Output path planning method and device and electronic equipment

Abstract

The invention provides an output path planning method and device and electronic equipment. The method comprises the steps that positioning pose data and environment data of a current vehicle are acquired; compiling the positioning pose data and the environment data into a description text; and compiling the description text into a visual language text, and obtaining a path planning output result according to the visual language text. In the invention, the visual language text can be directly output as a path planning output result. According to the method, the calculation of the path planning can be realized through multiple dimensions, so that the accuracy of the path planning is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a method, device and electronic device for outputting path planning. Background Art

[0002] At present, the intelligent driving technology of vehicles has been developed rapidly, and some vehicles can already realize intelligent driving in simple road environments, such as intelligent driving on highways with fewer vehicles.

[0003] In the scenario of intelligent driving, the vehicle needs to combine various types of sensors and processors to complete the perception and calculation of the vehicle's surrounding environment. Then, the vehicle's path planning can be realized through environmental perception data, navigation data, and positioning posture data. The current mainstream path planning solution is to select a planned path from many path plans through post-processing algorithms. The planned path selected here can be the global optimal, maximum probability, or maximum safety, etc.

[0004] However, current path planning is obtained according to a post-processing algorithm. This path planning method uses fewer latitudes, resulting in inaccurate final path planning results. Summary of the invention

[0005] The present application provides a method, device and electronic device for outputting path planning, which are used to calculate path planning in multiple dimensions, thereby improving the accuracy of path planning.

[0006] In a first aspect, the present application provides a method for outputting a path plan, the method comprising:

[0007] Acquire the current vehicle positioning posture data and environmental data, wherein the environmental data at least includes high-precision map data and navigation data;

[0008] Compiling the positioning posture data and the environment data into a description text, wherein the description text is text data describing the current vehicle surrounding environment;

[0009] The description text is compiled into a visual language text, and a path planning output result is obtained according to the visual language text.

[0010] Based on this method, visual language text can be directly used as the path planning output result, thereby realizing the calculation of path planning in multiple dimensions, thereby improving the accuracy of path planning.

[0011] In an optional embodiment, compiling the positioning posture data and the environment data into a description text includes:

[0012] Extracting posture keywords representing the current vehicle posture from the positioning posture data, and using the posture keywords as the target words;

[0013] Extracting a location keyword representing the current vehicle location from the high-precision map data, and using the location keyword as the map word;

[0014] Extracting a navigation keyword including the current vehicle destination from the navigation data, and using the navigation keyword as the navigation word;

[0015] The target word, the map word, and the navigation word are arranged into text to generate the description text. In an optional embodiment, the description text is compiled into a visual language text, including:

[0016] Importing the target word, the map word, and the navigation word into the visual language coding model for compilation, respectively obtaining environment words, behavior words, and result words, wherein the environment words are used to describe the environment around the current vehicle, the behavior words are used to describe the behavior of the current vehicle, and the result words are used to describe the relationship between the environment words and the behavior words;

[0017] The environment words, the behavior words and the result words are imported into the visual language model for text arrangement, so as to generate the visual language text including the environment words, the behavior words and the result words.

[0018] In an optional embodiment, compiling the description text into a visual language text, and obtaining a path planning output result according to the visual language text, includes:

[0019] Calculating the attention between different types of words in the visual language text by using an attention algorithm;

[0020] Based on the attention between the different types of words, the different types of words in the visual language text are rewritten and arranged to obtain an output language text, and the output language text is used as the path planning output result.

[0021] In an optional embodiment, rewriting and arranging each type of word in the visual language text based on the attention between each type of words to obtain an output language text includes:

[0022] Acquire the driving mode of the current vehicle and generate a mode text corresponding to the driving mode;

[0023] Based on the attention between the various types of words and the pattern text, the various types of words in the visual language text are rewritten and arranged to obtain an output language text containing the pattern text.

[0024] In a second aspect, the present application provides a device for outputting a path plan, the device comprising:

[0025] An acquisition unit, used to acquire the current vehicle positioning posture data and environmental data, wherein the environmental data at least includes high-precision map data and navigation data;

[0026] A description text compiling unit, used to compile the positioning posture data and the environment data into a description text, wherein the description text is text data describing the surrounding environment of the current vehicle;

[0027] A processing unit is used to compile the description text into a visual language text and obtain a path planning output result according to the visual language text.

[0028] In an optional embodiment, the description text compilation unit is specifically used to

[0029] Extracting posture keywords representing the current vehicle posture from the positioning posture data, and using the posture keywords as the target words;

[0030] Extracting a location keyword representing the current vehicle location from the high-precision map data, and using the location keyword as the map word;

[0031] Extracting a navigation keyword including the current vehicle destination from the navigation data, and using the navigation keyword as the navigation word;

[0032] The target word, the map word, and the navigation word are arranged into text format to generate the description text.

[0033] In an optional embodiment, the processing unit is specifically used to calculate the attention between each type of words in the visual language text through an attention algorithm;

[0034] Based on the attention between the different types of words, the different types of words in the visual language text are rewritten and arranged to obtain an output language text, and the output language text is used as the path planning output result.

[0035] In a third aspect, the present application provides an electronic device, including:

[0036] Memory, used to store computer programs;

[0037] The processor is used to implement the method steps of outputting path planning described in any of the above methods when executing the computer program stored in the memory.

[0038] In a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method steps of outputting path planning described in any of the above methods are implemented.

[0039] For each aspect from the second to the fourth aspect and the technical effects that may be achieved by each aspect, please refer to the above description of the technical effects that can be achieved by the first aspect or various possible schemes in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of a method for outputting path planning provided in this application;

[0041] Figure 2 A schematic diagram of the architecture of a path planning output system provided in this application;

[0042] Figure 3 Schematic diagram of the path planning display interface provided for this application;

[0043] Figure 4 A schematic diagram of the structure of a device for outputting path planning is provided for this application;

[0044] Figure 5 A schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The specific operating methods in the method embodiments can also be applied to device embodiments or system embodiments. It should be noted that in the description of the present application, "multiple" is understood as "at least two". "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A is connected to B, which can represent: A is directly connected to B and A is connected to B through C. In addition, in the description of the present application, words such as "first" and "second" are only used to distinguish the purpose of description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0046] The embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0047] At present, the intelligent driving technology of vehicles has been developed rapidly, and some vehicles can already realize intelligent driving in simple road environments, such as intelligent driving on highways with fewer vehicles.

[0048] In the scenario of intelligent driving, the vehicle needs to combine various types of sensors and processors to complete the perception and calculation of the vehicle's surrounding environment. Then, the vehicle's path planning can be realized through environmental perception data, navigation data, and positioning posture data. The current mainstream path planning solution is to select a planned path from many path plans through post-processing algorithms. The planned path selected here can be the global optimal, maximum probability, or maximum safety, etc.

[0049] However, current path planning is obtained according to a post-processing algorithm. This path planning method uses fewer latitudes, resulting in inaccurate final path planning results.

[0050] In order to solve the above technical problems, a method for outputting path planning is provided in an embodiment of the present application. In this method, the positioning posture data and environmental data of the current vehicle are first obtained, the positioning posture data and environmental data are compiled into a description text, the description text is compiled into a visual language text, and the path planning output result is obtained according to the visual language text. Through this method, path planning calculations can be performed in multiple dimensions such as vehicle data, positioning posture data, and environmental data, thereby ensuring that the path planning output result output in text form is more accurate.

[0051] Reference Figure 1 The figure is a flow chart of a method for outputting path planning provided by an embodiment of the present application, the method comprising:

[0052] S1, obtaining the current vehicle positioning posture data and environmental data;

[0053] Specifically, a method for outputting path planning provided in an embodiment of the present application can be applied to Figure 2 In the system architecture shown, the system architecture includes: a description text generation module, a text analysis module (not shown in the figure), a visual language text compilation module, and an attention calculation module.

[0054] The description text generation module is used to generate description text by encoding the input signal;

[0055] A text analysis module is used to analyze the input signal and extract different words from the input data signal;

[0056] The visual language text compilation module is used to compile the description text into visual language text.

[0057] Specifically, the system first obtains input data, which includes the current vehicle's positioning posture and the environmental data of the current vehicle's location. The environmental data here at least includes high-precision map data and navigation data. The high-precision map data can be a local high-precision map vector fragment, through which the local high-precision map around the current vehicle's location can be determined.

[0058] Of course, in addition to high-precision map data and navigation data, the environmental data may also include 3D occupied area data, which can accurately determine the location of the vehicle target and the area occupancy status.

[0059] In addition, in an embodiment of the present application, in addition to the high-precision map data, navigation data, and 3D occupied area data introduced above, other data related to the current vehicle may also be added to the environmental data, which will not be illustrated one by one here.

[0060] S2, compiles the positioning posture data and environmental data into description text;

[0061] In the embodiment of the present application, after obtaining the positioning posture data and the environmental data, the positioning posture data and the environmental data are firstly subjected to language analysis, and then posture keywords representing the current vehicle posture are extracted from the positioning posture data, and the posture keywords can be one word or multiple words, which are not limited here, and then the posture keywords are used as target words. The target words describe the current vehicle posture state.

[0062] By performing language analysis on the high-precision map data in the environmental data, location keywords representing the current vehicle location are extracted from the high-precision map data. The keyword extraction method here can be based on an existing text recognition method or can be implemented through a neural network model for keyword extraction. The extracted location keywords are then used as map words, which describe the map data of the current vehicle, such as surrounding vehicles, surrounding pedestrians, distance to surrounding vehicles, distance to pedestrians, etc.

[0063] By performing language analysis on the navigation data, the navigation keywords containing the current vehicle destination are extracted from the navigation data. The extraction method here can be based on the navigation data input by the user, such as the starting place and destination input, etc., and the navigation keywords can be extracted through the generated navigation path data, and then the navigation keywords are used as navigation words. The navigation words represent the navigation related information of the current vehicle, such as the starting position and end position of the current vehicle, the current vehicle driving path, etc. It should be noted here that the navigation word may not be a single keyword, but may be composed of multiple keywords, and the content contained in the navigation word is not limited here.

[0064] The above-mentioned target words, map words and navigation words describe the current driving status of the vehicle and the current status of the vehicle's surrounding environment, such as the vehicle's position, direction, speed, lane, nearby vehicles, nearby pedestrians, etc.

[0065] Of course, according to Figure 2 In the system shown, in addition to language analysis of positioning posture data, high-precision maps, and navigation data, language analysis can also be performed on other data to obtain other words. Figure 2 It also includes other words, such as the current vehicle's driving mode, operating status, and so on.

[0066] After obtaining the above-mentioned target words, map words, navigation words and other words through language analysis, the first step is to determine the relevance between the target words, map words and navigation words, which can be obtained by calculating the relevance between words. Then, based on the result of the relevance calculation, the target words, map words and navigation words are re-arranged. Of course, connecting words are added in the arrangement process to ensure the formation of a complete description text. Therefore, a description text is generated based on the target words, map words and navigation words. For example, the description text can be: "At the intersection 200 meters ahead, there are two cars around, and the distances from me are 10 meters and 50 meters respectively in an open area. There is an obvious dotted line on the ground that can be changed into a lane." In this way, the description text of the situation around the vehicle can be accurately obtained.

[0067] S3, compiles the description text into visual language text, and obtains the path planning output result according to the visual language text.

[0068] parameter Figure 2 In the system architecture shown, after the description text generation module generates the description text, the description text will be imported into the visual language text compilation model, and then the target words, map words and navigation words in the description text will be recompiled into environment words, behavior words and result words through the visual language text compilation model. Figure 2 In the context, the environment words and behavior words can be collectively referred to as state words.

[0069] Then, the environment words, behavior words and result words are imported into the visual language model. The visual language model mainly re-arranges the text of each type of words, thereby arranging the environment words, behavior words and result words into another text, which is the visual language text.

[0070] It should be noted here that environment words are used to describe the environment around the current vehicle, behavior words are used to describe the behavior of the current vehicle, and result words are used to describe the relationship between environment words and behavior words. Therefore, the visual language text is composed of environment words, behavior words and result words. In an embodiment of the present application, the visual language text can be directly output as a path planning output result. In this way, the calculation of path planning can be realized through multiple dimensions, thereby improving the accuracy of path planning.

[0071] In addition, the above method mainly performs language analysis and processing on the data, and no longer requires the CPU to perform calculations, thereby eliminating the data transmission between the CPU and the GPU (English full name: Graphic Processing Unit, Chinese name: Graphics Processing Unit), realizing efficient on-chip computing under the full GPU, and reducing the text of data transmission.

[0072] In an embodiment of the present application, in addition to outputting the path planning results, the attention mechanism algorithm can also obtain the expected behavior data, vehicle speed signal, and turning angle signal of the current vehicle. Of course, which signals need to be obtained can be set according to the actual application scenario, and examples will not be given one by one here.

[0073] Furthermore, in an embodiment of the present application, in order to improve the accuracy of the final output path planning result, after obtaining the visual language text, each type of word in the visual language text is decomposed and analyzed, and then the attention algorithm is used to calculate the attention between each type of words in the visual language text, and the attention represents the correlation between the words.

[0074] Based on the attention between different types of words, different types of words in the visual language text are rewritten and arranged to obtain output language text, and the output language text is used as the path planning output result.

[0075] That is to say, the attention mechanism can determine the correlation between words, and then the order between words can be determined through this correlation, so as to rearrange the words in the visual language text and obtain the final output result.

[0076] For example, Figure 3As shown, vehicle A is the current vehicle positioning posture, vehicle B is the position of other road participants and the possibility of a future section, and the gray area on the ground is the high-precision map and standard map points. Taking the current moment as an example, the final path planning output result can be described as: "The vehicle is currently at an intersection, and the standard map navigation tells me to go straight. There is a vehicle in front of me, driving in a straight line at a speed of 30km / h. There is also a vehicle on the left that is driving in a straight line at a speed of 30km / h. Lane changing is not allowed on the right. If recommended in a safe way, the vehicle recommends going straight and following the vehicle at 25km / h."

[0077] From the above examples, it can be seen that after analyzing and processing the positioning posture data, navigation data and map data, the final output result is the path planning output result of the visual language text, and after adding the analysis and processing of the attention mechanism, the correlation between each word can be made higher, thereby making the final output path planning result more accurate.

[0078] Furthermore, in an embodiment of the present application, when calculating the attention between different types of words through the attention mechanism, other information about the current vehicle, such as the driving mode of the vehicle, can also be added. Therefore, after obtaining the driving mode of the current vehicle, a mode text corresponding to the driving mode is generated, such as: aggressive mode, steady mode, safe mode, etc. Based on the attention between different types of words and the mode text, the different types of words in the visual language text are rewritten and arranged to obtain an output language text containing the mode text. In this way, other information can be added to the final path planning output result, so that the final path planning output result is more in line with the driver's driving habits and improves the driver's experience.

[0079] Based on the same inventive concept, a device for outputting path planning is also provided in the embodiment of the present application, referring to Figure 4 The figure is a schematic diagram of a device structure for outputting path planning provided in an embodiment of the present application, the device comprising:

[0080] The acquisition unit 401 is used to acquire the positioning posture data and environmental data of the current vehicle, wherein the environmental data at least includes high-precision map data and navigation data;

[0081] A description text compiling unit 402, used to compile the positioning posture data and the environment data into a description text, wherein the description text is text data describing the current vehicle surrounding environment;

[0082] The processing unit 403 is used to compile the description text into a visual language text, and obtain a path planning output result according to the visual language text.

[0083] In an optional embodiment, the description text compiling unit 402 is specifically configured to

[0084] Extracting posture keywords representing the current vehicle posture from the positioning posture data, and using the posture keywords as the target words;

[0085] Extracting a location keyword representing the current vehicle location from the high-precision map data, and using the location keyword as the map word;

[0086] Extracting a navigation keyword including the current vehicle destination from the navigation data, and using the navigation keyword as the navigation word;

[0087] The target word, the map word, and the navigation word are arranged into text format to generate the description text.

[0088] In an optional embodiment, the processing unit 403 is specifically configured to calculate the attention between each type of words in the visual language text by using an attention algorithm;

[0089] Based on the attention between the different types of words, the different types of words in the visual language text are rewritten and arranged to obtain an output language text, and the output language text is used as the path planning output result.

[0090] Based on the same inventive concept, an electronic device is also provided in an embodiment of the present application, and the electronic device can realize the function of the aforementioned device for outputting path planning, referring to Figure 5 , the electronic device comprises:

[0091] At least one processor 501, and a memory 502 connected to the at least one processor 501. The specific connection medium between the processor 501 and the memory 502 is not limited in the embodiment of the present application. Figure 5 In the example, the processor 501 and the memory 502 are connected via a bus 500. The bus 500 is Figure 5 The connections between other components are shown in bold lines, and are not intended to be limiting. The bus 500 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. Alternatively, the processor 501 can also be called a controller, and there is no limitation on the name.

[0092] In the embodiment of the present application, the memory 502 stores instructions that can be executed by at least one processor 501. The at least one processor 501 can execute the method of outputting path planning discussed above by executing the instructions stored in the memory 502. The processor 501 can implement Figure 4 The functions of each module in the device shown.

[0093] Among them, the processor 501 is the control center of the device, and can use various interfaces and lines to connect the various parts of the entire control device. By running or executing instructions stored in the memory 502 and calling data stored in the memory 502, the various functions of the device and processing data, the device can be monitored as a whole.

[0094] In one possible design, the processor 501 may include one or more processing units, and the processor 501 may integrate an application processor and a modem processor, wherein the application processor mainly processes an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the modem processor may not be integrated into the processor 501. In some embodiments, the processor 501 and the memory 502 may be implemented on the same chip, and in some embodiments, they may also be implemented separately on separate chips.

[0095] The processor 501 may be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and may implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of a method for outputting path planning disclosed in the embodiments of the present application may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0096] The memory 502 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 502 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (Random Access Memory, RAM), a static random access memory (Static Random Access Memory, SRAM), a programmable read-only memory (Programmable Read Only Memory, PROM), a read-only memory (Read Only Memory, ROM), an electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a magnetic memory, a disk, an optical disk, etc. The memory 502 is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 502 in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0097] By programming the processor 501, the code corresponding to the method for outputting the path planning described in the above embodiment can be fixed into the chip, so that the chip can execute the code when running. Figure 1 The steps of a method for outputting path planning in the embodiment shown are as follows: How to design and program the processor 501 is a technique known to those skilled in the art and will not be described in detail here.

[0098] Based on the same inventive concept, an embodiment of the present application further provides a storage medium, which stores computer instructions. When the computer instructions are executed on a computer, the computer executes a method for outputting path planning discussed above.

[0099] In some possible implementations, various aspects of a method for outputting path planning provided by the present application may also be implemented in the form of a program product, which includes a program code. When the program product is run on an apparatus, the program code is used to enable the control device to execute the steps of a method for outputting path planning according to various exemplary implementations of the present application described above in this specification.

[0100] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0101] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0102] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0103] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0104] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for outputting path planning, It is characterized in that The method comprises: Acquire the current vehicle positioning posture data and environmental data, wherein the environmental data at least includes high-precision map data and navigation data; Compiling the positioning posture data and the environment data into a description text, wherein the description text is text data describing the current vehicle surrounding environment; The description text is compiled into a visual language text, and a path planning output result is obtained according to the visual language text.

2. The method according to claim 1, It is characterized in that Compiling the positioning posture data and the environment data into a description text includes: Extracting posture keywords representing the current vehicle posture from the positioning posture data, and using the posture keywords as the target words; Extracting a location keyword representing the current vehicle location from the high-precision map data, and using the location keyword as the map word; Extracting a navigation keyword including the current vehicle destination from the navigation data, and using the navigation keyword as the navigation word; The target word, the map word, and the navigation word are arranged into text format to generate the description text.

3. The method according to claim 2, It is characterized in that Compiling the description text into visual language text, including: Importing the target word, the map word, and the navigation word into a visual language text encoding model for compilation, respectively obtaining environment words, behavior words, and result words, wherein the environment words are used to describe the environment around the current vehicle, the behavior words are used to describe the behavior of the current vehicle, and the result words are used to describe the relationship between the environment words and the behavior words; The environment words, the behavior words and the result words are imported into the visual language model for text arrangement to generate the visual language text containing the environment words, the behavior words and the result words.

4. The method according to claim 1, It is characterized in that Compiling the description text into a visual language text, and obtaining a path planning output result according to the visual language text, including: Calculating the attention between different types of words in the visual language text by using an attention algorithm; Based on the attention between the different types of words, the different types of words in the visual language text are rewritten and arranged to obtain an output language text, and the output language text is used as the path planning output result.

5. The method according to claim 4, It is characterized in that Rewriting and arranging each type of word in the visual language text based on the attention between each type of word to obtain an output language text, including: Acquire the driving mode of the current vehicle and generate a mode text corresponding to the driving mode; Based on the attention between the various types of words and the pattern text, the various types of words in the visual language text are rewritten and arranged to obtain an output language text containing the pattern text.

6. A device for outputting path planning, It is characterized in that The device comprises: An acquisition unit, used to acquire the current vehicle positioning posture data and environmental data, wherein the environmental data at least includes high-precision map data and navigation data; A description text compiling unit, used to compile the positioning posture data and the environment data into a description text, wherein the description text is text data describing the surrounding environment of the current vehicle; A processing unit is used to compile the description text into a visual language text and obtain a path planning output result according to the visual language text.

7. The device according to claim 6, It is characterized in that The description text compilation unit is specifically used for Extracting posture keywords representing the current vehicle posture from the positioning posture data, and using the posture keywords as the target words; Extracting a location keyword representing the current vehicle location from the high-precision map data, and using the location keyword as the map word; Extracting a navigation keyword including the current vehicle destination from the navigation data, and using the navigation keyword as the navigation word; The target word, the map word, and the navigation word are arranged into text format to generate the description text.

8. The device according to claim 6, It is characterized in that The processing unit is specifically used to calculate the attention between different types of words in the visual language text through an attention algorithm; Based on the attention between the different types of words, the different types of words in the visual language text are rewritten and arranged to obtain an output language text, and the output language text is used as the path planning output result.

9. An electronic device, It is characterized in that include: Memory, used to store computer programs; A processor, configured to implement the method steps of any one of claims 1 to 5 when executing the computer program stored in the memory.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in any one of claims 1 to 5 are implemented.

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