step 302: Input the aforementioned operating data and the current operating status data into the initial three-dimensional road model to obtain a three-dimensional road model centered on the target vehicle.

[0075] The target vehicle-centered 3D road model incorporates specific operational data into the initial 3D road model, including the target vehicle's operational status data, as well as the operational status data of surrounding and adjacent vehicles. Therefore, the target vehicle-centered 3D road model can directly reflect the driving conditions or road surface conditions around the target vehicle.

[0076] In this embodiment, point cloud data of the target vehicle, point cloud data of all surrounding vehicles, and point cloud data of all adjacent vehicles are acquired to construct an initial three-dimensional road model. The operational data and the current operational status data are then input into the initial three-dimensional road model to obtain a three-dimensional road model centered on the target vehicle. Since the three-dimensional road model centered on the target vehicle is composed of point cloud data of the target vehicle, all surrounding vehicles, and adjacent vehicles, combined with the corresponding operational status data, it accurately reflects the road surface traffic conditions.

[0077] As an optional implementation, in this embodiment, when the adjacent vehicle is a surrounding vehicle, the driving distance to each adjacent vehicle is measured by the ranging device of the target vehicle; when the adjacent vehicle is a neighboring vehicle, the driving distance to each adjacent vehicle is measured by the ranging device of the surrounding vehicle.

[0078] That is, the driving distance between the target vehicle and surrounding vehicles is measured by the ranging device on the target vehicle, and the driving distance between surrounding vehicles and adjacent vehicles is measured by the ranging device on the surrounding vehicles. The ranging device can be radar.

[0079] In this embodiment, the driving distance between the target vehicle and each surrounding vehicle can be measured by the distance measuring device of the target vehicle, and the driving distance between the surrounding vehicles and adjacent vehicles can be measured by the distance measuring device of the surrounding vehicles.

[0080] As an optional implementation, in this embodiment, the method further includes: acquiring real-time operating status data uploaded by each vehicle within a preset range, wherein the vehicles include the target vehicle and other vehicles besides the target vehicle.

[0081] The electronic devices can be in the cloud, which includes multiple cloud virtual machines and computing centers. Each vehicle uploads data to its corresponding cloud virtual machine. The target vehicle can be any vehicle within a preset range. Each vehicle within the preset range can be used as the target vehicle to determine its respective operating status data for the next moment.

[0082] The electronic equipment acquires real-time operational status data uploaded by each vehicle within a preset range. As mentioned above, the operational status data includes at least the throttle acceleration, vehicle speed, steering wheel angle, and driving distance of each vehicle to adjacent vehicles.

[0083] In this embodiment, by acquiring the real-time operating status data uploaded by each vehicle within a preset range, including the target vehicle and other vehicles, it is convenient to subsequently acquire the operating data collected by each surrounding vehicle.

[0084] Figure 5 This is a schematic diagram of the structure of a vehicle driving assistance device provided in an embodiment of this application, as shown below. Figure 5 As shown, the vehicle driving assistance device 40 provided in this embodiment is located in an electronic device. Therefore, the vehicle driving assistance device 40 provided in this embodiment includes: a running status data acquisition module 41, a running data acquisition module 42, a three-dimensional model construction module 43, and a running status transmission module 44, wherein:

[0085] The operation status data acquisition module 41 is used to acquire the current operation status data of the target vehicle, as well as multiple surrounding vehicles adjacent to the target vehicle.

[0086] The operation data acquisition module 42 is used to acquire the operation data collected by each of the surrounding vehicles. The operation data includes the surrounding vehicles and the operation status data of multiple adjacent vehicles adjacent to the surrounding vehicles.

[0087] The three-dimensional model construction module 43 is used to determine the operating status data of the target vehicle at the next moment based on the operating data collected by each of the surrounding vehicles, the operating status data at the current moment, and the preset driving assistance algorithm.

[0088] The running status sending module 44 is used to send the running status data of the next moment to the target vehicle so that the target vehicle drives according to the running status data of the next moment.

[0089] Optionally, the running status data acquisition module 41 is specifically used to: acquire images of the target vehicle from multiple directions obtained by the image acquisition device; identify the images from multiple directions using an image recognition algorithm to obtain multiple license plate numbers; and determine the vehicles corresponding to each license plate number as multiple surrounding vehicles adjacent to the target vehicle.

[0090] Optionally, the adjacent vehicles are surrounding vehicles or vehicles next to each other; the operating status data includes at least: throttle acceleration, vehicle speed, steering wheel angle, and driving distance to each adjacent vehicle.

[0091] Optionally, the 3D model construction module 43 is specifically used to: acquire point cloud data of the target vehicle, point cloud data of each of the surrounding vehicles, and point cloud data of each of the neighboring vehicles to construct an initial 3D road model; input each of the operating data and the operating status data at the current moment into the initial 3D road model to obtain a 3D road model centered on the target vehicle.

[0092] Optionally, the operating status data at the next moment includes: the target vehicle's driving direction and speed at the next moment.

[0093] Optionally, it also includes a real-time data acquisition module, used to: acquire real-time operating status data uploaded by each vehicle within a preset range, wherein the vehicles include the target vehicle and other vehicles besides the target vehicle.

[0094] Figure 6 This is a block diagram illustrating an electronic device according to an exemplary embodiment, the device being as follows: Figure 6 As shown, the electronic device includes: a memory 51 and a processor 52; the memory 51 is a memory for storing processor-executable instructions; the processor 52 is used to run computer programs or instructions to implement the vehicle driving assistance method provided in any of the above embodiments.

[0095] The memory 51 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions. The memory 51 may include high-speed RAM, and may also include non-volatile memory, such as at least one disk storage device.

[0096] The processor 52 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this disclosure.

[0097] Optionally, in specific implementations, if the memory 51 and processor 52 are implemented independently, then the memory 51 and processor 52 can be interconnected via bus 53 to complete mutual communication. Bus 53 can be an Industry Standard Architecture (ISA) bus 53, a Peripheral Component Interconnect (PCI) bus 53, or an Extended Industry Standard Architecture (EISA) bus 53, etc. Bus 53 can be divided into address bus 53, data bus 53, control bus 53, etc. For ease of representation, Figure 6 The bus 53 is represented by a single thick line, but this does not mean that there is only one bus 53 or only one type of bus 53.

[0098] Optionally, in a specific implementation, if the memory 51 and the processor 52 are integrated on a single chip, the memory 51 and the processor 52 can communicate with each other through an internal interface.

[0099] A non-transitory computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the vehicle driving assistance method of the electronic device.

[0100] The method includes:

[0101] The system acquires the current operating status data of the target vehicle and identifies multiple surrounding vehicles adjacent to the target vehicle, which are vehicles scanned by the target vehicle's image acquisition device and radar.

[0102] The operation data collected by each of the surrounding vehicles is obtained. The operation data includes the surrounding vehicles and the operation status data of multiple neighboring vehicles adjacent to the surrounding vehicles. The neighboring vehicles are the vehicles scanned by the image acquisition device and radar of the surrounding vehicles.

[0103] Based on the aforementioned operational data and the operational status data at the current moment, a three-dimensional road model centered on the target vehicle is constructed.

[0104] The three-dimensional road model centered on the target vehicle is sent to the target vehicle so that the target vehicle can determine the operating status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the operating status data of the next moment.

[0105] Optionally, determining the plurality of surrounding vehicles adjacent to the target vehicle includes:

[0106] Acquire images of the target vehicle from multiple directions using an image acquisition device;

[0107] Image recognition algorithms are used to identify images from the multiple directions to obtain multiple license plate numbers;

[0108] The vehicles corresponding to each of the aforementioned license plate numbers are identified as multiple surrounding vehicles adjacent to the target vehicle.

[0109] Optionally, the adjacent vehicles are surrounding vehicles or vehicles next to each other; the operating status data includes at least: throttle acceleration, vehicle speed, steering wheel angle, and driving distance to each adjacent vehicle.

[0110] Optionally, constructing a three-dimensional road model centered on the target vehicle based on the aforementioned operational data and the current operational status data includes:

[0111] The point cloud data of the target vehicle, the point cloud data of each of the surrounding vehicles, and the point cloud data of each of the neighboring vehicles are acquired to construct an initial three-dimensional road model.

[0112] The aforementioned operational data and the current operational status data are input into the initial three-dimensional road model to obtain a three-dimensional road model centered on the target vehicle.

[0113] Optionally, the operating status data at the next moment includes: the target vehicle's driving direction and speed at the next moment.

[0114] Optionally, the method further includes: acquiring real-time operating status data uploaded by each vehicle within a preset range, wherein the vehicles include the target vehicle and other vehicles besides the target vehicle.

[0115] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0116] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A vehicle driving assistance method characterized by comprising: The method includes: The system acquires the current operating status data of the target vehicle and identifies multiple surrounding vehicles adjacent to the target vehicle, which are vehicles scanned by the target vehicle's image acquisition device and radar. The operation data collected by each of the surrounding vehicles is obtained. The operation data includes the surrounding vehicles and the operation status data of multiple neighboring vehicles adjacent to the surrounding vehicles. The neighboring vehicles are the vehicles scanned by the image acquisition device and radar of the surrounding vehicles. The point cloud data of the target vehicle, the point cloud data of each of the surrounding vehicles, and the point cloud data of each of the neighboring vehicles are acquired to construct an initial three-dimensional road model. The aforementioned operational data and the current operational status data are input into the initial three-dimensional road model to construct a three-dimensional road model centered on the target vehicle. The three-dimensional road model centered on the target vehicle is sent to the target vehicle so that the target vehicle can determine the operating status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the operating status data of the next moment.

2. The method according to claim 1, characterized in that, The determination of multiple surrounding vehicles adjacent to the target vehicle includes: Acquire images of the target vehicle from multiple directions obtained by the image acquisition device; Image recognition algorithms are used to identify images from the multiple directions to obtain multiple license plate numbers; The vehicles corresponding to each of the aforementioned license plate numbers are identified as multiple surrounding vehicles adjacent to the target vehicle.

3. The method according to claim 2, characterized in that, Adjacent vehicles are those surrounding or adjacent to the vehicle; The operating status data includes at least: throttle acceleration, vehicle speed, steering wheel angle, and driving distance to each adjacent vehicle.

4. The method according to claim 2, characterized in that, The operational status data for the next moment includes: the target vehicle's direction of travel and speed at the next moment.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: The system acquires real-time operational status data uploaded by each vehicle within a preset range, including the target vehicle and other vehicles.

6. A vehicle driving assistance device, characterized in that, The device includes: The operation status data acquisition module is used to acquire the current operation status data of the target vehicle and identify multiple surrounding vehicles adjacent to the target vehicle. The surrounding vehicles are vehicles scanned by the image acquisition device and radar of the target vehicle. The operation data acquisition module is used to acquire the operation data collected by each of the surrounding vehicles. The operation data includes the surrounding vehicles and the operation status data of multiple neighboring vehicles adjacent to the surrounding vehicles. The neighboring vehicles are the vehicles scanned by the image acquisition device and radar of the surrounding vehicles. The three-dimensional model construction module is used to acquire the point cloud data of the target vehicle, the point cloud data of each of the surrounding vehicles, and the point cloud data of each of the adjacent vehicles, so as to construct an initial three-dimensional road model. The aforementioned operational data and the current operational status data are input into the initial three-dimensional road model to construct a three-dimensional road model centered on the target vehicle. The running status sending module is used to send the three-dimensional road model centered on the target vehicle to the target vehicle, so that the target vehicle can determine the running status data of the next moment based on the three-dimensional road model centered on the target vehicle, and drive according to the running status data of the next moment.

7. An electronic device, comprising: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-5.

9. A computer program product comprising a computer program that, when executed by a processor, implements the method of any one of claims 1-5.

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