Configuration method and device of vehicle scheduling system
By constructing a cross-document semantic alignment model and dynamic rule adaptation, the problem of insufficient collaboration of multi-source heterogeneous documents in the configuration of vehicle dispatching system is solved, realizing an efficient and accurate configuration process and significantly improving configuration efficiency and reliability.
Patent Information
- Application Number
- CN202511155700.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-18
- Publication Date
- 2026-01-02
AI Technical Summary
The existing vehicle dispatching system suffers from insufficient collaboration among multi-source heterogeneous documents during configuration, leading to inefficiency, semantic ambiguity, and difficulties in version adaptation.
By constructing a cross-document semantic alignment model, interface variables, UI controls, and ID encoding rules are automatically mapped to eliminate the semantic gap across documents, enabling dynamic rule adaptation and version iteration. A rule-data dual-drive generator is designed to support automatic parameter realignment after document changes, ensuring that the accuracy of version iteration reaches over 95%.
It significantly improves the configuration efficiency of the vehicle dispatching system, reduces the workload of manual verification, improves the accuracy and reliability of configuration, and reduces the overall time consumption.
Smart Images
Figure CN121257501A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of machine learning technology, and in particular to a configuration method and apparatus for a vehicle dispatching system. Background Technology
[0002] Vehicle dispatching systems are used for real-time monitoring and intelligent route optimization, providing accurate arrival time estimates and ensuring driving safety. They play a crucial role in the rail transit industry.
[0003] Currently, the configuration process of vehicle dispatching systems mainly relies on manual parsing and processing of multiple technical documents. In practice, staff need to manually map information from multiple technical documents to the "Vehicle Dispatch Code Configuration.xlsx" file to generate the required JSON configuration file. However, because the overall configuration process involves the interaction of multiple tools, it is complex and requires a lot of manpower and time, resulting in low configuration efficiency for the vehicle dispatching system. Summary of the Invention
[0004] This invention provides a configuration method and apparatus for a vehicle dispatching system, which solves the technical problem of low configuration efficiency in existing vehicle dispatching systems and achieves efficient configuration of vehicle dispatching systems.
[0005] This invention provides a configuration method for a vehicle dispatching system, comprising the following steps: Obtain the current configuration technical documentation for the vehicle dispatch system; The text document in the current configuration technical document is input into the first model to obtain the first configuration file output by the first model; the first model is used to perform normalized synthesis of the text document; The table document in the current configuration technical document is input into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The first configuration file is input into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align parameters of data in different files according to the configuration template; The vehicle dispatching system is configured based on the target configuration file.
[0006] The configuration method of a vehicle dispatching system provided by the present invention further includes a training step of a second model, wherein the training step of the second model further includes: Obtain the tables in the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration tables; The second model is trained using the table documents in the historical configuration technical documents as feature data and the corresponding historical configuration tables as label data.
[0007] The configuration method for a vehicle dispatching system provided by the present invention further includes a training step for a third model, wherein the training step for the third model further includes: Obtain the text documents from the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration mapping table; The third model is trained using text documents in the historical configuration technical documents as feature data and the corresponding historical configuration mapping table as label data.
[0008] According to a configuration method for a vehicle dispatching system provided by the present invention, before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Identify fields in the target configuration file where the terminology descriptions are inconsistent; The target field is determined from the fields using a weighted voting strategy; The terminology is uniformly described using the target field.
[0009] According to a configuration method for a vehicle dispatching system provided by the present invention, before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Record the document version of the target configuration file, the first confidence level of the second configuration file output by the second model, and the second confidence level of the current configuration mapping table output by the third model, and generate an operation log.
[0010] According to a configuration method for a vehicle dispatching system provided by the present invention, after generating the operation log, the method further includes: If the first confidence level is less than the first preset threshold, the second configuration file shall be manually reviewed; If the second confidence level is less than the second preset threshold, the current configuration mapping table is manually reviewed.
[0011] The present invention also provides a configuration device for a vehicle dispatching system, comprising the following modules: The acquisition module is used to acquire the current configuration technical documents of the vehicle dispatching system; The synthesis module is used to input the text document in the current configuration technical document into the first model and obtain the first configuration file output by the first model; the first model is used to perform standardized synthesis of the text document; The conversion module is used to input the table document in the current configuration technical document into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The semantic alignment module is used to input the first configuration file into the third model and obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The parameter alignment module is used to input the current configuration mapping table, the second configuration file, and the configuration template into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to perform parameter alignment on the data in different files according to the configuration template; The configuration module is used to configure the vehicle dispatching system based on the target configuration file.
[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement a configuration method for any of the vehicle dispatching systems described above.
[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the configuration method of the vehicle dispatching system as described above.
[0014] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements a configuration method for any of the vehicle dispatching systems described above.
[0015] This invention provides a configuration method for a vehicle dispatching system. The method involves: acquiring the current configuration technical document of the vehicle dispatching system; inputting the text document from the current configuration technical document into a first model to obtain a first configuration file output by the first model; the first model is used to standardize and synthesize the text document, thereby standardizing and organizing multi-source heterogeneous text documents to obtain a document with a unified format; inputting the table document from the current configuration technical document into a second model to obtain a second configuration file output by the second model; the second model is used to perform sequence conversion on the table document, thereby converting multi-source heterogeneous table documents into an ordered table; inputting the first configuration file into a third model to obtain a current configuration mapping table output by the third model; and the third model is used to process the text document from the first configuration file into a table. The content undergoes semantic alignment to further align the text content in the document, eliminating semantic ambiguity. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model. The configuration template is constructed based on the configuration rules of the vehicle dispatching system. The fourth model aligns the parameters of data in different files according to the configuration template, thereby integrating the results of collaborative processing by multiple models and combining them with the configuration template to generate a templated target configuration file, ensuring efficient parsing and accurate mapping of different document types. Based on the target configuration file, the vehicle dispatching system is configured, enabling automated configuration through a machine-readable target configuration file, significantly improving the configuration efficiency of the vehicle dispatching system. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating a configuration method for a vehicle dispatching system provided by the present invention.
[0018] Figure 2 This is a schematic diagram of the configuration device for a vehicle dispatching system provided by the present invention.
[0019] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.
[0021] In the rail transit industry, vehicle dispatching systems significantly improve operational efficiency and reduce operating costs through real-time monitoring and intelligent route optimization. Simultaneously, the system enhances customer service quality, providing accurate arrival time estimates and improving user experience. Furthermore, vehicle dispatching systems ensure driving safety by promptly identifying potential hazards and supporting management decision analysis, thus contributing to sustainable development.
[0022] Currently, the configuration process of the vehicle dispatching system mainly relies on manual parsing and processing of multiple technical documents. These documents include the "Vehicle Dispatch System Data Interface Specification," "Vehicle Dispatch Interface Description," "Vehicle Dispatch Technical Specifications," and "Vehicle Dispatch System Data Configuration Equipment Number Principles." In practice, staff need to manually map the information in these documents to "Vehicle Dispatch Code Configuration.xlsx," ultimately generating the required JSON configuration file (trans_vds_info.json).
[0023] However, due to various technical issues arising from the heterogeneous technical documentation from multiple sources during the actual configuration process, the entire process involves the interaction of multiple tools, making configuration difficult and requiring a significant amount of manpower and time (the overall time consumption is approximately 8 person-days per session), thus reducing the configuration efficiency of the vehicle dispatching system.
[0024] The various technical problems that arise during the actual configuration process of multi-source heterogeneous technical documents mainly include: semantic inconsistency, difficulty in version adaptation, and difficulty in directly reusing historical configurations.
[0025] Specifically, semantic inconsistency refers to differences in the descriptions of interface variable names, UI control names, and coding rules in different technical documents, which easily leads to errors during manual mapping, with an error rate as high as 15% or more; version adaptation difficulties mean that when technical documents are updated, the existing static rule engine cannot automatically adapt to the changes and needs to be reconfigured, which significantly increases the workload and time cost; difficulty in directly reusing historical configurations means that the generated JSON configuration file still needs to be manually rewritten, making it impossible to effectively reuse historical configuration logic, further reducing overall work efficiency.
[0026] To address these issues, this invention proposes a configuration method and apparatus for a vehicle dispatching system, aiming to solve the problems of inefficiency, semantic ambiguity, and version compatibility caused by insufficient collaboration of multi-source heterogeneous documents during the configuration process of vehicle dispatching systems. Its core objective is to eliminate the semantic gap across documents by constructing a cross-document semantic alignment model to automatically map interface variables, UI controls, and ID encoding rules, ensuring parameter consistency. The functional objective is to achieve dynamic rule adaptation and version iteration by designing a rule-data dual-driven generator to support automatic parameter realignment after document changes, ensuring an accuracy rate of over 95% for version iteration. The technical objective is to achieve fully automated configuration generation by significantly improving configuration efficiency and reducing manual review workload through machine learning models and template filling technology.
[0027] The following is combined Figures 1 to 3 This invention describes a configuration method and apparatus for a vehicle dispatching system.
[0028] Figure 1 This is a flowchart illustrating a configuration method for a vehicle dispatching system provided by the present invention, as shown below. Figure 1 As shown, the method includes the following steps: Step 101: Obtain the current configuration technical document of the vehicle dispatching system.
[0029] Specifically, the configuration process of the vehicle dispatching system mainly relies on manual parsing and processing of multiple configuration technical documents. These configuration technical documents include the "Vehicle Dispatch System Data Interface Specification", "Vehicle Dispatch Interface Description", "Vehicle Dispatch Technical Specifications", and "Principles for Vehicle Dispatch System Data Configuration Equipment Numbers", etc.
[0030] As equipment is upgraded or technology is updated, these configuration technical documents are usually updated accordingly. Therefore, the current configuration technical document mainly refers to the current version of the configuration technical document.
[0031] Step 102: Input the text document in the current configuration technical document into the first model to obtain the first configuration file output by the first model; the first model is used to perform standardized synthesis of the text document.
[0032] Step 103: Input the table document in the current configuration technical document into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document.
[0033] Specifically, the current configuration technical documents can be divided into text documents and table documents according to their type.
[0034] In this embodiment of the invention, a first model is used to normalize and synthesize text documents to obtain a first configuration file.
[0035] For example, a unified Named Entity Recognition (NER) method is used to extract variable names and descriptions from interface specifications; graphic and textual collaborative analysis is performed on interface descriptions to establish a mapping relationship between controls and functional points; a rule-based knowledge graph is constructed based on numbering principles to constrain ID generation logic, thereby standardizing and organizing multi-source heterogeneous text documents to obtain documents with a unified format.
[0036] The first model can be an intelligent parsing engine built based on large language models from the DeepSeek or GPT series. By inputting text documents and related text commands into the intelligent parsing engine, the engine can parse the input text documents and output relevant content according to the text commands. For example, if the text command is "Please standardize and organize the input text document and output a document with a uniform format," the intelligent parsing engine can automatically standardize and organize text documents with different structures and output a first configuration file with a uniform format.
[0037] On the other hand, embodiments of the present invention use a second model to perform sequence transformation on the tabular document to obtain a second configuration file. The second model can be various Seq2Seq models, such as a Seq2Seq model based on a recurrent neural network, a Seq2Seq model based on a convolutional neural network, or a Seq2Seq model based on a Transformer.
[0038] The Seq2Seq model enables sequence generation tasks with variable input and output sequence lengths by flexibly combining encoder and decoder architectures.
[0039] For example, during the configuration of a vehicle dispatching system, the interface specification requires that the device ID include line number + device type + serial number, and the numbering principle specifies the switch machine type code and ATP on-board unit type code. This information is typically scattered across multiple spreadsheet documents. In this case, inputting all spreadsheet documents into a second model allows for automated conversion and integration of each column of data from different spreadsheets according to the serial number, resulting in an ordered spreadsheet that conforms to the interface specification requirements and numbering principles. This serves as a second configuration file, saving manpower and time and improving efficiency.
[0040] Step 104: Input the first configuration file into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file.
[0041] Specifically, a third model is used to semantically align the text content in the uniformly formatted first configuration file to obtain the current configuration mapping table. This third model can be a BERT variant model, Domain-BERT, or other BERT models (such as BERT-Base or BERT-Large).
[0042] The third model extracts the semantic feature vector from the first configuration file, semantically aligns the semantic feature vector, interface controls, and device ID, eliminates semantic ambiguity, establishes a mapping relationship between device ID and signal system logical name, and generates the current configuration mapping table. This eliminates the terminology differences between interface variables, interface controls, and ID codes in the text document, achieves 100% parameter mapping coverage, reduces manual review workload by 70%, and improves configuration efficiency.
[0043] Step 105: Input the current configuration mapping table, the second configuration file, and the configuration template into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align the parameters of data in different files according to the configuration template.
[0044] Specifically, firstly, a configuration template is constructed based on the configuration rules of the vehicle dispatching system. Then, the file parameters of the current configuration mapping table and the second configuration file are aligned according to the configuration template. Finally, the target configuration file is automatically generated through a fourth model. This fourth model can be an intelligent parsing engine built based on large language models from the DeepSeek or GPT series.
[0045] By inputting the current configuration mapping table, the second configuration file, the configuration template, and related text commands into the intelligent parsing engine, the intelligent parsing engine can parse the input file and output the relevant content according to the text commands.
[0046] For example, the configuration template is a machine-readable JSON file template, and the text instruction is "Please align the file parameters of the current configuration mapping table and the second configuration file according to the configuration template, and output a machine-readable JSON file". The intelligent parsing engine can automatically align the file parameters of the current configuration mapping table and the second configuration file, automatically read the signal ID field in the table, map it to the internal logical name of the vehicle dispatching system (such as the logical name of the switch machine), establish the mapping relationship between the signal ID and the physical device address, inject parameters according to the JSON file template, and finally generate a machine-readable JSON file, which is the target configuration file.
[0047] This invention integrates the results of collaborative processing of multiple models and combines them with configuration templates to generate templated target configuration files, automating the configuration process and ensuring efficient parsing and accurate mapping of different document types. It can reduce the workload that originally required 8 people working together for a whole day to be completed in 2 hours, significantly improving configuration efficiency and accuracy.
[0048] Step 106: Configure the vehicle dispatching system based on the target configuration file.
[0049] Specifically, based on the machine-readable target configuration file generated by the fourth model, the equipment of the vehicle dispatching system can be automatically configured by directly reading the target configuration file.
[0050] This invention provides a configuration method for a vehicle dispatching system. The method involves: acquiring the current configuration technical document of the vehicle dispatching system; inputting the text document from the current configuration technical document into a first model to obtain a first configuration file output by the first model; the first model is used to standardize and synthesize the text document, thereby standardizing and organizing multi-source heterogeneous text documents to obtain a document with a unified format; inputting the table document from the current configuration technical document into a second model to obtain a second configuration file output by the second model; the second model is used to perform sequence conversion on the table document, thereby converting multi-source heterogeneous table documents into an ordered table; inputting the first configuration file into a third model to obtain a current configuration mapping table output by the third model; and the third model is used to process the text document from the first configuration file into a table. The content undergoes semantic alignment to further align the text content in the document, eliminating semantic ambiguity. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model. The configuration template is constructed based on the configuration rules of the vehicle dispatching system. The fourth model aligns the parameters of data in different files according to the configuration template, thereby integrating the results of collaborative processing by multiple models and combining them with the configuration template to generate a templated target configuration file, ensuring efficient parsing and accurate mapping of different document types. Based on the target configuration file, the vehicle dispatching system is configured, enabling automated configuration through a machine-readable target configuration file, significantly improving the configuration efficiency of the vehicle dispatching system.
[0051] Furthermore, the method also includes a training step for a second model, which further includes: Obtain the tables in the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration tables; The second model is trained using the table documents in the historical configuration technical documents as feature data and the corresponding historical configuration tables as label data.
[0052] Specifically, a supervised learning approach is adopted, using the tabular documents in historical configuration technical documents as feature data and the corresponding historical configuration tables as label data to train the second model. This training method enables the second model to learn the sequence transformation rules from the original tabular documents to the normalized configuration tables, especially for complex tables such as "Vehicle Adjustment Code Configuration.xlsx" that contain device ID mapping relationships.
[0053] For example, collect the past five versions of the "Numbering Principles" document and their corresponding historical configuration tables, extract and label the features of the document-table pairs for each version, train the model to learn the sequence transformation rules from document description to actual table fields, and verify the model's adaptability and generalization performance to the latest version of the "Numbering Principles".
[0054] This invention employs supervised training, enabling the trained second model to accurately understand the encoding rules in tabular documents and automatically generate compliant configuration tables. Even when the document version is updated (e.g., line number format changes from L1 to Line1), the model maintains a high conversion accuracy (≥95%), significantly reducing the need for manual intervention and improving configuration efficiency.
[0055] Furthermore, the method also includes a training step for a third model, which further includes: Obtain the text documents from the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration mapping table; The third model is trained using text documents in the historical configuration technical documents as feature data and the corresponding historical configuration mapping table as label data.
[0056] Specifically, a supervised learning approach is adopted, using text documents from historical configuration technical documents as feature data and corresponding historical configuration mapping tables as label data to train the third model. This pre-training enables the third model to focus on the conversion from text documents to configuration mapping tables.
[0057] For example, the model learns to extract key information from text documents such as "Interface Specifications" and "Interface Descriptions," and establishes semantic mapping relationships to resolve inconsistencies in terms such as "vehicle speed" and "speed value," thus eliminating semantic ambiguity. Specifically, during the training of the third model, multiple historical versions of text documents such as "Interface Specifications" and "Interface Descriptions" are first collected. Then, the historical configuration mapping tables corresponding to these text documents are obtained as labels for pre-training the third model. Finally, the model parameters are fine-tuned to enable it to recognize variable names, control names, and their mapping relationships in the documents. This allows the trained third model to achieve semantic alignment across documents, eliminate terminology differences between different documents, and achieve 100% coverage of parameter mapping. In practical applications, manual review is reduced by 70%, improving efficiency while ensuring the accuracy of the generated configuration mapping tables.
[0058] Furthermore, before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Identify fields in the target configuration file where the terminology descriptions are inconsistent; The target field is determined from the fields using a weighted voting strategy; The terminology is uniformly described using the target field.
[0059] Specifically, to address the potential inconsistencies in terminology descriptions within the target configuration file, this embodiment of the invention proposes a weighted voting solution. This strategy first identifies inconsistent fields as target fields to be adjusted, then assigns weights to the target fields based on factors such as the authority and version of each source document, ultimately determining a unified terminology description.
[0060] For example, when a terminology conflict occurs, it is detected that the Interface Specification uses "vehicle speed" while the Interface Description uses "speed value". The weights are assigned according to document type and version: Interface Specification has a weight of 0.6 and Interface Description has a weight of 0.4. Then, combined with historical usage frequency, "vehicle speed" gets a higher overall score. Finally, "vehicle speed" is uniformly adopted as the standard term in the target configuration file.
[0061] This invention ensures consistency of terminology in configuration files through a conflict resolution mechanism, avoiding system parsing errors caused by terminology differences. Simultaneously, the weighted strategy considers the authority and timeliness of different documents, making the decision results more reasonable and reliable.
[0062] Furthermore, before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Record the document version of the target configuration file, the first confidence level of the second configuration file output by the second model, and the second confidence level of the current configuration mapping table output by the third model, and generate an operation log.
[0063] Specifically, by recording the document version of the target configuration file, the first confidence level of the second configuration file output by the second model, and the second confidence level of the current configuration mapping table output by the third model, operation logs are generated. This allows for the tracking of key parameters throughout the target configuration file generation process, including document version and model confidence levels. This traceability mechanism not only meets auditing requirements but also provides complete data support for problem diagnosis and version backtracking.
[0064] For example, during any generation of the target configuration file, the document versions used are first recorded as: "Interface Specification V3.2" and "Numbering Principle V5.0"; then, the confidence level of the "Vehicle Adjustment Code Configuration.xlsx" table file generated by the second model is saved as 92%, and the confidence level of the current configuration mapping table generated by the third model is saved as 88%; an operation log containing all this information is generated; when configuration problems are discovered later, the problem can be quickly located through the operation log.
[0065] This invention helps to quickly diagnose problems (such as configuration errors caused by low confidence) by recording operation logs, while also meeting the audit requirements of the rail transit industry for critical system changes. Furthermore, by designing a full-process traceability mechanism, it improves the maintainability and transparency of the vehicle dispatching system.
[0066] Furthermore, after generating the operation log, the method further includes: If the first confidence level is less than the first preset threshold, the second configuration file shall be manually reviewed; If the second confidence level is less than the second preset threshold, the current configuration mapping table is manually reviewed.
[0067] Specifically, this embodiment of the invention also adds an automatic review mechanism for low-confidence outputs. When the confidence level of the model output is lower than a preset threshold, the system will automatically trigger a manual review process to ensure the accuracy of key configuration items.
[0068] For example, if the system detects that the confidence level of the third model in the current configuration mapping table is only 85%, which is lower than the 90% threshold, it will automatically mark the mapping table as "requires review" and notify technical personnel to manually check the relevant fields. Only after confirming that there are no errors or making corrections will the mapping table be allowed to be used.
[0069] This invention, through its embodiments, achieves a balance between automated processes and manual intervention by adding an automatic review mechanism for low-confidence outputs, maintaining high efficiency while ensuring the accuracy of critical configuration items. In practical applications, although the workload of manual review is reduced by 70%, the critical error rate is reduced by more than 90%, improving the overall reliability of the vehicle dispatching system configuration.
[0070] The following describes a configuration device for a vehicle dispatching system provided by the present invention. The configuration device for the vehicle dispatching system described below can be referred to in correspondence with the configuration method for the vehicle dispatching system described above.
[0071] Based on any of the above embodiments Figure 2 This is a schematic diagram of the configuration device for a vehicle dispatching system provided by the present invention, as shown below. Figure 2 As shown. This embodiment of the invention provides a configuration device for a vehicle dispatching system, including an acquisition module 201, a synthesis module 202, a conversion module 203, a semantic alignment module 204, a parameter alignment module 205, and a configuration module 206, wherein: The acquisition module 201 is used to acquire the current configuration technical document of the vehicle dispatching system; the synthesis module 202 is used to input the text document in the current configuration technical document into a first model to obtain a first configuration file output by the first model; the first model is used to perform normalization synthesis on the text document; the conversion module 203 is used to input the table document in the current configuration technical document into a second model to obtain a second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; the semantic alignment module 204 is used to input the first configuration file into a third model to obtain a current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file; the parameter alignment module 205 is used to input the current configuration mapping table, the second configuration file, and the configuration template into a fourth model to obtain a target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to perform parameter alignment on the data in different files according to the configuration template; the configuration module 206 is used to configure the vehicle dispatching system based on the target configuration file.
[0072] This invention provides a configuration device for a vehicle dispatching system. The device acquires the current configuration technical document of the vehicle dispatching system; inputs the text document from the current configuration technical document into a first model to obtain a first configuration file output by the first model; the first model is used to standardize and synthesize the text document, thereby standardizing and organizing multi-source heterogeneous text documents to obtain a document with a unified format; inputs the table document from the current configuration technical document into a second model to obtain a second configuration file output by the second model; the second model is used to perform sequence conversion on the table document, thereby converting multi-source heterogeneous table documents into an ordered table; inputs the first configuration file into a third model to obtain a current configuration mapping table output by the third model; the third model is used to process the text document in the first configuration file... The content undergoes semantic alignment to further align the text content in the document, eliminating semantic ambiguity. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model. The configuration template is constructed based on the configuration rules of the vehicle dispatching system. The fourth model aligns the parameters of data in different files according to the configuration template, thereby integrating the results of collaborative processing by multiple models and combining them with the configuration template to generate a templated target configuration file, ensuring efficient parsing and accurate mapping of different document types. Based on the target configuration file, the vehicle dispatching system is configured, enabling automated configuration through a machine-readable target configuration file, significantly improving the configuration efficiency of the vehicle dispatching system.
[0073] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute a configuration method for the vehicle dispatching system, the method including: Obtain the current configuration technical documentation for the vehicle dispatch system; The text document in the current configuration technical document is input into the first model to obtain the first configuration file output by the first model; the first model is used to perform normalized synthesis of the text document; The table document in the current configuration technical document is input into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The first configuration file is input into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align parameters of data in different files according to the configuration template; The vehicle dispatching system is configured based on the target configuration file.
[0074] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0075] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is able to execute the configuration method of the vehicle dispatching system provided by the above methods, the method comprising: Obtain the current configuration technical documentation for the vehicle dispatch system; The text document in the current configuration technical document is input into the first model to obtain the first configuration file output by the first model; the first model is used to perform normalized synthesis of the text document; The table document in the current configuration technical document is input into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The first configuration file is input into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align parameters of data in different files according to the configuration template; The vehicle dispatching system is configured based on the target configuration file.
[0076] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a configuration method for a vehicle dispatching system provided by the methods described above, the method comprising: Obtain the current configuration technical documentation for the vehicle dispatch system; The text document in the current configuration technical document is input into the first model to obtain the first configuration file output by the first model; the first model is used to perform normalized synthesis of the text document; The table document in the current configuration technical document is input into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The first configuration file is input into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align parameters of data in different files according to the configuration template; The vehicle dispatching system is configured based on the target configuration file.
[0077] 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. Those skilled in the art can understand and implement this without any creative effort.
[0078] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, 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.
[0079] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
[0080] It should also be noted that the terms "target," "first," and "second" in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first" and "second" are generally of the same class, without limiting the number of objects; for example, the first object can be one or more.
[0081] In this application's embodiments, "determine B based on A" means that factor A must be considered when determining B. It is not limited to "B can be determined based solely on A," but should also include: "determine B based on A and C," "determine B based on A, C, and E," "determine C based on A, and further determine B based on C," etc. Additionally, it can include using A as a condition for determining B, for example, "when A meets the first condition, determine B using the first method"; another example, "when A meets the second condition, determine B," etc.; another example, "when A meets the third condition, determine B based on the first parameter," etc. Of course, it can also be a condition where A is a factor in determining B, for example, "when A meets the first condition, determine C using the first method, and further determine B based on C," etc.
[0082] In this invention, the term "multiple" refers to two or more, and other quantifiers are similar.
[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A configuration method for a vehicle dispatching system, characterized in that, include: Obtain the current configuration technical documentation for the vehicle dispatch system; Input the text document from the current configuration technical document into the first model to obtain the first configuration file output by the first model; The first model is used to perform standardized synthesis of the text document; The table document in the current configuration technical document is input into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The first configuration file is input into the third model to obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The current configuration mapping table, the second configuration file, and the configuration template are input into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to align parameters of data in different files according to the configuration template; The vehicle dispatching system is configured based on the target configuration file.
2. The configuration method of the vehicle dispatching system according to claim 1, characterized in that, It also includes a training step for a second model, which further includes: Obtain the tables in the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration tables; The second model is trained using the table documents in the historical configuration technical documents as feature data and the corresponding historical configuration tables as label data.
3. The configuration method of the vehicle dispatching system according to claim 1, characterized in that, It also includes a training step for the third model, which further includes: Obtain the text documents from the historical configuration technical documents of the vehicle dispatching system and the corresponding historical configuration mapping table; The third model is trained using text documents in the historical configuration technical documents as feature data and the corresponding historical configuration mapping table as label data.
4. The configuration method of the vehicle dispatching system according to claim 1, characterized in that, Before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Identify fields in the target configuration file where the terminology descriptions are inconsistent; The target field is determined from the fields using a weighted voting strategy; The terminology is uniformly described using the target field.
5. The configuration method of the vehicle dispatching system according to claim 1, characterized in that, Before configuring the vehicle dispatching system based on the target configuration file, the method further includes: Record the document version of the target configuration file, the first confidence level of the second configuration file output by the second model, and the second confidence level of the current configuration mapping table output by the third model, and generate an operation log.
6. The configuration method of the vehicle dispatching system according to claim 5, characterized in that, After generating the operation log, the method further includes: If the first confidence level is less than the first preset threshold, the second configuration file shall be manually reviewed; If the second confidence level is less than the second preset threshold, the current configuration mapping table is manually reviewed.
7. A configuration device for a vehicle dispatching system, characterized in that, include: The acquisition module is used to acquire the current configuration technical documents of the vehicle dispatching system; The synthesis module is used to input the text document in the current configuration technical document into the first model and obtain the first configuration file output by the first model; The first model is used to perform standardized synthesis of the text document; The conversion module is used to input the table document in the current configuration technical document into the second model to obtain the second configuration file output by the second model; the second model is used to perform sequence conversion on the table document; The semantic alignment module is used to input the first configuration file into the third model and obtain the current configuration mapping table output by the third model; the third model is used to perform semantic alignment on the text content in the first configuration file. The parameter alignment module is used to input the current configuration mapping table, the second configuration file, and the configuration template into the fourth model to obtain the target configuration file output by the fourth model; wherein, the configuration template is constructed according to the configuration rules of the vehicle dispatching system; the fourth model is used to perform parameter alignment on the data in different files according to the configuration template; The configuration module is used to configure the vehicle dispatching system based on the target configuration file.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the configuration method of the vehicle dispatching system as described in any one of claims 1 to 6.
9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the configuration method of the vehicle dispatching system as described in any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the configuration method of the vehicle dispatching system as described in any one of claims 1 to 6.