CN114912233B - Method and system for determining and cooperatively managing and controlling influence range of road network transportation capacity reduction - Google Patents
Method and system for determining and cooperatively managing and controlling influence range of road network transportation capacity reduction Download PDFInfo
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Abstract
The application provides a method and a system for determining and cooperatively managing and controlling an influence range of road network transportation capacity reduction, which can comprise the following steps: constructing a start point path set and a stop point path set of each node in a road network according to a road network graph of rail transit; collecting characteristic parameters of the emergency, wherein the characteristic parameters comprise position information, occurrence time, the degree of the capacity reduction and predicted duration of the emergency; screening a target path set in the start point path set and the stop point path set according to the characteristic parameters of the emergency; determining a shortest path set of the emergency and an information equipment point bit table of each node in the shortest path set, and performing iterative matching on the shortest path set and a target path set to determine an influence range of the emergency, wherein the influence range comprises a boundary node set and a universe node set; and matching the influence range with the information equipment point position table, and triggering the information equipment located in the influence range.
Description
Technical Field
The application relates to the technical field of rail transit, in particular to a method and a system for determining and cooperatively managing and controlling an influence range of road network transportation capacity reduction.
Background
The rail transit is the main body of urban public transport and is responsible for extremely important responsibilities. Along with the rapid expansion of urban rail road network scale, the transportation capacity is continuously enhanced, the road network accessibility and the trip stability are continuously improved, and the dependence of people on rail traffic is stronger and stronger. Meanwhile, various uncertain factors influencing the normal operation of the rail road network system also increase sharply along with the enlargement of the scale of the rail road network, and if the operation of rail transit is interrupted in an emergency, the influence is larger. Due to the differences of the shapes, the structures and the surrounding environments of the rail transit network, the influence modes and the scales of the interrupted operation at different positions of the urban rail transit network are different, and the number of the changes and the combination forms is large.
The prior art can not meet the requirement of a high-quality development target of a smart city, namely, under the condition of failure of rail network capacity, accurate and quick information control of high-strength and massive network passenger flow is difficult to realize; at present, how to carry out large-scale individual information equipment collaborative management and control in a spatially dispersed manner is a prominent scientific problem and an engineering contradiction of emergency management.
Disclosure of Invention
The present application provides a method and a system for determining and cooperatively managing an influence range of a road network traffic capacity decrease, so as to solve or partially solve at least one of the above problems related to the background art and other disadvantages of the related art.
The application provides a method for determining and cooperatively managing and controlling an influence range of road network transportation capacity reduction, which comprises the following steps: according to a road network graph of rail transit, constructing a start point and stop point path set of each node in a road network, wherein the start point and stop point path set comprises commuting paths from a start node to other stations of the road network and commuting time; collecting characteristic parameters of the emergency, wherein the characteristic parameters comprise position information, occurrence time, the degree of the capacity reduction and the predicted duration of the emergency; screening a target path set in the starting and stopping point path set according to the characteristic parameters of the emergency, wherein the target path set is a path set with the highest matching degree of the starting and stopping point path set and the characteristic parameters of the emergency; determining a shortest path set of the emergency and an information equipment point position table of each node in the shortest path set, and performing iterative matching on the shortest path set and a target path set to determine an influence range of the emergency, wherein the influence range comprises a boundary node set and a universe node set; and matching the influence range with the information equipment point bit table, and triggering the information equipment located in the influence range.
In some embodiments, constructing a set of start and stop point paths of each node in a road network according to a road network graph of rail transit may include: carrying out structure identification on the road network graph to obtain a graph theory model; and determining a starting point and ending point path set of each node according to a failure starting point quantity calculation formula on the basis of a graph theory model.
In some embodiments, the graph-theoretic model is represented as:
，
wherein, the first and the second end of the pipe are connected with each other,
，/>
wherein V denotes the total number of nodes of the road network, E denotes the total number of sections between unidirectional nodes, N is the total number of routes in the road network graph, i is the node number, K is the total number of station nodes of any route in the road network graph, and C is the total number of transfer nodes of the road network. />
In some embodiments, the number of failure initiation points is calculated as:
wherein, T is road network operation duration, and T is step time.
In some embodiments, further comprising: determining the total amount of passengers who should enter or not enter the passenger and the total amount of passengers who should exit or not exit the passenger in the influence range; integrating the total amount of passengers who should enter but not enter and the total amount of passengers who should not exit to determine the actual carrying capacity of the influence range; and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range.
The application also provides a system for determining the influence range of the road network transportation capacity reduction and cooperatively managing and controlling, which comprises: the system comprises a start point and stop point path set construction module, an emergency acquisition module, a target path set screening module, an influence range determination module and a cooperative management and control module. The start point path set and stop point path set building module is used for building a start point path set and a stop point path set of each node in the road network according to a road network graph of rail transit, wherein the start point path set and the stop point path set comprise commuting paths from the start node to other stations of the road network and commuting time. The emergency acquisition module is used for acquiring the characteristic parameters of the emergency, wherein the characteristic parameters comprise the position information, the occurrence time, the degree of the capacity reduction and the predicted duration of the emergency. And the target path set screening module is used for screening a target path set in the start and stop point path set according to the characteristic parameters of the emergency, wherein the target path set is the path set with the highest matching degree with the characteristic parameters of the emergency in the start and stop point path set. The influence range determining module is used for determining a shortest path set of the emergency and an information equipment point position table of each node in the shortest path set, performing iterative matching on the shortest path set and a target path set, and determining the influence range of the emergency, wherein the influence range comprises a boundary node set and a universe node set. And the cooperative management and control module is used for matching the influence range with the information equipment point position table and triggering the information equipment within the influence range.
In some embodiments, the executing step of the start-stop point path set constructing module includes: carrying out structure identification on the road network graph to obtain a graph theory model; and on the basis of the graph theory model, determining a starting point and ending point path set of each node according to a failure starting point quantity calculation formula.
In some embodiments, the graph theory model is represented as:
wherein is present>
，
Wherein V denotes the total number of nodes of the road network, E denotes the total number of sections between unidirectional nodes, N is the total number of routes in the road network graph, i is the node number, K is the total number of station nodes of any route in the road network graph, and C is the total number of transfer nodes of the road network.
In some embodiments, the number of failure initiation points is calculated by the formula:
wherein, T is the road network operation duration, and T is the step time.
In some embodiments, the method further includes a load degree calculation module, configured to obtain a load degree of the influence range, and the main execution steps include: determining the total amount of passengers who should enter or not enter and the total amount of passengers who should not exit in the influence range; integrating the total amount of passengers who should enter but not enter and the total amount of passengers who should not exit to determine the actual carrying capacity of the influence range; and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range.
According to the technical scheme of the embodiment, at least one of the following advantages can be obtained.
According to the method and the system for determining and cooperatively managing and controlling the influence range of the road network traffic capacity reduction, the influence range of any road network node in an emergency at any time point is determined, the space spread is predicted, and the defect of fuzzy description of the influence range in the prior art is overcome; in addition, the method and the device accurately position the key attention objects of the emergency, specifically issue the emergency, and achieve targeted management and control.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings in which:
fig. 1 is a flowchart of a method for determining and cooperatively managing the influence range of road network traffic capacity reduction according to an exemplary embodiment of the present application;
FIG. 2 is a basic pattern diagram of a failure unreachable path according to an exemplary embodiment of the present application;
FIGS. 3A through 3C are schematic diagrams of the propagation of the impact of network traffic failure of an incident detection module according to exemplary embodiments of the present application; and
fig. 4 is a system block diagram of the influence range determination and cooperative management and control of the road network transportation capacity decline according to the exemplary embodiment of the present application.
Detailed Description
For a better understanding of the present application, various aspects of the present application will be described in more detail with reference to the accompanying drawings. It should be understood that the detailed description is merely illustrative of exemplary embodiments of the present application and does not limit the scope of the present application in any way. Like reference numerals refer to like elements throughout the specification. The expression "and/or" includes any and all combinations of one or more of the associated listed items.
In the drawings, the size, dimension, and shape of elements have been slightly adjusted for convenience of explanation. The figures are purely diagrammatic and not drawn to scale. As used herein, the terms "approximately," "about," and the like are used as table approximation terms, not as table degree terms, and are intended to account for inherent deviations in measured or calculated values that would be recognized by one of ordinary skill in the art. In addition, in the present application, the order in which the processes of the respective steps are described does not necessarily indicate an order in which the processes occur in actual operation, unless explicitly defined otherwise or can be inferred from the context.
It will be further understood that terms such as "comprising," "including," "having," "including," and/or "containing," when used in this specification, are open-ended and not closed-ended, and specify the presence of stated features, elements, and/or components, but do not preclude the presence or addition of one or more other features, elements, components, and/or groups thereof. Furthermore, when a statement such as "at least one of" appears after a list of listed features, it modifies that entire list of features rather than just individual elements in the list. Furthermore, when describing embodiments of the present application, the use of "may" mean "one or more embodiments of the present application. Also, the term "exemplary" is intended to refer to an example or illustration.
Unless otherwise defined, all terms (including engineering and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In addition, the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
According to the method, the characteristics of staggered implementation and speed combination of rapid nonlinear diffusion and directional spread of dual intensity and direction presented by the propagation of the composite urban mass in the axial domain based on the track network failure influence are mainly characterized in that on the basis of identifying the spatial structure characteristics of the track network of the composite urban mass in the axial domain, the propagation and evolution characteristics of the influence under the condition of transport capacity failure are analyzed, a diffusion boundary, unconventional flow distribution and form calculation models of the influence are established, a large-scale distributed information terminal data driving and full-process large-system automatic control technology is researched, emergency scheduling and cooperative disposal under the condition of a composite dynamic road network facing typical emergencies are realized, and methodology is provided for the construction of a track network emergency disposal system.
Fig. 1 is a flowchart of a method for determining and cooperatively managing the influence range of road network traffic capacity reduction according to an exemplary embodiment of the present application.
As shown in fig. 1, the present application provides a method for determining and cooperatively managing an influence range of a road network transportation capacity decrease, which may include: step S1, according to a road network graph of rail transit, a starting point and ending point path set of each node in a road network is constructed, wherein the starting point and ending point path set comprises commuting paths from a starting node to other stations of the road network and commuting time; s2, collecting characteristic parameters of the emergency, wherein the characteristic parameters comprise position information, occurrence time, the degree of the capacity reduction and expected duration of the emergency; s3, screening a target path set in the start and stop point path set according to the characteristic parameters of the emergency, wherein the target path set is the path set with the highest matching degree of the start and stop point path set and the characteristic parameters of the emergency; s4, determining a shortest path set of the emergency and an information equipment point position table of each node in the shortest path set, performing iterative matching on the shortest path set and a target path set, and determining an influence range of the emergency, wherein the influence range comprises a boundary node set and a universe node set; and step S5, matching the influence range with the information equipment point position table, and triggering the information equipment in the influence range.
In some embodiments, a start-stop point path set, i.e., an OD (origin-destination) path set, of each node in the road network is first constructed according to the road network graph of the rail transit. Specifically, structure recognition is carried out on the road network graph to obtain a graph theory model, namely, a graph on a space is converted into a one-way weighted graph, namely, the graph is used
Where V denotes the total number of nodes of the road network and E denotes the total number of segments between unidirectional nodes. More specifically, if the urban railway network comprises N lines, the number of station nodes of any line is K, and the number of network transfer nodes of the road network is C, the whole railway network forms a system capable of being used/substituted>
The figure shown. Note that the number of nodes of a general station where no transfer station exists is represented by
The number of transfer station nodes in the transfer station is ^>
And then->
。
Further, the edges in the road network graph are usually bidirectional edges, that is, one line includes uplink and downlink, and one station node includes uplink station node and downlink station node, but the edges defined in the graph theory modeling can only be unidirectional edges, so that bidirectional edges in the road network graph need to be modeledAnd (4) carrying out splitting. In other words, the edges of the space in the traffic network including the express way, the expressway and the track are all bidirectional edges in reality, but the influence of the capacity decline or the failure is generally propagated along a definite single-axis directional edge, and when the dynamic range of the spreading space is determined and the boundary is searched, all single-axis road up-and-down intervals and the affiliated stations included in the track network need to be split into unidirectional nodes for graph theory modeling. The number of any station node of any one split line is K x 2, and the number of the single-axis line intervals after splitting is (K-1) x 2. Thus, the number of composite nodes that are not split can be expressed as
(ii) a However, after splitting, there may be several duplicate station nodes, for example, the station node of the transfer station belongs to two or more lines, after splitting, there may be duplicate nodes, at this time, the duplicate node formed by the transfer node should be removed, and then the total number of sections between the unidirectional nodes is greater than or equal to>
. Similarly, after the division is carried out according to the single-axis directed edge, the total number of the sections between the unidirectional nodes is greater than or equal to>
. A typical metropolitan area track network formation->
=G(/>
, />
) The figure (a). Suppose a line contains only a two-line transfer node +>
And a three-wire transfer node>
Then>
. At this point, the graph theory model may be expressed as ≧ greater>
=G(/>
) Where i represents the node sequence number.
Furthermore, the logarithm of OD flows formed by any split individual node at any time point is: k is 2-C, the total number of the space point positions of the rail transit network which are failed is as follows:
then, the number of kinds corresponding to the logarithm of the formed OD flow is: n (K-1) 2 (K2-C-1), if a line contains only two-line transfer nodes>
And a three-wire transfer node>
Then->
. Further, if the actual time step T of the orbit network OD flows is considered and the operation duration is T hours, the number of failure starting points formed by any space-time combination is T
This is the number of basic data patterns for diffusion propagation and boundary search. The OD flow time step of the current actual track network is basically 5 minutes
. Finally, on the basis of the graph theory modelDetermining a starting point and a stopping point path set of each node according to a failure starting point quantity calculation formula
In some embodiments, when the capacity of a line decreases or fails, if the line adopts a short-circuit operation mode, the failure influence propagation speed and the influence margin and limit in any operation scheme are different. If the starting point line with transport capacity failure has the turn-back capability and the section of the opened small traffic road is M, then
If a line contains only two-line transfer node->
And a three-wire transfer node>
Then->
。
Fig. 2 is a basic pattern diagram of a failure unreachable path according to an exemplary embodiment of the present application. As shown in fig. 2, after the transportation capacity fails in any section, the passengers can spread the inaccessible routes and the affected boundaries spread to the section from the section with the transportation capacity falling to a distant station and a far line, and in the constructed urban area rail transit network map, the outstanding characteristics are that the passengers can spread in a staggered way between the axis areas, and spread rapidly in the urban area, and then the passengers can turn to the orbit through the transfer node to continue spreading and dispersing in the small-range orbit network in the urban satellite. The freedom degree of the physical network is fixed, namely, under the condition that the station is set not to quit operation and basic conditions such as electric power, signals and the like are kept, the driving network is allowed to fix an emergency traffic scheme, and the freedom degree of network passenger flow is completely released to carry out propagation calculation and information synergy efficiency verification.
In some embodiments, the characteristic parameters of the emergency are collected. Specifically, the sensor data and the video data of each station node can be acquired through equipment such as a sensor or a monitoring camera, and an emergency can be discovered in time, and the station node can be monitored in time through other modes. Further, characteristic parameters of the emergency are collected, including location information of the emergency, occurrence time, degree of capacity reduction, and expected duration.
In some embodiments, a path traffic distribution scale table of a target date and a target time interval is determined according to a maximum probability attribution far side based on all valid OD path sets in a road network according to characteristic parameters of an emergency, and a total failure duration (predicted duration) of the emergency is set as 5 minutes step length for example
If the number of the allocation tables S is:
(ii) a Further, according to the characteristic parameters of the emergency, a target path set is screened in the start and stop point path set, wherein the target path set is the path set with the highest matching degree with the characteristic parameters of the emergency in the start and stop point path set, that is, the path set closest to the occurrence date of the emergency is screened in the start and stop point path set.
In some embodiments, the shortest path set P for the emergency is listed, including the normal train operation interval, station stop and interval travel time of each node in the historical similar day corresponding period corresponding to the time of occurrence of the emergency. And meanwhile, listing the point bit table of each node information device.
In some embodiments, the set of shortest paths P is iteratively matched with the set of directed paths R. When P is smaller than R, the corresponding station node is the node in the reverse thrust range of the failure influence, and the boundary nodes and the universe nodes propagated in each target time interval are obtained by summarizing one by one, namely
And/or>
. I.e. determining the impact range of said emergency eventThe enclosure comprises a boundary node set and a universe node set; and respectively in->
And/or>
And comparing the data with the point location table of each node information device, and automatically triggering the node information devices in the propagation boundary to realize the dynamic cooperative triggering linkage of the dispersed individuals. Specifically, the information device, namely a broadcast and other terminals (commonly called PIS), determines a station or train within an influence range by dynamically determining a range of failure influence according to a screened shortest path table. The information equipment list of each station is prepared in advance, so that the affected stations can be determined according to the influence range, the information equipment of the affected stations is triggered, and information is issued. Therefore, targeted management and control are formed, the information is sent to the passengers going to the influence range in a targeted mode, the existing technology that the information is broadcasted and published to all stations of the whole road network once an emergency happens is not adopted, the technology is more scientific, accurate and efficient compared with the existing mode, and negative influence can be controlled within the minimum range.
In some embodiments, further comprising: determining the total amount of passengers who should enter or not enter and the total amount of passengers who should not exit in the influence range, determining the total amount of passengers who should enter or not exit by utilizing the collected data of the monitoring camera and a tracking algorithm, namely collecting the actual entered amount and the actual exited amount, comparing the actual entered amount with the entered amount on the same day of the history to determine the amount of passengers who should enter or not enter, and comparing the actual exited amount with the exited amount on the same day of the history to determine the amount of passengers who should exit or not exit; integrating the amount of passengers who should enter or not enter
And the sum of outstanding passengers should be judged>
Wherein n denotes the nth station node, is>
Represents the number of people arriving from the nth station node on the upper line and is based on the number of people>
Indicates the number of persons arriving from the nth station node down>
Represents the number of people coming out from the nth station node on the upper line and is selected>
The number of people who exit from the nth station node of the descending is shown, so that the actual bearing capacity of the influence range, namely the actual number of people waiting for entering the station is determined; and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range, specifically, for any station and any train, a bearing upper limit exists, such as a station of 1000 square meters, and according to the hall and table area of the station, the bearing upper limit of the station or the train can be determined according to the number of people bearing per square meter in the national standard.
In some embodiments, an axis domain type urban group orbit network formed by a Beijing central area and a group around the central area is taken as an object, and the whole process of failure propagation search and collaborative emergency computing efficiency is simulated and verified by combining data of early peak hours of actual working days. Fig. 3A-3C are schematic diagrams illustrating propagation of network traffic impact of failure of an incident detection module according to an exemplary embodiment of the present application. As shown in fig. 3A, the diagram shows a road network diagram formed by each line of the beijing subway, and an area a shows a passenger flow propagation diagram affected when an emergency happens; FIG. 3B is a schematic diagram of the passenger flow propagation after a certain time of an emergency; the region C in fig. 3C shows the passenger flow propagation diagram of the impact when the emergency happens to the peak, and it can be seen that the impact range on the passenger flow from the time of the emergency to the peak is larger and larger as the emergency evolves, and the impact range is dynamically changed. Of course, the propagation boundary of the failed station node is expanded outwards, and the number of the inaccessible path global nodes is increased.
With 24 lines, 428 stations and 64 transfer stations (including 3 three-line transfer stations) of Beijing and its peripheral satellite urban rail transit network in 2021 as objects, the propagation boundary of the failed station node is expanded outwards along with the dynamic evolution of the sudden event trace, and the number of global nodes of the inaccessible path is increased. At the moment, the total number of the space point positions with the failure of the rail transit network is
Is 832; the number of the failure starting points formed by any space-time combination corresponding to any 5min step length time period is ^ or>
658944; if the operating time period T is 17 hours, the total time of the day is->
For 134424576, i.e., according to the technical idea of pre-screening and storage, it is necessary to prepare more than 1.3 × 108 OD path tables. In a particular simulation verification, the total length of time to failure (expected duration) for an incident is set to ≦>
Based on the data warehouse, the couple is judged to be 60 minutes>
(T = 12) =7907328l type OD tables for fast calculation and deduction. Result display,. Sup or>
And/or>
The propagation search speed is between 27 and 120s, the maximum influence space range of the failure of the transport capacity at a specific moment can be quickly defined, and the dynamic boundary search speed can meet the situation of advance prejudgment and transferThe demand of node passenger transport organization and passenger information publishing; the matching speed of all affected stations and interval information terminals is 2-4s, and the level of urban group track network failure collaborative emergency and information interactive release can be greatly improved.
According to the method for determining the influence range of the road network transportation capacity reduction and cooperatively managing and controlling, the influence range of any time point and any road network node in an emergency is determined, the space spread is predicted, and the defect of fuzzy description of the influence range in the prior art is overcome; in addition, the method and the device accurately position the key attention objects of the emergency, specifically issue the emergency, and achieve targeted management and control.
Fig. 4 is a system block diagram of the influence range determination and cooperative management and control of the road network transportation capacity decline according to the exemplary embodiment of the present application.
As shown in fig. 4, the present application further provides a system for determining and cooperatively managing the influence range of the road network transportation capacity reduction, which may include: the system comprises a start point path set construction module 1, an emergency acquisition module 2, a target path set screening module 3, an influence range determination module 4 and a cooperative management and control module 5. The starting point path set building module 1 is configured to build a starting point path set of each node in the road network according to a road network graph of rail transit, where the starting point path set includes commuting paths from the starting node to other stations of the road network and commuting time. The emergency collecting module 2 is used for collecting the characteristic parameters of the emergency, and the characteristic parameters comprise the position information, the occurrence time, the degree of the capacity reduction and the predicted duration of the emergency. The target path set screening module 3 is configured to screen a target path set in the start and stop point path set according to the characteristic parameters of the emergency, where the target path set is a path set with a highest matching degree with the characteristic parameters of the emergency in the start and stop point path set. The influence range determining module 4 is configured to determine a shortest path set of the emergency and an information device node bit table of each node in the shortest path set, perform iterative matching on the shortest path set and a target path set, and determine an influence range of the emergency, where the influence range includes a boundary node set and a global node set. And the cooperative management and control module 5 is used for matching the influence range with the information equipment point position table and triggering the information equipment within the influence range.
In some embodiments, the start-stop point path set building module 1 executes steps including: carrying out structure identification on the road network graph to obtain a graph theory model; and on the basis of the graph theory model, determining a starting point and ending point path set of each node according to a failure starting point quantity calculation formula.
In some embodiments, the graph-theoretic model is represented as:
wherein is present>
，
Wherein V denotes the total number of nodes of the road network, E denotes the total number of sections between unidirectional nodes, N is the total number of routes in the road network graph, i is the node number, K is the total number of station nodes of any route in the road network graph, and C is the total number of transfer nodes of the road network.
In some embodiments, the number of failure initiation points is calculated by the formula:
wherein, T is the road network operation duration, and T is the step time.
In some embodiments, the system further comprises a load calculation module 6 for obtaining the load of the influence range, and the main execution steps include: determining the total amount of passengers who should enter or not enter and the total amount of passengers who should not exit in the influence range; integrating the total amount of passengers who should enter but not enter and the total amount of passengers who should not exit to determine the actual carrying capacity of the influence range; and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range.
According to the system for determining and cooperatively managing and controlling the influence range of the road network transport capacity reduction, the influence range of any road network node occurring emergency at any time point is determined, the space spread is predicted, and the defect of fuzzy description of the influence range in the prior art is overcome; in addition, the method and the system accurately position the key attention objects of the emergency, issue the emergency in a targeted mode, and achieve targeted management and control.
Claims (4)
1. A method for determining and cooperatively managing and controlling influence range of road network transportation capacity reduction is characterized by comprising the following steps:
according to a road network graph of rail transit, constructing a start point and stop point path set of each node in the road network, wherein the start point and stop point path set comprises commuting paths from a start node to other stations of the road network and commuting time;
collecting characteristic parameters of an emergency, wherein the characteristic parameters comprise position information, occurrence time, the degree of capacity reduction and predicted duration of the emergency;
screening a target path set in the start and stop point path set according to the characteristic parameters of the emergency, wherein the target path set is a path set with the highest matching degree with the characteristic parameters of the emergency in the start and stop point path set;
determining a shortest path set of the emergency and an information equipment point position table of each node in the shortest path set, and performing iterative matching on the shortest path set and the target path set to determine an influence range of the emergency, wherein the influence range comprises a boundary node set and a universe node set; and
matching the influence range with the information equipment point position table, and triggering the information equipment in the influence range;
the method for constructing the start-stop point path set of each node in the road network according to the road network graph of the rail transit comprises the following steps:
carrying out structure recognition on the road network graph to obtain a graph theory model;
determining a starting point and ending point path set of each node according to a failure starting point quantity calculation formula on the basis of a graph theory model;
the graph theory model is represented as:
，
wherein the content of the first and second substances,
，
wherein V represents the total number of nodes of the road network, E represents the total number of sections between unidirectional nodes, N is the total number of lines in the road network graph, i is the node number, K is the total number of station nodes of any line in the road network graph, and C is the total number of transfer nodes of the road network;
the failure starting point quantity calculation formula is as follows:
wherein, T is road network operation duration, and T is step length time.
2. The method for determining and cooperatively managing and controlling the influence range of road network transportation capacity reduction according to claim 1, further comprising:
determining the total amount of passengers who should enter or not enter the influence range and the total amount of passengers who should be discharged or not discharged in the influence range;
integrating the total amount of passengers who should enter or not enter and the total amount of passengers who should exit or not exit to determine the actual carrying capacity of the influence range; and
and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range.
3. The utility model provides a road network transportation capacity decline influence scope confirms and cooperates management and control's system which characterized in that includes:
the system comprises a start point path set construction module, a stop point path set construction module and a traffic control module, wherein the start point path set construction module is used for constructing a start point path set and a stop point path set of each node in the road network according to a road network graph of rail transit, and the start point path set and the stop point path set comprise commuting paths from a start node to other stations of the road network and commuting time;
the emergency acquisition module is used for acquiring the characteristic parameters of the emergency, wherein the characteristic parameters comprise the position information, the occurrence time, the degree of the capacity reduction and the predicted duration of the emergency;
a target path set screening module, configured to screen a target path set in the start and stop point path set according to the feature parameters of the emergency, where the target path set is a path set in the start and stop point path set with a highest matching degree with the feature parameters of the emergency;
an influence range determining module, configured to determine a shortest path set of the emergency and an information device node bit table of each node in the shortest path set, perform iterative matching on the shortest path set and the target path set, and determine an influence range of the emergency, where the influence range includes a boundary node set and a global node set; and
the cooperative management and control module is used for matching the influence range with the information equipment point position table and triggering the information equipment in the influence range;
the execution steps of the start-stop point path set building module comprise:
carrying out structure identification on the road network graph to obtain a graph theory model;
determining a starting point and ending point path set of each node according to a failure starting point quantity calculation formula on the basis of a graph theory model;
the graph theory model is represented as:
，
wherein, the first and the second end of the pipe are connected with each other,
，
wherein V represents the total number of nodes of the road network, E represents the total number of sections between unidirectional nodes, N is the total number of lines in the road network graph, i is the node number, K is the total number of station nodes of any line in the road network graph, and C is the total number of transfer nodes of the road network;
the calculation formula of the number of the failure starting points is as follows:
wherein, T is road network operation duration, and T is step length time.
4. The system for determining and cooperatively managing influence ranges of road network traffic reduction according to claim 3, further comprising: the load degree calculation module is used for obtaining the load degree of the influence range, and mainly comprises the following execution steps:
determining the total amount of passengers who should enter or not enter the influence range and the total amount of passengers who should be discharged or not discharged in the influence range;
integrating the total amount of passengers who should enter or not enter and the total amount of passengers who should exit or not exit to determine the actual carrying capacity of the influence range; and
and comparing the actual bearing capacity with the bearing capacity of the influence range to obtain the load degree of the influence range.
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