A method and device for developing a vehicle function, an electronic device, and a storage medium

Abstract

The application relates to a vehicle function development method and device, electronic equipment and a storage medium. The method comprises the following steps: in the case that function requirement information for vehicle design is received, a technical specification prompt word template of a function component corresponding to the function requirement information is acquired; the function requirement information and the technical specification prompt word template are input into a pre-trained function analysis model to obtain vehicle atomic functions and vehicle scene functions contained in the function requirement information; the vehicle atomic functions and the vehicle scene functions are respectively stored in corresponding databases, and an association relationship between the vehicle atomic functions and the vehicle scene functions in the databases is constructed to develop vehicle functions corresponding to the function requirement information based on the association relationship. Therefore, the efficiency and accuracy of vehicle function development can be greatly improved, and the requirement communication cost and development iteration period are reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, and particularly relates to a development method and device of vehicle functions, an electronic device and a storage medium. BACKGROUND

[0002] In the field of vehicles, with the continuous iteration and update of vehicles, the vehicle cabin is becoming more and more intelligent, and the cabin functions are not only multiple but also can be updated like Internet products. Therefore, in the process of function design and development of the intelligent cabin, there are a large amount of function requirement information, such as function requirement ideas provided by different function developers or a large amount of function requirement documents. This results in that in the actual development process, the function developers need to analyze a large amount of function requirement information and determine the vehicle functions to be developed.

[0003] The above method not only requires the function developers to pay a large communication cost, but also is prone to cause unclear function requirements due to the dependence on manual experience, and cannot accurately develop the vehicle functions. SUMMARY

[0004] The present application provides a development method and device of vehicle functions, an electronic device and a storage medium, to solve the technical problem that in the prior art, when developing vehicle functions, the function developers need to pay a large communication cost, and due to the dependence on manual experience, the determined function requirements are prone to be unclear and the vehicle functions cannot be accurately developed.

[0005] In a first aspect, the present application provides a development method of vehicle functions, and the method comprises:

[0006] In the case that function requirement information for vehicle design is received, a technical specification prompt word template of a function component corresponding to the function requirement information is acquired;

[0007] The function requirement information and the technical specification prompt word template are input into a pre-trained function analysis model, to obtain vehicle atomic functions and vehicle scene functions contained in the function requirement information; wherein the vehicle atomic function is an indivisible minimum function unit, and the scene function is obtained by combining at least two vehicle atomic functions;

[0008] The vehicle atomic functions and the vehicle scene functions are respectively stored in respective corresponding databases, and an association relationship between the vehicle atomic functions and the vehicle scene functions in the databases is constructed, to develop vehicle functions corresponding to the function requirement information based on the association relationship;

[0009] The vehicle atomic functions and the vehicle scene functions are respectively stored in respective corresponding databases, and an association relationship between the vehicle atomic functions and the vehicle scene functions in the databases is constructed, to develop vehicle functions corresponding to the function requirement information based on the association relationship;

[0010] determining whether a target vehicle atomic function identical to the vehicle atomic function exists in an atomic function database corresponding to the vehicle atomic function, and determining whether a target vehicle scene function identical to the vehicle scene function exists in a scene function database corresponding to the vehicle scene function;

[0011] in a case where it is determined that the target vehicle atomic function does not exist, storing the vehicle atomic function into the atomic function database;

[0012] in a case where it is determined that the target vehicle scene function does not exist, storing the vehicle scene function into the scene function database.

[0013] As an optional implementation, the received function requirement information for vehicle design includes:

[0014] in a case where the function requirement text is received, determining the function requirement text as the received function requirement information for vehicle design;

[0015] or,

[0016] in a case where the function requirement voice signal is received, determining the function requirement voice signal as the received function requirement information for vehicle design.

[0017] As an optional implementation, the technical specification prompt word template corresponding to the function requirement information is obtained, including:

[0018] determining a function component corresponding to the function requirement information, and determining a vehicle sub-technical field to which the function component belongs;

[0019] obtaining a technical specification prompt word template corresponding to the vehicle sub-technical field.

[0020] As an optional implementation, the function requirement information and the technical specification prompt word template are input into a pre-trained function analysis model to obtain vehicle atomic functions and vehicle scene functions contained in the function requirement information, including:

[0021] embedding the function requirement information into the technical specification prompt word template to obtain a function requirement analysis instruction;

[0022] inputting the function requirement analysis instruction into the pre-trained function analysis model to obtain the vehicle atomic functions and the vehicle scene functions contained in the function requirement information.

[0023] As an optional implementation, the determination of whether a target vehicle atomic function identical to the vehicle atomic function exists in an atomic function database corresponding to the vehicle atomic function includes:

[0024] determine an atomic text similarity between each atomic function in the atomic function database and the vehicle atomic function, to obtain a plurality of atomic text similarities;

[0025] determine whether there is a first target atomic text similarity greater than a first preset threshold in the plurality of atomic text similarities;

[0026] In a case where it is determined that there is no first target atomic text similarity, it is determined that there is no target vehicle atomic function in the atomic function database.

[0027] As an optional implementation, the method further comprises:

[0028] In a case where it is determined that there is at least one first target atomic text similarity, it is determined whether there is a second target atomic text similarity greater than a second preset threshold in the first target atomic text similarity; the second preset threshold is greater than the first preset threshold.

[0029] In a case where it is determined that there is a second target atomic text similarity, it is determined that there is a target vehicle atomic function in the atomic function database.

[0030] In a case where it is determined that there is no second target atomic text similarity, it is determined whether there is a target vehicle atomic function in an atomic function corresponding to the first target atomic text similarity based on a preset semantic analysis model.

[0031] As an optional implementation, determining whether there is a target vehicle atomic function in an atomic function corresponding to the first target atomic text similarity based on a preset semantic analysis model comprises:

[0032] For each atomic function corresponding to a first target atomic text similarity, the atomic function and the vehicle atomic function are input into a preset semantic analysis template to obtain a semantic analysis instruction.

[0033] The semantic analysis instruction is input into a pre-trained semantic analysis model to obtain a semantic analysis result of whether the atomic function and the vehicle atomic function are duplicated.

[0034] In a case where the semantic analysis results of all atomic functions corresponding to the first target atomic text similarity are not duplicated, it is determined that there is no target vehicle atomic function.

[0035] In a case where the semantic analysis result of at least one atomic function corresponding to the first target atomic text similarity is duplicated, it is determined that there is a target vehicle atomic function.

[0036] As an optional implementation manner, the determining whether the target vehicle scene function identical to the vehicle scene function exists in the scene function database corresponding to the vehicle scene function comprises:

[0037] The scene text similarity between each scene function in the scene function database and the vehicle scene function is determined, to obtain a plurality of scene text similarities;

[0038] It is determined whether there is a first target scene text similarity greater than a first preset threshold in the plurality of scene text similarities;

[0039] In a case where it is determined that the first target scene text similarity does not exist, it is determined that the target vehicle scene function does not exist in the scene function database.

[0040] As an optional implementation manner, the method further comprises:

[0041] In a case where it is determined that at least one first target scene text similarity exists, it is determined from the first target scene text similarity whether there is a second target scene text similarity greater than a second preset threshold;

[0042] In a case where it is determined that the second target scene text similarity exists, it is determined that the target vehicle scene function exists in the scene function database;

[0043] In a case where it is determined that the second target scene text similarity does not exist, it is determined, based on a preset semantic analysis model, whether the target vehicle scene function exists in a scene function corresponding to the first target scene text similarity.

[0044] As an optional implementation manner, the determining, based on the preset semantic analysis model, whether the target vehicle scene function exists in the scene function corresponding to the first target scene text similarity comprises:

[0045] For each scene function corresponding to a first target scene text similarity, the scene function and the vehicle scene function are input into a preset semantic analysis template to obtain a semantic analysis instruction;

[0046] The semantic analysis instruction is input into a pre-trained semantic analysis model to obtain a semantic analysis result of whether the scene function and the vehicle scene function are repetitive;

[0047] In a case where the semantic analysis results of all scene functions corresponding to the first target scene text similarities are not repetitive, it is determined that the target vehicle scene function does not exist;

[0048] In a case where the semantic analysis result of the at least one first target scene text similarity corresponding scene function is repetition, it is determined that the target vehicle scene function exists.

[0049] As an optional implementation, the vehicle atomic function has a corresponding referenced identifier list in the corresponding atomic function database, and the vehicle scene function has a corresponding reference identifier list in the corresponding scene function database; the referenced identifier list is used to record the scene identifier of the vehicle scene function referencing the corresponding vehicle atomic function, and the reference identifier list is used to record the atomic identifier of the vehicle atomic function referenced by the corresponding vehicle scene function.

[0050] The association relationship between the vehicle atomic function and the vehicle scene function in the database is constructed, including:

[0051] The atomic function database and the scene function database are input into a pre-trained association relationship determination model to obtain an association relationship list between the vehicle atomic function of the atomic function database and the vehicle scene function of the scene function database.

[0052] According to the association relationship list, the referenced identifier list of the vehicle atomic function in the atomic function database is updated, and the reference identifier list of the vehicle scene function in the scene function database is updated.

[0053] As an optional implementation, the vehicle atomic function in the atomic function database further includes a reference times identifier, and the reference times identifier is used to record the number of times the corresponding vehicle atomic function is referenced by the scene vehicle function; the method further includes:

[0054] According to the reference times identifier corresponding to each vehicle atomic function, a priority corresponding to each vehicle atomic function is determined.

[0055] In a case where a function development recommendation instruction is received, the vehicle atomic function with the highest priority is output.

[0056] As an optional implementation, after the association relationship between the vehicle atomic function and the vehicle scene function in the database is constructed, the method further includes:

[0057] It is determined whether a target vehicle scene function that does not reference any vehicle atomic function exists in the scene function database.

[0058] In a case where the target vehicle scene function exists, the target vehicle scene function is deleted.

[0059] As an optional implementation, after the association relationship between the vehicle atomic function and the vehicle scene function in the database is constructed, the method further includes:

[0060] Upon receiving a query instruction or export instruction, a functional requirements document is generated based on the aforementioned relationship. The functional requirements document includes vehicle atomic functions, vehicle scenario functions, and the relationship between the two.

[0061] Output the aforementioned functional requirements document.

[0062] As an optional implementation, after establishing the association between the vehicle atomic functions and the vehicle scene functions in the database, the following is also included:

[0063] Upon receiving a modification instruction, the atomic function database and the scenario function database are backed up to the backup database;

[0064] The atomic function database and / or the scenario function database are updated according to the modification instructions;

[0065] Determine whether there are any abnormal functions in the updated atomic function database and / or scenario function database. The abnormal functions include functions with abnormal relationships and / or functions with abnormal function categories.

[0066] If the abnormal function is confirmed to exist, the atomic function database and / or the scenario function database shall be restored based on the backup database.

[0067] As an optional implementation, the method further includes:

[0068] Determine the number of new vehicle atomic functions to be added within a preset time period;

[0069] When the number exceeds a preset threshold, the atomic function database and the scene function database are respectively input into a pre-trained semantic analysis model to obtain similar vehicle atomic functions in the atomic function database with a similarity greater than a first preset similarity threshold and similar vehicle scene functions in the scene function database with a similarity greater than a second preset similarity threshold.

[0070] The atomic functions of the same type of vehicle and the scene functions of the same type of vehicle are deduplicated respectively.

[0071] Secondly, this application provides a vehicle function development apparatus, the apparatus comprising:

[0072] The prompt word template acquisition module is used to acquire the technical specification prompt word template of the functional component corresponding to the functional requirement information when receiving functional requirement information for vehicle design.

[0073] The functional analysis module is used to input the functional requirement information and the technical specification prompt word template into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions contained in the functional requirement information; wherein, the vehicle atomic function is an indivisible minimum functional unit, and the scene function is obtained by combining at least two vehicle atomic functions;

[0074] The function development module is used to store the vehicle atomic functions and the vehicle scene functions into their respective databases, and to build the association between the vehicle atomic functions and the vehicle scene functions in the databases, so as to develop the vehicle functions corresponding to the function requirement information based on the association.

[0075] The step of storing the vehicle atomic functions and the vehicle scene functions into their respective databases includes:

[0076] Determine whether there is a target vehicle atomic function identical to the vehicle atomic function in the atomic function database corresponding to the vehicle atomic function, and determine whether there is a target vehicle scene function identical to the vehicle scene function in the scene function database corresponding to the vehicle scene function;

[0077] If it is determined that the target vehicle atomic function does not exist, the vehicle atomic function is stored in the atomic function database;

[0078] If it is determined that the target vehicle scene function does not exist, the vehicle scene function is stored in the scene function database.

[0079] Thirdly, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; the memory is used to store a computer program; and the processor is used to implement the development method of any of the vehicle functions described in the first aspect when executing the computer program.

[0080] Fourthly, this application provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements a development method for the vehicle functions described in any of the first aspects.

[0081] Compared with the prior art, the technical scheme provided by the embodiments of the present application has the following advantages: the method provided by the embodiments of the present application, by pre-acquiring a technical specification prompt word template of an adaptive function component, combining a mature function analysis model trained to accurately disassemble function requirement information, and efficiently separating out vehicle atomic functions that cannot be disassembled and vehicle scene functions composed of multiple atomic functions, not only realizes the structured disassembly of function requirements, avoids the problems of function overlap or omission caused by traditional manual disassembly, but also ensures that the disassembly result conforms to the technical specification with the help of the standardized template; at the same time, by classifying and storing atomic functions and scene functions and constructing the association relationship therebetween, not only a standardized function database is established, function redundancy is reduced, but also clear function calling logic is provided for subsequent function development, which facilitates quick tracing of the corresponding relationship between atomic functions and scene functions, thereby the efficiency and accuracy of vehicle function development can be greatly improved, the requirement communication cost and development iteration cycle are reduced, thereby adapting to the rapid development requirements of complex vehicle functions such as intelligent automobile cockpits. BRIEF DESCRIPTION OF DRAWINGS

[0082] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application.

[0083] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, brief introductions will be given to the drawings needed to be used in the embodiments or prior art descriptions. Obviously, for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0084] One or more embodiments are exemplarily illustrated by pictures in the drawings corresponding thereto, and these exemplary illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, unless otherwise specified. The drawings in the drawings do not constitute a proportional limitation.

[0085] Figure 1 An embodiment flowchart of a vehicle function development method provided by the embodiments of the present application;

[0086] Figure 2 An embodiment flowchart of another vehicle function development method provided by the embodiments of the present application;

[0087] Figure 3 An embodiment flowchart of still another vehicle function development method provided by the embodiments of the present application;

[0088] Figure 4 An embodiment flowchart of still another vehicle function development method provided by the embodiments of the present application;

[0089] Figure 5 An embodiment block diagram of a vehicle function development device provided by an embodiment of the present application is provided.

[0090] Figure 6 A structural schematic diagram of an electronic device provided by an embodiment of the present application is provided. DETAILED DESCRIPTION

[0091] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in detail with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0092] The following disclosure provides many different embodiments, or examples, for implementing different structures of the present application. For the purpose of simplicity, the components and arrangements of the examples that are described herein are shown and described separately. It is to be understood, however, that the implementations of the present application are not limited to the examples described and / or illustrated herein. Moreover, the present application can be implemented in various examples having fewer than or more than the number of components described and / or illustrated herein. Additionally, the present application can be implemented using any number combination of the examples described and / or illustrated herein. All such modifications are intended to be within the scope of the present application.

[0093] To solve the technical problem in the prior art that a great communication cost needs to be paid by a function developer when developing a vehicle function, and the determined function requirement is not clear due to the reliance on manual experience, and the vehicle function cannot be accurately developed, the present application provides a vehicle function development method, device, electronic equipment and storage medium, which can pre-acquire a technical specification prompt word template of an adaptive function component, combine a trained function analysis model to accurately disassemble function requirement information, and efficiently separate out vehicle atomic functions that cannot be disassembled and vehicle scene functions composed of multiple atomic functions, so as to not only realize the structured disassembly of function requirements, avoid the function overlap or omission problem caused by traditional manual disassembly, but also guarantee that the disassembly result conforms to the technical specification with the help of the standardized template; at the same time, by classifying and storing the atomic functions and the scene functions and constructing the association relationship therebetween, a standardized function database is established, function redundancy is reduced, clear function calling logic is provided for subsequent function development, the corresponding relationship between the atomic functions and the scene functions is conveniently traced back, and thus the efficiency and accuracy of vehicle function development can be greatly improved, the requirement communication cost and the development iteration period are reduced, and the rapid development requirement of complex vehicle functions such as an intelligent automobile cabin is adapted.

[0094] Referring to Figure 1 An embodiment flowchart of a vehicle function development method provided by an embodiment of the present application is provided. As shown in FIG. 2, the vehicle function development method provided by the embodiment of the present application includes the following steps.Figure 1 As shown, the flow can include the following steps:

[0095] Step 101, in the case of receiving functional requirement information for vehicle design, the technical specification prompt word template of the functional component corresponding to the functional requirement information is acquired.

[0096] The above-mentioned functional requirement information refers to the core initial input of vehicle function development, which is a structured or unstructured description of the target, scene, behavior and constraints of the specific function of the vehicle by the developer. Its content needs to cover the function application scene (such as "driver voice control navigation destination modification in high-speed driving", "automatically adjust the cabin temperature to 22℃ after starting in winter"), the expected implementation effect (such as "voice command response delay not more than 1.5 seconds", "temperature regulation accuracy ±1℃"), the interaction logic (such as "repeat the inquiry once when the user does not confirm, and default to cancel the operation if there is no response after timeout"), the associated components (such as the hardware or software modules involved in the cabin display screen, voice recognition module, air conditioning control system), and the compliance requirements (such as compliance with ISO26262 functional safety standards and vehicle HMI (Human Machine Interface) design specifications), which can be directly entered in the form of natural language short sentences or paragraphs, or can be imported in bulk through text files.

[0097] The above-mentioned technical specification prompt word template refers to a standardized text framework that contains function splitting rules, output format requirements, compliance constraints, etc., which is formulated in advance based on automotive industry technical standards (such as ISO 26262, AUTOSAR, vehicle HMI design specifications, etc.) and functional component characteristics, and is used to guide the accurate disassembly of functional requirement information by the function analysis model, and to ensure that the output atomic functions and scene functions meet the industry standards and development requirements.

[0098] The above-mentioned functional component refers to a collection of hardware and software units or modules that support the implementation of specific vehicle functions and have independent technical attributes and interaction logic, including hardware components (such as cabin display screen, environmental sensor, air conditioning control unit) and software components (such as voice recognition module, navigation algorithm module, HMI interaction program). Its type, technical parameters (such as response rate, detection accuracy) and cooperation relationship with other components need to comply with automotive industry technical standards (such as AUTOSAR, ISO26262), and is the core technical carrier for disassembling functional requirement information into atomic functions and scene functions and realizing vehicle function development.

[0099] In this step, the execution subject of the embodiment of the present application, in the case of receiving functional requirement information, in order to facilitate the analysis of the vehicle function contained in the functional requirement information, can acquire the technical specification prompt word template of the functional component corresponding to the functional requirement information.

[0100] In an embodiment, a function development technician can input a function requirement text to an execution subject of the embodiment. Based on this, the execution subject of the embodiment can determine the function requirement text as the received function requirement information for vehicle design when receiving the function requirement text.

[0101] In another embodiment, the execution subject of the embodiment can include a voice signal collection module. Based on this, the execution subject of the embodiment can actively collect the function requirement voice output by the user when actively or receiving a voice collection instruction. In this case, the execution subject of the embodiment can determine the function requirement voice signal as the received function requirement information for vehicle design when collecting the function requirement voice signal.

[0102] In an embodiment, the function requirement information can include the function requirement of one vehicle function, or the function requirement of multiple vehicle functions, which is not limited by the embodiment.

[0103] In an embodiment, the execution subject of the embodiment can determine the function component corresponding to the function requirement information and the vehicle sub-technical field to which the function component belongs when obtaining the technical specification prompt word template corresponding to the function requirement information. The vehicle sub-technical field is a subdivided field of the overall technical system of the vehicle according to the function component attribute, application scenario and technical specification difference, such as the intelligent cockpit field (including cockpit display, voice interaction related components), power control field (including battery management, motor control related components), autonomous driving field (including environment perception, path planning related components), etc. Each sub-field corresponds to a dedicated technical standard and development specification.

[0104] Based on this, the execution subject of the embodiment can obtain the technical specification prompt word template corresponding to the vehicle sub-technical field.

[0105] As an optional implementation manner, the execution subject of the embodiment can pre-store the vehicle sub-technical field, the technical specification prompt word template, and the association relationship therebetween. Based on this, the execution subject of the embodiment can determine the technical specification prompt word template corresponding to the vehicle sub-technical field from the association relationship according to the vehicle sub-technical field after determining the vehicle sub-technical field.

[0106] As another optional implementation manner, the execution subject of the embodiment can pre-train and store a technical specification prompt word template determination model. Based on this, the execution subject of the embodiment can determine the function component corresponding to the function requirement information when receiving the function requirement information. Then, the function component can be input into the technical specification prompt word template determination model to obtain the technical specification prompt word template corresponding to the function component.

[0107] As an optional implementation manner, the execution subject of the embodiment of the present application can input the functional requirement information into a pre-trained functional component determination model to obtain the functional component corresponding to the functional requirement information output by the functional component determination model when determining the functional component corresponding to the functional requirement information.

[0108] In step 102, the functional requirement information and the technical specification prompt word template are input into a pre-trained functional analysis model to obtain the vehicle atomic function and the vehicle scene function contained in the functional requirement information. The vehicle atomic function is the smallest indivisible functional unit in the vehicle function development, and the scene function is obtained by combining at least two vehicle atomic functions.

[0109] The vehicle atomic function refers to the smallest independent functional unit that cannot be further divided in vehicle function development, which is the basis for constructing the vehicle scene function and meets the industry technical specifications.

[0110] The vehicle scene function refers to a vehicle functional unit combined by at least two vehicle atomic functions in vehicle function development, which is adapted to a specific use scenario (such as linkage of window control and air circulation in foggy weather).

[0111] The functional analysis model refers to a pre-trained intelligent model that can receive functional requirement information and corresponding technical specification prompt word templates as input, accurately split the functional requirements through AI (Artificial Intelligence) semantic analysis, and output vehicle atomic functions (the smallest indivisible functional unit) and vehicle scene functions (combined by at least two atomic functions) that meet the industry technical specifications.

[0112] In this step, in order to efficiently and quickly analyze the vehicle atomic function and the vehicle scene function contained in the received functional requirement information, the execution subject of the embodiment of the present application can analyze the functional requirement information by using the pre-trained functional analysis model to obtain the vehicle atomic function and the vehicle scene function contained in the functional requirement information.

[0113] In an embodiment, the execution subject of the embodiment of the present application can input the functional requirement information and the technical specification prompt word template corresponding to the functional requirement information into a pre-trained functional analysis model to obtain the vehicle atomic function and the vehicle scene function contained in the functional requirement information.

[0114] As an optional implementation manner, the execution subject of the embodiment of the present application can embed the functional requirement information into the technical specification prompt word template to obtain a functional requirement analysis instruction.

[0115] Afterwards, the above functional requirement analysis instruction can be input into the above pre-trained function analysis model, the function analysis model can analyze the received functional requirement information to obtain the vehicle atomic function and the vehicle scene function contained in the functional requirement information. At the same time, the function analysis model can analyze the vehicle atomic function and the vehicle scene function according to the technical specification prompt word template to obtain the vehicle atomic function and the vehicle scene function conforming to the industry technical specification. Optionally, the function analysis model can output the vehicle atomic function, the vehicle scene function and the association relationship therebetween in JSON format.

[0116] Step 103, store the above vehicle atomic function and vehicle scene function into the respective corresponding database, and construct the association relationship between the vehicle atomic function and the vehicle scene function in the database, so as to develop the vehicle function corresponding to the functional requirement information based on the above association relationship.

[0117] The above database refers to the database for storing the vehicle atomic function and the vehicle scene function of the vehicle. The database for storing the vehicle atomic function and the database for storing the vehicle scene function can be different databases. For the convenience of distinction, the database for storing the vehicle atomic function can be referred to as "atomic function database", and the database for storing the vehicle scene function can be referred to as "scene function database".

[0118] The above association relationship refers to the association relationship between the vehicle atomic function and the vehicle scene function stored in the database. The association relationship can represent the reference relationship between the vehicle atomic function and the vehicle scene function, that is, the vehicle scene function can be realized by referencing at least two vehicle atomic functions.

[0119] In this step, after determining the vehicle atomic function and the vehicle scene function contained in the functional requirement information, in order to facilitate the management and storage of the vehicle atomic function and the vehicle scene function, the execution subject of the embodiment of the application can store the above vehicle atomic function and vehicle scene function into the respective corresponding database.

[0120] As an optional implementation manner, the above vehicle atomic function can be stored into the atomic function database, and the above vehicle scene function can be stored into the scene function database.

[0121] Further, in order to prevent the existence of redundant vehicle functions in the database (atomic function database and scene function database), the execution subject of the embodiment of the application can determine whether there is a target vehicle atomic function same as the vehicle atomic function in the atomic function database before storing the vehicle atomic function into the atomic function database, and store the vehicle atomic function into the atomic function database in the case that there is no target vehicle atomic function.

[0122] At the same time, before storing the vehicle scene function into the scene function database, it can be determined whether there is a target vehicle scene function that is the same as the vehicle scene function in the scene function database, and if it is determined that there is no target vehicle scene function, the vehicle scene function is stored into the scene function database.

[0123] As for how to determine whether the target vehicle's atomic function exists in the atomic function database, and whether the target vehicle's scene function exists in the scene function database, this will be explained below. Figure 2 The process shown will be explained in detail here.

[0124] In this embodiment of the application, after storing vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database, in order to store the reference relationship between vehicle atomic functions and vehicle scene functions in the database, the executing entity of this embodiment of the application can construct and store the association relationship between vehicle atomic functions and vehicle scene functions in the database, so as to develop vehicle functions corresponding to functional requirement information based on the association relationship.

[0125] As an optional implementation, the execution entity of this application embodiment can construct the association relationship between all vehicle atomic functions in the atomic function database and all vehicle scene functions in the scene function database in real time or periodically, and store the association relationship.

[0126] The specific details of how these relationships are constructed will be explained below. Figure 3 The process shown will be explained in detail here.

[0127] Furthermore, in one embodiment, when functional development technicians need to develop vehicle functions, they can obtain standard functional requirements documents through the vehicle atomic functions and vehicle scenario functions stored in the database.

[0128] As an optional implementation, functional developers can obtain functional requirements documents corresponding to specific vehicle functions. In this case, functional developers can input query instructions for the vehicle scenario functions to be developed into the execution entity of this application embodiment.

[0129] Based on this, after constructing the association between vehicle atomic functions and vehicle scene functions in the database, the executing entity of this application embodiment can generate a functional requirement document corresponding to the query instruction based on the constructed association when receiving the aforementioned query instruction, and output the functional requirement document. The aforementioned functional requirement document may include vehicle atomic functions, vehicle scene functions, and the association between the two.

[0130] Optionally, the aforementioned functional requirements document may be a functional requirements table, which may include vehicle atomic functions, vehicle scene functions, and the relationship between the two; the aforementioned functional requirements document may also be a tree diagram, which may include vehicle atomic functions, vehicle scene functions, and the relationship between the two.

[0131] As an exemplary implementation, the scene function identifier of the vehicle scene function can be obtained from the above query instruction, and the target vehicle scene function corresponding to the scene function identifier can be queried from the scene function database according to the scene function identifier.

[0132] Subsequently, based on the pre-built relationships mentioned above, the target vehicle atomic functions that are related to the target vehicle scene functions can be identified, and a functional requirements document can be generated based on the relationship between the target vehicle atomic functions and the target vehicle scene functions.

[0133] The technical solution provided in this application involves obtaining technical specification prompt templates for functional components corresponding to the functional requirements information upon receiving functional requirement information for vehicle design. The functional requirement information and technical specification prompt templates are then input into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scenario functions included in the functional requirement information. The vehicle atomic functions and vehicle scenario functions are stored in their respective databases, and the association between the vehicle atomic functions and vehicle scenario functions in the databases is constructed. Based on the above association, vehicle functions corresponding to the functional requirement information are developed. This technical solution, by pre-acquiring technical specification prompt templates for compatible functional components and combining them with a well-trained functional analysis model, precisely decomposes functional requirement information. It efficiently separates indivisible vehicle atomic functions from vehicle scene functions composed of multiple atomic functions. This achieves structured decomposition of functional requirements, avoiding functional overlap or omissions caused by traditional manual decomposition, and ensures that the decomposition results conform to technical specifications through standardized templates. Simultaneously, by classifying and storing atomic functions and scene functions and establishing their relationship, it not only establishes a standardized functional database, reducing functional redundancy, but also provides clear functional call logic for subsequent functional development, facilitating rapid tracing of the correspondence between atomic functions and scene functions. This significantly improves the efficiency and accuracy of vehicle function development, reduces requirement communication costs and development iteration cycles, thus adapting to the rapid development needs of complex vehicle functions such as intelligent car cockpits.

[0134] See Figure 2 This is a flowchart illustrating an embodiment of another vehicle function development method provided in this application. Figure 2 The process shown is in Figure 1Based on the illustrated process, the specific details of how vehicle atomic functions and vehicle scenario functions are stored in their respective databases are described. For example... Figure 2 As shown, the process may include the following steps:

[0135] Step 201: Determine whether there is a target vehicle atomic function in the atomic function database corresponding to the vehicle atomic function, and determine whether there is a target vehicle scene function in the scene function database corresponding to the vehicle scene function.

[0136] Step 202: If it is determined that there is no target vehicle atomic function, store the vehicle atomic function in the atomic function database.

[0137] Step 203: If it is determined that the target vehicle scene function does not exist, store the vehicle scene function in the scene function database.

[0138] The following provides a unified explanation of steps 201 to 203:

[0139] The aforementioned atomic function database refers to a database used to store vehicle atomic functions.

[0140] The aforementioned scenario function database refers to a database used to store vehicle scenario functions.

[0141] The aforementioned target vehicle atomic functions refer to vehicle atomic functions that are identical or highly similar to vehicle atomic functions stored in the atomic function database.

[0142] The aforementioned target vehicle scene function refers to the vehicle scene function stored in the scene function database that is the same as or highly similar to the vehicle scene function.

[0143] In this step, in order to prevent redundant vehicle functions from existing in the atomic function database and the scene function database, the executing entity of this application embodiment can determine whether there is a target vehicle atomic function identical to the vehicle atomic function in the atomic function database and whether there is a target vehicle scene function identical to the vehicle scene function in the scene function database before storing the vehicle atomic function and vehicle scene function in the database.

[0144] In one embodiment, when determining whether a target vehicle atomic function with the same atomic function as the vehicle atomic function exists in the atomic function database, the atomic text similarity between each atomic function in the atomic function database and the vehicle atomic function can be determined to obtain multiple atomic text similarities.

[0145] As an optional implementation, for each atomic function in the atomic function database, the function names of both the atomic function and the vehicle atomic function can be segmented using preset word segmentation rules to obtain the segmented text of the atomic function and the segmented text of the vehicle atomic function. Then, the cosine similarity of the vectors between the segmented texts of the atomic function and the vehicle atomic function can be determined, and this cosine similarity is taken as the atomic text similarity corresponding to that atomic function.

[0146] Then, it can be determined whether there exists a first target atomic text similarity greater than a first preset threshold among multiple atomic text similarities. Here, the first preset threshold refers to a pre-set threshold representing that the functions of two atoms are completely different.

[0147] Optionally, if it is determined that there is no first target atomic text similarity, it means that the vehicle atomic function is different from the atomic functions in the atomic function database. Therefore, it can be determined that the target vehicle atomic function does not exist in the atomic function database.

[0148] Optionally, if it is determined that at least one first target atomic text similarity exists, it indicates that there may be target vehicle atomic functions in the atomic function database that are the same as or similar to the vehicle atomic function. Therefore, in order to further determine whether there is a target vehicle atomic function in the atomic function database, the executing entity of this application embodiment can determine from the above-mentioned first target atomic text similarity whether there is a second target atomic text similarity greater than a second preset threshold. The above-mentioned second preset threshold can represent that two atomic functions are the same, and the second preset threshold can be greater than the above-mentioned first preset threshold.

[0149] As one implementation method, if the existence of the aforementioned second target atomic text similarity is determined, it can be determined that the target vehicle atomic function exists in the atomic function database.

[0150] As another implementation, in order to further determine whether there is a target vehicle atomic function, if it is determined that there is no second target atomic text similarity, the execution subject of this application embodiment may determine whether there is a target vehicle atomic function among the atomic functions corresponding to the first target atomic text similarity based on a preset semantic analysis model.

[0151] As an exemplary implementation, for each target atomic text similarity corresponding to the atomic function, the atomic function and the vehicle atomic function can be input into a pre-set semantic analysis template to obtain semantic analysis instructions.

[0152] Then, the above semantic analysis instructions can be input into a pre-trained semantic analysis model, which outputs semantic analysis results indicating whether the atomic functions and vehicle atomic functions are duplicated.

[0153] Then, based on the semantic analysis results of the atomic functions corresponding to the text similarity of each first target atomic function, it can be determined whether the target vehicle atomic function exists.

[0154] Optionally, if the semantic analysis results of the atomic functions corresponding to all first target atomic text similarities are not repeated, it indicates that the atomic function corresponding to each first target atomic text similarity is different from the vehicle atomic function. Therefore, it can be determined that the target vehicle atomic function does not exist in the atomic function database.

[0155] Optionally, if the semantic analysis results of at least one first target atomic text similarity corresponding to the atomic function are duplicated, the existence of the target vehicle atomic function can be determined.

[0156] In one embodiment, based on the above process, if the executing entity of this application determines that the target vehicle atomic function does not exist in the atomic function database, it may store the vehicle atomic function in the atomic function database; if it determines that the target vehicle atomic function exists in the atomic function database, it may not store the vehicle atomic function in the atomic function database.

[0157] Optionally, when writing vehicle atomic functions into the atomic function database, a corresponding ID (Identity document) can be set and stored for the vehicle atomic function. When storing the above-mentioned vehicle atomic functions, the system may also include the vehicle atomic function name, function overview, category (such as HMI interactive system), preconditions, inputs, outputs, and a list of referenced identifiers.

[0158] In one embodiment, when determining whether a target vehicle scene function with the same characteristics as the vehicle scene function exists in the scene function database, the scene text similarity between each scene function in the scene function database and the vehicle scene function can be determined to obtain multiple scene text similarities.

[0159] As an optional implementation, for each scene function in the scene function database, the function names of the scene function and the vehicle scene function can be segmented using preset word segmentation rules to obtain the segmented text of the scene function and the segmented text of the vehicle scene function. Then, the cosine similarity of the vectors between the segmented texts of the scene function and the vehicle scene function can be determined, and this cosine similarity is taken as the scene text similarity corresponding to that scene function.

[0160] Then, it can be determined whether there exists a first target scene text similarity greater than a first preset threshold among multiple scene text similarities. Here, the first preset threshold refers to a pre-set threshold representing that the functions of the two scenes are completely different.

[0161] Optionally, if it is determined that there is no text similarity to the first target scene, it means that the vehicle scene function is different from the scene function in the scene function database. Therefore, it can be determined that the target vehicle scene function does not exist in the scene function database.

[0162] Optionally, if it is determined that at least one first target scene text similarity exists, it indicates that the scene function database may contain target vehicle scene functions that are the same as or similar to vehicle scene functions. Therefore, in order to further determine whether a target vehicle scene function exists in the scene function database, the executing entity of this application embodiment can determine from the above-mentioned first target scene text similarity whether there is a second target scene text similarity greater than a second preset threshold. The above-mentioned second preset threshold can indicate that two scene functions are the same, and the second preset threshold can be greater than the above-mentioned first preset threshold.

[0163] As one implementation method, if the text similarity of the second target scene is determined to exist, it can be determined that the target vehicle scene function exists in the scene function database.

[0164] As another implementation, in order to further determine whether a target vehicle scene function exists, if it is determined that there is no text similarity of the second target scene, the execution subject of this application embodiment may determine whether a target vehicle scene function exists in the scene function corresponding to the text similarity of the first target scene based on a preset semantic analysis model.

[0165] As an exemplary implementation, for each target scene text similarity corresponding to the scene function, the scene function and the vehicle scene function can be input into a pre-set semantic analysis template to obtain semantic analysis instructions.

[0166] Then, the above semantic analysis instructions can be input into a pre-trained semantic analysis model, which outputs semantic analysis results indicating whether the scene function and the vehicle scene function are duplicated.

[0167] Then, based on the semantic analysis results of the scene function corresponding to the text similarity of each first target scene, it can be determined whether there is a target vehicle scene function.

[0168] Optionally, if the semantic analysis results of the scene functions corresponding to the text similarity of all first target scenes are not repeated, it indicates that the scene function corresponding to each text similarity of the first target scene is different from the vehicle scene function. Therefore, it can be determined that the target vehicle scene function does not exist in the scene function database.

[0169] Optionally, if the semantic analysis results of at least one first target scene text similarity corresponding to the scene function are duplicated, the existence of a target vehicle scene function can be determined.

[0170] In one embodiment, based on the above process, if the executing entity of this application determines that the target vehicle scene function does not exist in the scene function database, it may store the vehicle scene function in the scene function database; if it determines that the target vehicle scene function exists in the scene function database, it may not store the vehicle scene function in the scene function database.

[0171] Optionally, when writing vehicle scene functions into the scene function database, a corresponding ID number can be set and stored for the vehicle scene function. When storing the above-mentioned vehicle scene functions, the system may also include the vehicle function name, function overview, category (such as HMI interaction system), preconditions, inputs, outputs, and a list of reference identifiers.

[0172] Furthermore, in one embodiment, when storing vehicle atomic functions and / or vehicle scene functions in a database, in order to enable function developers to understand the currently stored vehicle functions, the execution entity of this application embodiment can output a list of functions included in the function requirement information. The list of functions may include vehicle atomic functions and vehicle scene functions, as well as a storage identifier indicating whether each vehicle function is stored in the corresponding database. The storage identifier can be used to characterize whether the corresponding vehicle function (vehicle atomic function or vehicle scene function) is stored in the database.

[0173] The technical solution provided in this application determines whether a target vehicle atomic function identical to the vehicle atomic function exists in the atomic function database corresponding to the vehicle atomic function, and whether a target vehicle scene function identical to the vehicle scene function exists in the scene function database corresponding to the vehicle scene function. If no target vehicle atomic function is found, the vehicle atomic function is stored in the atomic function database; if no target vehicle scene function is found, the vehicle scene function is stored in the scene function database. This technical solution, by verifying the existence of identical target functions in the atomic function database and scene function database before storing vehicle atomic functions and vehicle scene functions, and storing only those confirmed to be unique, achieves automatic deduplication of functional data, effectively avoiding the waste of storage resources and low efficiency of subsequent queries and calls caused by functional redundancy in the database. It also reduces the time-consuming cost of manually checking for duplicate functions, adapting to the rapid iteration development needs of intelligent vehicle functions. Simultaneously, it ensures the uniqueness and standardization of atomic functions and scene functions in the database, laying a solid foundation for accurately constructing the relationship between them, improving function reuse efficiency, and forming a high-quality enterprise-level functional knowledge base, further ensuring the accuracy and consistency of vehicle function development.

[0174] See Figure 3 This is a flowchart illustrating an embodiment of a vehicle function development method provided in this application. Figure 3 The process shown is in Figure 1 Based on the illustrated process, this section describes how the association between vehicle atomic functions and vehicle scene functions in the database is constructed, assuming that vehicle atomic functions have corresponding referenced identifier lists in their respective atomic function databases, and vehicle scene functions have corresponding referenced identifier lists in their respective scene function databases. For example... Figure 3 As shown, the process may include the following steps:

[0175] Step 301: Input the atomic function database and the scene function database into the pre-trained correlation determination model to obtain a list of correlations between vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database.

[0176] The aforementioned correlation determination model refers to a pre-trained model used to determine the correlation between vehicle atomic functions and vehicle scene functions. It can be a pre-trained AI model, and it can be used with... Figure 1 The functional analysis model in the process shown can be the same model or a different model; this application embodiment does not limit this.

[0177] In this step, in order to quickly determine the relationship between vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database, the execution subject of this application embodiment can pre-train and store the relationship determination model.

[0178] Based on this, when determining the relationship between vehicle atomic functions and vehicle scene functions, the executing entity of this application embodiment can input the aforementioned atomic function database and scene function database into a pre-trained relationship determination model.

[0179] The aforementioned relationship determination model can analyze vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database to identify vehicle atomic functions and vehicle scene functions with existing relationships, and output a relationship list containing these relationships. In this case, the executing entity of this application embodiment can obtain the aforementioned relationship list output by the relationship determination model. This relationship list may include the relationships between all vehicle atomic functions in the atomic function database and all vehicle scene functions in the scene function database.

[0180] Step 302: Based on the above association list, update the list of referenced identifiers for vehicle atomic functions in the atomic function database, and update the list of referenced identifiers for vehicle scene functions in the scene function database.

[0181] The aforementioned list of referenced identifiers refers to the list of referenced identifiers corresponding to each vehicle atomic function. This list of referenced identifiers may include the scene identifier of the vehicle scene function that references the corresponding vehicle atomic function. The scene identifier may be the ID number when the vehicle scene function is written into the scene function database, or it may be other unique identifiers used to characterize the vehicle scene function. This application embodiment does not impose any restrictions on this.

[0182] The aforementioned list of reference identifiers refers to the list of reference identifiers corresponding to each vehicle scenario function. This list of reference identifiers may include the atomic identifiers of the referenced vehicle atomic functions. These atomic identifiers may be the ID number of the vehicle atomic function when it is written into the atomic function database, or other unique identifiers used to characterize the vehicle scenario function. This application embodiment does not impose any restrictions on this.

[0183] In this step, after obtaining the association relationship list output by the association relationship determination model, the executing entity of this application embodiment can update the list of referenced identifiers of vehicle atomic functions in the atomic function database and the list of referenced identifiers of vehicle scene functions in the scene function database according to the above association relationship list in order to identify the association relationship in the database.

[0184] In one embodiment, the executing entity of this application embodiment can traverse each association contained in the association list, and for each traversed association, determine the associated vehicle atomic function and associated vehicle scene function included in the association, and respectively obtain the associated atomic identifier of the associated vehicle atomic function and the associated scene identifier of the associated vehicle scene function.

[0185] Subsequently, the related vehicle atomic functions can be queried from the atomic function database, and the related scenario identifiers of the related vehicle scenario functions with related relationships can be written into the referenced identifier list of the related vehicle atomic functions.

[0186] At the same time, the associated vehicle scenario functions can be queried from the aforementioned scenario function database, and the associated atomic identifiers of the associated vehicle atomic functions that have a relationship can be written into the reference identifier list of the aforementioned associated vehicle scenario functions.

[0187] Furthermore, in one embodiment, the executing entity of this application may also possess a vehicle function development recommendation function. With this function, the executing entity of this application can determine the priority of each vehicle atomic function and recommend the vehicle atomic function with the highest priority.

[0188] As an optional implementation, the vehicle atomic functions in the aforementioned vehicle function database may also include a reference count identifier, which can be used to record the number of times the corresponding vehicle atomic function is referenced by the scene vehicle functions. Based on this, the execution entity of this application embodiment can determine the priority of each vehicle atomic function according to the reference count identifier corresponding to each vehicle atomic function.

[0189] As an exemplary implementation, the number of references indicated by the aforementioned reference count identifier can be positively correlated with the priority of the vehicle atomic function; that is, the more times a vehicle atomic function is referenced, the higher its development priority. Based on this, the executing entity of this application embodiment can obtain the reference count identifier for each vehicle atomic function and determine the priority corresponding to the reference count identifier according to the pre-set correlation between the reference count and priority.

[0190] Based on the priority of each vehicle atomic function, the execution entity of this application embodiment can determine and output the vehicle atomic function with the highest priority according to the priority corresponding to each vehicle atomic function when it receives the function development recommendation instruction input by the function developer.

[0191] Furthermore, in one embodiment, in order to save database storage space, after the execution entity of this application embodiment constructs the association relationship between vehicle atomic functions and vehicle scene functions in the database, it can determine in real time or periodically whether there is a target vehicle scene function in the scene function database that does not reference any vehicle atomic functions.

[0192] As an optional implementation, when the vehicle scene function includes a reference identifier list, and the reference identifier list is used to record the atomic identifiers of the vehicle atomic functions referenced by the corresponding vehicle scene function, when determining whether there is a target vehicle scene function in the scene function database that does not reference any vehicle atomic functions, it can be determined whether the reference identifier list corresponding to each vehicle scene function includes the atomic identifiers of the vehicle atomic functions.

[0193] Optionally, if the reference identifier list is determined to be empty, the vehicle scene function corresponding to the empty reference identifier list can be determined as the target vehicle scene function.

[0194] Optionally, if it is determined that the list of reference identifiers is not empty, the vehicle scene function corresponding to the list of reference identifiers can be determined as a non-target vehicle scene function.

[0195] Based on this, if the target vehicle scenario function is confirmed to exist in the scenario function database, the target vehicle scenario function can be deleted.

[0196] Furthermore, in one embodiment, to further prevent redundancy of vehicle functions stored in the database, the execution entity of this application embodiment can dynamically deduplicate the vehicle functions in the database.

[0197] As an optional implementation, the executing entity in this application embodiment can determine the number of newly added vehicle atomic functions within a preset time period. The preset time period is a pre-defined time frame, such as the last 10 minutes, the last 2 hours, or the last week.

[0198] Optionally, if the number exceeds a preset threshold, the atomic function database and the scene function database can be input into a pre-trained semantic analysis model to obtain similar vehicle atomic functions in the atomic function database with a similarity greater than a first preset similarity threshold and similar vehicle scene functions in the scene function database with a similarity greater than a second preset similarity threshold.

[0199] Then, the atomic functions and scene functions of the same type of vehicle can be deduplicated respectively.

[0200] The technical solution provided in this application, by inputting an atomic function database and a scene function database into a pre-trained association relationship determination model, obtains a list of association relationships between vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database. Based on the above association relationship list, the list of referenced identifiers for vehicle atomic functions in the atomic function database and the list of referenced identifiers for vehicle scene functions in the scene function database are updated. This technical solution, by inputting the atomic function database and the scene function database into a pre-trained association relationship determination model, automatically generates a list of association relationships between vehicle atomic functions and vehicle scene functions, and synchronously updates the list of referenced identifiers and the list of referenced identifiers for both. This not only replaces the tedious manual sorting of association relationships with the intelligent analysis capabilities of the model, significantly reducing association deviations caused by human error and improving the accuracy and efficiency of association relationships; but also, by dynamically updating the identifier list, makes the reuse status of atomic functions and the composition logic of scene functions clear at a glance, providing clear data support for subsequent function queries, reuse priority determination, and development process optimization; at the same time, it standardizes the storage format of function associations in the database, further improves the structure of the functional knowledge base, facilitates the rapid iteration and efficient development of complex functions of intelligent vehicles, and reduces cross-team communication costs.

[0201] See Figure 4 This is a flowchart illustrating another embodiment of a vehicle function development method provided in this application. Figure 4 The process shown is in Figure 3 Based on the illustrated process, this section describes how the vehicle functions in the database are modified after establishing the relationships between the vehicle atomic functions and vehicle scene functions in the database. For example... Figure 4 As shown, the process may include the following steps:

[0202] Step 401: Upon receiving a modification instruction, back up the atomic function database and the scene function database to the backup database.

[0203] The aforementioned modification instructions refer to instructions that modify vehicle atomic functions and / or vehicle scene functions.

[0204] In this step, feature developers can modify the vehicle atomic functions in the atomic function database and the vehicle scene functions in the scene function database. These modifications may include, but are not limited to, changing the ID, function definition, or function name of the vehicle function (vehicle atomic function or vehicle scene function).

[0205] In one embodiment, the executing entity of this application can display a list of newly added vehicle atomic functions and / or a list of vehicle scene functions within a recently preset time period according to user instructions. Function developers can modify the vehicle functions in the displayed list of vehicle atomic functions and / or vehicle scene functions, and generate corresponding modification instructions.

[0206] In order to prevent erroneous data from existing data in the modified database, the executing entity of this application embodiment may first back up the current atomic function database and scenario function database to the backup database upon receiving the above modification instruction.

[0207] As a backup method, if the aforementioned atomic function database and scenario function database are not backed up, the aforementioned atomic function database and scenario function database can be fully backed up to the backup database.

[0208] As another backup method, if the aforementioned atomic function database and scenario function database have already been backed up, the aforementioned atomic function database and scenario function database can be incrementally backed up to the backup database.

[0209] Step 402: Update the atomic function database and / or scenario function database according to the above modification instructions.

[0210] In this step, the executing entity of this application embodiment can directly modify the vehicle functions in the database according to the received modification instructions.

[0211] As one method of modification, if the modification instruction includes atomic function modification information for vehicle atomic functions, the corresponding vehicle atomic functions in the atomic function database can be modified according to the aforementioned atomic function modification information.

[0212] As another modification method, if the modification instruction includes scene function modification information for vehicle scene functions, the corresponding vehicle scene functions in the scene function database can be modified according to the aforementioned scene function modification information.

[0213] As another modification method, when the modification instruction includes atomic function modification information for vehicle atomic functions and scene function modification information for vehicle scene functions, the vehicle atomic functions in the atomic function database can be modified according to the aforementioned atomic function modification information, and the vehicle scene functions in the scene function database can be modified according to the aforementioned scene function modification information.

[0214] Step 403: Determine whether there are any abnormal functions in the updated atomic function database and / or scenario function database; wherein, the abnormal functions may include functions with abnormal relationships, and / or functions with abnormal function categories.

[0215] Step 404: If it is determined that there is an abnormal function, restore the atomic function database and / or scenario function database according to the above backup database.

[0216] The following provides a unified explanation of steps 403 and 404:

[0217] The aforementioned abnormal functions refer to vehicle functions that are abnormal in the atomic function database and the scenario function database. These may include, but are not limited to: functions with abnormal relationships (e.g., there is a mutual exclusion relationship between vehicle atomic functions and vehicle scenario functions) and functions with abnormal function categories (e.g., in the process of developing functions in the field of vehicle intelligent cockpit, the field to which the vehicle function belongs is the field of vehicle power).

[0218] In this step, to prevent abnormalities in the modified data, after modifying the atomic function database and / or scenario function database, the executing entity of this application embodiment can detect the updated atomic function database and scenario function database to determine whether there are abnormal functions in the updated atomic function database and / or scenario function database.

[0219] As an optional implementation, the updated vehicle functions and related vehicle functions that are associated with the updated vehicle functions can be input into a pre-built association determination model. The updated vehicle functions and related vehicle functions, as well as the association between them, can be determined and verified through the association determination model to determine whether they are abnormal functions.

[0220] Optionally, if an abnormal function is determined to exist, the aforementioned atomic function database and / or scenario function database can be restored based on the backup database.

[0221] The technical solution provided in this application involves backing up the atomic function database and the scene function database to a backup database upon receiving a modification instruction, updating the atomic function database and / or the scene function database according to the modification instruction, and determining whether there are any abnormal functions in the updated atomic function database and / or scene function database. These abnormal functions may include functions with abnormal relationships, and / or functions with abnormal function categories. If an abnormal function is determined to exist, the atomic function database and / or scene function database are restored according to the backup database. This technical solution employs a closed-loop design: backing up the atomic and scenario function databases before modification, detecting abnormal functions (including abnormal relationships and function category anomalies) after modification, and restoring the database based on backups when anomalies occur. This approach not only avoids database chaos and functional data failure caused by modification operation errors (such as mistakenly changing relationships or misclassifying function categories) from the source, providing dual protection for data security, but also reduces the time-consuming cost of manual error investigation through automated anomaly detection, ensuring the accuracy and standardization of functional data in the database. Simultaneously, the flexible update and recovery mechanism allows users to adjust functional information as needed without worrying about operational risks. This adapts to the need for dynamic database optimization during the rapid iteration of intelligent vehicle functions, while also ensuring the stability of the functional knowledge base. This provides reliable support for subsequent function association queries, reuse, and the continuity of vehicle function development, further reducing rework costs during the development process.

[0222] See Figure 5 This is a block diagram illustrating an embodiment of a vehicle function development apparatus provided in this application. Figure 5 As shown, the device may include:

[0223] The prompt word template acquisition module 51 is used to acquire the technical specification prompt word template of the functional component corresponding to the functional requirement information when receiving functional requirement information for vehicle design.

[0224] The functional analysis module 52 is used to input the functional requirement information and the technical specification prompt word template into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions contained in the functional requirement information; wherein, the vehicle atomic function is an indivisible minimum functional unit, and the scene function is obtained by combining at least two vehicle atomic functions;

[0225] The function development module 53 is used to store the vehicle atomic functions and the vehicle scene functions into their respective databases, and to build the association between the vehicle atomic functions and the vehicle scene functions in the databases, so as to develop the vehicle functions corresponding to the function requirement information based on the association.

[0226] likeFigure 6 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this application, including a processor 61, a communication interface 62, a memory 63, and a communication bus 64. The processor 61, communication interface 62, and memory 63 communicate with each other via the communication bus 64.

[0227] Memory 63 is used to store computer programs;

[0228] In one embodiment of this application, when the processor 61 executes a program stored in the memory 63, it implements a method for developing vehicle functions provided in any of the foregoing method embodiments, including:

[0229] Upon receiving functional requirement information for vehicle design, obtain the technical specification prompt template for the corresponding functional component;

[0230] The functional requirement information and the technical specification prompt template are input into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions contained in the functional requirement information; wherein, the vehicle atomic function is the smallest indivisible functional unit, and the scene function is obtained by combining at least two vehicle atomic functions;

[0231] The vehicle atomic functions and the vehicle scene functions are stored in their respective databases, and the association between the vehicle atomic functions and the vehicle scene functions in the databases is constructed, so as to develop the vehicle functions corresponding to the functional requirements information based on the association.

[0232] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the vehicle function development method provided in any of the foregoing method embodiments.

[0233] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0234] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0235] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0236] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for developing vehicle functions, characterized in that, The method includes: Upon receiving functional requirement information for vehicle design, obtain the technical specification prompt template for the corresponding functional component; The functional requirement information and the technical specification prompt template are input into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information; wherein, the vehicle atomic function is an indivisible minimum functional unit, and the scene function is obtained by combining at least two vehicle atomic functions; the step of inputting the functional requirement information and the technical specification prompt template into the pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information includes: embedding the functional requirement information into the technical specification prompt template to obtain a functional requirement analysis instruction; and inputting the functional requirement analysis instruction into the pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information; The vehicle atomic functions and the vehicle scene functions are stored in their respective databases, and the association between the vehicle atomic functions and the vehicle scene functions in the databases is constructed, so as to develop the vehicle functions corresponding to the functional requirement information based on the association. The step of storing the vehicle atomic functions and the vehicle scene functions into their respective databases includes: Determine whether there is a target vehicle atomic function identical to the vehicle atomic function in the atomic function database corresponding to the vehicle atomic function, and determine whether there is a target vehicle scene function identical to the vehicle scene function in the scene function database corresponding to the vehicle scene function; If it is determined that the target vehicle atomic function does not exist, the vehicle atomic function is stored in the atomic function database; If it is determined that the target vehicle scene function does not exist, the vehicle scene function is stored in the scene function database.

2. The method according to claim 1, characterized in that, Received functional requirements information for vehicle design, including: Upon receiving a functional requirement text, the functional requirement text is identified as the received functional requirement information for vehicle design. or, When a functional requirement voice signal is collected, the functional requirement voice signal is identified as the received functional requirement information for the vehicle design.

3. The method according to claim 1, characterized in that, Obtain the technical specification prompt templates for the functional components corresponding to the aforementioned functional requirements information, including: Identify the functional components corresponding to the functional requirements information, and determine the vehicle sub-technology field to which the functional components belong; Obtain the technical specification prompt template corresponding to the vehicle sub-technology field.

4. The method according to claim 1, characterized in that, Determining whether a target vehicle atomic function identical to the vehicle atomic function exists in the atomic function database corresponding to the vehicle atomic function includes: Determine the atomic text similarity between each atomic function in the atomic function database and the vehicle atomic function to obtain multiple atomic text similarities; Determine whether, among the multiple atomic text similarities, there exists a first target atomic text similarity greater than a first preset threshold; If it is determined that there is no similarity between the first target atomic text and the target vehicle atomic function does not exist in the atomic function database, then the target vehicle atomic function is determined to be absent from the atomic function database.

5. The method according to claim 4, characterized in that, Also includes: If it is determined that there is at least one first target atomic text similarity, determine from the first target atomic text similarity whether there is a second target atomic text similarity greater than a second preset threshold; The second preset threshold is greater than the first preset threshold; If the second target atomic text similarity is determined to exist, it is determined that the target vehicle atomic function exists in the atomic function database; If it is determined that there is no second target atomic text similarity, the target vehicle atomic function is determined to exist in the atomic function corresponding to the first target atomic text similarity based on a preset semantic analysis model.

6. The method according to claim 5, characterized in that, Determining whether the target vehicle atomic function exists in the atomic function corresponding to the first target atomic text similarity based on a preset semantic analysis model includes: For each atomic function corresponding to the first target atomic text similarity, the atomic function and the vehicle atomic function are input into a pre-set semantic analysis template to obtain semantic analysis instructions; The semantic analysis instructions are input into a pre-trained semantic analysis model to obtain semantic analysis results indicating whether the atomic functions and the vehicle atomic functions are duplicated. If the semantic analysis results of the atomic functions corresponding to the similarity of all first target atomic texts are not repeated, it is determined that the target vehicle atomic function does not exist. If the semantic analysis result of at least one first target atomic text similarity corresponds to the atomic function being duplicated, then the existence of the target vehicle atomic function is determined.

7. The method according to claim 1, characterized in that, Determining whether a target vehicle scene function identical to the vehicle scene function exists in the scene function database corresponding to the vehicle scene function includes: Determine the scene text similarity between each scene function in the scene function database and the vehicle scene function to obtain multiple scene text similarities; Determine whether, among the multiple scene text similarities, there exists a first target scene text similarity greater than a first preset threshold; If it is determined that there is no text similarity to the first target scene, then it is determined that the target vehicle scene function does not exist in the scene function database.

8. The method according to claim 7, characterized in that, Also includes: If it is determined that there is at least one text similarity of the first target scene, determine whether there is a text similarity of the second target scene greater than a second preset threshold from the text similarity of the first target scene; If the text similarity of the second target scene is determined to exist, it is determined that the target vehicle scene function exists in the scene function database; If it is determined that there is no text similarity to the second target scene, the target vehicle scene function is determined to exist in the scene function corresponding to the text similarity to the first target scene based on a preset semantic analysis model.

9. The method according to claim 8, characterized in that, Determining whether the target vehicle scene function exists in the scene function corresponding to the first target scene text similarity based on a preset semantic analysis model includes: For each scene function corresponding to the text similarity of the first target scene, the scene function and the vehicle scene function are input into a pre-set semantic analysis template to obtain semantic analysis instructions; The semantic analysis instructions are input into a pre-trained semantic analysis model to obtain semantic analysis results indicating whether the scene function and the vehicle scene function are duplicated. If the semantic analysis results of all the first target scene text similarity corresponding to the scene function are not repeated, it is determined that the target vehicle scene function does not exist; If the semantic analysis result of at least one first target scene text similarity corresponding to the scene function is duplicated, the existence of the target vehicle scene function is determined.

10. The method according to claim 1, characterized in that, The vehicle atomic function has a corresponding referenced identifier list in the corresponding atomic function database, and the vehicle scene function has a corresponding referenced identifier list in the corresponding scene function database; the referenced identifier list is used to record the scene identifier of the vehicle scene function that references the corresponding vehicle atomic function, and the referenced identifier list is used to record the atomic identifier of the vehicle atomic function referenced by the corresponding vehicle scene function. Constructing the association between the vehicle atomic functions and the vehicle scene functions in the database includes: Input the atomic function database and the scene function database into a pre-trained correlation determination model to obtain a list of correlations between vehicle atomic functions in the atomic function database and vehicle scene functions in the scene function database. Based on the aforementioned association list, the list of referenced identifiers for vehicle atomic functions in the atomic function database is updated, as is the list of referenced identifiers for vehicle scene functions in the scene function database.

11. The method according to claim 10, characterized in that, The vehicle atomic functions in the atomic function database also include a reference count identifier, which is used to record the number of times the corresponding vehicle atomic function is referenced by the scene vehicle function; the method further includes: The priority of each vehicle atomic function is determined based on the reference count identifier corresponding to each vehicle atomic function. Upon receiving a feature development recommendation instruction, output the vehicle atomic function with the highest priority.

12. The method according to claim 10, characterized in that, After establishing the association between the vehicle atomic functions and the vehicle scene functions in the database, the following is also included: Determine whether a target vehicle scenario function exists in the scenario function database that does not reference any vehicle atomic functions; If the target vehicle scene function exists, delete the target vehicle scene function.

13. The method according to claim 1, characterized in that, After establishing the association between the vehicle atomic functions and the vehicle scene functions in the database, the following is also included: Upon receiving a query instruction or export instruction, a functional requirements document is generated based on the aforementioned relationship. The functional requirements document includes vehicle atomic functions, vehicle scenario functions, and the relationship between the two. Output the aforementioned functional requirements document.

14. The method according to claim 10, characterized in that, After establishing the association between the vehicle atomic functions and the vehicle scene functions in the database, the following is also included: Upon receiving a modification instruction, the atomic function database and the scenario function database are backed up to the backup database; The atomic function database and / or the scenario function database are updated according to the modification instructions; Determine whether there are any abnormal functions in the updated atomic function database and / or scenario function database. The abnormal functions include functions with abnormal relationships and / or functions with abnormal function categories. If the abnormal function is confirmed to exist, the atomic function database and / or the scenario function database shall be restored based on the backup database.

15. The method according to claim 10, characterized in that, The method further includes: Determine the number of new vehicle atomic functions to be added within a preset time period; When the number exceeds a preset threshold, the atomic function database and the scene function database are respectively input into a pre-trained semantic analysis model to obtain similar vehicle atomic functions in the atomic function database with a similarity greater than a first preset similarity threshold and similar vehicle scene functions in the scene function database with a similarity greater than a second preset similarity threshold. The atomic functions of the same type of vehicle and the scene functions of the same type of vehicle are deduplicated respectively.

16. A vehicle function development apparatus, characterized in that, The device includes: The prompt word template acquisition module is used to acquire the technical specification prompt word template of the functional component corresponding to the functional requirement information when receiving functional requirement information for vehicle design. The functional analysis module is used to input the functional requirement information and the technical specification prompt word template into a pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information; wherein, the vehicle atomic function is an indivisible minimum functional unit, and the scene function is obtained by combining at least two vehicle atomic functions; the step of inputting the functional requirement information and the technical specification prompt word template into the pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information includes: embedding the functional requirement information into the technical specification prompt word template to obtain a functional requirement analysis instruction; and inputting the functional requirement analysis instruction into the pre-trained functional analysis model to obtain the vehicle atomic functions and vehicle scene functions included in the functional requirement information; The function development module is used to store the vehicle atomic functions and the vehicle scene functions into their respective databases, and to build the association between the vehicle atomic functions and the vehicle scene functions in the databases, so as to develop the vehicle functions corresponding to the function requirement information based on the association. The step of storing the vehicle atomic functions and the vehicle scene functions into their respective databases includes: Determine whether there is a target vehicle atomic function identical to the vehicle atomic function in the atomic function database corresponding to the vehicle atomic function, and determine whether there is a target vehicle scene function identical to the vehicle scene function in the scene function database corresponding to the vehicle scene function; If it is determined that the target vehicle atomic function does not exist, the vehicle atomic function is stored in the atomic function database; If it is determined that the target vehicle scene function does not exist, the vehicle scene function is stored in the scene function database.

17. An electronic device, characterized in that, include: The processor, communication interface, memory, and communication bus are connected, with the processor, communication interface, and memory communicating with each other via the communication bus. The memory is used to store computer programs; the processor is used to execute the computer programs to implement the development method of the vehicle functions described in any one of claims 1 to 15.

18. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the development method of the vehicle functions described in any one of claims 1 to 15.

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