Design support device and design support method

Abstract

This invention provides a design support device and method that can identify control parameters to be changed in response to free-form text requests and facilitate their setting. [Solution] The design support device includes an input unit that receives requests regarding vehicle behavior described in natural language, a module selection unit that selects a target module related to the vehicle behavior included in the request based on a first processing result obtained by natural language processing from module description information that describes the functions of software modules into which the vehicle's control software is divided by function, and the request, a reference parameter extraction unit that extracts vehicle control parameters referenced by the target module, a parameter selection unit that selects a target parameter related to the vehicle behavior included in the request based on a second processing result obtained by natural language processing from parameter description information that describes the functions of the reference parameter, and the request, and an output unit that outputs the target parameter.

Description

Technical Field

[0001] The present invention relates to a design support device and a design support method.

Background Art

[0002] In recent years, due to the diversification of driver preferences, the Software Defined Vehicle (SDV) transformation of automobiles has been accelerating. Until now, the software of automobiles has been developed in accordance with hardware such as Electronic Control Units (ECUs). However, as the SDV transformation progresses, it becomes unnecessary to create software based on specific hardware, and functions can be realized mainly by software. Therefore, it becomes possible to provide software according to various driver preferences. Also, by individually adjusting the control parameters of the software, customization for specific applications and personalization for specific drivers become easier.

[0003] On the other hand, as the role of software becomes larger, the scale of software and the number of control parameters are increasing. Therefore, if each control parameter is set manually, a huge amount of man-hours is required, and a mechanism that can easily set these is desired.

[0004] Conventionally, an invention of this kind was described in Japanese Patent Publication No. 2017-206239 (Patent Document 1). Patent Document 1 describes a method performed by a vehicle including an ADAS system (Advanced Driver Assistance System) and a communication unit, comprising: a receiving step in which the vehicle's communication unit receives a wireless message via a wireless network; and a changing step in which the vehicle's processor changes the control parameters of the ADAS system, wherein the wireless message includes optimization setting value data describing how to change the operation of the ADAS system based on the preferences of a first user who has reserved use of the vehicle, and the changing step is characterized in that, based on the optimization setting value data, the control parameters of the ADAS system are changed so that the operation of the ADAS system matches the preferences of the first user (Claim 1) [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2017-206239 [Overview of the project] [Problems that the invention aims to solve]

[0006] However, in order to map user settings to software control parameters, it is necessary to pre-define the items that users can set, which reduces the flexibility of customization and personalization. On the other hand, if the system is not pre-definitely limited in the items that users can set, and attempts are made to flexibly respond to various user requests defined by free-form natural language descriptions, it becomes difficult to identify the control parameters that need to be adjusted.

[0007] This invention has been made in view of the above circumstances, and its purpose is to provide a design support device that can identify control parameters to be changed in response to free-form user requests and facilitate their setting. [Means for solving the problem]

[0008] To achieve the above objective, the design support device of the present invention comprises: an input unit that receives requests relating to vehicle behavior described in natural language; a module selection unit that, based on a first processing result obtained by natural language processing, selects software modules related to vehicle behavior included in the requests as target modules, based on module description information and requests that describe the functions of software modules into which the vehicle's control software is divided by function, based on the requests; a reference parameter extraction unit that extracts reference parameters, which are vehicle control parameters referenced by the target modules; a parameter selection unit that, based on a second processing result obtained by natural language processing, selects target parameters related to vehicle behavior included in the requests, based on parameter description information and requests that describe the functions of the reference parameters in natural language; and an output unit that outputs the target parameters. [Effects of the Invention]

[0009] According to the present invention, it is possible to identify the control parameters to be changed in response to a free-form description request and to facilitate their setting. Problems, configurations, and effects other than those described above will be clarified by the following description of embodiments. [Brief explanation of the drawing]

[0010] [Figure 1A] This figure shows the schematic configuration of the design support device in the first embodiment. [Figure 1B] This is the hardware configuration of the design support server in the first embodiment. [Figure 2] This is a functional block diagram of the design support operation in the first embodiment. [Figure 3] This is a flowchart showing the design support operation in the first embodiment. [Figure 4] This is an example of the data structure of the module storage unit in the first embodiment. [Figure 5]An example of the data structure of the reference storage unit in the first embodiment. [Figure 6] An example of the data structure of the parameter storage unit in the first embodiment. [Figure 7] An example of the data structure of the setting condition storage unit in the first embodiment. [Figure 8A] An example of the data structure of the set value storage unit in the first embodiment. [Figure 8B] An example of the data structure of the set value storage unit in the first embodiment. [Figure 9] The hardware configuration of the design support server in the second embodiment. [Figure 10] A functional block diagram of the design support operation in the second embodiment. [Figure 11] A flowchart showing the design support operation in the second embodiment. [Figure 12A] An example of the data structure of the setting history storage unit in the second embodiment. [Figure 12B] An example of the data structure of the setting history storage unit in the second embodiment. [Figure 13] An example of the data structure of the scenario storage unit in the second embodiment.

Best Mode for Carrying Out the Invention

[0011] Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. In the embodiments described below, the case where the present invention is applied to a design support device for automatic driving control of an automobile as a vehicle is taken as an example, but the present invention can also be applied to design support devices for control of hybrid vehicles, control of electric vehicles, control of transport vehicles traveling in a warehouse, control of construction vehicles traveling at a construction site, and the like.

Examples

[0012] FIG. 1A is a diagram showing a schematic configuration of a design support device 1 in the first embodiment. The broken line arrows in FIG. 1 indicate the flow of signals.

[0013] The design support device 1 includes a design support server 100 that adjusts control parameters affecting the behavior of vehicle control software for a vehicle 3 that travels autonomously or with driving support based on the execution results of the vehicle control software, and a design support server terminal 100A that is a user interface between the designer 2, who is a user of the design support device 1, and the design support server 100.

[0014] The design support server 100 is composed of a CPU, GPU (Graphic Processing Unit), memory, hard disk drive (HDD), etc., executes a design support program to adjust the control parameters of the vehicle control software of vehicle 2, and transmits the adjusted control parameters to vehicle 2 by wireless communication such as Wi-Fi, LTE (Long Term Evolution), 5G (Generation), or wired communication via a communication cable or the like (not shown).

[0015] The design support server terminal 100A is composed of a display device such as a display and input devices such as a keyboard and mouse, accepts the requests of the designer 2, who is a user of the design support device 1, in a free-form description from the keyboard, transmits them to the design support server 100, and displays the control parameters adjusted by the design support server 100 on the display or the like.

[0016] The vehicle 3 includes a measurement device 31 such as a camera or LiDAR (Light Detection And Ranging) that measures the driving environment, vehicle control software 32 for performing various controls of the vehicle, an ECU 33 that executes the vehicle control software 32, an acceleration / deceleration mechanism 34 such as a motor or brake that accelerates and decelerates the vehicle 3 based on the execution results of the vehicle control software 32, a steering mechanism 35 that steers the vehicle 3 based on the execution results of the vehicle control software 32, and the like. Also, the vehicle control software 32 is composed of a plurality of software modules_1~n (321~32n) divided by function.

[0017] Figure 1B shows an example of the hardware configuration of the design support server 100, which consists of a main memory device 110 such as memory, an auxiliary storage device 120 such as an HDD, a processing unit 130 such as a CPU / GPU, and a Large Language Model (LLM) 140. The LLM 140 is not limited to a large language model; any device that performs natural language processing may work, and it may be a general language model or one that performs morphological analysis, etc.

[0018] The main memory 110 stores programs that execute the functions of each of the following parts: the input unit 111, the module selection unit 112, the reference parameter extraction unit 113, the parameter selection unit 114, the output unit 115, the duplicate reference warning unit 116, the duplicate modification warning unit 117, and the non-satisfaction warning unit 118. These programs are executed by the arithmetic processing unit 130, causing each part to function. The main memory 110 also stores a design support program 110A. When the arithmetic processing unit 130 executes the design support program 110A, it uses the aforementioned parts (111-118) and the parts of the auxiliary memory 120 to perform the design support operations described later.

[0019] The auxiliary storage device 120 includes a module storage unit 121, a reference storage unit 122, a parameter storage unit 123, a setting condition storage unit 124, and a setting value storage unit 125. The contents of each part of the auxiliary storage device 120 and the functions and operations of each part of the main storage device 110 will be explained in the series of operation flows of the design support device described later.

[0020] Figure 2 is a functional block diagram of the design support operation of the design support device 1 in the first embodiment, illustrating the processing and signal flow between each part in the hardware configuration diagram shown in Figure 1B. Figure 3 is a flowchart of the design support operation (steps S301 to S311) of the design support device 1 in the first embodiment. The design support operation of the first embodiment will be explained below mainly using Figures 2 and 3.

[0021] <Step S301> The input unit 111 receives a request for free-form text in natural language from the design support server terminal 100A, sends it to the module selection unit 112 and the parameter selection unit 114, and proceeds to step S302.

[0022] <Step S302> First, let's explain the module description information used in this step. Figure 4 shows an example of the data structure of the module storage unit 121, in which the vehicle control software 32 of the vehicle 3 is divided into multiple software modules, each with a name 121A and a natural language description of that function (module description information) 121B are stored in pairs.

[0023] The module selection unit 112 compares the request 201 transmitted from the input unit 111 with the module description information 121B stored in the module storage unit 121, selects the software module related to the behavior of vehicle 3 included in the request 201 as the target module, and sends the name 121A of that target module to the reference parameter extraction unit 113 and the duplicate reference warning unit 116, and proceeds to step S303. For example, if the request 201 was "Keep a safe distance when avoiding pedestrians," the module selection unit 112 compares this request 201 with each description in the module description information 121B in Figure 4, and selects the relevant "avoidance_module" as the target module. This narrows down the software modules that require adjustment for free-form user requests, simplifying the design.

[0024] When the module selection unit 112 compares the request 201 with the module description information 121B to select a target module, a prompt containing the request 201 and the module description information 121B is input to the large-scale language model 140 executed on the design support server 100. The large-scale language model 140 can, for example, extract keywords from both or summarize them, allowing the module selection unit 112 to select the module description information 121B corresponding to the request 201. This allows for highly accurate narrowing down of software modules that require adjustment in response to free-form user requests, thereby simplifying the design process.

[0025] <Step S303> First, let's explain the reference information used in this step. Figure 5 shows an example of the data structure of the reference storage unit 122, where the names 122A of the software modules of the vehicle control software 32 of the vehicle 3 are stored as reference information, with the parameters 122B that they reference indicated by "○".

[0026] The reference parameter extraction unit 113 refers to the module name 122A of the reference information stored in the reference storage unit 122 that matches the target module 121A input from the module selection unit 112, extracts the reference parameter 122B which is a control parameter referenced from the target module, and sends the extracted reference parameter 122B to the parameter selection unit 114 to proceed to step S304. For example, if "avoidance_module" is selected as the target module 121A from the module selection unit 112 and sent to the reference parameter extraction unit 113, the reference parameter extraction unit 113 will extract "min_dist_avo" as the reference parameter 122B. In this way, the control parameters that require adjustment in response to the free-form user requirements can be narrowed down, simplifying the design.

[0027] <Step S304> If multiple target modules are selected in step S302, the reference parameter extraction process in step S303 is repeatedly performed for each of them (resulting in "NO" in step S304), and once processing for all target modules is complete (resulting in "YES" in step S304), the process proceeds to step S305.

[0028] <Step S305> First, we will explain the parameter description information, setting condition information, and setting value information used in this step. Figure 6 is an example of the data structure of the parameter storage unit 123, where the parameter name 123A and its natural language description of its function 123B (parameter description information) are stored in pairs. Figure 7 is an example of the data structure of the setting condition storage unit 124, where the parameter name 124A and its setting condition information (initial value, tolerance range (maximum / minimum value)) 124B are stored in pairs. Figure 8A is an example of the data structure of the setting value storage unit 125, where the parameter name 125A and its past (i.e., current) setting value 125B (setting value information) are stored in pairs.

[0029] The parameter selection unit 114 inputs the request 201 transmitted from the input unit 111, the reference parameter 122B extracted by the reference parameter extraction unit 113, the parameter description information 123B stored in the parameter storage unit 123 for that parameter, the setting condition information 124B stored in the setting condition storage unit 124, and the setting value information 125B stored in the setting value storage unit 125 to the large-scale language model 140. The large-scale language model 140 selects the target parameter from the reference parameter 122B that is related to the behavior of the vehicle 3 included in the request 201, and adjusts the setting value of the target parameter to satisfy the request 201. This allows for highly accurate narrowing down of control parameters that require adjustment for free-form user requests and adjusts the setting values, thereby simplifying the design. The target parameter and setting value (114A) are then transmitted to the setting value storage unit 125, the output unit 115, the non-satisfaction warning unit 118, the duplicate reference warning unit 116, and the duplicate change warning unit 117, and the process proceeds to step S306.

[0030] <Step S306> The setting value storage unit 125 stores (overwrites) the target parameter and setting value 114A transmitted from the parameter selection unit 114 and proceeds to step S307.

[0031] Here, an example of parameter extraction and adjustment in this embodiment will be described. As shown in Figure 8A, the setting value storage unit 125 contains the names 125A and setting values ​​125B of previously adjusted control parameters, and under these conditions, other control parameters are extracted and their setting values ​​are adjusted.

[0032] For example, if request 201 is "Maintain distance when avoiding pedestrians," the prompt containing this request and the parameter description information 123B is input to the large-scale language model 140 for comparison and reference, thereby selecting the relevant "min_dist_avo" as the target parameter. Furthermore, the prompt containing request 201, the setting conditions (initial value, tolerance range (maximum / minimum value)) 124B of the setting condition storage unit 124, and the setting value 125B of the setting value storage unit 125 is input to the large-scale language model 140 for comparison and reference, thereby adjusting "min_dist_avo" from "1.0" to "1.5" as shown in Figure 8B to satisfy the request "Maintain distance."

[0033] This allows for narrowing down the control parameters that need adjustment in response to free-form user requests, and simplifies the design process by adjusting the set values. Furthermore, the setting value storage unit 125 stores the fact that "min_dist_avo" has been adjusted to "1.5," allowing for stepwise adjustment of control parameters by referencing this information when selecting and adjusting control parameters for subsequent requests.

[0034] <Step S307> The non-satisfaction warning unit 118 issues a non-satisfaction warning if there are no suitable module parameters corresponding to request 201, or if the target parameter 114A transmitted from the parameter selection unit 114 is empty. This warning is then displayed, for example, on the screen of the design support server terminal 100A, and the system proceeds to step S308. This informs the designer, who is user 2, that the control parameters have not been adjusted to satisfy request 201.

[0035] <Step S308> The duplicate reference warning unit 116 compares the target module 121A transmitted from the module selection unit 112, the target parameter 114A transmitted from the parameter selection unit 114, and the reference information 122A and B stored in the reference storage unit 122. If the target parameter 114A is referenced by a software module other than the target module 121A, it issues a warning, displays it on the screen of the design support server terminal 100A, and proceeds to step S309. In other words, since there may be parameters that are commonly used (referenced) by multiple software modules, it is possible to inform the designer (user 2) that adjusting the control parameters in response to a request may affect the behavior of other software modules.

[0036] <Step S309> The duplicate change warning unit 23 issues a warning if the target parameter 114A transmitted from the parameter selection unit 114 has been adjusted multiple times (two or more times), displays it on the design support server terminal 100A screen, and proceeds to step S310. This informs the designer (user 2) that the adjustment value of the control parameter for a previous request may have been overwritten by the adjustment of the control parameter for a later request, potentially rendering the parameter adjustment value for the previous request inappropriate.

[0037] <Step S310> The output unit 115 determines whether a termination command, which is an indication of the user 2's intention to finish parameter adjustment, has been received from the design support server terminal 100A. If it is determined that the command has been received (YES in step S310), the process proceeds to step S311. If it is determined that the command has not been received (NO in step S310), that is, if there are still unprocessed requests 201, the process returns to step S301 to receive the request 201 from user 2 and repeats the processing from step S302 onwards.

[0038] <Step S311> The output unit 115 sends the target parameters and latest settings for all processed requests 201 to the vehicle 3, and then terminates the design support operation.

[0039] As described above, according to this embodiment, by using natural language processing for design support, it is possible to identify control parameters that should be changed in response to free-form text requests and adjust their values ​​to adjust the vehicle's behavior. [Examples]

[0040] Figure 9 shows an example of the hardware configuration of the design support server 100' in a second embodiment of the present invention, which is a modification of some of the configurations of the first embodiment described above. The same reference numerals are used for elements that are the same as in the first embodiment, and the differences will be described below.

[0041] The main memory 110' is equipped with an evaluation unit 119 in place of the duplicate reference warning unit 116, duplicate change warning unit 117, and non-satisfaction warning unit 118 in the first embodiment (Figure 1B), and the auxiliary memory 120' is equipped with a setting history storage unit 126 and a scenario storage unit 127 in place of the setting value storage unit 125 in the first embodiment (Figure 1B).

[0042] Figure 10 is a functional block diagram of the design support operation of the design support device 1 in the second embodiment, illustrating the processing and signal flow between each part in the hardware configuration diagram shown in Figure 9. Figure 11 is a flowchart of the design support operation (steps S1101 to S1110) of the design support device 1 in the second embodiment. The design support operation of the second embodiment will be explained below mainly using Figures 10 and 11. <Step S1101> The input unit 111 sends the free-text request 201 transmitted from the design support server terminal 100A to the module selection unit 112, the parameter selection unit 114, the setting history storage unit 126, and the evaluation unit 119, and proceeds to step S1102.

[0043] <Step S1102> The module selection unit 112 compares the request 201 transmitted from the input unit 111 with the module description information 121B stored in the module storage unit 121, selects a software module related to the behavior of the vehicle 3 included in the request 201 as the target module, and transmits the name 121A of the target module to the reference parameter extraction unit 113 to proceed to step S1103. In addition, as in the first embodiment, when the module selection unit 112 selects a target module by comparing the request 201 with the module description information 121B, a prompt containing the request 201 and the module description information 121B is input to the large-scale language model 140 executed on the design support server 100.

[0044] <Step S1103> The reference parameter extraction unit 113 refers to the module name 122A of the reference information stored in the reference storage unit 122 that matches the target module 121A input from the module selection unit 112, extracts the reference parameter 122B which is a control parameter referenced from the target module, and transmits the extracted reference parameter 122B to the parameter selection unit 114 to proceed to step S1104.

[0045] <Step S1104> If multiple target modules are selected in step S1102, the reference parameter extraction process in step S1103 is repeatedly performed for each of them (resulting in "NO" in step S1104). Once processing for all target modules is complete (resulting in "YES" in step S1104), the process proceeds to step S1105.

[0046] <Step S1105> First, let's explain the setting history information used in this step. Figure 12A is an example of the data structure of the setting history storage unit 126, which includes past requests 126A, the names of the adjusted control parameters 126B, the setting values ​​before adjustment 126C, and the setting values ​​after adjustment 126D.

[0047] The parameter selection unit 114 inputs the request 201 transmitted from the input unit 111, the reference parameter 122B input from the reference parameter extraction unit 113, the parameter description information 123B stored in the parameter storage unit 123, the setting condition information 124B stored in the setting condition storage unit 124, and the installation history information 126A to D stored in the setting history storage unit 126 to the large-scale language model 140. The large-scale language model 140 selects the target parameter from the reference parameter 122B that is related to the behavior of vehicle 3 included in the request 201, and adjusts the setting value of the target parameter to satisfy the request 201.

[0048] For example, as shown in Figure 12A, if the previous request was "Maintain distance when avoiding pedestrians" and the parameter "min_dist_avo" was adjusted from "1.0" to "1.5", and the current request is "Maintain more distance when avoiding pedestrians" as shown in Figure 12B, then by comparing the current request with the previous request and the setting values ​​before and after adjustment, the parameter "min_dist_avo" is adjusted, for example, from "1.5" to "2.0" to satisfy the request "Maintain more distance", and this adjusted value is stored in the setting history storage unit 126 as described later. This makes it possible to readjust control parameters step by step in response to free-form user requests, simplifying the design.

[0049] Then, the target parameter and setting value (114A) are sent to the setting history storage unit 126, the output unit 115, and the evaluation unit 119, and the process proceeds to step S1106.

[0050] <Step S1106> The setting history storage unit 126 stores the request 201 transmitted from the input unit 111 and the target parameter and setting value (114A) transmitted from the parameter selection unit 114, and proceeds to step S1107.

[0051] <Step S1107> First, let's explain the scenario description information used in this step. Figure 13 shows an example of the data structure of the scenario storage unit 127, in which a natural language description 127B of the content of various simulation programs (simulators) held by the evaluation unit 119 and a scenario number 127A that identifies them are stored in pairs.

[0052] The evaluation unit 119 inputs a prompt to the large-scale language model 140 that includes the request 201 transmitted from the input unit 111 and the scenario description information (127A, B) stored in the scenario storage unit 127. The large-scale language model 140 narrows down the simulation scenarios suitable for evaluating the adjusted control parameters and proceeds to step S1108. For example, if the request 201 is "Keep more distance when avoiding pedestrians," the system compares this request 201 with each scenario description 127B to select "Pass pedestrians on a straight road," where scenario number 127A is "2." This narrows down the simulation scenarios suitable for evaluating free-form user requests, making it easier to evaluate the results of adjusting the control parameters.

[0053] <Step S1108> The evaluation unit 119 performs a control simulation using the adjusted control parameters 114A under the narrowed-down simulation scenario. The simulation results are displayed on the design support server terminal 100A, including, for example, an autonomous driving simulation, charts, histograms, and distribution diagrams for each signal (speed, acceleration, distance to pedestrians, etc.), which allow for confirmation of changes in behavior in relation to requirement 201, and the process proceeds to step S1109.

[0054] <Step S1109> The output unit 115 determines whether a termination command has been received from the design support server terminal 100A. If it is determined that a termination command has been received (YES in step S1109), the process proceeds to step S1110. If it is determined that a termination command has not been received (NO in step S1109), the process returns to step S1101 to receive the next request 201 from the user and repeats the processing from step S1102 onwards.

[0055] <Step S1110> The output unit 115 sends the target parameters and latest settings for all processed requests 201 to the vehicle 3, and then terminates the design support operation.

[0056] As described above, according to this embodiment, by using natural language processing for design support, it is possible to identify control parameters that should be changed in response to free-form text requests, adjust their values ​​to adjust the vehicle's behavior, and select an appropriate simulation scenario to verify the validity of those parameter values.

[0057] Furthermore, each of the above embodiments can be modified as appropriate to the extent possible, and components of one embodiment can be incorporated into another embodiment. For example, LLM140 may be located in an external cloud or the like, and does not have to be specifically trained for the design support device of this embodiment.

[0058] Furthermore, in each of the above embodiments, the output unit 115 selects the target parameter in response to the request, adjusts its setting value, and transmits it to the vehicle 3. However, it is also possible to transmit only the selected target parameter to the design support server terminal 100A, and have the user 2 adjust its setting value and then transmit it to the vehicle 3.

[0059] Furthermore, by providing the vehicle 3 with a request receiving unit that receives requests for free-form text and transmits them to the design support server 100 (100'), control parameters may be adjusted in response to the free-form text requests from the driver of the vehicle 3, thereby adjusting the vehicle's behavior to match the driver's preferences.

[0060] Furthermore, the duplicate reference warning unit 116, the duplicate modification warning unit 117, and the non-satisfaction warning unit 118 of Example 1 may be incorporated into the configuration of Example 2 as needed. [Explanation of Symbols]

[0061] 1:Design support equipment 2: User 3: Vehicles 100: Design support server 100A: Design support server terminal 110: Main memory 111: Input section 112: Module Selection Section 113: Reference parameter extraction unit 114: Parameter Selection Section 115: Output section 116: Duplicate reference warning section 117: Duplicate Change Warning Section 118: Insufficient Warning Section 110A: Design support program 120:Auxiliary storage device 121: Module Storage Unit 122:Reference storage 123: Parameter storage unit 124: Setting Condition Memory Unit 125: Setting value storage unit 130: Arithmetic Processing Unit 140: Large-scale language models

Claims

1. An input unit that accepts requests regarding vehicle behavior described in natural language, A module selection unit selects a software module related to the behavior of the vehicle included in the request as a target module, based on a first processing result obtained by natural language processing, with respect to module description information that describes the functions of software modules divided into functional units for the vehicle control software of the vehicle in natural language and the request, A reference parameter extraction unit extracts reference parameters, which are control parameters of the vehicle referenced by the target module. A parameter selection unit selects target parameters related to the vehicle behavior included in the request based on a second processing result obtained by natural language processing, with respect to parameter description information that describes the function of the reference parameter in natural language and the request. A design support device comprising an output unit that outputs the aforementioned target parameters.

2. A design support device according to claim 1, The parameter selection unit sets the setting value of the target parameter based on the second processing result, which further includes the processing result of setting condition information including the initial value and tolerance range of the target parameter and the request.

3. A design support device according to claim 2, The parameter selection unit retrieves a setting value for a target parameter that was previously set from the storage device. A design support device that sets the setting values ​​of other target parameters under the condition that the setting value of one target parameter is set.

4. A design support device according to claim 2, If a setting value has been previously set for a target parameter that is the same as the target parameter associated with the second request received by the input unit, the parameter selection unit obtains setting history information from the storage device, including the previously set setting value for the target parameter and the first request corresponding to that setting value. A design support device that sets the setting value of the first target parameter based on the second processing result, which further includes the result obtained by natural language processing, in response to the setting history information related to the first target parameter and the second request.

5. A design support device according to claim 1, The module selection unit is a design support device that acquires the first processing result output in response to inputting a prompt containing the request and the module description information into a language model.

6. A design support device according to claim 1, The parameter selection unit is a design support device that acquires the second processing result output in response to inputting a prompt containing the request and the parameter description information into a language model.

7. A design support device according to claim 1, A non-satisfaction warning unit that issues a non-satisfaction warning if the aforementioned target parameter does not exist, A design support device equipped with this device.

8. A design support device according to claim 1, A design support device comprising: a duplicate reference warning unit that issues a duplicate reference warning when the target parameter is referenced from a module other than the target module.

9. A design support device according to claim 3, A design support device comprising a duplicate change warning unit that issues a duplicate change warning when the same parameter is changed multiple times.

10. A design support device according to claim 2, A design support device comprising: an evaluation unit that evaluates the behavior of the vehicle control software in relation to the set value of the target parameter.

11. A design support device according to claim 10, The evaluation unit is a design support device that selects the evaluation scenario based on a third processing result obtained by natural language processing in response to scenario description information indicating the content of the evaluation scenario for the vehicle control software and the request.

12. A design support device according to claim 11, The evaluation unit is a design support device that acquires a third processing result output in response to inputting a prompt containing the request and the scenario description information into a language model.

13. An input unit that accepts requests regarding vehicle behavior described in natural language, The vehicle's control software includes a module storage unit that stores module description information that explains the functions of software modules, which are divided into functional units, in natural language. A parameter storage unit that stores parameter description information in natural language that describes the function of the vehicle control parameters referenced by a software module related to the vehicle's behavior included in the request, A design support device comprising: an output unit that outputs the control parameters to which the parameter description information related to the request is associated, among the control parameters referenced by a software module to which the module description information related to the request is associated, the control parameters to which the parameter module description information related to the request is associated, the design support device.

14. An input process that accepts requests regarding vehicle behavior described in natural language, The vehicle control software of the vehicle comprises module description information that describes the functions of software modules divided into functions in natural language, and the request, and based on a first processing result obtained by natural language processing, a module selection process is performed to select a software module related to the behavior of the vehicle included in the request as the target module. A reference parameter extraction process for extracting reference parameters, which are control parameters of the vehicle referenced by the target module, A parameter selection process that selects target parameters related to the vehicle behavior included in the request based on a second processing result obtained by natural language processing, with respect to parameter description information that describes the function of the reference parameter in natural language and the request, Output processing to output the aforementioned target parameter, A design support method having [a certain feature].

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