Method and apparatus for converting interface of automatic train operation(ATO)

Abstract

One embodiment of the present invention provides an interface conversion method performed by at least one processor. The method comprises the steps of: receiving interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of an automatic train operation device; extracting attribute values ​​from the interface data and classifying the interface data according to the identification number of each of the first interfaces to create an interface-specific data group; and creating a header for each of the data groups based on the attribute values ​​of the interface-specific data included in each of the data groups, and summing the headers for each of the data groups to create a converted interface that converts the first interfaces.

Description

Technology Field

[0001] The present invention relates to a method and apparatus for converting an interface of an automatic train driving device, and more specifically, to a method and apparatus for converting an interface by extracting attribute values ​​from interface data received from a test specimen, generating a header for each data group classified according to an identification number, and summing the headers for each data group to generate a converted interface. Background Technology

[0002] The Automatic Train Operation System (ATM) receives driving information through interfaces with other devices within the vehicle and transmits propulsion and braking commands for vehicle control. In this process, the interface specifications of the ATM vary by manufacturer, and these differences act as a major constraint on the configuration and operation of the test environment.

[0003] Current testers require the manual configuration of interface specifications from various manufacturers to interoperate with automated train operation systems. In particular, specifications for connecting devices, including vehicle controllers, must be matched to simulate the physical interfaces of all devices connecting the test specimen and the tester. This necessitates the repetitive task of verifying and configuring interfaces for every test, resulting in significant inefficiency during the test preparation phase.

[0004] Furthermore, the test preparation process requires verifying and inputting the specifications and periodicity information of data transmitted and received from each interface, which entails a procedure to obtain accurate test data. However, interface specifications differing by manufacturer complicate this task, leading to increased preparation time and a higher possibility of data processing errors.

[0005] To solve this problem, prior art 1 is presented, which is an invention relating to a system for processing an integrated interface to efficiently control different interfaces when the interfaces are different.

[0006] However, although prior art 1 creates an integrated interface, it has the limitation that the interface configuration must be reconfigured if the tester is changed.

[0007] Furthermore, existing testers adopted a method of manually correcting or reconfiguring differences in the interface of the test target; however, this is inefficient in terms of time and cost and causes an increase in the workload of test personnel due to repetitive tasks.

[0008] To address this, there is a need for an interface conversion method and device that can reduce the time and cost required to configure the test environment by converting each different interface configuration into a common interface when testing test specimens and loading the training script of previously trained interface data. Prior art literature

[0009] (Prior Art 1) Korean Patent Publication No. 10-2021-0067289 "Integrated Interface Processing System" (Published June 8, 2021) The problem to be solved

[0010] To solve the aforementioned technical problem, the present invention aims to provide a method and system for converting the interface of a test specimen by extracting and classifying interface data received from the test specimen to create data groups, creating headers for each data group, and summing the created headers to the data groups.

[0011] The technical problems that the present invention aims to solve are not limited to the technical problems described above, and other technical problems of the present invention may be derived from the following description. means of solving the problem

[0012] To solve the aforementioned technical problem, one embodiment of the present invention provides an interface conversion method performed by at least one processor. The method comprises the steps of: receiving interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of an automatic train operation device; extracting attribute values ​​from the interface data and classifying the interface data according to the identification number of each of the first interfaces to create an interface-specific data group; and creating a header for each of the data groups based on the attribute values ​​of the interface-specific data included in each of the data groups, and summing the headers for each of the data groups to create a converted interface that converts the first interfaces.

[0013] Additionally, another embodiment of the present invention provides an interface conversion system. The system comprises a communication module, at least one processor, and a memory electrically connected to the processor and storing at least one code executed by the processor. The memory stores a code that, when executed through the processor, causes the processor to receive interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of the automatic train operation device, extract attribute values ​​from the interface data, classify the interface data according to the identification number of each of the first interfaces to create an interface-specific data group, create a header for each of the data groups based on the attribute values ​​of the interface-specific data included in each of the data groups, and sum the headers to each of the data groups to create a converted interface that converts the first interfaces. Effects of the invention

[0014] According to the means for solving the problem of the present invention described above, the test environment preparation time can be shortened by automatically processing interface differences by manufacturer.

[0015] In addition, according to the means for solving the problem of the present invention described above, efficiency can be increased by utilizing a saved script without reconfiguring the interface when changing the test specimen.

[0016] In addition, according to the means for solving the problem of the present invention described above, the cost required for test preparation can be reduced.

[0017] In addition, according to the means for solving the problem of the present invention described above, the precision and speed of testing can be improved by automating data analysis and management tasks.

[0018] In addition, according to the means for solving the problem of the present invention described above, flexibility can be provided by customizing the existing learning script when changing the test specimen.

[0019] In addition, according to the means for solving the problem of the present invention described above, the versatility of the test equipment can be enhanced by integrating a physical interface that supports various communication methods.

[0020] In addition, according to the means for solving the problem of the present invention described above, repetitive tasks during the test preparation process can be reduced, thereby increasing the work efficiency of the worker.

[0021] The effects of the present invention are not limited to the effects described above, but include all effects understood from the following description. Brief explanation of the drawing

[0022] FIG. 1 is a diagram illustrating an interface conversion device according to one embodiment of the present invention that is communicationally connected to a test specimen and a tester. Figure 2 is a diagram showing the detailed configuration of the interface conversion device illustrated in Figure 1. FIG. 3 is a conceptual diagram showing another example of the interface conversion device illustrated in FIG. 1 and FIG. 2, and the interface conversion device being connected to an automatic train driving device and a tester to provide a common interface. Figure 4 is a flowchart illustrating an example of the process in which an interface conversion device converts an interface. FIG. 5 is a flowchart illustrating the sequence of an interface conversion method according to another embodiment of the present invention. FIG. 6 is a flowchart illustrated to explain additional steps included in the interface conversion method illustrated in FIG. 5. Specific details for implementing the invention

[0023] The present invention will be described in detail below with reference to the attached drawings. However, the present invention may be embodied in various different forms and is not limited to the embodiments described herein. Furthermore, the attached drawings are intended only to facilitate understanding of the embodiments invented in this specification, and the technical concept invented in this specification is not limited by the attached drawings. All terms used herein, including technical and scientific terms, should be interpreted in the sense generally understood by those skilled in the art to which the present invention pertains. Terms defined in advance should be interpreted as having additional meanings consistent with relevant technical literature and the currently invented content, and unless otherwise defined, should not be interpreted in a highly ideal or restrictive sense.

[0024] In order to clearly explain the invention in the drawings, parts unrelated to the explanation have been omitted, and the size, form, and shape of each component shown in the drawings may be varied. Throughout the specification, identical or similar parts are denoted by identical or similar reference numerals.

[0025] In the following description, suffixes such as "part," "module," and "function" regarding components are assigned or used interchangeably solely for the ease of drafting the specification, and do not inherently possess distinct meanings or roles. Furthermore, in describing the embodiments invented in this specification, detailed descriptions of related prior art have been omitted where it is determined that such detailed descriptions could obscure the essence of the embodiments invented in this specification.

[0026] Throughout the specification, when it is stated that a part is "connected (connected, contacted, or coupled)" to another part, this includes not only cases where they are "directly connected (connected, contacted, or coupled)," but also cases where they are "indirectly connected (connected, contacted, or coupled)" with other members interposed therebetween. Furthermore, when it is stated that a part "includes (provides, or provides)" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but rather allows for additional "included (provided, or provided)" of other components.

[0027] Terms indicating ordinal numbers, such as "first," "second," etc., used herein are used solely for the purpose of distinguishing one component from another and do not limit the order or relationship of the components. For example, the first component of the present invention may be named the second component, and similarly, the second component may be named the first component. Singular forms used herein should be interpreted to include plural forms unless explicitly to the contrary.

[0028] Throughout the specification, the common interface is substantially identical to the conversion interface. That is, since the interface conversion device according to one embodiment of the present invention converts the interface of the test specimen to generate a conversion interface and provides it to the test device, the conversion interface generated by the automatic train operation device and provided to the test device is substantially identical to the common interface.

[0029] FIG. 1 is a diagram illustrating an interface conversion device according to one embodiment of the present invention that is connected to a train automatic driving device and a tester.

[0030] The interface conversion device (100) is communicationally connected to the automatic train operation device (300) and can receive interface data from the automatic train operation device (300). The interface conversion device (100) can generate a common interface based on the interface data received from the automatic train operation device (300) and transmit the generated common interface to the test device (400). The automatic train operation device (300) may include a plurality of interfaces and may provide interface data for each interface to the interface conversion device (100) and the test device (400). The types of interfaces provided by the automatic train operation device (300) and the interfaces compatible with the test device (400) may differ, and the types of interfaces compatible with the test device (400) may include serial communication interfaces, Ethernet communication interfaces, and DIO (Digital Input / Output). Serial communication interfaces may include RS232, RS422, RS485, SPI, and Profibus.

[0031] The automatic train operation device (300) may be a test subject subject to performance inspection by a test device (400). The test device (400) may be a device separately provided to inspect the performance of the automatic train operation device (300).

[0032] Figure 2 is a diagram showing the detailed configuration of the interface conversion device illustrated in Figure 1.

[0033] The interface conversion device (100) can be implemented in the form of a computing device or various smart devices and can operate in a cloud computing service model such as SaaS (Software as a Service), PaaS (Platform as a Service), or IaaS (Infrastructure as a Service). Additionally, the interface conversion device (100) may be built in the form of a private cloud, a public cloud, or a hybrid cloud system, but the scope of the present invention is not limited thereto.

[0034] The interface conversion device (100) can be implemented as a computer or portable terminal capable of connecting to a server or other terminal via a network. Here, the computer includes, for example, a notebook, desktop, or laptop equipped with a web browser, and the portable terminal can include, for example, a wireless communication device that ensures portability and mobility, and can include all types of handheld-based wireless communication devices such as various types of communication-based terminals, smartphones, tablet PCs, etc. Additionally, the portable terminal may be an edge device or an on-device AI having at least one processor capable of performing artificial intelligence model inference tasks. The network can be implemented as a wired network such as a Local Area Network (LAN), Wide Area Network (WAN), or Value Added Network (VAN), or any type of wireless network such as a mobile radio communication network or a satellite communication network.

[0035] Referring to FIG. 2, the interface conversion device (100) includes a communication module (110), a processor (120) that performs operations according to code stored in memory (130), and a memory (130) that stores code.

[0036] The communication module (110) may include a device comprising hardware and software necessary to transmit and receive signals, such as control signals or data signals, through a wired or wireless connection with another network device. It transmits and receives wireless signals with at least one of a base station, an external terminal, or a server on a mobile communication network built according to technical standards or communication methods for mobile communication used in the mobile communication module (e.g., GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), CDMA2000 (Code Division Multi Access 2000), EV-DO (Enhanced Voice-Data Optimized or Enhanced Voice-Data Only), WCDMA (Wideband CDMA), HSDPA (High Speed ​​Downlink Packet Access), HSUPA (High Speed ​​Uplink Packet Access), LTE (Long Term Evolution), LTEA (Long Term Evolution-Advanced), etc.).

[0037] The interface conversion device (100) can be connected to the train automatic driving device (300) and the test device (400) via a communication module (110).

[0038] The processor (120) may include various types of devices for controlling and processing data. The processor (120) may refer to a data processing device embedded in hardware having a physically structured circuit to perform a function expressed by code or instructions included in a program. In one example, the processor (120) may be implemented in the form of a microprocessor, a central processing unit (CPU), a processor core, a multiprocessor, an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc., but the scope of the invention is not limited thereto.

[0039] The memory (130) can store at least one of the information and data input to the communication module (110), the information and data required for the function performed by the processor (120), and the data generated according to the execution of the processor (120).

[0040] Memory (130) should be interpreted as a general term for non-volatile storage devices that retain stored information even when power is not supplied, and volatile storage devices that require power to retain stored information. In addition to volatile storage devices that require power to retain stored information, memory (130) may include cloud storage, SSD, magnetic storage media, or flash storage media, but the scope of the present invention is not limited thereto.

[0041] Memory (130) is electrically connected to the processor (120) and stores at least one code that is executed by the processor (120). Memory (130) stores code that causes the processor (120) to perform the following functions and procedures when executed through the processor (120).

[0042] The memory (130) stores code that causes the processor (120) to receive at least one test interface from the train automatic driving device (300).

[0043] The memory (130) stores code that causes the processor (120) to receive interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of the train automatic driving device.

[0044] Memory (130) stores code that causes the processor (120) to extract attribute values ​​from the interface data and classify the interface data according to the identification number of each of the first interfaces to create an interface-specific data group. The attribute values ​​may include one or more of an identification number, an interface type, and the size of a specific data among the interface data. Data groups may be created for each interface identification number. For example, assuming that test interfaces are received from interface 1, interface 2, and interface 3, the interface data extracted from interface 1 may be classified as data X, the interface data extracted from interface 2 as data Y, and the interface data extracted from interface 3 as data Z to create each data group.

[0045] The memory (130) stores code that causes the processor (120) to generate a header for each of the data groups based on the attribute values ​​of the interface-specific data included in each of the data groups, and to generate a converted interface that converts the first interfaces by summing the headers for each of the data groups.

[0046] Memory (130) may further store code that causes the processor (120) to generate an attribute vector for each of the data groups based on the attribute values. Memory (130) may further store code that causes the processor (120) to define an attribute combination matrix for each of the data groups based on the attribute vectors. Memory (130) may further store code that causes the processor (120) to generate the header for each of the data groups by taking an inner product of the attribute combination matrix and the attribute vectors. The attribute combination matrix is ​​the group policy matrix to be mentioned below. It can be named as such. The attribute vector and the attribute combination matrix will be described below with reference to FIGS. 3, FIGS. 4 and Example 1.

[0047] The memory (130) may further store code that causes the processor (120) to generate a learning result script for the interface data through a pre-configured learning model. The learning model may be trained to take the interface data as learning data and, when receiving specific interface data, output a learning result script for the specific interface.

[0048] The memory (130) may further store code that causes the processor (120) to transmit the conversion interface to a tester (400) that checks the performance of the automatic train driving device (300). The conversion interface may store the learning result script.

[0049] FIG. 3 is a conceptual diagram showing another example of the interface conversion device illustrated in FIG. 1 and FIG. 2, and the interface conversion device being connected to an automatic train driving device and a tester to provide a common interface.

[0050] Referring to FIG. 3, the interface conversion device (200) may include a second interface (210) and a data learning unit (220), and may provide a common interface (230) to a tester (400).

[0051] The interface conversion device (200) is substantially the same as the interface conversion device (100) illustrated in FIGS. 1 and 2. That is, the operations and functions of the interface conversion device (200) can be performed identically by the processor (120) and memory (130) of the interface conversion device (100). Therefore, redundant descriptions will be omitted.

[0052] Figure 4 is a flowchart illustrating an example of the process in which an interface conversion device converts an interface.

[0053] The processes described below are performed by the interface conversion device (200) shown in FIG. 3, and can also be performed in the same way by the processor (120) and memory (130) of the interface conversion device (100) shown in FIG. 1 and FIG. 2. Hereinafter, an example of the process of the interface conversion device (100) converting an interface will be described with reference to FIG. 3 and FIG. 4.

[0054] The first train automatic driving device (310) transmits interface data of each of the first interfaces (311) to the interface conversion device (200) via the interface conversion device (100). The first interface (311) may include interface 1 (IF 1), interface 3 (IF 3), interface 4 (IF 4), and interface 6 (IF 6). The second train automatic driving device (320) transmits interface data of each of the first interfaces (311') to the interface conversion device (200) via the interface conversion device (100). The first interface (311') may include interface 1 (IF 1), interface 2 (IF 2), and interface 5 (IF 5). When the interface conversion device (200) receives interface data from the first train automatic driving device (310) and the second train automatic driving device (320), it may receive the data using the second interface (210) corresponding to each of the interfaces included in the first interface (311) (311'). The interface conversion device (200) may support all physical interfaces that can be connected between the first train automatic driving device (310) and the second train automatic driving device (320) and the tester (400).

[0055] The interface conversion device (200) defines a group of data by assigning an identifier to the data received from the first train automatic driving device (310) and the second train automatic driving device (320). For example, data received from IF 1 of the first train automatic driving device (310) may be defined as data X, data received from IF 3 of the first train automatic driving device (310) may be defined as data Z, data received from IF 1 of the second train automatic driving device (320) may be defined as data X', and data received from IF 2 of the second train automatic driving device (320) may be defined as data Y.

[0056] The interface conversion device (200) extracts attribute values ​​of the data included in each data group through analysis of the defined data group and generates an attribute vector for each data group based on the attribute values ​​(S11). The attribute values ​​may include an interface number, an interface type, a data size, and a byte value of a specific data. The attribute vector can be expressed by the following mathematical formula 1.

[0057]

[0058] In the above mathematical formula 1, represents the attribute vector of data X. represents the attribute value of each data. For example, is the interface number, is a type of interface, can mean the size of the data. represents the number of attribute values. represents the matrix transpose. As shown in Equation 1, the attribute vector for each data group can be expressed as an M by 1 matrix obtained by transposing a 1 by M matrix.

[0059] The interface conversion device (200) is based on the attribute value and group policy and attribute vector Data group headers by performing an inner product A header is generated (S13). Subsequently, the header is summed with each of the data included in the data group to generate the final data (S14). Additionally, the interface conversion device (200) stores the final data script and further stores the learning result scripts of the data received from each interface. The final data script may be generated based on the final data learned by the data learning unit (220), and the learning result script may be generated based on the interface data learned by the data learning unit (220). By storing the learning result script, the previously stored script is uploaded whenever the test object is changed, so there is no need to reconfigure the interface configuration when the test object is changed. Additionally, when the test object is changed, the script can be customized to fit the test object by modifying the previously stored script. The interface conversion device (200) may include a separate database (not shown), and the database may store learning information of the interface data, preset settings for each interface, and raw data collected from the interface.

[0060] Subsequently, the interface conversion device (200) generates a common interface (230) based on the generated final data and transmits the common interface (230) to the tester (400). At this time, the final data script can also be transmitted to the tester (400). The common interface (230) transmitted to the tester (400) supports a bandwidth sufficient to transmit all data received by the interface conversion device (200).

[0061] FIG. 5 is a flowchart illustrating the sequence of an interface conversion method according to another embodiment of the present invention.

[0062] The interface conversion method described below can be performed by the interface conversion device (100) and the interface conversion device (200) described above with reference to FIGS. 1 to 4. Accordingly, the description of the embodiment of the present invention described above with reference to FIGS. 1 to 4 can be applied in the same way to the embodiment described below, and any content that overlaps with the description above will be omitted. The steps described below do not necessarily have to be performed in order, the order of the steps can be set in various ways, and the steps may be performed almost simultaneously.

[0063] Referring to FIG. 5, the interface conversion method includes an interface data reception step (S110), an attribute value extraction and data group creation step (S120), a header creation and conversion interface creation step (S130), a learning result script creation step (S140), and a conversion interface transmission step (S150).

[0064] The interface data reception step (S110) is a step of receiving interface data of each of the first interfaces (311)(311') using the second interfaces (210) corresponding to each of the first interfaces (311)(311') of the train automatic driving device (300).

[0065] The attribute value extraction and data group creation step (S120) is a step of extracting attribute values ​​from interface data and classifying interface data according to the identification number of each of the first interfaces (311)(311') to create interface-specific data groups. The attribute values ​​may include one or more of an identification number, an interface type, and the size of a specific data among the interface data.

[0066] The header generation and conversion interface generation step (S130) is a step of generating a header for each data group based on the attribute values ​​of the interface-specific data included in each data group, and generating a conversion interface that converts the first interfaces by summing the headers for each data group.

[0067] The learning result script generation step (S140) is a step of generating a learning result script for the interface data through a pre-configured learning model. The learning model may be trained to use the interface data as learning data and to output a learning result script for the specific interface data when a specific interface is received.

[0068] The conversion interface transmission step (S150) is a step of transmitting the conversion interface (230) to a tester (400) that checks the performance of the automatic train driving device (300). The conversion interface (230) can store a learning result script.

[0069] Referring to FIG. 6, the header generation and transformation interface generation step (S130) may include an attribute vector generation step (S131), an attribute combination matrix definition step (S132), and a header generation step (S133).

[0070] The step of generating attribute vectors for data groups (S131) ​​is a step of generating attribute vectors for each data group based on attribute values. The step of defining an attribute combination matrix (S132) is a step of defining an attribute combination matrix for each data group based on attribute vectors. The step of generating headers (S133) is a step of generating the headers for each data group by performing an inner product of the attribute combination matrix and the attribute vectors.

[0071] The interface conversion method of the embodiments of the present invention described above may also be implemented in the form of a recording medium containing computer-executable instructions, such as program modules executed by a computer. A computer-readable medium may be any available medium accessible by a computer and includes both volatile and non-volatile media, as well as removable and inseparable media. Additionally, a computer-readable medium may include a computer storage medium. A computer storage medium includes both volatile and non-volatile, removable and inseparable media implemented by any method or technique for storing information such as computer-readable instructions, data structures, program modules, or other data.

[0072] A person skilled in the art to which the present invention pertains will understand that, based on the foregoing description, other specific forms can be easily modified without altering the technical spirit or essential features of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims set forth below, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present invention. The scope of the present invention is defined by the claims set forth below rather than by the detailed description above, and all modifications or variations derived from the meaning and scope of the claims and equivalent concepts thereof should be interpreted as being included within the scope of the present invention. Explanation of the symbols

[0073] 100: Interface conversion device 200: Interface conversion device 300: Automatic Train Operation System 400: Tester

Claims

Claim 1 An interface conversion method performed by at least one processor, comprising: a) receiving interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of an automatic train operation device; b) extracting attribute values ​​from the interface data and classifying the interface data according to the identification number of each of the first interfaces to create an interface-specific data group; c) creating a header for each of the data groups based on the attribute values ​​of the interface-specific data included in each of the data groups, and summing the headers for each of the data groups to create a converted interface that converts the first interfaces; wherein step c) further comprises: c-1) creating an attribute vector for each of the data groups based on the attribute values; c-2) defining an attribute combination matrix for each of the data groups based on the attribute vectors; and c-3) creating the header for each of the data groups by performing an inner product of the attribute combination matrix and the attribute vectors. Claim 2 An interface conversion method according to claim 1, wherein the attribute value includes one or more of the identification number, the interface type, and the size of a specific data among the interface data. Claim 3 delete Claim 4 An interface conversion method according to claim 1, further comprising the step of d) generating a learning result script for the interface data through a pre-set learning model. Claim 5 An interface conversion method according to claim 4, wherein the learning model is trained to use the interface data as learning data and to output a learning result script for the specific interface data when receiving specific interface data. Claim 6 In paragraph 4, the interface conversion method further comprises the step of transmitting the conversion interface to a tester that checks the performance of the train automatic driving device, wherein the conversion interface stores the learning result script. Claim 7 Communication module; at least one processor; An interface conversion device comprising a memory electrically connected to the processor and storing at least one code executed in the processor, wherein the memory stores a code that, when executed through the processor, causes the processor to receive interface data of each of the first interfaces using second interfaces corresponding to each of the first interfaces of the automatic train operation device, extract attribute values ​​from the interface data, classify the interface data according to the identification number of each of the first interfaces to create an interface-specific data group, create a header for each of the data group based on the attribute values ​​of the interface-specific data included in each of the data group, and sum the headers to each of the data groups to create a converted interface that converts the first interfaces, and the memory further stores a code that causes the processor to create an attribute vector for each of the data groups based on the attribute values, define an attribute combination matrix for each of the data groups based on the attribute vectors, and create a header for each of the data groups by performing an inner product of the attribute combination matrix and the attribute vectors. Claim 8 An interface conversion device according to claim 7, wherein the attribute value comprises one or more of the identification number, the interface type, and the size of a specific data among the interface data. Claim 9 delete Claim 10 In claim 7, the interface conversion device, wherein the memory further stores code that causes the processor to generate a learning result script for the interface data through a pre-set learning model. Claim 11 An interface conversion device according to claim 10, wherein the learning model is trained to use the interface data as learning data and to output a learning result script for the specific interface data when receiving specific interface data. Claim 12 An interface conversion device according to claim 10, wherein the memory further stores code that causes the processor to transmit the conversion interface to a tester that checks the performance of the automatic train driving device, and the conversion interface stores the learning result script.

Images