CN119428805A - Intelligent dispatching method and device for urban rail train broadcast fault scenario - Google Patents
Intelligent dispatching method and device for urban rail train broadcast fault scenario Download PDFInfo
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Abstract
本申请涉及城市轨道交通行车调度技术领域，公开了一种城轨列车广播故障场景下的智能调度方法及装置。方法包括：实时收集列车广播系统的工作参数，使用机器学习算法分析识别故障，生成故障信息；对故障信息进行处理并发送，还校验故障信息，校验失败后进行校正，之后将校正后的故障信息加密后发送；在人工广播可用的情况下，提示调度员启用远程人工广播，并通知车辆基地准备备用车，否则，直接通知车辆基地准备备用车；根据故障类型和严重程度判断是否需要加开备用车，若需要则调整列车交路，自动生成并执行动态调整运行方案，本发明通过智能故障识别和动态调整机制，提高了列车广播系统故障处理的效率和列车运行的安全性。
The present application relates to the technical field of urban rail transit train dispatching, and discloses an intelligent dispatching method and device in the scenario of urban rail train broadcasting fault. The method includes: collecting the working parameters of the train broadcasting system in real time, using machine learning algorithms to analyze and identify faults, and generating fault information; processing and sending the fault information, and also verifying the fault information, correcting it after verification fails, and then encrypting and sending the corrected fault information; when manual broadcasting is available, prompting the dispatcher to enable remote manual broadcasting, and notifying the vehicle base to prepare spare vehicles, otherwise, directly notifying the vehicle base to prepare spare vehicles; judging whether to add spare vehicles according to the type and severity of the fault, and adjusting the train route if necessary, automatically generating and executing a dynamic adjustment operation plan. The present invention improves the efficiency of train broadcasting system fault handling and the safety of train operation through intelligent fault identification and dynamic adjustment mechanisms.
Description
Technical Field
The application relates to the technical field of urban rail transit driving scheduling, in particular to an intelligent scheduling method and device under a urban rail train broadcasting fault scene.
Background
The train broadcast fault is one of common faults of the train in the urban rail transit operation process, the fault occurrence rate is higher, if the fault treatment is not timely, the passenger service and the normal operation of the train are greatly influenced, even the operation order is influenced, at present, in the actual operation process of the urban rail transit line, the train broadcast fault is mainly treated manually by means of cooperation of a central driving dispatcher and a driver, the fault treatment is mainly carried out according to personal experience and operation regulations, the treatment time is long, the efficiency is lower, the comprehensive capability of the fault treatment of the operators is required to be higher, and the risk of further expanding the fault influence range due to improper treatment exists. At present, an intelligent auxiliary scheduling method for a train broadcasting fault scene in urban rail transit does not exist, and a corresponding intelligent scheduling device for the fault scene is also lacked.
A similar prior art publication number CN110329319A provides a full-automatic operation system for an intelligent urban rail, which comprises an intelligent urban rail facility layer, an intelligent urban rail platform layer and an intelligent urban rail application layer, wherein the intelligent urban rail facility layer is an IaaS layer and comprises a production cloud, a high-speed network, big data processing calculation and storage equipment, the intelligent urban rail platform layer is a PaaS layer and comprises a data center, a real-time database and a plug and play soft bus, and the intelligent urban rail application layer is an SaaS layer and comprises an intelligent scheduling subsystem, an intelligent station, an intelligent parking lot, an intelligent operation and maintenance subsystem and an unmanned intelligent train. A similar prior art also has a chinese patent application with publication number CN118722791a, and provides an intelligent adjustment method, apparatus, medium and product under conditions of sudden large passenger flow, where the method includes obtaining relevant information of location, scale, time, etc. of large-scale activities, and a weekday rail transit plan; determining a temporary passenger train adding plan according to the activity information and the weekday plan, determining a planned train number, adding passenger limit and passenger operation constraint model according to the adding plan and the weekday plan, determining a passenger taking and descending constraint model by adopting a time discretization method, establishing a train operation adjustment model by taking the minimum waiting time of passengers staying at a platform as a target, solving the model by adopting a CPLEX and a Benders decomposition method to obtain a train operation data set, and determining a train operation diagram after adding passenger according to the data set.
However, the technical solutions of the two applications do not consider how to intelligently schedule trains in a train broadcasting fault scenario. Therefore, the invention provides an intelligent scheduling method and device in a broadcasting fault scene of a urban rail train.
Disclosure of Invention
The application provides an intelligent scheduling method in a urban rail train broadcasting fault scene, which is used for improving the scheduling treatment efficiency after train broadcasting faults, reducing the dependence on personal experience of scheduling personnel by an automatic and intelligent means, reducing the fault treatment time and improving the operation efficiency.
In a first aspect, the present application provides an intelligent scheduling method in a broadcast fault scenario of a urban rail train, where the method includes:
S1, collecting working parameters of a train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults, generating fault information under the condition that the train broadcasting system is identified to have faults, wherein the fault information comprises train broadcasting fault information and information about whether manual broadcasting is available, and transmitting the fault information to a TCMS (train control system);
S2, establishing communication connection between a TCMS system and each subsystem of a train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes fault information after receiving the fault information and sends the processed fault information to a vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, and sends the fault information to a central ATS subsystem after encrypting the fault information if the verification is successful, and corrects the fault information if the verification is unsuccessful and sends the corrected fault information to the central ATS subsystem after encrypting the fault information;
S3, prompting a central driving dispatcher to start remote manual broadcasting on the fault train at a system interface under the condition that manual broadcasting is available, and sending an electronic scheduling command to inform the vehicle base driving dispatcher of preparing for adding the spare vehicle;
And S4, judging whether the spare vehicle needs to be started according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing an operation diagram preview interface.
With reference to the first aspect, in a first implementation manner of the first aspect of the present application, processing fault information includes:
S21, converting the fault information into binary data, dividing the binary data into a plurality of data according to a preset bit number, generating a corresponding correction code based on each data, combining each data with the corresponding correction code to generate a data group, numbering each data group from the beginning in sequence, presetting a first quantity, arranging the first quantity of data groups into a row according to the sequence of the numbers until all the data groups are arranged, generating a corresponding data group sequence diagram, taking the first data group of the data group sequence diagram as a first data group, taking the second quantity of other data groups forming right diagonal with the first data group as a second data group, and when the quantity of the second data group forming right diagonal with the first data group is smaller than the second quantity, supplementing a second data group by using preset first data as a supplementing data group, enabling the number of the second data group to reach a second number, carrying out first operation on the second data group and the first data group to generate first check data, further enabling a second number of other data groups forming a left diagonal with the first data group to be called a third data group, carrying out first operation on the third data group and the first data group to generate second check data, supplementing the third data group by using preset first data as the supplementing data group under the condition that the number of the third data group forming the left diagonal with the third data group is smaller than the second number, enabling the number of the third data group to reach a second number which is equal to the first number minus one, repeating the steps, calculating the first check data and the second check data corresponding to all the data groups in the data group sequence diagram;
And S22, transmitting all the data groups and the corresponding numbers, the first check data and the second check data to the vehicle-mounted VOBC.
With reference to the first aspect, in a second implementation manner of the first aspect of the present application, after the vehicle-mounted VOBC receives the fault information, verifying the fault information includes:
S221, generating a data set sequence diagram by the vehicle-mounted VOBC based on the number, judging whether a missing data set exists or not based on the number, and if so, acquiring a first missing data set as a first missing data set, and acquiring the second data set forming a right diagonal line with the first missing data set based on the data set sequence diagram;
s222, under the condition that the second data set is not missing, corresponding first check data are obtained, first operation is carried out on the first check data and the second data set to obtain a result value, and the obtained result value is used as the first missing data set to be supplemented into the data set sequence diagram;
S223, under the condition that the second data set is missing, acquiring the missing data set in the second data set as a second missing data set, and acquiring a third data set forming a left diagonal line with the second missing data set;
S224, under the condition that the third data set does not have a deletion, acquiring the second check data corresponding to a second missing data set, performing first operation on the second check data and the third data set to acquire a result value, taking the result value as the second missing data set, supplementing the second missing data set into a data set sequence diagram, acquiring the second data set without the deletion, and acquiring the first missing data set based on the second data set and the corresponding first check data;
s225, returning to S223 to acquire the missing data set in the third data set under the condition that the third data set is missing;
s226, judging whether the missing data sets are not supplemented, if not, ending the step, and if so, returning to S221 until all the missing data sets are supplemented completely.
With reference to the first aspect, in a third implementation manner of the first aspect of the present application, after all missing data sets are complemented, further performing:
Generating first verification data and second verification data corresponding to each data group based on the data group sequence diagram, comparing the first verification data with the first verification data, comparing the second verification data with the second verification data, judging that the corresponding data group is successful in verification if the first verification data is identical to the first verification data, otherwise, judging that the corresponding data group is failed in verification, and correcting the data group which is failed in verification.
With reference to the first aspect, in a fourth implementation manner of the first aspect of the present application, correcting the data set that fails to be checked includes:
and acquiring a data set, acquiring original data and a corresponding correction code based on the data set, and correcting the original data based on the correction code.
With reference to the first aspect, in a fifth implementation manner of the first aspect of the present application, the sending the corrected fault information after encryption to the central ATS subsystem includes:
Obtaining a current time stamp, generating a first key based on the time stamp and fault information, encrypting the fault information for a plurality of times based on the first key to generate first secret data, generating a corresponding first hash value based on the first secret data, encrypting the first key, the first hash value and the first secret data by using a second key to generate second secret data, and transmitting the second secret data to a central ATS subsystem.
With reference to the first aspect, in a sixth implementation manner of the first aspect of the present application, after the central ATS subsystem receives the second secret data, the method includes:
Decrypting the second secret data based on the second key to obtain the first key, the first hash value and the first secret data;
And decrypting the first secret data based on the first key to obtain corresponding first decrypted data, generating a corresponding second hash value based on the first decrypted data, judging whether the second hash value is identical to the first hash value, ending the step if the second hash value is identical to the first hash value, and repeating the step if the second hash value is not identical to the first hash value until the second hash value is identical to the first hash value.
With reference to the first aspect, in a seventh implementation manner of the first aspect of the present application, automatically generating a dynamically adjusted operation scheme includes:
The method comprises the steps of representing stations as nodes of a graph, representing track sections between stations as edges of the graph, collecting train operation data and passenger flow data of a fault train operation line, generating a delay propagation model based on train delay caused by a graph simulation train fault, predicting influence of the fault train on a subsequent train based on the propagation model, deferring departure time for the affected but not yet departure train, and adjusting operation speed for the affected already operated train.
In a second aspect, the present application provides an intelligent scheduling apparatus in a broadcast fault scenario of a urban rail train, where the apparatus includes:
The identification module is used for collecting working parameters of the train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults, generating fault information under the condition that the train broadcasting system is identified to have faults, wherein the fault information comprises train broadcasting fault information and information about whether manual broadcasting is available, and transmitting the fault information to the TCMS;
The transmission module is used for establishing communication connection between the TCMS system and each subsystem of the train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes the fault information after receiving the fault information and transmits the processed fault information to the vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, and the fault information is encrypted and then transmitted to the central ATS subsystem when the verification is successful, and the fault information is corrected when the verification is unsuccessful and the corrected fault information is encrypted and then transmitted to the central ATS subsystem;
The scheduling module is used for prompting a central driving scheduler to start remote manual broadcasting on a fault train at a system interface under the condition that manual broadcasting is available, sending an electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle, and directly sending the electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle under the condition that manual broadcasting is unavailable;
The adjustment module is used for judging whether the spare vehicle needs to be started according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing an operation diagram preview interface.
Compared with the prior art, the invention has the following beneficial effects:
According to the technical scheme, working parameters of a train broadcasting system are collected in real time, faults are analyzed and identified by using a machine learning algorithm, fault information can be quickly generated and processed, so that the efficiency of fault processing of the train broadcasting system is improved, when the broadcasting system breaks down, a train running scheme is timely adjusted, train delay time is shortened, train running safety is guaranteed, an automatic and intelligent fault identification mechanism reduces dependence on personal experience of a modulator, the risk of improper fault handling caused by insufficient personal experience is reduced, the train running scheme can be quickly adjusted when the faults happen, the influence on the running order is reduced by the dynamic adjustment mechanism, the overall running efficiency is improved, safety of the fault information in the transmission process is guaranteed through an encryption technology, data is prevented from being tampered, two check data on a left diagonal line and a right diagonal line are generated for each data set, the recovery capability of the data set under the condition of losing is improved, the vehicle-mounted VOBC is guaranteed to obtain accurate fault information through the check and correction mechanism, correct scheduling decision is made, the automatic train running scheme is required to be automatically started, the influence on the running efficiency of the railway system due to the fact that the fault is required to be insufficient, the automatic train running scheme is adjusted, the running efficiency of the system is reduced, the running efficiency of the railway is reduced, the running system is improved, the running efficiency is improved and the running efficiency of the railway is improved and the running system is improved due to the fact that the artificial running system is based on the fact that the artificial running scheme is adjusted is in a complicated and the running scheme is adjusted.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained based on these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an embodiment of an intelligent scheduling method under a broadcast fault scenario of a urban rail train according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an embodiment of a sequence diagram of data sets in an embodiment of the application
Fig. 3 is a schematic diagram of an embodiment of an intelligent scheduling apparatus in a broadcast fault scenario of a urban rail train according to an embodiment of the present application.
Detailed Description
The embodiment of the application provides an intelligent scheduling method and device in a broadcasting fault scene of a urban rail train. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For easy understanding, a specific flow of an embodiment of the present application is described below, referring to fig. 1, and an embodiment of an intelligent scheduling method in a broadcast fault scenario of a urban rail train in the embodiment of the present application includes:
S1, collecting working parameters of a train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults, generating fault information under the condition that the train broadcasting system is identified to have faults, wherein the fault information comprises train broadcasting fault information and information about whether manual broadcasting is available, and transmitting the fault information to a TCMS.
Specifically, in the urban rail transit operation process, the train broadcasting system is an important operation production system, is a voice broadcasting system for broadcasting service information such as emergency notification, train operation, passenger guidance and the like and issuing operation commands and notifications to staff, and the train broadcasting fault is one of common faults of the train in the urban rail transit operation process, has higher fault occurrence rate, and can cause great influence on passenger service and normal operation of the train even influence the operation order if the fault is recognized or handled untimely.
In order to timely identify whether a city rail train broadcasting system breaks down or not, the operation state of the city rail train broadcasting system is monitored by collecting the operation parameters of the train broadcasting system in real time, the operation parameters comprise broadcasting volume, tone quality, broadcasting equipment power state, broadcasting signal intensity, broadcasting system hardware temperature, voltage and the like, then the collected operation parameters are analyzed by using a machine learning algorithm, the operation parameters are preprocessed firstly, key feature extraction is carried out, such as volume fluctuation range, tone quality distortion degree, power voltage fluctuation, signal intensity attenuation rate and the like, model training is carried out by using historical fault data and normal data to construct a fault identification model, the fault identification model judges whether faults exist according to the extracted key features, fault types, such as loudspeaker damage, power faults, program abnormality, signal interference and the like, the fault severity degree is also evaluated, such as slight faults affecting part of carriage broadcasting functions, serious faults affecting whole train broadcasting functions are also judged by monitoring whether the artificial broadcasting equipment states are available or not, fault information is generated after the fault information is identified, the fault information comprises fault time, fault type, fault severity degree and whether artificial broadcasting is available or not is sent to a TCMS system.
S2, establishing communication connection between the TCMS system and each subsystem of the train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes the fault information after receiving the fault information and sends the processed fault information to the vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, encrypts the fault information and sends the fault information to the central ATS subsystem under the condition of successful check, corrects the fault information under the condition of unsuccessful check, encrypts the corrected fault information and sends the fault information to the central ATS subsystem.
Specifically, if the vehicle-mounted VOBC receives wrong fault information, the subsequent fault processing may cause a larger problem, in order to enable the vehicle-mounted VOBC to receive the correct fault information, the TCMS system processes the fault information after receiving the fault information, the specific processing process may be explained in detail later, the processed fault information is sent to the vehicle-mounted VOBC, the vehicle-mounted VOBC further verifies the fault information after receiving the fault information, under the condition of successful verification, the fault information is accurate, and because the vehicle-mounted VOBC and the central ATS subsystem are in communication through a wireless network, in the process of transmitting the fault information, the fault information may be tampered, so that in order to ensure the safety of the fault information in the transmission process, the fault information is encrypted and then sent to the central ATS subsystem, under the condition of unsuccessful verification, the fault information is indicated to have errors, the fault information after being corrected, and the fault information after being encrypted is sent to the central ATS subsystem, and the reliability and the safety of the fault information transmission can be ensured through the method.
S3, prompting a central driving dispatcher to start remote manual broadcasting on the fault train at a system interface under the condition that manual broadcasting is available, and sending an electronic dispatching command to inform the vehicle base driving dispatcher of preparing for adding the spare vehicle.
Specifically, after the central ATS subsystem acquires fault information, under the condition that manual broadcasting is available, a central driving dispatcher is automatically prompted to start remote manual broadcasting on a fault train through a system interface, after the central driving dispatcher confirms the prompt manually, remote manual broadcasting is started, an electronic scheduling command is also automatically sent to inform a vehicle base driving dispatcher of preparing for adding a spare vehicle, the vehicle base driving dispatcher signs a scheduling command and prepares for adding, under the condition that manual broadcasting is unavailable, the electronic scheduling command is directly sent to inform the vehicle base driving dispatcher of preparing for adding the spare vehicle, the vehicle base driving dispatcher immediately arranges the spare vehicle to enter a standby state after receiving the command, and performs relevant preparation work, for example, whether a broadcasting system of the spare vehicle is normal or not is checked, a driver is arranged to stand by, a station is informed of preparing for taking a vehicle, and the like.
S4, judging whether the spare vehicle needs to be started or not according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing an operation diagram preview interface.
Specifically, the central ATS subsystem judges whether the spare vehicle needs to be started according to the received fault information, fault type and severity, for example, if the fault severity reaches a certain degree, manual broadcasting is unavailable or the train delay time exceeds a preset threshold value, the need of the spare vehicle is determined, when the spare vehicle needs to be started, the central ATS subsystem automatically generates an adjusted train crossing scheme according to the current train running state, station passenger flow condition and other factors, the scheme content comprises crossing adjustment of a fault train and other related trains, the time and position of the running of the spare vehicle, adjustment of a train stop station, adjustment of the running speed of the train and the like, the dynamic adjusted train running scheme such as train schedule adjustment, train running speed adjustment, train stop station adjustment and the like is automatically generated, a central traffic dispatcher checks the generated adjustment running scheme on a running map preview interface, after confirming that the error is avoided, the central ATS subsystem clicks and executes the adjusted train running scheme.
When the urban rail train broadcasting system fails, the method processes the failure in time, and under the condition of adding the spare vehicle, the train operation safety is ensured by adjusting the road crossing of the failure train and other related trains and the train operation scheme, the train delay time is reduced, and the operation efficiency is improved.
Through the implementation mode, faults of the urban rail train broadcasting system can be effectively handled, and reliability and safety of train operation are improved.
In a specific embodiment, the fault information processing method specifically includes the following steps:
S21, converting fault information into binary data, dividing the binary data into a plurality of data according to a preset bit number, generating a corresponding correction code based on each data, combining each data and the corresponding correction code to generate data groups, numbering each data group from the beginning in sequence, presetting a first quantity, arranging the first quantity of data groups into a line according to the sequence of numbers until all data groups are arranged to generate a corresponding data group sequence diagram, taking the first data group of the data group sequence diagram as the first data group, taking the second quantity of other data groups forming right diagonal with the first data group as the second data group, supplementing the second data group by using the preset first data as a supplementing data group under the condition that the quantity of the second data group forming right diagonal with the first data group is smaller than the second quantity, the number of the second data groups reaches a second number, first operation is carried out on the second data groups and the first data groups to generate first check data, the second number of other data groups forming left diagonal lines with the first data groups are also called third data groups, first operation is carried out on the third data groups and the first data groups to generate second check data, when the number of the third data groups forming left diagonal lines with the third data groups is smaller than the second number, the preset first data are used as supplementary data groups to supplement the third data groups, the number of the third data groups reaches the second number, the second number is equal to the first number minus one, the steps are repeated, and the first check data and the second check data corresponding to all the data groups in the data group sequence diagram are calculated;
s22, all the data sets, the corresponding numbers, the first check data and the second check data are sent to the vehicle-mounted VOBC.
Specifically, the fault information to be transmitted is converted into binary data for subsequent grouping and verification processing, the binary data is divided into a plurality of data according to a preset bit number (for example, 8 bits, 16 bits or 32 bits), a corresponding correction code is generated based on each data, the correction code can correct the data in the case that the data is in error, and the data and the correction code are combined to generate a data set. Each data group contains the same number of bits, each data group is numbered from the beginning in sequence for subsequent identification and processing, a first number (assumed to be 5) is preset and represents the number of data groups in each row, the first number of data groups are arranged into one row according to the sequence of the numbers to generate a data group sequence diagram shown in figure 2, for the first data group a1 of fault information, as shown in figure 2, a1 and a7, a13, a19 and a25 forming a diagonal with a1 are subjected to first operation to generate corresponding first check data C5, wherein a7, a13, a19 and a25 are connected with a1 to form a right diagonal in the data group sequence diagram, the first operation is an exclusive OR operation, the first check data of the 5 data a1, a2, a3, a4 and a5 are all C5, corresponding second check data are also generated for a1, as shown in figure 2, since a1 is the first data group, 4 a0 are used as the replacement data and a1 form a left diagonal line, and a first operation is performed to generate corresponding second check data D1, a2 and a6 are two data, 3 a0 and a2, a6 are added to form a left diagonal line, and a first operation is performed to generate second check data D2, at this time, the second check data of a2 and a6 are all D2, as shown in fig. 2, a8, a14 and a20 also form a right diagonal line, but the number of them is only four, so that a preset first data, namely a0 is used as the replacement data and a2, a8, a14 and a20 are performed to generate corresponding first check data C4, and then all data groups in the data group sequence diagram are generated corresponding first check data and second check data by using the same method as described above, and all data groups and corresponding numbers are then, the first verification data and the second verification data are sent to the vehicle-mounted VOBC.
In a specific embodiment, after the vehicle-mounted VOBC receives the fault information, the fault information is checked, which specifically includes the following steps:
S221, generating a data set sequence diagram by the vehicle-mounted VOBC based on the number, and judging whether a missing data set exists or not based on the number, if so, acquiring a first missing data set as a first missing data set, and acquiring a second data set forming a right diagonal line with the first missing data set based on the data set sequence diagram;
S222, under the condition that the second data set is not missing, corresponding first check data are obtained, first operation is carried out on the first check data and the second data set to obtain a result value, and the obtained result value is used as a first missing data set to be supplemented into a data set sequence diagram;
S223, under the condition that the second data set is missing, acquiring the missing data set in the second data set as a second missing data set, and acquiring a third data set forming a left diagonal line with the second missing data set;
S224, under the condition that the third data set does not have a defect, obtaining second check data corresponding to the second missing data set, performing first operation on the second check data and the third data set to obtain a result value, taking the result value as the second missing data set, supplementing the second missing data set into a data set sequence diagram, obtaining the second data set without the defect, and obtaining the first missing data set based on the second data set and the corresponding first check data;
s225, returning to S223 to acquire the missing data set in the third data set under the condition that the third data set is missing;
s226, judging whether the missing data sets are not supplemented, if not, ending the step, and if so, returning to S221 until all the missing data sets are supplemented completely.
Specifically, as shown in fig. 2, assuming that a1 is a missing data set, a second data set (a 7, a13, a19 and a 25) with diagonal lines formed with a1 is acquired, if the second data set, that is, a7, a13, a19 and a25 are not missing, corresponding first check data C5 is acquired, the result value obtained by performing the dissimilation operation on C5 and a7, a13, a19 and a25 is assumed to be b1, b1 is supplemented to the data set sequence diagram, and the missing data set a1 is supplemented.
If there is a missing second data set, assuming that a7 is the missing second data set, a third data set (a 3, a11, a0, a 0) forming a left diagonal line with a7 is acquired, and if there is no missing in both a3 and a11, corresponding second check data D3 is acquired, the third data set, that is, (a 3, a11, a0, a 0) and the second check data D3 acquire a result value b2, and b2 is supplemented as the missing data set a7 to the data set sequence diagram, at this time, the second data set is supplemented completely, and the missing data set a1 can be supplemented based on the second data set and the corresponding first check data.
It should be noted that if the second calibration data D3 is found to be missing, it may be obtained by performing an exclusive or operation based on a3, a11 and two a0, or if a3 or a11 is found to be missing, it may be calculated after supplementing a3 or a 11.
In the case that the third data set is missing, assuming that a3 is missing, the second data sets a9 and a15 forming a diagonal line with a3 are acquired, corresponding first check data C3 is also acquired, a9, a15 and C3 are subjected to a first operation to acquire a corresponding result value b3, b3 is added to the third data set as missing a3, the third data set is added completely, the second data set is added based on the third data set and the corresponding second check data D3, and the missing data set a1 is added based on the second data set and the first check data C5.
And judging whether the missing data group exists in the data group sequence diagram, if not, ending the step, and if so, continuing to execute the missing data group supplementation from S221 until the missing data group is supplemented completely.
According to the method, the two check data on the left diagonal line and the right diagonal line are generated for each data set, so that the lost data set can be recovered based on the two check data under the condition that the data set is lost, the recovery capacity of the data set is improved, and the vehicle-mounted VOBC is ensured to receive complete fault information.
In one embodiment, the following steps are performed after all missing data sets are complemented:
And generating first verification data and second verification data corresponding to each data group based on the data group sequence diagram, comparing the first verification data with the first verification data, comparing the second verification data with the second verification data, judging that the corresponding data group is successfully verified if the first verification data is identical with the first verification data, otherwise, judging that the corresponding data group is failed to verify, and correcting the data group which is failed to verify.
Specifically, in order to make the VOBC acquire accurate fault information, after the missing data set is complemented and complete, there may be some faulty data sets, so that the data sets are verified again, the first verification data of each data set is generated by using a method for generating the first verification data, the second verification data of the data sets is generated by using a method for generating the second verification data, the first verification data and the first verification data are compared for each data set, the second verification data and the second verification data are compared, if they are the same, it is indicated that the data sets are not faulty, it is determined that the data sets are successful, if the first verification data and the first verification data are different, or the second verification data and the second verification data are different, or they are different, it is indicated that the data sets may be faulty, a correction is required for the data sets that fail in verification, and a specific correction method will be explained in detail later.
In one embodiment, the method for correcting the data set with failed verification specifically includes the following steps:
The data set is acquired, the original data and the corresponding correction code are acquired based on the data set, and the original data is corrected based on the correction code.
Specifically, the correction code may be a code with a correction function, such as a hamming code, obtained based on the original data, and correct the original data based on the correction code, so as to obtain the original data without errors, and finally recover the fault information based on the original data, so that the vehicle-mounted VOBC can be ensured to obtain the accurate fault information without errors based on the method.
In a specific embodiment, the corrected fault information is encrypted and then sent to the central ATS subsystem, which specifically includes the following steps:
The method comprises the steps of obtaining a current time stamp, generating a first key based on the time stamp and fault information, encrypting the fault information for multiple times based on the first key to generate first secret data, generating a corresponding first hash value based on the first secret data, encrypting the first key, the first hash value and the first secret data by using a second key to generate second secret data, and sending the second secret data to a central ATS subsystem.
Specifically, since the vehicle-mounted VOBC and the central ATS subsystem communicate through the wireless network, the vehicle-mounted VOBC is easy to be tampered when data transmission is performed, in order to ensure the security of fault information in the transmission process, the vehicle-mounted VOBC encrypts the corrected fault information and then sends the encrypted fault information to the central ATS subsystem, firstly, a current time stamp is obtained, a first secret key is generated based on the time stamp and the fault information, for example, an existing HMAC-SHA256 algorithm can be used, the time stamp and the fault information are used as input, a secret key with a fixed length is generated, the security is enhanced by generating a dynamic secret key, then the fault information is encrypted for multiple times by using the first secret key to generate first secret data, the difficulty of cracking is increased by encrypting the fault information for multiple times, the security is improved, the corresponding first hash value is generated based on the first secret data, for example, the first secret data can be subjected to hash calculation by using a preset hash function SHA-256, the first secret key, the first hash value and the first secret data are encrypted by using a second secret key, the second secret key is generated by using the second secret key, the second secret key is encrypted by using the first hash value and the vehicle-mounted vos data is the second secret key and the vehicle-mounted ATS subsystem is further encrypted by using the second secret key, the fault information is encrypted by the vehicle-mounted vos has good secret key, and the security is further encrypted by the fault information.
In one embodiment, after the central ATS subsystem receives the second secret data, the method specifically includes the following steps:
Decrypting the second secret data based on the second key to obtain a first key, a first hash value and the first secret data;
And decrypting the first secret data based on the first key to obtain corresponding first decrypted data, generating a corresponding second hash value based on the first decrypted data, judging whether the second hash value is identical to the first hash value, ending the step if the second hash value is identical to the first hash value, and repeating the step if the second hash value is not identical to the first hash value until the second hash value is identical to the first hash value.
Specifically, after the central ATS subsystem receives the second secret data, it decrypts the second secret data based on the second key to obtain the first key, the first hash value and the first secret data, decrypts the first secret data based on the first key to obtain the first decrypted data, generates the second hash value based on the first decrypted data, determines whether the second hash value is identical to the first hash value, if so, it indicates that the vehicle-mounted VOBC encrypts the fault information once, the first decrypted data at this time is the fault information, if not, it indicates that the vehicle-mounted VOBC encrypts the fault information more than once, at this time, it continues to decrypt the first decrypted data using the first key until the second hash value is identical to the first hash value, and uses the obtained corresponding second decrypted data as the fault information.
In a specific embodiment, the method for automatically generating the dynamic adjustment operation scheme specifically includes the following steps:
the method comprises the steps of representing stations as nodes of a graph, representing track sections between stations as edges of the graph, collecting train operation data and passenger flow data of a fault train operation line, generating a delay propagation model based on train delay caused by a graph simulation train fault, predicting influence of the fault train on a subsequent train based on the propagation model, deferring departure time for the affected but not yet departure train, and adjusting operation speed for the affected already operated train.
Specifically, a station and a track section are abstracted into a graph model, delay propagation caused by train faults is simulated by utilizing train operation data and passenger flow data, the departure time and the operation speed of the affected train are adjusted based on the propagation model, the delay propagation caused by the train faults is simulated, and the operation plan of the following train is dynamically adjusted based on the simulation result, so that the influence of the faults on the whole track traffic system is reduced.
The foregoing describes an intelligent scheduling method in a broadcasting fault scenario of a urban rail train in an embodiment of the present application, and the following describes an intelligent scheduling device in a broadcasting fault scenario of a urban rail train in an embodiment of the present application, referring to fig. 3, an embodiment of an intelligent scheduling device in a broadcasting fault scenario of a urban rail train in an embodiment of the present application includes:
The identification module is used for collecting working parameters of the train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults or not, generating fault information under the condition that the train broadcasting system is identified to have faults, and transmitting the fault information to the TCMS system, wherein the fault information comprises train broadcasting fault information and available information of manual broadcasting or not;
The transmission module is used for establishing communication connection between the TCMS system and each subsystem of the train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes the fault information after receiving the fault information and sends the processed fault information to the vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, encrypts the fault information and sends the fault information to the central ATS subsystem under the condition of successful check, corrects the fault information under the condition of unsuccessful check, and encrypts the corrected fault information and sends the fault information to the central ATS subsystem;
The scheduling module is used for prompting a central driving scheduler to start remote manual broadcasting on a fault train at a system interface under the condition that manual broadcasting is available, sending an electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle, and directly sending the electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle under the condition that manual broadcasting is unavailable;
The adjustment module is used for judging whether the spare vehicle needs to be started according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing the operation scheme preview interface.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, systems and units may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. The storage medium includes a U disk, a removable hard disk, a read-only memory (ROM), a random access memory (random acceS memory, RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
While the application has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that the foregoing embodiments may be modified or equivalents may be substituted for some of the features thereof, and that the modifications or substitutions do not depart from the spirit and scope of the embodiments of the application.
Claims (9)
1. An intelligent scheduling method in a urban rail train broadcasting fault scene is characterized by comprising the following steps:
S1, collecting working parameters of a train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults, generating fault information under the condition that the train broadcasting system is identified to have faults, wherein the fault information comprises train broadcasting fault information and information about whether manual broadcasting is available, and transmitting the fault information to a TCMS (train control system);
S2, establishing communication connection between a TCMS system and each subsystem of a train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes fault information after receiving the fault information and sends the processed fault information to a vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, and sends the fault information to a central ATS subsystem after encrypting the fault information if the verification is successful, and corrects the fault information if the verification is unsuccessful and sends the corrected fault information to the central ATS subsystem after encrypting the fault information;
S3, prompting a central driving dispatcher to start remote manual broadcasting on the fault train at a system interface under the condition that manual broadcasting is available, and sending an electronic scheduling command to inform the vehicle base driving dispatcher of preparing for adding the spare vehicle;
And S4, judging whether the spare vehicle needs to be started according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing an operation diagram preview interface.
2. The method of claim 1, wherein processing the fault information comprises:
S21, converting the fault information into binary data, dividing the binary data into a plurality of data according to a preset bit number, generating a corresponding correction code based on each data, combining each data with the corresponding correction code to generate a data group, numbering each data group from the beginning in sequence, presetting a first quantity, arranging the first quantity of data groups into a row according to the sequence of the numbers until all the data groups are arranged, generating a corresponding data group sequence diagram, taking the first data group of the data group sequence diagram as a first data group, taking the second quantity of other data groups forming right diagonal with the first data group as a second data group, and when the quantity of the second data group forming right diagonal with the first data group is smaller than the second quantity, supplementing a second data group by using preset first data as a supplementing data group, enabling the number of the second data group to reach a second number, carrying out first operation on the second data group and the first data group to generate first check data, further enabling a second number of other data groups forming a left diagonal with the first data group to be called a third data group, carrying out first operation on the third data group and the first data group to generate second check data, supplementing the third data group by using preset first data as the supplementing data group under the condition that the number of the third data group forming the left diagonal with the third data group is smaller than the second number, enabling the number of the third data group to reach a second number which is equal to the first number minus one, repeating the steps, calculating the first check data and the second check data corresponding to all the data groups in the data group sequence diagram;
And S22, transmitting all the data groups and the corresponding numbers, the first check data and the second check data to the vehicle-mounted VOBC.
3. The method of claim 2, wherein verifying the fault information after the vehicle-mounted VOBC receives the fault information comprises:
S221, generating a data set sequence diagram by the vehicle-mounted VOBC based on the number, judging whether a missing data set exists or not based on the number, and if so, acquiring a first missing data set as a first missing data set, and acquiring the second data set forming a right diagonal line with the first missing data set based on the data set sequence diagram;
s222, under the condition that the second data set is not missing, corresponding first check data are obtained, first operation is carried out on the first check data and the second data set to obtain a result value, and the obtained result value is used as the first missing data set to be supplemented into the data set sequence diagram;
S223, under the condition that the second data set is missing, acquiring the missing data set in the second data set as a second missing data set, and acquiring a third data set forming a left diagonal line with the second missing data set;
S224, under the condition that the third data set does not have a deletion, acquiring the second check data corresponding to a second missing data set, performing first operation on the second check data and the third data set to acquire a result value, taking the result value as the second missing data set, supplementing the second missing data set into a data set sequence diagram, acquiring the second data set without the deletion, and acquiring the first missing data set based on the second data set and the corresponding first check data;
s225, returning to S223 to acquire the missing data set in the third data set under the condition that the third data set is missing;
s226, judging whether the missing data sets are not supplemented, if not, ending the step, and if so, returning to S221 until all the missing data sets are supplemented completely.
4. A method according to claim 3, wherein after supplementing all missing data sets with complete, further performing:
Generating first verification data and second verification data corresponding to each data group based on the data group sequence diagram, comparing the first verification data with the first verification data, comparing the second verification data with the second verification data, judging that the corresponding data group is successful in verification if the first verification data is identical to the first verification data, otherwise, judging that the corresponding data group is failed in verification, and correcting the data group which is failed in verification.
5. The method of claim 4, wherein correcting the data set that failed the verification comprises:
and acquiring a data set, acquiring original data and a corresponding correction code based on the data set, and correcting the original data based on the correction code.
6. The method of claim 1, wherein encrypting the corrected fault information for transmission to a central ATS subsystem comprises:
Obtaining a current time stamp, generating a first key based on the time stamp and fault information, encrypting the fault information for a plurality of times based on the first key to generate first secret data, generating a corresponding first hash value based on the first secret data, encrypting the first key, the first hash value and the first secret data by using a second key to generate second secret data, and transmitting the second secret data to a central ATS subsystem.
7. The method of claim 6, wherein after the central ATS subsystem receives the second secret data, performing:
Decrypting the second secret data based on the second key to obtain the first key, the first hash value and the first secret data;
And decrypting the first secret data based on the first key to obtain corresponding first decrypted data, generating a corresponding second hash value based on the first decrypted data, judging whether the second hash value is identical to the first hash value, ending the step if the second hash value is identical to the first hash value, and repeating the step if the second hash value is not identical to the first hash value until the second hash value is identical to the first hash value.
8. The method of claim 1, wherein automatically generating the dynamically adjusted operating recipe comprises:
The method comprises the steps of representing stations as nodes of a graph, representing track sections between stations as edges of the graph, collecting train operation data and passenger flow data of a fault train operation line, generating a delay propagation model based on train delay caused by a graph simulation train fault, predicting influence of the fault train on a subsequent train based on the propagation model, deferring departure time for the affected but not yet departure train, and adjusting operation speed for the affected already operated train.
9. An intelligent scheduling device in a urban rail train broadcast fault scene, which is characterized by comprising:
The identification module is used for collecting working parameters of the train broadcasting system in real time, analyzing the collected working parameters by using a machine learning algorithm, identifying whether the train broadcasting system has faults, generating fault information under the condition that the train broadcasting system is identified to have faults, wherein the fault information comprises train broadcasting fault information and information about whether manual broadcasting is available, and transmitting the fault information to the TCMS;
The transmission module is used for establishing communication connection between the TCMS system and each subsystem of the train, wherein the subsystems comprise a train broadcasting system, the TCMS system processes the fault information after receiving the fault information and transmits the processed fault information to the vehicle-mounted VOBC, the vehicle-mounted VOBC checks the fault information after receiving the fault information, and the fault information is encrypted and then transmitted to the central ATS subsystem when the verification is successful, and the fault information is corrected when the verification is unsuccessful and the corrected fault information is encrypted and then transmitted to the central ATS subsystem;
The scheduling module is used for prompting a central driving scheduler to start remote manual broadcasting on a fault train at a system interface under the condition that manual broadcasting is available, sending an electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle, and directly sending the electronic scheduling command to inform the vehicle base driving scheduler of preparing for adding the spare vehicle under the condition that manual broadcasting is unavailable;
The adjustment module is used for judging whether the spare vehicle needs to be started according to the fault type and the severity of the fault information, adjusting the intersection of the fault train and other related trains under the condition that the spare vehicle needs to be started, automatically generating a dynamic adjustment operation scheme, previewing the generated adjustment operation scheme by a central driving dispatcher, and starting to execute the adjusted train operation scheme by the central ATS subsystem after clicking and executing an operation diagram preview interface.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109050582A (en) * | 2018-08-23 | 2018-12-21 | 天津市北海通信技术有限公司 | Train status intelligent control method and system |
| JP2022006614A (en) * | 2020-06-24 | 2022-01-13 | 八幡電気産業株式会社 | Railway vehicle automatic broadcasting system, terminal connection device, terminal, automatic broadcasting control method and program |
| CN114244376A (en) * | 2022-02-22 | 2022-03-25 | 苏州浪潮智能科技有限公司 | Data encoding method, system, device and medium |
| CN115225186A (en) * | 2021-03-30 | 2022-10-21 | 比亚迪股份有限公司 | Test system and test method of broadcasting system for rail transit |
| CN115805972A (en) * | 2022-11-28 | 2023-03-17 | 卡斯柯信号有限公司 | Method and system for broadcasting resource status under failure of train control system based on short-wave communication |
| CN117565947A (en) * | 2023-11-21 | 2024-02-20 | 西安铁路信号有限责任公司 | Fault analysis and processing method for urban rail transit train |
| WO2024164682A1 (en) * | 2023-02-10 | 2024-08-15 | 上海富欣智能交通控制有限公司 | Method and apparatus for supervising and controlling train on the basis of integrated scheduling system, as well as medium and system |
| KR102730303B1 (en) * | 2024-05-24 | 2024-11-14 | 주식회사 현대종합기술 | AI-based railway signal system abnormality detection and diagnosis method |
-
2025
- 2025-01-10 CN CN202510037570.6A patent/CN119428805B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109050582A (en) * | 2018-08-23 | 2018-12-21 | 天津市北海通信技术有限公司 | Train status intelligent control method and system |
| JP2022006614A (en) * | 2020-06-24 | 2022-01-13 | 八幡電気産業株式会社 | Railway vehicle automatic broadcasting system, terminal connection device, terminal, automatic broadcasting control method and program |
| CN115225186A (en) * | 2021-03-30 | 2022-10-21 | 比亚迪股份有限公司 | Test system and test method of broadcasting system for rail transit |
| CN114244376A (en) * | 2022-02-22 | 2022-03-25 | 苏州浪潮智能科技有限公司 | Data encoding method, system, device and medium |
| CN115805972A (en) * | 2022-11-28 | 2023-03-17 | 卡斯柯信号有限公司 | Method and system for broadcasting resource status under failure of train control system based on short-wave communication |
| WO2024164682A1 (en) * | 2023-02-10 | 2024-08-15 | 上海富欣智能交通控制有限公司 | Method and apparatus for supervising and controlling train on the basis of integrated scheduling system, as well as medium and system |
| CN117565947A (en) * | 2023-11-21 | 2024-02-20 | 西安铁路信号有限责任公司 | Fault analysis and processing method for urban rail transit train |
| KR102730303B1 (en) * | 2024-05-24 | 2024-11-14 | 주식회사 현대종합기술 | AI-based railway signal system abnormality detection and diagnosis method |
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