Rail transit emergency command method and system based on minimum key task item

Abstract

The invention provides a rail transit emergency command method and system based on minimum key task items, and the method comprises the steps: S1, constructing a minimum task item library according to an urban rail transit emergency plan; establishing a sensing and early warning system for the operation safety risk of the urban rail transit; s2, sensing an early warning emergency event, and deducing delay time; calculating the constant of the passenger flow volume of the station, and obtaining the predicted passenger flow volume according to the constant of the passenger flow volume of the station; s3, based on the predicted passenger flow volume or delay time, assigning a code to match an event level; and S4, generating an emergency disposal scheme according to the event level and the minimum task item library, and issuing the emergency disposal scheme to post personnel of a corresponding unit. According to the emergency level study and judgment response result, the minimum unit and post needing to be disposed are positioned, items which are abstractly sorted before are automatically selected from the item library, and customized emergency disposal items are formed.

Description

Technical Field

[0001] The present invention belongs to the field of rail transit technology, and in particular, relates to a rail transit emergency command method and system based on minimum critical mission items. Background Art

[0002] In recent years, with the further increase of urban population and vehicles, urban road traffic is facing tremendous pressure, and road congestion has become normalized. Rail transit has gradually become one of the important choices for residents to travel due to its economic, punctual and efficient characteristics, and is the backbone of urban public transportation. Since rail transit mostly operates in a closed space, after an accident, the space is small, the population is dense, there are few entrances and exits, the ventilation and lighting conditions are poor, and the evacuation lines are long, which leads to the rapid amplification of the accident and even serious consequences of casualties. Learning lessons from disasters, minimizing the adverse consequences of disasters, safely evacuating people, and reducing casualties have attracted the Chinese government's high attention to the safety of urban rail transit.

[0003] The existing literature obtained through the search is as follows:

[0004] 1. "Research on Key Technologies of Digital Emergency Plans for Rail Transit Operations", "Modern Information Technology", Issue 3, 2024, pp. 143-148, 153, 7 pages in total, which discloses that digital emergency plans use computer technology and network information technology to form comprehensive, specific, targeted, intuitive and efficient emergency plans, so that the formulation and implementation of the plans can reach a standardized and visualized level, shorten the preparation cycle of emergency plans, and improve the operability of the plans. Digital emergency plans are to apply various digital technologies to the implementation of emergency plans. According to the emergency handling process, the text plans will be replaced by a series of digital operation procedures that can be executed sequentially with the evolution of the emergency. According to the emergency handling process, on the basis of the real-time information of the development of the situation, a comprehensive, specific, targeted, intuitive and efficient emergency plan is formed, so that the formulation and implementation of the plan can reach a standardized and visualized level. It solves a series of shortcomings of traditional text-based emergency plans, such as non-targeted, abstract, inconvenient for archiving and preservation, and open-loop systems without feedback.

[0005] 2. Patent document CN112365092A discloses an adaptive early warning system for large passenger flow risk in urban rail transit network, which includes an operation terminal, a road network large passenger flow risk warning server, a large passenger flow risk factor calculation server and a big data server. The operation terminal is used for users to visualize the large passenger flow risk warning according to the user's customization; the road network large passenger flow risk warning server calls the road network large passenger flow risk warning server to obtain the input of related factors, calculates the large passenger flow risk according to the scene and parameter settings, and generates a large passenger flow risk warning scheme; the large passenger flow risk factor calculation server extracts related factors and calculates the value of related factors according to historical data, and provides the calculation results to the road network large passenger flow risk warning server. This solution provides the road network large passenger flow risk warning function for urban rail transit network managers, provides a basis for road network passenger flow organization and information release, improves the intelligent level of passenger transportation services, and ensures the travel safety of road network passengers.

[0006] In summary, the current urban rail transit system has problems such as lack of advance preparation when facing emergencies, difficulty in coordination during the event, insufficient timeliness, and insufficient post-event review and analysis. This problem needs to be solved urgently. Summary of the invention

[0007] In view of the defects in the prior art, the purpose of the present invention is to provide a rail transit emergency command method and system based on minimum critical tasks.

[0008] A rail transit emergency command method based on minimum critical tasks provided by the present invention includes:

[0009] Step S1: According to the urban rail transit emergency plan, a minimum task database is constructed; a perception and early warning system for urban rail transit operation safety risks is established;

[0010] Step S2: sensing the early warning emergency event and inferring the delay time; calculating the station passenger flow constant, and obtaining the expected passenger flow according to the station passenger flow constant;

[0011] Step S3: assigning a code to match the event level based on the estimated passenger flow or delay time;

[0012] Step S4: Generate an emergency response plan based on the event level and the minimum task database, and send it to the post personnel of the corresponding unit.

[0013] Preferably, in step S1, the urban rail transit operation safety risk perception and early warning system is a monitoring, alarming and early warning system for the operation, passenger flow, power supply, facilities and equipment, and meteorological disasters of the urban rail transit.

[0014] Preferably, in step S2, the step of automatically sensing the early warning alarm information includes:

[0015] Step S2.1: Collect monitoring, warning and early warning information of urban rail transit operation, passenger flow, power supply, facilities and equipment, and meteorological disasters; analyze and judge train delays through correlation analysis algorithms to obtain delay time;

[0016] Step S2.2: Obtaining the estimated passenger flow according to the delay time;

[0017] The mathematical expression of the association analysis algorithm is:

[0018] T=t+|(Ls-Le)|÷VL-|(Ls-Le)|÷Vt

[0019] Among them, T represents the train speed limit delay time; t represents the fault handling required time; Ls represents the speed limit operation starting kilometer mark; Le represents the speed limit operation end kilometer mark; VL represents the train speed limit; Vt represents the train technical speed;

[0020] The estimated passenger flow is the estimated hourly passenger flow of the station; the estimated passenger flow is obtained based on the passenger flow constant of the station;

[0021] The mathematical expression of the station passenger flow constant is:

[0022] Y=Min(a,b,c,d,e)

[0023] Among them, Y represents the passenger flow constant of the station; a represents the capacity of the stairs; b represents the capacity of the passage; c represents the capacity of the escalator; d represents the capacity of the ticket machine; e represents the capacity of the entrance gate; Min represents the minimum value.

[0024] Preferably, in step S3, the event is coded according to the delay time, i.e., the train delay time; the relationship between the delay time and the coding is:

[0025] 120min≤Train delay time: Level 1 response event, assigned a red code;

[0026] 60min≤Train delay time<120min: Level 2 response event, assigned orange code;

[0027] 30min≤Train delay time<60min: Level 3 response event, assigned yellow code;

[0028] 15min≤Train delay time<30min: Level 4 response event, assigned a blue code;

[0029] In step S3, the event is coded according to the hourly estimated passenger flow of the station; the relationship between the hourly estimated passenger flow of the station and the coding is:

[0030] 1.8Y≤Estimated hourly passenger flow of the station: Level 1 response event, assigned a red code;

[0031] 1.4Y≤ Station hourly estimated passenger flow<1.8Y: Level 2 response event, assigned orange code;

[0032] 1.2Y≤ Station hourly estimated passenger flow<1.4Y: Level 3 response event, assigned yellow code;

[0033] Y≤ Station hourly estimated passenger flow<1.2Y: Level 4 response event, assigned a blue code;

[0034] Where Y represents the station passenger flow constant.

[0035] Preferably, in step S4, the minimum task item library is screened by the emergency plan intelligent matching algorithm to screen out the minimum task items with a similarity higher than a preset value, and an emergency disposal plan is generated according to the combination of the minimum task items;

[0036] The mathematical expression of the emergency plan intelligent matching algorithm is:

[0037]

[0038] Among them, TF represents the similarity between ω and the minimum task item; N represents the total number of documents; Nω represents the total number of documents containing ω, ω represents the type and level of the emergency event; nω represents the number of times ω appears in the document; Nz represents the number of all words in the document.

[0039] According to the present invention, a rail transit emergency command system based on minimum critical tasks is provided, comprising:

[0040] Module M1: Based on the urban rail transit emergency plan, build a minimum task database; establish a perception and early warning system for urban rail transit operation safety risks;

[0041] Module M2: Sense and warn emergency events, infer delay time; calculate station passenger flow constant, and obtain expected passenger flow based on the station passenger flow constant;

[0042] Module M3: assigning codes to match event levels based on the expected passenger flow or delay time;

[0043] Module M4: Generate an emergency response plan based on the event level and the minimum task library, and send it to the post personnel of the corresponding unit.

[0044] Preferably, in the module M1, the urban rail transit operation safety risk perception and early warning system is a monitoring, alarming and early warning system for the operation, passenger flow, power supply, facilities and equipment, and meteorological disasters of the urban rail transit.

[0045] Preferably, in the module M2, the step of automatically sensing the early warning alarm information includes:

[0046] Module M2.1: Collect information on monitoring, warning and early warning of urban rail transit, passenger flow, power supply, facilities and equipment, and meteorological disasters; analyze and judge train delays through correlation analysis algorithms to determine the delay time;

[0047] Module M2.2: Obtaining the estimated passenger flow according to the delay time;

[0048] The mathematical expression of the association analysis algorithm is:

[0049] T=t+|(Ls-Le)|÷VL-|(Ls-Le)|÷Vt

[0050] Among them, T represents the train speed limit delay time; t represents the fault handling required time; Ls represents the speed limit operation starting kilometer mark; Le represents the speed limit operation end kilometer mark; VL represents the train speed limit; Vt represents the train technical speed;

[0051] The estimated passenger flow is the estimated hourly passenger flow of the station; the estimated passenger flow is obtained based on the passenger flow constant of the station;

[0052] The mathematical expression of the station passenger flow constant is:

[0053] Y=Min(a,b,c,d,e)

[0054] Among them, Y represents the passenger flow constant of the station; a represents the capacity of the stairs; b represents the capacity of the passage; c represents the capacity of the escalator; d represents the capacity of the ticket machine; e represents the capacity of the entrance gate; Min represents the minimum value.

[0055] Preferably, in the module M3, the event is coded according to the delay time, that is, the train delay time; the relationship between the delay time and the coding is:

[0056] 120min≤Train delay time: Level 1 response event, assigned a red code;

[0057] 60min≤Train delay time<120min: Level 2 response event, assigned orange code;

[0058] 30min≤Train delay time<60min: Level 3 response event, assigned yellow code;

[0059] 15min≤Train delay time<30min: Level 4 response event, assigned a blue code;

[0060] In step S3, the event is coded according to the hourly estimated passenger flow of the station; the relationship between the hourly estimated passenger flow of the station and the coding is:

[0061] 1.8Y≤Estimated hourly passenger flow of the station: Level 1 response event, assigned a red code;

[0062] 1.4Y≤ Station hourly estimated passenger flow<1.8Y: Level 2 response event, assigned orange code;

[0063] 1.2Y≤ Station hourly estimated passenger flow<1.4Y: Level 3 response event, assigned yellow code;

[0064] Y≤ Station hourly estimated passenger flow<1.2Y: Level 4 response event, assigned a blue code;

[0065] Among them, Y represents the passenger flow constant of the station.

[0066] Preferably, in the module M4, the minimum task item library is screened by the emergency plan intelligent matching algorithm to screen out the minimum task items with a similarity higher than a preset value, and an emergency disposal plan is generated according to the combination of the minimum task items;

[0067] The mathematical expression of the emergency plan intelligent matching algorithm is:

[0068]

[0069] Among them, TF represents the similarity between ω and the minimum task item; N represents the total number of documents; Nω represents the total number of documents containing ω, ω represents the type and level of the emergency event; nω represents the number of times ω appears in the document; Nz represents the number of all words in the document.

[0070] Compared with the prior art, the present invention has the following beneficial effects:

[0071] 1. The emergency command system of the present invention is based on the smallest task items. In the early stage, it is necessary to abstract and sort out the disposal items of each smallest unit based on the emergency plan and the actual disposal process, rather than simply digitizing the emergency plan; and the present invention judges the response results according to the emergency level, locates the smallest unit and position that needs to be disposed of, and automatically selects the previously abstracted and sorted items from the item library to form customized emergency disposal items.

[0072] 2. According to the National Emergency Plan for Urban Rail Transit Operation Emergencies, the present invention uses the duration of train delays and operation interruptions as important parameter indicators for judging the emergency response level. Specifically, according to the Metro Design Code (GB50157-2013), the maximum throughput capacity of each part of a rail transit station is specified. According to the setting of station equipment and facilities and the congestion points on the approach to the station, the tolerable passenger flow constant of each rail station is set in accordance with the "one station, one policy" approach. Therefore, a risk quantification standard system is constructed around the train delay time and the large passenger flow at the station.

[0073] 3. The train delay time of the present invention is automatically calculated using the planned operation and train speed reduction data, and assisted by manual correction; the station's hourly estimated passenger flow adopts passenger flow prediction, video analysis, mobile phone signaling and other means, and uses the correlation analysis algorithm to automatically warn of large passenger flows. The system automatically judges the level according to the standard, and according to the risk quantification results, each emergency event is color-coded in red, orange, yellow, blue and green to clarify the emergency command decision-making level and improve the emergency coordination efficiency and decision-making ability.

[0074] 4. The present invention realizes the management of a complete rail transit emergency command system from perception discovery-decision-making command-reaction disposal-terminal feedback; through risk quantification means, the present invention can make judgments on the impact scope of emergency events and automatically generate corresponding disposal plans. At the same time, the constructed minimum task library can flexibly adapt to various emergency scenarios. The application of this method can solve the pain points of rail transit in the process of emergency collaborative disposal, such as the difficulty in obtaining pre-incident warnings, the difficulty in emergency linkage during disposal, the poor communication of cross-collaborative business among various commissions, bureaus and units, and the lack of scientificity and timeliness.

[0075] 5. The present invention can be applied to the construction of rail transit emergency command system. Compared with the existing rail transit emergency response system, which has separate handling at each level and separate handling inside and outside the track, it can realize the connection of the internal network-line-station-site of the track, promote the reform of the emergency command business within the rail group, and realize efficient coordinated handling inside and outside the track. It can solve the pain points of the current rail transit in the process of coordinated emergency handling, such as the difficulty in obtaining pre-incident warnings, the difficulty in emergency linkage during handling, the poor communication of cross-collaborative business among various commissions, bureaus and units, and the lack of scientificity and timeliness. It has a significant effect on improving efficiency and has a very broad prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0077] Figure 1 Schematic diagram of the disposal scheme provided by the present invention. DETAILED DESCRIPTION

[0078] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0079] The present invention establishes a rail transit emergency command system and method based on minimum critical tasks, realizes intelligent recommendation of emergency plans based on key information of emergency events, one-click assembling of emergency teams, online dispatching of emergency tasks, full tracking of handling processes, and efficient and intelligent handling of emergencies based on data analysis.

[0080] The present invention solves the problems that rail operations are affected by complex operating environments, aging facilities and equipment, and multiple operating entities, resulting in high safety operation risks; it is difficult to obtain early warnings before emergencies occur, it is difficult to coordinate emergency response during handling, and the scientificity and timeliness are insufficient; there are multiple operating entities, it is difficult for departments to coordinate, and there is a lack of effective collaborative supervision mechanisms. The minimum critical task item is the minimum unit of the key handling and operation points that each unit, department, and position is responsible for according to the emergency plan during the emergency response process.

[0081] The present invention aims at the characteristics of rail lines, stations and vehicles, and establishes a complete set of urban rail transit emergency command system and method, from perception discovery-decision command-response disposal-terminal feedback, to realize the closed loop of the whole process of emergency disposal, which will be conducive to the rapid evacuation of people in emergency situations, ensure the safety of passengers' lives and property, and provide valuable reference for the emergency management of urban rail transit emergencies. At the same time, a series of intelligent management platform applications make up for the lack of information technology means of urban rail transit emergency management, and provide strong technical support for the digital operation of rail transit.

[0082] The present invention can realize risk quantification of the warnings automatically perceived by the system, generate emergency event codes, and use them to select disposal plans from the minimum task library and push them to the disposal personnel. It can track the disposal process according to the completion of the disposal items, complete closed-loop disposal, and build a complete and efficient collaborative disposal system.

[0083] The present invention follows the idea of ​​"small-scale planning, small-system start-up, and priority for emergency use", and takes "life first, quick response to emergencies" as the principle, to achieve the overall goal of "1-minute response, 5-minute plan launch, 10-minute feedback on disposal status, and full-process visualization and control".

[0084] According to the present invention, a rail transit emergency command method based on minimum critical tasks is provided, which can be summarized as follows: emergency response tasks are minimized; full-domain perception, automatic warning; risk quantification, graded coding; code-based collaboration, linkage to people; full-process visualization, closed-loop handling;

[0085] Specifically, the specific steps of this software system to achieve emergency command are:

[0086] Step 1: Using semantic analysis tools for the urban rail transit emergency plan system, classify and extract various elements of the emergency response process, key handling and operation points of each object, etc. through a combination of automatic and semi-automatic methods. After minimizing the key handling and operation points of all scenarios, build a minimum task library;

[0087] The minimum task library is a task library in which the key handling and operation points of all scenarios are minimized.

[0088] The urban rail transit emergency response plan system is formulated based on the "National Urban Rail Transit Operation Emergency Response Plan".

[0089] Step 2: Based on the comprehensive monitoring of information such as driving, passenger flow, key facilities and equipment, electricity, control and protection areas, meteorology, and geological disasters that affect the safety of urban rail transit operations, a perception and early warning system for the safety risks of urban rail transit operations is established; the perception and early warning system for the safety risks of urban rail transit operations is the monitoring, alarming and early warning of the driving, passenger flow, power supply, key facilities and equipment, and meteorological disasters of urban rail transit.

[0090] Step 3: By automatically sensing the early warning alarm information, using the correlation analysis algorithm to analyze and judge the train delay, the impact of specific events on the delay time of train operation is calculated, and the hourly estimated passenger flow of each station on the line network is automatically obtained;

[0091] In step 3, the automatic sensing of early warning alarm information is specifically achieved by automatically generating early warning alarm information after reaching a preset threshold based on the information of driving, passenger flow, power supply, key facilities and equipment, and meteorological disasters monitored in step 2;

[0092] The association analysis algorithm estimates the train delay time, and the mathematical expression is:

[0093] T=t+|(Ls-Le)| / VL-|(Ls-Le)| / Vt

[0094] Among them, T represents the train speed limit delay time; t represents the time required for fault handling; Ls represents the starting kilometer mark of the speed limit operation; Le represents the ending kilometer mark of the speed limit operation; VL represents the train speed limit; Vt represents the technical speed of the train.

[0095] In other words, the association analysis algorithm estimates the train delay time, and the mathematical expression is:

[0096]

[0097] The steps and methods for automatically obtaining the hourly estimated passenger flow of each station in the line network are to automatically generate the hourly estimated passenger flow of each station in the line network through a line network passenger flow prediction system based on a neural network algorithm; the line network passenger flow prediction system is not within the scope of this patent.

[0098] Step 4: Analyze the hourly passenger flow constant of each station in the network according to the one-station-one-policy approach;

[0099] Step 5: Based on the estimated train delay time or the estimated hourly passenger flow at the station, the emergency event level matching algorithm is used to automatically match the event level and assign codes for management;

[0100] Step 6: Based on the type and level of the emergency event, the system uses the emergency plan intelligent matching algorithm to automatically select related items from the minimum task item library, automatically generate an emergency response plan, and send the minimum critical task items to specific personnel in the corresponding collaborative unit with one click;

[0101] Step 7: The personnel of each unit shall handle the task on site according to the task items and feedback the handling results through the system to complete the closed-loop management of the task items online;

[0102] Step 8: The dispatching personnel of the command center can use this system to achieve full visual tracking of the development of emergency events and the progress of handling the smallest critical tasks, comprehensively improve the overall control capability of emergency event handling and the feasibility of emergency plans, and effectively enhance the emergency response capability of the rail transit network.

[0103] Specifically, in step 3, the hourly estimated passenger flow of the station is the prediction result of the line network passenger flow prediction system, which is automatically obtained by the system through an interface;

[0104] Specifically, in step 4, the station hourly passenger flow constant refers to the setting of each station's equipment and facilities and the congestion points on the entry and exit paths according to the "Metro Design Specifications" (GB 50157-2013), which is set in a "one station one policy" manner, and the mathematical expression is:

[0105] Y=Min(a,b,c,d,e)

[0106] Among them, Y represents the passenger flow constant of the station; a represents the capacity of the stairs; b represents the capacity of the passage; c represents the capacity of the escalator; d represents the capacity of the ticket machine; e represents the capacity of the entrance gate;

[0107] Specifically, in step 5, the emergency event level matching algorithm (train delay time) refers to:

[0108] 120min≤Train delay time: Level 1 response event, assigned a red code;

[0109] 60min≤Train delay time<120min: Level 2 response event, assigned orange code;

[0110] 30min≤Train delay time<60min: Level 3 response event, assigned yellow code;

[0111] 15min≤Train delay time<30min: Level 4 response event, assigned a blue code;

[0112] Specifically, in step 5, the emergency event level matching algorithm (station hourly estimated passenger flow) refers to:

[0113] 1.8Y≤Estimated hourly passenger flow of the station: Level 1 response event, assigned a red code;

[0114] 1.4Y≤ Station hourly estimated passenger flow<1.8Y: Level 2 response event, assigned orange code;

[0115] 1.2Y≤ Station hourly estimated passenger flow<1.4Y: Level 3 response event, assigned yellow code;

[0116] Y≤ Station hourly estimated passenger flow<1.2Y: Level 4 response event, assigned a blue code;

[0117] Among them, Y represents the passenger flow constant of the station;

[0118] Specifically, in step 6, the emergency plan intelligent matching algorithm is based on the vector space model VSM, namely, Vector Space Model, and the mathematical expression is:

[0119]

[0120] Then, combined with the similarity threshold screening method, the automatic generation of emergency response plans is realized; the specific operation steps of the similarity threshold screening method are: according to the type and level of the emergency event, the emergency plan intelligent matching algorithm is used to screen in the minimum task item library, and the minimum task items with high similarity are screened out, and the emergency response plan is generated based on the combination of the minimum task items.

[0121] In other words, the mathematical expression of the emergency plan intelligent matching algorithm is:

[0122]

[0123] Among them, TF represents the similarity between ω and the minimum task item; N represents the total number of documents; Nω represents the total number of documents containing ω, ω represents the type and level of the emergency event; nω represents the number of times ω appears in the document; Nz represents the number of all words in the document.

[0124] Constructing the minimum task item library: By sorting and classifying the events in the rail transit emergency case library, we can obtain the common types and scenarios of emergency events, and combine the emergency response plans and actual response processes in each scenario. We can analyze and sort out the response plans, extract the detailed minimum response units, and each response unit can be accurately matched to a position, so as to construct a minimum task item library. After reorganizing each item, we can generate a list of response items for different scenarios, and expand the list of response items to different ranges, and finally form a scenario-based and level-based item analysis and management pool.

[0125] Full-area perception and automatic warning: Based on the data collected from rail transit, including driving, passenger flow, equipment, electricity, etc., external public security, fire, meteorological, public transportation and other data that affect rail transit operations are collected to jointly build a rail transit emergency command data warehouse, achieving full coverage of the five major elements of "people", "cars", "stations", "lines" and "networks". Based on the data warehouse, a variety of comprehensive monitoring methods and correlation analysis algorithms are used to perceive the operation of rail transit in all directions, and automatic alarms are issued in abnormal situations.

[0126] Risk quantification and classification coding: According to the National Emergency Plan for Urban Rail Transit Operation, the length of train delays and operation interruptions can be used as important parameter indicators for judging the emergency response level; according to the Metro Design Code (GB50157-2013), the maximum capacity of each part of the rail transit station is stipulated. According to the setting of station equipment and facilities and the congestion points on the access route, the permissible passenger flow constant of each rail station is set in accordance with the "one station, one policy" approach. Therefore, a risk quantification standard system is constructed around the train delay time and the large passenger flow at the station. The train delay time is automatically calculated using the planned operation and train speed reduction operation data, and assisted by manual correction; the station hourly estimated passenger flow adopts passenger flow prediction, video analysis, mobile phone signaling and other means, and uses management analysis algorithms to automatically warn of large passenger flows. The system automatically judges the level according to the standard, and implements red, orange, yellow, blue and green color coding for each emergency event based on the risk quantification results, clarifies the emergency command decision-making level, and improves the emergency coordination efficiency and decision-making ability.

[0127] Collaboration based on codes, linkage to people: Based on the emergency event code generated in step 3, it is transmitted to the track model together with event information such as scene type and event location as input. The system will automatically generate emergency response plans from the "minimum handling matter library" constructed in step 1 by intelligent selection. At the same time, based on the color of the emergency event code, the level, position and coordination matters of the handling coordination unit are clarified, and it is pushed to the corresponding coordination unit position personnel in a hierarchical manner, completing the "call-response" closed-loop management online.

[0128] Full visibility and closed-loop handling: The system in step 4 automatically generates emergency handling plans and pushes them to the corresponding handling personnel. The rail network emergency command center conducts visual tracking and remote command of the on-site handling situation through audio and video dialogue, system feedback, and manual response.

[0129] Specifically, the emergency response task is minimized, including: by sorting and classifying the case library, analyzing and combing the response plans, extracting detailed minimum response units, and building a minimum response item library. Among them, each item is reorganized to generate a list of response items for different scenarios, which are divided into different positions and levels, and then expanded in combination with the response level, and finally a management pool of item assessment and judgment is formed for different scenarios and levels.

[0130] Specifically, full-domain perception and automatic warning include: collecting internal and external data that affect rail transit operations and building an emergency command data warehouse. Based on the data warehouse, a variety of comprehensive monitoring methods and correlation analysis algorithms are used to conduct all-round perception of rail transit operations, and automatic alarms are issued in abnormal situations.

[0131] Specifically, risk quantification and classification coding include: building a quantitative standard system for emergency response levels based on train delay time. The system automatically determines the level according to the standard, and according to the risk quantification results, color codes the events to clarify the emergency command decision-making level.

[0132] Specifically, collaboration based on codes and linkage to people include: the system automatically generates emergency response plans from the "minimum handling items library" through intelligent selection and pushes them to the corresponding collaborative unit personnel in a hierarchical manner.

[0133] Specifically, the entire process is visual and closed-loop, including: real-time visual tracking of on-site handling situations and remote command of handling through audio and video dialogue, system feedback, manual response, etc.

[0134] Embodiment 2: This solution has practical application in Chongqing Rail Transit Emergency Intelligent Handling System.

[0135] Project Overview: A municipal project to promote the modernization of rail transit governance capabilities and governance systems. Based on the Chongqing Rail Line Network Command Center COCC, it builds a "1241" application architecture for rail emergency intelligent handling with "1 task, 2 capabilities, 4 types of typical events, and 1 minimum handling database", actively promoting the digital transformation of rail transit.

[0136] Implementation process, step one: sorting out key scenarios: forming a special working group, working together with the Municipal Transportation Commission, Road Transport Affairs Center, Kaito Group, and Rail Group to tackle the problem, and reversing the task schedule on a daily basis.

[0137] Step 2: Disassemble the business units: break down the list of 85 minimum handling items and build a minimum handling item library, with each item broken down to the post and linked to the person.

[0138] Step 3: Cooperation with collaborative units: A dedicated person will organize a special meeting to understand the IRS data sharing and item cataloging of collaborative units and promote the progress of collaborative disposal. Regular scheduling meetings will be held to promote the overall work in an orderly manner.

[0139] Step 4: Connect the "three-level governance center": Combined with the overall framework of Digital Chongqing "1361", the scenario tasks are submitted according to the application process of the Big Data Bureau. The business departments break down the tasks and list the tasks based on the core businesses determined by the "three lists". The operators of the three-level governance center configure the tasks in the task center components based on the task list and set the related events.

[0140] Step 5: Town-street connection: According to the departments involved in the incident handling process and their responsibilities, the towns and streets will go through the application process separately and determine the operating entity and leading section by referring to the "Guidelines for the List of Statutory Responsibilities of Townships (Streets)".

[0141] Step 6: Joint debugging and testing: The business department supports the manufacturer and the technical party of the three-level governance center and the technical party of the grassroots smart governance platform to jointly complete the testing and debugging of the full-process business at the city, district, and town levels.

[0142] Application features: Through business process reengineering, the online application of "Intelligent Handling of Rail Emergency" has five major innovative breakthroughs:

[0143] (I) One-screen monitoring in the cockpit: The application has built two cockpits for rail intelligent perception and rail emergency intelligent handling, and 15 drill-down pages, which collect 1,054 types of data from fire protection, public security meteorology, earthquake, water conservancy, the Cyberspace Administration of China, and related companies, and realize one-screen control of rail emergency handling.

[0144] (II) Automatic generation of disposal plans: The emergency disposal plans are automatically generated in a menu-based calling mode based on the concept of "one scenario, one plan". Among them, the large passenger flow evacuation scenario calls 42 minimum business units, the signal failure scenario calls 30, the foreign object intrusion scenario calls 26, and the disaster weather scenario calls 30. Each business item is manually adjustable and controllable, and subsequent business items can be increased or decreased according to specific circumstances. The disaster weather includes: heavy rain.

[0145] (III) 5-color response command and dispatch: Quantify risks from the two aspects of passenger evacuation and troubleshooting, and implement color-coded early warning and graded disposal. In terms of passenger evacuation, based on the number of people entering the station, combined with passenger flow forecasts, mobile phone signaling, video analysis and other data, dynamically monitor passenger flow, and set the tolerable passenger flow constant for each rail station in a "one station, one policy" manner. With a threshold of 1, 1.2, 1.4, and 1.8 times the constant, implement early warning and disposal of sudden large passenger flows in green, blue, yellow, orange, and red. In terms of troubleshooting, according to the maximum delay time, with 15 minutes, 30 minutes, 1 hour, and 2 hours as the boundaries, set a 5-color graded disposal process. According to the different response levels of rail emergencies, the corresponding command and dispatch levels are matched.

[0146] (IV) The disposal process is visible and controllable: The 85 smallest business items sorted out can be drilled down into the page, and the on-site disposal situation can be updated in real time through data monitoring, video surveillance, information feedback, etc., making the entire disposal process visible and controllable.

[0147] (V) Realize multi-cross coordinated response: Relying on the three-level governance center and based on the "response mechanism", 13 units including public security, fire protection, health and other units are linked to carry out coordinated disposal, realizing a closed loop of coordinated and linked disposal of rail emergencies.

[0148] Achievements: Completed government-enterprise business collaboration for rail emergencies, sorted out the smallest disposal business items from 0 to 1, built a minimum disposal item database, and constructed an efficient and intelligent handling system for rail transit emergencies, achieving the following results:

[0149] (I) Efficiency improvement: Intelligent perception and early warning of sudden incidents in rail operations, and early disposal by rail operating units to improve overall disposal efficiency.

[0150] (II) Multi-department collaboration to improve emergency response plans: The emergency response intelligent application automatically generates multi-cross collaborative response plans, and uses SMS coverage to accurately push emergency information to passengers. The various commissions and bureaus collaborate on closed-loop task management, review the response process online, and continuously improve the existing emergency response plans for the rail system.

[0151] (III) More comprehensive system perception: In addition to the existing track data, cross-departmental data such as water level monitoring data from the Water Resources Bureau, rapid report and early warning data from the Earthquake Bureau, public opinion data from the Cyberspace Administration of China, and emergency vehicle information from the National Health Commission can also be obtained, allowing for a more comprehensive analysis of the current situation and emergency response capabilities, thereby improving the comprehensiveness of data perception.

[0152] (IV) Cost savings: allowing data to travel more efficiently reduces the time for manual intervention, and initially achieves the overall goal of “1-minute response, 5-minute plan launch, 10-minute feedback on disposal status, and full visibility and control.”

[0153] (V) It has achieved interconnection with Chongqing Digital City Operation and Governance Center, becoming an important part of the comprehensive urban governance scenario and a core vital sign indicator of the Digital City Operation and Governance Center, and completed the system demonstration and technical support work with high quality.

[0154] The present invention also provides a rail transit emergency command system based on minimum critical tasks. The rail transit emergency command system based on minimum critical tasks can be implemented by executing the process steps of the rail transit emergency command method based on minimum critical tasks, that is, technical personnel in this field can understand the rail transit emergency command method based on minimum critical tasks as a preferred implementation of the rail transit emergency command system based on minimum critical tasks.

[0155] According to the present invention, a rail transit emergency command system based on minimum critical tasks is provided, comprising:

[0156] Module M1: Based on the urban rail transit emergency plan, build a minimum task database; establish a perception and early warning system for urban rail transit operation safety risks;

[0157] Module M2: Sense and warn emergency events, infer delay time; calculate station passenger flow constant, and obtain expected passenger flow based on the station passenger flow constant;

[0158] Module M3: assigning codes to match event levels based on the expected passenger flow or delay time;

[0159] Module M4: Generate an emergency response plan based on the event level and the minimum task library, and send it to the post personnel of the corresponding unit.

[0160] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0161] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A rail transit emergency command method based on minimum critical tasks, characterized in that: include: Step S1: construct a minimum task database according to the urban rail transit emergency plan; Establish a perception and early warning system for urban rail transit operation safety risks; Step S2: Sense the warning emergency event and infer the delay time; Calculating a station passenger flow constant, and obtaining an estimated passenger flow based on the station passenger flow constant; Step S3: assigning a code to match the event level based on the estimated passenger flow or delay time; Step S4: Generate an emergency response plan based on the event level and the minimum task database, and send it to the post personnel of the corresponding unit.

2. The rail transit emergency command method based on the minimum critical task items according to claim 1 is characterized in that: In step S1, the urban rail transit operation safety risk perception and early warning system is a monitoring, alarming and early warning system for the operation, passenger flow, power supply, facilities and equipment, and meteorological disasters of the urban rail transit.

3. The rail transit emergency command method based on the minimum critical task items according to claim 2 is characterized in that: In step S2, the step of automatically sensing the early warning alarm information includes: Step S2.1: Collect monitoring, warning and early warning information of urban rail transit operation, passenger flow, power supply, facilities and equipment, and meteorological disasters; analyze and judge train delays through correlation analysis algorithms to obtain delay time; Step S2.2: Obtaining the estimated passenger flow according to the delay time; The mathematical expression of the association analysis algorithm is: T=t+|(Ls-Le)|÷VL-|(Ls-Le)|÷Vt Among them, T represents the train speed limit delay time; t represents the fault handling required time; Ls represents the speed limit operation starting kilometer mark; Le represents the speed limit operation end kilometer mark; VL represents the train speed limit; Vt represents the train technical speed; The estimated passenger flow is the estimated hourly passenger flow of the station; the estimated passenger flow is obtained based on the passenger flow constant of the station; The mathematical expression of the station passenger flow constant is: Y=Min(a,b,c,d,e) Among them, Y represents the passenger flow constant of the station; a represents the capacity of the stairs; b represents the capacity of the passage; c represents the capacity of the escalator; d represents the capacity of the ticket machine; e represents the capacity of the entrance gate; Min represents the minimum value.

4. The rail transit emergency command method based on the minimum critical task items according to claim 3 is characterized in that: In the step S3, the event is coded according to the delay time, i.e., the train delay time; the relationship between the delay time and the coding is: 120min≤train delay time: first-level response event, red code; 60min≤train delay time<120min: second-level response event, orange code; 30min≤Train delay time<60min: Level 3 response event, assigned yellow code; 15min≤Train delay time<30min: Level 4 response event, assigned blue code; In step S3, the event is coded according to the hourly estimated passenger flow of the station; the relationship between the hourly estimated passenger flow of the station and the coding is: 1.8Y≤hourly estimated passenger flow of the station: first-level response event, red code is assigned; 1.4Y≤ Station hourly estimated passenger flow<1.8Y: Level 2 response event, assigned orange code; 1.2Y≤ Station hourly estimated passenger flow<1.4Y: Level 3 response event, assigned yellow code; Y≤ Station hourly estimated passenger flow<1.2Y: Level 4 response event, assigned blue code; Where Y represents the station passenger flow constant.

5. The rail transit emergency command method based on the minimum critical task items according to claim 4 is characterized in that: In step S4, the minimum task item library is screened by the emergency plan intelligent matching algorithm to screen out the minimum task items with a similarity higher than a preset value, and an emergency response plan is generated based on the combination of the minimum task items; The mathematical expression of the emergency plan intelligent matching algorithm is: Among them, TF represents the similarity between ω and the minimum task item; N represents the total number of documents; Nω represents the total number of documents containing ω, ω represents the type and level of the emergency event; nω represents the number of times ω appears in the document; Nz represents the number of all words in the document.

6. A rail transit emergency command system based on minimum critical tasks, characterized in that: include: Module M1: Construct a minimum task library based on the urban rail transit emergency plan; Establish a perception and early warning system for urban rail transit operation safety risks; Module M2: Perceive and warn of emergency events and infer delay time; Calculating a station passenger flow constant, and obtaining an estimated passenger flow based on the station passenger flow constant; Module M3: assigning codes to match event levels based on the expected passenger flow or delay time; Module M4: Generate an emergency response plan based on the event level and the minimum task library, and send it to the post personnel of the corresponding unit.

7. The rail transit emergency command system based on minimum critical tasks according to claim 6 is characterized in that: In the module M1, the urban rail transit operation safety risk perception and early warning system is a monitoring, alarming and early warning system for the operation, passenger flow, power supply, facilities and equipment, and meteorological disasters of the urban rail transit.

8. The rail transit emergency command system based on minimum critical tasks according to claim 7 is characterized in that: In the module M2, the step of automatically sensing the early warning alarm information includes: Module M2.1: Collect information on monitoring, warning and early warning of urban rail transit, passenger flow, power supply, facilities and equipment, and meteorological disasters; analyze and judge train delays through correlation analysis algorithms to determine the delay time; Module M2.2: Obtaining the estimated passenger flow according to the delay time; The mathematical expression of the association analysis algorithm is: T=t+|(Ls-Le)|÷VL-|(Ls-Le)|÷Vt Among them, T represents the train speed limit delay time; t represents the fault handling required time; Ls represents the speed limit operation starting kilometer mark; Le represents the speed limit operation end kilometer mark; VL represents the train speed limit; Vt represents the train technical speed; The estimated passenger flow is the estimated hourly passenger flow of the station; the estimated passenger flow is obtained based on the passenger flow constant of the station; The mathematical expression of the station passenger flow constant is: Y=Min(a,b,c,d,e) Among them, Y represents the passenger flow constant of the station; a represents the capacity of the stairs; b represents the capacity of the passage; c represents the capacity of the escalator; d represents the capacity of the ticket machine; e represents the capacity of the entrance gate; Min represents the minimum value.

9. The rail transit emergency command system based on minimum critical tasks according to claim 8, characterized in that: In the module M3, the event is coded according to the delay time, i.e., the train delay time; the relationship between the delay time and the coding is: 120min≤train delay time: first-level response event, red code; 60min≤train delay time<120min: second-level response event, orange code; 30min≤Train delay time<60min: Level 3 response event, assigned yellow code; 15min≤Train delay time<30min: Level 4 response event, assigned blue code; In step S3, the event is coded according to the hourly estimated passenger flow of the station; the relationship between the hourly estimated passenger flow of the station and the coding is: 1.8Y≤hourly estimated passenger flow of the station: first-level response event, red code is assigned; 1.4Y≤ Station hourly estimated passenger flow<1.8Y: Level 2 response event, assigned orange code; 1.2Y≤ Station hourly estimated passenger flow<1.4Y: Level 3 response event, assigned yellow code; Y≤ Station hourly estimated passenger flow<1.2Y: Level 4 response event, assigned blue code; Among them, Y represents the passenger flow constant of the station.

10. The rail transit emergency command system based on minimum critical tasks according to claim 9, characterized in that: In the module M4, the minimum task item library is screened through the emergency plan intelligent matching algorithm to screen out the minimum task items with a similarity higher than a preset value, and an emergency response plan is generated based on the combination of the minimum task items; The mathematical expression of the emergency plan intelligent matching algorithm is: Among them, TF represents the similarity between ω and the minimum task item; N represents the total number of documents; Nω represents the total number of documents containing ω, ω represents the type and level of the emergency event; nω represents the number of times ω appears in the document; Nz represents the number of all words in the document.

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