Intelligent scheduling method and system for urban rail transit

Abstract

The invention provides an intelligent scheduling method and system for urban rail transit, and the method is applied to a scheduling system comprising an automatic train monitoring module, a scheduling service module, a command auditing and correcting module and a scheduling command issuing module, and specifically comprises the steps: triggering a template configuration file based on the state of train and line equipment in combination with a scheduling command condition, generating scheduling command information in a current state, triggering command auditing according to a corresponding scheduling command priority, performing command auditing according to an associated scheduling factor, performing correction according to an auditing result, identifying a distribution target according to the corrected scheduling command information or the scheduling command information which does not trigger command auditing, and issuing a corresponding scheduling command. And triggering secondary command auditing of the scheduling command based on the command receipt of the distribution target, and performing secondary correction on the scheduling command in combination with the associated scheduling factors during the triggering auditing. According to the invention, manual intervention in the scheduling command formulation process can be effectively reduced, and the scheduling command accuracy and the scheduling efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of urban rail transit technology, and in particular to intelligent scheduling methods and systems for urban rail transit. Background Technology

[0002] With the development of urban rail transit, the complexity of rail transit lines and the density of station locations are increasing, while train intervals are becoming shorter. In response to special conditions and emergencies of line equipment, it is necessary to quickly formulate and issue dispatch orders to respond to emergencies and ensure the normal operation of trains.

[0003] Conventional dispatch command systems mostly involve dispatchers drafting templates of dispatch command content for daily use. Then, the dispatchers select a template based on the current system situation, manually write and modify the template content, and select a specific receiving terminal to issue the command.

[0004] Furthermore, after the scheduling command is formulated, in order to avoid misjudgment or omission of the scheduling command by manual formulation, a scheduling command review is also set up. Specifically, the scheduling command is sent to the scheduling personnel for manual review. The reviewers determine whether to approve the issuance of the scheduling command by verifying the current operation status and operation plan of the system. This review method often results in low review efficiency and information gaps between scheduling personnel, which leads to inappropriate issuance of commands.

[0005] It is evident that the current urban rail transit dispatching orders are formulated and reviewed manually, resulting in inaccurate dispatching orders and low dispatching efficiency. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies that rely on manual formulation and review of train dispatching commands, which are prone to inaccurate commands and low dispatching efficiency. This invention provides an intelligent dispatching method and system for urban rail transit. It automatically generates command information based on template matching of train and line equipment status, and combines priority-based hierarchical review to reduce manual intervention in the command formulation process. This enables rapid response in emergency situations. Furthermore, by associating dispatching factors with the command, it reviews and corrects the dispatching commands, and then relies on command receipts to trigger secondary review and dynamic correction. This avoids problems such as human error, omissions, and information gaps between dispatchers and the command, ensuring the accuracy of dispatching commands.

[0007] The objective of this invention is achieved through the following technical solution: Intelligent scheduling methods for urban rail transit include: Based on the status of trains and track equipment, and combined with the dispatch command condition trigger template configuration file, dispatch command information for the current status is generated; Identify the priority of the current scheduling command based on the scheduling command information, and trigger command review based on the scheduling command priority; The scheduling command information is reviewed based on the associated scheduling factors, and the scheduling command information is corrected based on the review results. Identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and issue the corresponding scheduling command. The system receives command receipts from the distribution target in real time, triggers a secondary command review of the scheduling command based on the command receipt, and makes secondary corrections to the scheduling command by taking into account the associated scheduling factors at the time of the review.

[0008] Furthermore, the generation of dispatch command information for the current state based on the status of trains and track equipment, combined with the dispatch command condition trigger template configuration file, includes: Collect train operation status data and track equipment status data, and form a status dataset after preprocessing; The scheduling command triggering conditions of each template configuration file are matched one by one based on the state dataset, and the target scheduling command template is selected according to the matching results. The target scheduling command template is populated based on the state dataset to obtain scheduling command information.

[0009] Furthermore, the step of identifying the current scheduling command priority based on the scheduling command information and triggering command review based on the scheduling command priority includes: Based on the scheduling command information, the associated influencing factors of the scheduling command are extracted, including the command security attributes, scope of influence, and urgency level; Input the associated influencing factors into the priority rule base to match and obtain the priority of the current scheduling command; The corresponding review process is triggered based on the scheduling priority, and the review subject is identified according to the scheduling command information. The corresponding scheduling command information and review task are then sent to the corresponding review subject.

[0010] Furthermore, the step of reviewing the scheduling command information based on associated scheduling factors and correcting the scheduling command information based on the review results includes: The auditing entity receives the corresponding scheduling command information and auditing task, and extracts the corresponding command execution object and command execution content based on the scheduling command information. Extract the corresponding associated scheduling factors based on the command execution object, and perform logical verification on the associated scheduling factors and command execution content based on preset audit rules; When a logic check fails, the type of check problem is identified based on the check result. Based on the type of verification problem, perform corrections to associated scheduling factors or adjustments to command execution content until the logical verification is passed.

[0011] Furthermore, the step of identifying the verification problem type based on the verification result includes: Based on the verification results, identify conflict-related scheduling factors and conflict content fragments; Based on the conflict-related scheduling factors, extract the corresponding real-time data source data, and combine it with the conflict-related scheduling factor data applied during logical verification to identify data deviations. When data bias is detected, it is classified as a factor data bias problem. When there is no data bias, extract the factor requirements according to the conflict-related scheduling factors, and identify the limit-breaking of command parameters in the conflict content fragments according to the factor requirements. When command parameters are found to be out of bounds, the issue is classified as a command parameter deviation problem. In other cases, it is judged as a rule adaptation anomaly.

[0012] Furthermore, the command receipt of the distribution target includes a command receipt and a command signature receipt.

[0013] Furthermore, the real-time receipt of command acknowledgments from the distribution target, and the triggering of secondary command review of the scheduling command based on the command acknowledgments, includes: The received command receipts from the distribution targets are classified, and the command receipt receipts and command signature receipt receipts are associated according to the scheduling command. Based on preset indicators, abnormal scenarios can be identified by considering associated command receipts and command signing receipts. The system matches the trigger conditions for secondary review based on abnormal scenarios, and determines whether the trigger conditions for secondary review are met based on the scheduling command and the corresponding command receipt and command sign-off receipt. When the conditions for triggering a secondary review are met, a secondary review order is triggered.

[0014] Furthermore, the secondary modification of the scheduling command based on the associated scheduling factors triggered by the audit includes: An audit information package is constructed based on the scheduling command to be corrected, the associated command receipt and command signature receipt, and the real-time associated scheduling factors when the audit is triggered, and then uploaded to the corresponding audit entity. Logical verification is performed based on the audit information package to identify the anomaly type and locate the cause of the anomaly. Based on the identification of abnormal causes, the command parameters to be adjusted are optimized by taking real-time associated scheduling factors as constraints and combining them with corresponding audit rules.

[0015] Furthermore, the dispatch command information includes at least the command receiving station, the station command content, the command receiving train, and the train command content.

[0016] An intelligent dispatching system for urban rail transit, used to execute any of the intelligent dispatching methods described above, including: The automatic train monitoring module is used to collect real-time data on the status of trains and equipment. The dispatch service module is used to generate dispatch command information under the current status based on the status of trains and line equipment, combined with the dispatch command condition trigger template configuration file, identify the priority of the current dispatch command based on the dispatch command information, trigger command review based on the dispatch command priority, and receive command receipts from the distribution target in real time, and trigger secondary command review of the dispatch command based on the command receipts. The command review and correction module is used to review the scheduling command information based on the associated scheduling factors, and correct the scheduling command information based on the review results, or to make secondary corrections to the scheduling command based on the associated scheduling factors that triggered the review. The scheduling command issuing module is used to identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and to issue the corresponding scheduling command.

[0017] The beneficial effects of this invention are: Dispatch commands are automatically generated based on preset templates matched with real-time train operation status and line equipment data. This eliminates the need for dispatchers to manually select templates and modify command content word by word, reducing the time spent on manual operations. Furthermore, it incorporates priority-based, tiered review processes to avoid delays caused by full-process manual review. In emergency scenarios such as equipment failures or sudden surges in passenger flow, it can quickly output appropriate commands, effectively addressing the operational pressures of complex lines and short train intervals, ensuring rapid dispatch response in emergency situations. By associating dispatch factors with logical validation and parameter correction of command content, it avoids misjudgments and omissions when manually formulating commands based on experience. A second review is triggered by command receipts. If anomalies are found in the receipts, dynamic corrections are made based on real-time factors at the time of triggering. This solves the problem of inappropriate commands caused by information asynchrony among dispatchers in traditional manual review, ensuring the adaptability of dispatch commands to actual operational status, reducing operational risks caused by command errors, and guaranteeing the reliability of urban rail transit dispatch. Attached Figure Description

[0018] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Example: Intelligent scheduling methods for urban rail transit, such as Figure 1 As shown, it includes: Based on the status of trains and track equipment, and combined with the dispatch command condition trigger template configuration file, dispatch command information for the current status is generated; Identify the priority of the current scheduling command based on the scheduling command information, and trigger command review based on the scheduling command priority; The scheduling command information is reviewed based on the associated scheduling factors, and the scheduling command information is corrected based on the review results. Identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and issue the corresponding scheduling command. The system receives command receipts from the distribution target in real time, triggers a secondary command review of the scheduling command based on the command receipt, and makes secondary corrections to the scheduling command by taking into account the associated scheduling factors at the time of the review.

[0021] In the traditional model, dispatchers need to manually select templates and modify content word by word, which is not only time-consuming but also prone to delaying responses to emergencies. To optimize the efficiency of dispatch command formulation, based on real-time status data of trains and track equipment, the system first triggers the template configuration file through preset dispatch command conditions to automatically generate dispatch command information, eliminating the need for manual template selection or content modification and reducing efficiency losses and errors caused by manual intervention.

[0022] The step of generating dispatch command information for the current state based on the status of trains and track equipment, combined with the dispatch command condition trigger template configuration file, includes: Collect train operation status data and track equipment status data, and form a status dataset after preprocessing; The scheduling command triggering conditions of each template configuration file are matched one by one based on the state dataset, and the target scheduling command template is selected according to the matching results. The target scheduling command template is populated based on the state dataset to obtain scheduling command information.

[0023] The train operation status data includes information such as the train's real-time location, speed, door opening and closing status, fault diagnosis codes, and remaining power. The track equipment status data includes information such as signal display status, track occupancy, turnout switching status, power supply equipment voltage, and real-time passenger flow statistics at stations.

[0024] After acquiring the corresponding train operation status data and track equipment status data, the collected data undergoes preprocessing such as duplicate data removal, missing value completion, and standardization. At the same time, data association is established, linking the train operation status data with the track equipment status data of the corresponding section according to the real-time location of the corresponding train, thereby forming a status dataset.

[0025] For the automatic generation of dispatching commands, there are multiple types of dispatching command template configuration files. Each type of template has a corresponding dispatching command triggering condition, which is the combination of train and line status required to trigger the type of template.

[0026] Based on this, the target scheduling command template that is suitable for the current state is selected by matching the state dataset with the template triggering conditions one by one. If multiple suitable templates are selected, the final target scheduling command template is selected according to the matching priority of the corresponding template triggering conditions to avoid multiple template conflicts.

[0027] The selected target scheduling command template has a frame structure, which includes fixed descriptions and variable fields to be filled. The specific data corresponding to the variable fields is extracted from the status dataset, automatically filled into the variable fields of the template, and its integrity is checked. After the check passes, the final scheduling command information is generated.

[0028] After generating scheduling command information, its priority is automatically identified, and the corresponding command process is triggered according to the priority. Priority identification is based on the security attributes associated with the command, the scope of impact, and the degree of urgency, and is divided into emergency, important, and routine levels. Different levels correspond to different review mechanisms, which not only ensures the rigor of the review of high-priority commands, but also avoids the low efficiency caused by manual review throughout the entire process.

[0029] Specifically, the step of identifying the priority of the current scheduling command based on the scheduling command information and triggering command review based on the scheduling command priority includes: Based on the scheduling command information, the associated influencing factors of the scheduling command are extracted, including the command security attributes, scope of influence, and urgency level; Input the associated influencing factors into the priority rule base to match and obtain the priority of the current scheduling command; The corresponding review process is triggered based on the scheduling priority, and the review subject is identified according to the scheduling command information. The corresponding scheduling command information and review task are then sent to the corresponding review subject.

[0030] The command security attributes are obtained by the degree of correlation between scheduling commands and operational security. The specific extraction dimensions include whether the command content involves security risk sources and whether the security parameters meet basic security rules. Ultimately, the command security attributes can be divided into three levels: high, medium, and low.

[0031] The scope of impact is determined by the command execution object and the coverage area. The specific extraction dimensions include the number of affected trains, the number of stations involved, and the operational links affected, which can also be divided into three levels: large, medium, and small.

[0032] The urgency level needs to be obtained by combining the time constraints of command execution and business requirements. The extraction dimensions include the response time limit required by the command, the severity of the consequences of non-execution, etc., and then the urgency level of the command is divided into three levels: urgent, relatively urgent, and normal.

[0033] During the extraction process, information is automatically retrieved based on preset mapping rules for associated influencing factors and command fields.

[0034] Then, the combination of command security attributes, scope of impact, and urgency is input into a preset priority rule base, and the priority of the current scheduling command is automatically output through rule matching.

[0035] The priority rule base has multiple pre-set relationships between factor combinations and priorities. The combination of factors associated with the current scheduling command is compared with the entries in the rule base one by one to determine the rule entry with the highest matching degree, and then the corresponding priority result is determined.

[0036] Based on the determined priority of the scheduling commands, the corresponding review process is triggered, and the review entity with the appropriate permissions is automatically identified. For the highest priority scheduling commands, a dual review process of automatic and manual review is triggered. Subsequent commands can only be issued if both types of review results are passed, ensuring operational security in emergency scenarios. For medium priority scheduling commands, a review process with automatic review as the primary method and manual review as a supplement is triggered. If the automatic review fails or has deviations, manual review is conducted to determine the final review result, avoiding excessive consumption of high-weight review resources. For the lowest priority scheduling commands, an automatic review process is triggered to improve the flow efficiency of regular commands.

[0037] Based on priority and command execution scope, the system automatically matches the review entity with the corresponding permissions and then issues the review task to the review entity's terminal, including the full text of the scheduling command, extracted related influencing factors, and matching priority rules.

[0038] While automatically generated dispatch commands are based on initial state data of trains and track equipment, they do not incorporate multi-dimensional related dispatch factors such as safety, operation, and environment. This may lead to hidden problems such as parameters not matching actual operating scenarios or conflicts with safety rules. Therefore, during the review process, corresponding related dispatch factors are automatically extracted and logically verified against preset review rules to identify such potential risks. Simultaneously, dispatch commands with different priorities correspond to differentiated safety constraints and operational needs. While reviewing dispatch commands in conjunction with related dispatch factors, they are also modified as needed, integrating review and correction into a unified process. This replaces the traditional subjective judgment mode of single-person manual review. Objective data verification reduces misjudgments and omissions caused by information gaps and experience biases among dispatchers, improving review efficiency while ensuring the accuracy of dispatch commands and avoiding operational risks caused by inappropriate commands.

[0039] In addition to serving as the basis for review in the automatic review process, the aforementioned associated scheduling factors can also provide corresponding review assistance in the manual review or manual verification stages.

[0040] The step of reviewing scheduling command information based on associated scheduling factors and correcting the scheduling command information based on the review results includes: The auditing entity receives the corresponding scheduling command information and auditing task, and extracts the corresponding command execution object and command execution content based on the scheduling command information. Extract the corresponding associated scheduling factors based on the command execution object, and perform logical verification on the associated scheduling factors and command execution content based on preset audit rules; When a logic check fails, the type of check problem is identified based on the check result. Based on the type of verification problem, perform corrections to associated scheduling factors or adjustments to command execution content until the logical verification is passed.

[0041] After receiving the corresponding dispatch command information and review task, the reviewing entity automatically extracts the corresponding command execution object, such as the train to be executed, the target station or the designated line section, and the command execution content, such as the travel route, running speed, and stop duration.

[0042] Then, based on the extracted command execution object, the system automatically matches and extracts the corresponding associated scheduling factors. The extraction dimensions correspond to the priority of the current scheduling command. For the highest priority scheduling command, associated scheduling factors of safety, conflict, and operation are extracted, including the real-time location of the command execution object, track occupancy status, real-time speed limit of the line, other train operation plans, and real-time passenger flow at stations. For medium priority scheduling commands, associated scheduling factors of safety and operation are extracted, such as real-time passenger flow density at stations and subsequent train intervals. For the lowest priority scheduling command, only basic compliance factors are extracted, including the device permissions of the execution object and fixed operation plans.

[0043] After extracting relevant scheduling factors, a preset review rule base corresponding to the priority is invoked to perform a dimension-by-dimensional logical verification of the relevant scheduling factors and command execution content. For example, the verification checks whether the travel route in the command execution content conflicts with trains en route and whether the stop duration for passenger flow guidance meets the real-time passenger flow evacuation requirements. The review rules in the preset review rule base can be set according to actual needs.

[0044] If the logic verification passes, it proceeds directly to the distribution stage; if the verification fails, the verification problem type is automatically identified, and corresponding adjustments and corrections are made accordingly.

[0045] The step of identifying the verification problem type based on the verification result includes: Based on the verification results, identify conflict-related scheduling factors and conflict content fragments; Based on the conflict-related scheduling factors, extract the corresponding real-time data source data, and combine it with the conflict-related scheduling factor data applied during logical verification to identify data deviations. When data bias is detected, it is classified as a factor data bias problem. When there is no data bias, extract the factor requirements according to the conflict-related scheduling factors, and identify the limit-breaking of command parameters in the conflict content fragments according to the factor requirements. When command parameters are found to be out of bounds, the issue is classified as a command parameter deviation problem. In other cases, it is judged as a rule adaptation anomaly.

[0046] The conflict-related scheduling factor is the specific factor dimension that conflicts with the command execution content, and the conflict content fragment is the specific part of the command execution content that conflicts with the conflict-related scheduling factor.

[0047] To eliminate conflicts caused by inaccurate data of the associated scheduling factors, the latest data of the corresponding real-time data source is extracted according to the type of conflicting associated scheduling factors. The latest data is then compared with the data of the conflicting associated scheduling factors used in the logical verification. If there is a data deviation, it is directly determined to be a factor data deviation problem. The reason for the logical verification failure is that the data of the associated scheduling factors has not been updated synchronously or has been collected incorrectly, rather than that there is a problem with the command itself or the audit rules.

[0048] If no data deviation exists, the rationality of the scheduling command itself needs to be further identified. First, explicit factor requirements are extracted from the conflict-related scheduling factors. These factor requirements originate from preset review rules or real-time operational constraints. Then, the corresponding command parameters in the conflict content fragment are compared to identify any exceeding limits. It is determined whether the command parameters exceed the reasonable range of the factor requirements. If they are found to exceed the range of factor requirements, it can be identified as a command parameter deviation issue. The reason for the logical verification failure is that the command execution parameters do not match the actual requirements of the associated scheduling factors.

[0049] If there is neither data deviation nor parameter exceeding the limit, it is judged as a rule adaptation anomaly. In this case, data correction or command content modification is not adopted, but conflict resolution is achieved by optimizing the audit rules.

[0050] When dealing with issues related to factor data deviation, the associated scheduling factors are corrected based on the extracted real-time data source, and then the logic is re-verified.

[0051] When dealing with command parameter deviation issues, corresponding correction rules are matched according to the priority level. For the highest priority scheduling commands, correction suggestions are given based on associated scheduling factors and the corresponding issue type, and then manual review is conducted to determine the final command correction. For scheduling commands with medium or lowest priority, command correction is performed during the automatic review process. Manual confirmation is triggered only when a basic compliance conflict occurs and automatic correction is not possible, thus implementing command correction.

[0052] By modifying commands, the final dispatch commands issued are ensured to meet safety requirements and adapt to real-time operation scenarios, thus guaranteeing the normal operation of rail transit.

[0053] After the scheduling command is approved, the corresponding scheduling command is further issued to the execution object. When the execution object receives the scheduling command, it will send a command receipt to ensure the effective issuance of the scheduling command.

[0054] The command receipt of the distribution target includes a command receipt and a command signature receipt.

[0055] When the execution object receives a command receipt, it will automatically send back a command receipt. After the specific operator of the execution object confirms and signs off on the dispatch command, it will further send back a command receipt.

[0056] The operation of rail transit is characterized by real-time dynamic changes. From the time a command is issued until its execution at the receiving end, new related scheduling factors may change, or hidden problems may arise that were not discovered during the preliminary review. These problems cannot be fully covered by preliminary review alone. Therefore, by receiving command receipts from the distribution target in real time, the actual situation of the command in the transmission and execution stages can be captured. If the receipt shows abnormalities such as reception failure, rejection, or execution obstruction, it indicates that there are compatibility issues in the command that were not discovered during the preliminary review, and a second review is required for rapid intervention. If the receipt is normal, the validity of the command transmission and initial execution conditions can also be confirmed.

[0057] The real-time receipt of command acknowledgments from the distribution target, and the triggering of secondary command review of the scheduling command based on the command acknowledgments, include: The received command receipts from the distribution targets are classified, and the command receipt receipts and command signature receipt receipts are associated according to the scheduling command. Based on preset indicators, abnormal scenarios can be identified by considering associated command receipts and command signing receipts. The system matches the trigger conditions for secondary review based on abnormal scenarios, and determines whether the trigger conditions for secondary review are met based on the scheduling command and the corresponding command receipt and command sign-off receipt. When the conditions for triggering a secondary review are met, a secondary review order is triggered.

[0058] First, the receipts are divided into command receiving receipts and command signing receipts according to their type. At the same time, key identification information such as command number, execution object number, feedback time, and exception description keywords are extracted from the receipts. Then, the receiving receipts and signing receipts corresponding to the same scheduling command are bound by the two-dimensional association rules of command number and execution object number.

[0059] Based on the association of receipts, abnormal scenarios are identified by combining preset indicators. The preset indicators mainly include receipt completeness, feedback timeliness, and abnormal keyword matching degree of the content. By comparing the associated receipt information with these preset indicators one by one, abnormal scenarios are automatically identified.

[0060] The abnormal scenarios specifically include receiving timeout exceptions, signing exceptions due to parameter conflicts, and execution precondition exceptions.

[0061] Based on the identified abnormal scenarios, the system matches the preset secondary review trigger condition library and combines the information of the scheduling command itself and the associated receipt content to comprehensively determine whether the secondary review start requirements are met.

[0062] The secondary review triggering conditions are mainly composed of the severity of the anomaly and the priority of the corresponding scheduling command, and mainly include two types of triggering rules. The first is the absolute triggering condition, which applies to severe anomaly scenarios for all priority commands, such as reception failure, receipt containing security-related abnormal keywords, etc. As long as such situations occur, secondary review is directly triggered regardless of the command priority. The second is the threshold triggering condition, which is for timeout and non-severe anomaly scenarios. Differentiated thresholds are set based on command priority, and secondary review is only triggered when the corresponding threshold is exceeded.

[0063] When the conditions for triggering a secondary review are met, the corresponding secondary review process will be initiated according to the command priority, and the scheduling command will be modified again based on the associated scheduling factors when the review is triggered.

[0064] The step of modifying the scheduling command by incorporating the associated scheduling factors at the time of triggering the review includes: An audit information package is constructed based on the scheduling command to be corrected, the associated command receipt and command signature receipt, and the real-time associated scheduling factors when the audit is triggered, and then uploaded to the corresponding audit entity. Logical verification is performed based on the audit information package to identify the anomaly type and locate the cause of the anomaly. Based on the identification of abnormal causes, the command parameters to be adjusted are optimized by taking real-time associated scheduling factors as constraints and combining them with corresponding audit rules.

[0065] The abnormal scenarios that trigger secondary review during execution are mainly caused by changes in related scheduling factors. Therefore, the review process in the previous scheduling command formulation process can be used as a reference. Based on the scheduling command to be corrected, the associated command receiving receipt and command signing receipt, and the real-time related scheduling factors when the review is triggered, the review information package can be constructed, re-uploaded to the corresponding review subject, and the logic verification can be re-executed to determine the type of abnormality and locate the cause of the abnormality.

[0066] If the verification finds that the real-time related factors are consistent with the abnormal receipt description, but conflict with the command parameters to be corrected, the cause is identified as a command parameter deviation. If the real-time related factors are found to be significantly different from the factors in the previous review, and this difference causes the abnormal receipt, the cause is identified as a factor dynamic change. If both the real-time related factors and command parameters are found to be compliant, but the receipt is still abnormal, the cause is identified as a rule adaptation anomaly.

[0067] Based on the identification of abnormal causes, parameters to be adjusted are optimized using real-time scheduling factors as constraints and audit rules as the basis. Specifically, the corresponding parameter optimization can be achieved through optimization methods such as parameter optimization search.

[0068] Another aspect of this embodiment provides an intelligent dispatching system for urban rail transit, including: The automatic train monitoring module is used to collect real-time data on the status of trains and equipment. The dispatch service module is used to generate dispatch command information under the current status based on the status of trains and line equipment, combined with the dispatch command condition trigger template configuration file, identify the priority of the current dispatch command based on the dispatch command information, trigger command review based on the dispatch command priority, and receive command receipts from the distribution target in real time, and trigger secondary command review of the dispatch command based on the command receipts. The command review and correction module is used to review the scheduling command information based on the associated scheduling factors, and correct the scheduling command information based on the review results, or to make secondary corrections to the scheduling command based on the associated scheduling factors that triggered the review. The scheduling command issuing module is used to identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and to issue the corresponding scheduling command.

[0069] The Automatic Train Monitoring (ATM) module is installed in the Automatic Train Monitoring (ATM) system. It can monitor the status of signal system equipment and trains in real time during rail transit operation, so as to provide train and equipment status data generated by dispatching commands.

[0070] The scheduling service module consists of computers and other devices with corresponding data processing capabilities. It has built-in template files and audit trigger conditions, and can automatically generate scheduling commands and identify the audit requirements of the scheduling commands, thereby automatically issuing audit tasks.

[0071] The command review and correction module is also a computer or other device with corresponding command review and correction functions. It has built-in algorithms for automatic review and correction, and also has a corresponding manual review section for relevant reviewers to review scheduling commands.

[0072] The scheduling command publishing module is equipped with a computer and other devices featuring a scheduling command communication interface and an external database server. It can distribute scheduling commands and record corresponding scheduling commands to the database server. Furthermore, the scheduling command publishing module includes a scheduling command query interface and a template editing interface, allowing users to query scheduling commands or adjust template files in the scheduling service module as needed.

[0073] Taking fire-triggered dispatch commands as an example, when a fire is detected and the status of the equipment changes, the automatic train monitoring module will update the fire status and the train's operating status to the dispatch service module. The dispatch service module will then match the corresponding fire dispatch command strategy and retrieve the corresponding fire dispatch command template.

[0074] The fire dispatch command template mainly includes station command content and train command content. The station command content is "All trains on the line will stop at station %1", and the train command content is "Train %1 (car %2) will stop at station %3". Based on the station to which the fire-affected equipment belongs and the section where the train is located, the station and train affected by the fire are determined, and the corresponding station and train dispatch command content is generated by replacing the %1%2%3 parameters in the template.

[0075] Since dispatch orders for fire incidents have the highest priority, after automatic and manual review by the dispatch review and correction module, the dispatch order issuing module splits the dispatch order into station fire dispatch orders and train dispatch orders, and issues them separately to the corresponding station terminals and trains. Upon receiving the dispatch orders, the station terminals and trains send relevant acknowledgments based on the actual situation.

[0076] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Other variations and modifications are possible without departing from the technical solutions described in the claims.

Claims

1. An intelligent scheduling method for urban rail transit, characterized in that, include: Based on the status of trains and track equipment, and combined with the dispatch command condition trigger template configuration file, dispatch command information for the current status is generated; Identify the priority of the current scheduling command based on the scheduling command information, and trigger command review based on the scheduling command priority; The scheduling command information is reviewed based on the associated scheduling factors, and the scheduling command information is corrected based on the review results. Identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and issue the corresponding scheduling command. The system receives command receipts from the distribution target in real time, triggers a secondary command review of the scheduling command based on the command receipt, and makes secondary corrections to the scheduling command by taking into account the associated scheduling factors at the time of the review.

2. The intelligent scheduling method for urban rail transit according to claim 1, characterized in that, The process of generating dispatch command information based on the status of trains and track equipment, combined with the dispatch command condition trigger template configuration file, for the current status includes: Collect train operation status data and track equipment status data, and form a status dataset after preprocessing; The scheduling command triggering conditions of each template configuration file are matched one by one based on the state dataset, and the target scheduling command template is selected according to the matching results. The target scheduling command template is populated based on the state dataset to obtain scheduling command information.

3. The intelligent scheduling method for urban rail transit according to claim 1, characterized in that, The step of identifying the priority of the current scheduling command based on the scheduling command information and triggering command review based on the scheduling command priority includes: Based on the scheduling command information, the associated influencing factors of the scheduling command are extracted, including the command security attributes, scope of influence, and urgency level; Input the associated influencing factors into the priority rule base to match and obtain the priority of the current scheduling command; The corresponding review process is triggered based on the scheduling priority, and the review subject is identified according to the scheduling command information. The corresponding scheduling command information and review task are then sent to the corresponding review subject.

4. The intelligent scheduling method for urban rail transit according to claim 3, characterized in that, The step of reviewing scheduling command information based on associated scheduling factors and correcting the scheduling command information based on the review results includes: The auditing entity receives the corresponding scheduling command information and auditing task, and extracts the corresponding command execution object and command execution content based on the scheduling command information. Extract the corresponding associated scheduling factors based on the command execution object, and perform logical verification on the associated scheduling factors and command execution content based on preset audit rules; When a logic check fails, the type of check problem is identified based on the check result. Based on the type of verification problem, perform corrections to associated scheduling factors or adjustments to command execution content until the logical verification is passed.

5. The intelligent scheduling method for urban rail transit according to claim 4, characterized in that, The step of identifying the type of verification problem based on the verification result includes: Based on the verification results, identify conflict-related scheduling factors and conflict content fragments; Based on the conflict-related scheduling factors, extract the corresponding real-time data source data, and combine it with the conflict-related scheduling factor data applied during logical verification to identify data deviations. When data bias is detected, it is classified as a factor data bias problem. When there is no data bias, extract the factor requirements according to the conflict-related scheduling factors, and identify the limit-breaking of command parameters in the conflict content fragments according to the factor requirements. When command parameters are found to be out of bounds, the issue is classified as a command parameter deviation problem. In other cases, it is judged as a rule adaptation anomaly.

6. The intelligent scheduling method for urban rail transit according to claim 1, characterized in that, The command receipt for the distribution target includes a command receipt and a command signature receipt.

7. The intelligent scheduling method for urban rail transit according to claim 6, characterized in that, The real-time reception of command acknowledgments from the distribution target, and the triggering of secondary command review of the scheduling command based on the command acknowledgments, include: The received command receipts from the distribution targets are classified, and the command receipt receipts and command signature receipt receipts are associated according to the scheduling command. Based on preset indicators, abnormal scenarios can be identified by considering associated command receipts and command signing receipts. The system matches the trigger conditions for secondary review based on abnormal scenarios, and determines whether the trigger conditions for secondary review are met based on the scheduling command and the corresponding command receipt and command sign-off receipt. When the conditions for triggering a secondary review are met, a secondary review order is triggered.

8. The intelligent scheduling method for urban rail transit according to claim 7, characterized in that, The secondary modification of the scheduling command based on the associated scheduling factors triggered during the review process includes: An audit information package is constructed based on the scheduling command to be corrected, the associated command receipt and command signature receipt, and the real-time associated scheduling factors when the audit is triggered, and then uploaded to the corresponding audit entity. Logical verification is performed based on the audit information package to identify the anomaly type and locate the cause of the anomaly. Based on the identification of abnormal causes, the command parameters to be adjusted are optimized by taking real-time associated scheduling factors as constraints and combining them with corresponding audit rules.

9. The intelligent scheduling method for urban rail transit according to any one of claims 1 to 8, characterized in that, The dispatch command information includes at least the command receiving station, the station command content, the command receiving train, and the train command content.

10. An intelligent dispatching system for urban rail transit, used to execute the intelligent dispatching method according to any one of claims 1 to 9, characterized in that, include: The automatic train monitoring module is used to collect real-time data on the status of trains and equipment. The dispatch service module is used to generate dispatch command information under the current status based on the status of trains and line equipment, combined with the dispatch command condition trigger template configuration file, identify the priority of the current dispatch command based on the dispatch command information, trigger command review based on the dispatch command priority, and receive command receipts from the distribution target in real time, and trigger secondary command review of the dispatch command based on the command receipts. The command review and correction module is used to review the scheduling command information based on the associated scheduling factors, and correct the scheduling command information based on the review results, or to make secondary corrections to the scheduling command based on the associated scheduling factors that triggered the review. The scheduling command issuing module is used to identify the distribution target based on the corrected scheduling command information or the scheduling command information that has not triggered command review, and to issue the corresponding scheduling command.

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