阅读说明：本技术 一种轨道交通系统的晚点在线恢复方法及其系统 (Late point on-line recovery method and system for rail transit system ) 是由 卿光明 李江红 张朝阳 张宇 陈华国 李卫红 李艳军 张瞄 于 2020-04-23 设计创作，主要内容包括：本发明提供了一种轨道交通系统的晚点在线恢复方法。所述晚点在线恢复方法包括：基于当前晚点列车的剩余行驶路径以及所述当前晚点列车的连带晚点列车的剩余行驶路径的相同程度判断所述当前晚点列车及其连带晚点列车的运行场景；响应于所述当前晚点列车与其连带晚点列车的运行场景为无交路运行,将所述当前晚点列车的当前晚点站至终点站作为晚点恢复站点输入至晚点恢复算法以确定出时间调节量；以及响应于所述当前晚点列车与其连带晚点列车的运行场景为交路运行,将所述当前晚点列车的当前晚点站至所述当前晚点列车与其连带晚点列车的截断站点作为晚点恢复站点输入至晚点恢复算法以确定出时间调节量。(The invention provides a late point online recovery method of a rail transit system. The late point online recovery method comprises the following steps: judging the running scenes of the current late train and the connected late trains thereof based on the same degree of the residual running paths of the current late train and the residual running paths of the connected late trains of the current late train; responding to the situation that the current late train and the associated late train thereof run without traffic, and inputting the current late station to the terminal station of the current late train as a late recovery station to a late recovery algorithm to determine the time adjustment amount; and responding to the fact that the running scene of the current late train and the running scene of the current late train connected with the current late train are in traffic running, and inputting the current late station of the current late train to the truncation station of the current late train and the connected late train as late recovery stations into a late recovery algorithm to determine the time adjustment quantity.)

1. A late point online recovery method of a rail transit system, the rail transit system including a running line and a plurality of trains running on the running line, the running line including a plurality of stations, the late point online recovery method comprising:

judging the running scenes of the current late train and the connected late trains thereof based on the same degree of the residual running paths of the current late train and the residual running paths of the connected late trains of the current late train, wherein the running scenes comprise non-traffic running and traffic running, and the connected late trains are trains influenced by the current late train and are late;

responding to the fact that the running scene of the current late train and the connected late trains thereof is non-traffic running, inputting the current late station to the terminal station of the current late train as late recovery stations into a late recovery algorithm to determine the time adjustment amount of the current late train and the connected late trains thereof at each late recovery station; and

and responding to the fact that the running scene of the current late train and the train with the late train is road crossing running, inputting the current late station of the current late train to a cut-off station of the current late train and the train with the late train as a late recovery station into a late recovery algorithm to determine the time adjustment amount of the current late train and the train with the late train at each late recovery station, wherein the cut-off station is a first different station of the rest running path of the current late train and the rest running path of the train with the late train.

2. The late point online recovery method according to claim 1, wherein the judging of the operation scene of the current late point train and its associated late point trains based on the same degree of the remaining travel path of the current late point train and the remaining travel paths of the associated late point trains of the current late point train comprises:

responding to that all stations on the remaining travel path of the current late train are completely the same as the stations on the remaining travel path of the connected late train in sequence, and judging that the operation scene of the current late train and the connected late train is non-traffic operation; and

and in response to that any station on the remaining running path of the current late train is different from all stations on the remaining running path of the connected late train, judging that the running scene of the current late train and the connected late train is traffic running.

3. The late online recovery method of claim 1, further comprising:

and updating the actual operation timetable of the current late train and the associated late trains at each station based on the time adjustment quantity of the current late train and the associated late trains at each late recovery station, wherein the time adjustment quantity comprises the station entering time and the departure time, and the actual operation timetable at least comprises the station entering time and the departure time.

4. The late online recovery method of claim 3, further comprising:

and controlling the current late train and the associated late trains to run based on the actual operation schedules of the current late train and the associated late trains at all stations.

5. The late online recovery method of claim 3, further comprising:

acquiring the late point information of all late point trains from an actual operation schedule, wherein the late point information at least comprises train numbers and arrival time of the late point trains;

acquiring the running direction and the planned arrival time of each late train from a planned operation schedule based on the train number of each late train;

determining a first late train in the driving direction as the current late train; and

and determining the linked late train of the current late train based on the arrival time of the current late train.

6. The late point online recovery method according to claim 5, wherein the determining of the associated late point train of the current late point train based on the arrival time of the current late point train comprises:

determining the delay spread depth of the current delay train based on the delay time deviation of the current delay train, wherein the delay spread depth represents the delay degree of the current delay train; and

and determining the associated late train of the current late train based on the late propagation depth.

7. The late on-line restoration method according to claim 6, wherein the late propagation depth is the number of trains affected by the late train,

the determining the late point propagation depth of the current late point train based on the late point time deviation of the current late point train comprises:

determining the delay time deviation of the delay train based on the arrival time of the current delay train and the planned arrival time of the delay train; and

dividing the delay time deviation by the departure time interval to obtain the delay propagation depth; and

determining the associated late train of the current late train based on the late propagation depth comprises:

and determining the trains which are in the same direction as the current late train and are sequentially positioned behind the current late train and have the late propagation depth number as the associated late train of the current late train.

8. The late peer online recovery method of claim 7, wherein said determining the associated late peer train of the current late peer train based on late peer propagation depth further comprises:

responding to the situation that the number of trains behind the current late train is smaller than the late propagation depth, and determining all trains behind the current late train in the same direction and in sequence as the associated late train.

9. The late point online recovery method according to claim 1, wherein the late point recovery algorithm comprises a late point model and a solving method of the late point model, and the inputting of the late point recovery site into the late point recovery algorithm to determine the time adjustment amount of the current late point train and its associated late point train at each late point recovery site comprises:

inputting the planned operation schedule of the current late train and the associated late trains thereof and the late recovery site into a late model of the operation line, wherein the late model takes the recovery of the planned operation schedule as an adjustment target; and

and solving the optimal solution of the delay model by using the solving method, wherein the optimal solution comprises the time adjustment quantity of the current delay train and the delay trains connected with the current delay train at each delay recovery station.

10. A late point on-line restoration device of a rail transit system, the rail transit system including a running line and a plurality of trains running on the running line, the running line including a plurality of stations, the late point on-line restoration device comprising:

a memory; and

a processor configured to:

judging the running scenes of the current late train and the connected late trains thereof based on the same degree of the residual running paths of the current late train and the residual running paths of the connected late trains of the current late train, wherein the running scenes comprise non-traffic running and traffic running, and the connected late trains are trains influenced by the current late train and are late;

responding to the fact that the running scene of the current late train and the connected late trains thereof is non-traffic running, inputting the current late station to the terminal station of the current late train as late recovery stations into a late recovery algorithm to determine the time adjustment amount of the current late train and the connected late trains thereof at each late recovery station; and

and responding to the fact that the running scene of the current late train and the train with the late train is road crossing running, inputting the current late station of the current late train to a cut-off station of the current late train and the train with the late train as a late recovery station into a late recovery algorithm to determine the time adjustment amount of the current late train and the train with the late train at each late recovery station, wherein the cut-off station is a first different station of the rest running path of the current late train and the rest running path of the train with the late train.

11. The late online recovery device of claim 10, wherein the processor is further configured to:

responding to that all stations on the remaining travel path of the current late train are completely the same as the stations on the remaining travel path of the connected late train in sequence, and judging that the operation scene of the current late train and the connected late train is non-traffic operation; and

and in response to that any station on the remaining running path of the current late train is different from all stations on the remaining running path of the connected late train, judging that the running scene of the current late train and the connected late train is traffic running.

12. The late online recovery device of claim 10, wherein the processor is further configured to:

and updating the actual operation timetable of the current late train and the associated late trains at each station based on the time adjustment quantity of the current late train and the associated late trains at each late recovery station, wherein the time adjustment quantity comprises the station entering time and the departure time, and the actual operation timetable at least comprises the station entering time and the departure time.

13. The late online recovery device of claim 12, wherein the processor is further configured to:

and controlling the current late train and the associated late trains to run based on the actual operation schedules of the current late train and the associated late trains at all stations.

14. The late online recovery device of claim 12, wherein the processor is further configured to:

acquiring the late point information of all late point trains from an actual operation schedule, wherein the late point information at least comprises train numbers and arrival time of the late point trains;

acquiring the running direction and the planned arrival time of each late train from a planned operation schedule based on the train number of each late train;

determining a first late train in the driving direction as the current late train; and

and determining the linked late train of the current late train based on the arrival time of the current late train.

15. The late online recovery device of claim 14, wherein the processor is further configured to:

determining the delay spread depth of the current delay train based on the delay time deviation of the current delay train, wherein the delay spread depth represents the delay degree of the current delay train; and

and determining the associated late train of the current late train based on the late propagation depth.

16. The late point online recovery device of claim 14, wherein the late point propagation depth is a number of trains affected by the late point train, the processor further configured to:

determining the delay time deviation of the delay train based on the arrival time of the current delay train and the planned arrival time of the delay train;

dividing the delay time deviation by the departure time interval to obtain the delay propagation depth; and

and determining the trains which are in the same direction as the current late train and are sequentially positioned behind the current late train and have the late propagation depth number as the associated late train of the current late train.

17. The late online recovery device of claim 16, wherein the processor is further configured to:

responding to the situation that the number of trains behind the current late train is smaller than the late propagation depth, and determining all trains behind the current late train in the same direction and in sequence as the associated late train.

18. The late point online recovery device of claim 10, wherein the late point recovery algorithm comprises a late point model and a means for solving the late point model, the processor further configured to:

inputting the planned operation schedule of the current late train and the associated late trains thereof and the late recovery site into a late model of the operation line, wherein the late model takes the recovery of the planned operation schedule as an adjustment target; and

and solving the optimal solution of the late model by using the solving device, wherein the optimal solution comprises the time adjustment quantity of the current late train and the associated late trains at each late recovery station.

19. A computer storage medium on which a computer program is stored, characterized in that the computer program, when executed, implements the steps of the late point online restoration method of a track traffic system according to any of claims 1 to 9.

Technical Field

The invention relates to the field of rail transit control, in particular to a late point online recovery method and a system of a rail transit system.

Background

In recent years, with the acceleration of urbanization and the increasing demand for public transportation, the construction of urban rail transit has come to a rush hour. Particularly, in a city, subway lines are more and more dense, and the departure interval of the train is greatly shortened. However, the train operation system is a complex system in which a plurality of bodies are associated with each other. The dynamic change of passenger flow and the disturbance of other factors can cause certain influence on the on-line operation of the train, thereby causing the arrival or departure delay of the train and even causing the associated delay of the subsequent train (delay spread effect). Therefore, how to ensure that the train is recovered to the planned operation diagram as fast as possible on the premise of meeting the requirements of safe operation and operation provides challenges for the real-time performance and optimality of the recovery of the subway at a later point.

At the present stage, when the train operation late point condition occurs, the adjustment method in actual work usually mainly adopts manual experience adjustment, and a mature and efficient subway late point recovery method is not found to be put into operation and use.

Therefore, the invention provides a method and a system for recovering the late point on line, which not only aim at a subway system, but also can solve the late point problem of rail transit systems such as high-speed rails, intercity railways and the like.

Disclosure of Invention

The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

According to an aspect of the present invention, there is provided a late point online recovery method for a rail transit system, the rail transit system including a travel route and a plurality of trains traveling on the travel route, the travel route including a plurality of stations, the late point online recovery method including: judging the running scenes of the current late train and the connected late trains thereof based on the same degree of the residual running paths of the current late train and the residual running paths of the connected late trains of the current late train, wherein the running scenes comprise non-traffic running and traffic running, and the connected late trains are trains influenced by the current late train and are late; responding to the fact that the running scene of the current late train and the connected late trains thereof is non-traffic running, inputting the current late station to the terminal station of the current late train as late recovery stations into a late recovery algorithm to determine the time adjustment amount of the current late train and the connected late trains thereof at each late recovery station; and responding to the fact that the running scene of the current late train and the train with the late train is road crossing running, inputting the current late station of the current late train to a cut-off station of the current late train and the train with the late train as a late recovery station into a late recovery algorithm to determine the time adjustment amount of the current late train and the train with the late train at each late recovery station, wherein the cut-off station is a first different station of the rest running path of the current late train and the rest running path of the train with the late train.

Further, the determining the operation scene of the current late train and the associated late trains thereof based on the same degree of the remaining travel route of the current late train and the remaining travel route of the associated late train of the current late train comprises: responding to that all stations on the remaining travel path of the current late train are completely the same as the stations on the remaining travel path of the connected late train in sequence, and judging that the operation scene of the current late train and the connected late train is non-traffic operation; and responding to the situation that any one station on the remaining running path of the current late train is different from all stations on the remaining running path of the connected late train, and judging that the running scene of the current late train and the connected late train is traffic running.

Still further, the late online recovery method further comprises: and updating the actual operation timetable of the current late train and the associated late trains at each station based on the time adjustment quantity of the current late train and the associated late trains at each late recovery station, wherein the time adjustment quantity comprises the station entering time and the departure time, and the actual operation timetable at least comprises the station entering time and the departure time.

Still further, the late online recovery method further comprises: and controlling the current late train and the associated late trains to run based on the actual operation schedules of the current late train and the associated late trains at all stations.

Still further, the late online recovery method further comprises: acquiring the late point information of all late point trains from an actual operation schedule, wherein the late point information at least comprises train numbers and arrival time of the late point trains; acquiring the running direction and the planned arrival time of each late train from a planned operation schedule based on the train number of each late train; determining a first late train in the driving direction as the current late train; and determining the linked late train of the current late train based on the arrival time of the current late train.

Still further, the determining of the linked late train of the current late train based on the arrival time of the current late train comprises: determining the delay spread depth of the current delay train based on the delay time deviation of the current delay train, wherein the delay spread depth represents the delay degree of the current delay train; and determining the associated late train of the current late train based on the late propagation depth.

Further, the late train propagation depth is the number of trains affected by the late train, and determining the late train propagation depth based on the late time deviation of the current late train includes: determining the delay time deviation of the delay train based on the arrival time of the current delay train and the planned arrival time of the delay train; dividing the delay time deviation by the departure time interval to obtain the delay propagation depth; and the determining of the associated late train of the current late train based on the late propagation depth comprises: and determining the trains which are in the same direction as the current late train and are sequentially positioned behind the current late train and have the late propagation depth number as the associated late train of the current late train.

Still further, the determining the associated late train of the current late train based on the late propagation depth further comprises: responding to the situation that the number of trains behind the current late train is smaller than the late propagation depth, and determining all trains behind the current late train in the same direction and in sequence as the associated late train.

Furthermore, the late point recovery algorithm comprises a late point model and a solving method of the late point model, and the step of inputting the late point recovery station into the late point recovery algorithm to determine the time adjustment amount of the current late point train and the associated late point train at each late point recovery station comprises the following steps: inputting the planned operation schedule of the current late train and the associated late trains thereof and the late recovery site into a late model of the operation line, wherein the late model takes the recovery of the planned operation schedule as an adjustment target; and solving the optimal solution of the delay model by using the solving method, wherein the optimal solution comprises the time adjustment quantity of the current delay train and the delay trains connected with the current delay train at each delay recovery station.

According to another aspect of the present invention, there is also provided a late point on-line restoration apparatus of a rail transit system including a running line and a plurality of trains running on the running line, the running line including a plurality of stations, the late point on-line restoration apparatus including: a memory; and

a processor configured to: judging the running scenes of the current late train and the connected late trains thereof based on the same degree of the residual running paths of the current late train and the residual running paths of the connected late trains of the current late train, wherein the running scenes comprise non-traffic running and traffic running, and the connected late trains are trains influenced by the current late train and are late; responding to the fact that the running scene of the current late train and the connected late trains thereof is non-traffic running, inputting the current late station to the terminal station of the current late train as late recovery stations into a late recovery algorithm to determine the time adjustment amount of the current late train and the connected late trains thereof at each late recovery station; and responding to the fact that the running scene of the current late train and the train with the late train is road crossing running, inputting the current late station of the current late train to a cut-off station of the current late train and the train with the late train as a late recovery station into a late recovery algorithm to determine the time adjustment amount of the current late train and the train with the late train at each late recovery station, wherein the cut-off station is a first different station of the rest running path of the current late train and the rest running path of the train with the late train.

Still further, the processor is further configured to: responding to that all stations on the remaining travel path of the current late train are completely the same as the stations on the remaining travel path of the connected late train in sequence, and judging that the operation scene of the current late train and the connected late train is non-traffic operation; and responding to the situation that any one station on the remaining running path of the current late train is different from all stations on the remaining running path of the connected late train, and judging that the running scene of the current late train and the connected late train is traffic running.

Still further, the processor is further configured to: and updating the actual operation timetable of the current late train and the associated late trains at each station based on the time adjustment quantity of the current late train and the associated late trains at each late recovery station, wherein the time adjustment quantity comprises the station entering time and the departure time, and the actual operation timetable at least comprises the station entering time and the departure time.

Still further, the processor is further configured to: and controlling the current late train and the associated late trains to run based on the actual operation schedules of the current late train and the associated late trains at all stations.

Still further, the processor is further configured to: acquiring the late point information of all late point trains from an actual operation schedule, wherein the late point information at least comprises train numbers and arrival time of the late point trains; acquiring the running direction and the planned arrival time of each late train from a planned operation schedule based on the train number of each late train; determining a first late train in the driving direction as the current late train; and determining the linked late train of the current late train based on the arrival time of the current late train.

Still further, the processor is further configured to: determining the delay spread depth of the current delay train based on the delay time deviation of the current delay train, wherein the delay spread depth represents the delay degree of the current delay train; and determining the associated late train of the current late train based on the late propagation depth.

Still further, the late train propagation depth is a number of trains affected by the late train, the processor further configured to: determining the delay time deviation of the delay train based on the arrival time of the current delay train and the planned arrival time of the delay train; dividing the delay time deviation by the departure time interval to obtain the delay propagation depth; and determining the trains which are in the same direction as the current late train and are sequentially positioned behind the current late train and have the late propagation depth number as the associated late train of the current late train.

Still further, the processor is further configured to: responding to the situation that the number of trains behind the current late train is smaller than the late propagation depth, and determining all trains behind the current late train in the same direction and in sequence as the associated late train.

Still further, the late recovery algorithm includes a late model and a solving means for the late model, the processor is further configured to: inputting the planned operation schedule of the current late train and the associated late trains thereof and the late recovery site into a late model of the operation line, wherein the late model takes the recovery of the planned operation schedule as an adjustment target; and solving the optimal solution of the delay model by using the solving device, wherein the optimal solution comprises the time adjustment quantity of the current delay train and the delay trains connected with the current delay train at each delay recovery station.

According to a further aspect of the present invention, there is also provided a computer storage medium having a computer program stored thereon, which when executed, performs the steps of the late online restoration method of a rail transit system as described in any one of the above.

Drawings

The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings.

FIG. 1 is a flow diagram illustrating a late point online recovery method in one embodiment according to one aspect of the present invention;

FIG. 2 is a partial flow diagram of a late online recovery method in one embodiment according to one aspect of the present invention;

FIG. 3 is a partial flow diagram of a late online recovery method in one embodiment according to an aspect of the present invention;

FIG. 4 is a partial flow diagram of a late online recovery method in one embodiment according to an aspect of the present invention;

FIG. 5 is a schematic illustration of single-pass operation of one of the travel routes of the rail transit system in one embodiment according to an aspect of the present invention;

FIG. 6 is a schematic illustration of single-pass operation of one of the travel routes of the rail transit system in one embodiment according to an aspect of the present invention;

FIG. 7 is a partial flow diagram of a late online recovery method in one embodiment according to an aspect of the present invention;

FIG. 8 is a schematic block diagram of a late point online restoration device in an embodiment depicted in accordance with another aspect of the present invention.

Detailed Description

The following description is presented to enable any person skilled in the art to make and use the invention and is incorporated in the context of a particular application. Various modifications, as well as various uses in different applications will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to a wide range of embodiments. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

In the following detailed description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. It will be apparent, however, to one skilled in the art that the practice of the invention may not necessarily be limited to these specific details. In other instances, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring the present invention.

The reader's attention is directed to all papers and documents which are filed concurrently with this specification and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference. All the features disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.

Note that where used, the designations left, right, front, back, top, bottom, positive, negative, clockwise, and counterclockwise are used for convenience only and do not imply any particular fixed orientation. In fact, they are used to reflect the relative position and/or orientation between the various parts of the object. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.

It is noted that, where used, further, preferably, still further and more preferably is a brief introduction to the exposition of the alternative embodiment on the basis of the preceding embodiment, the contents of the further, preferably, still further or more preferably back band being combined with the preceding embodiment as a complete constituent of the alternative embodiment. Several further, preferred, still further or more preferred arrangements of the belt after the same embodiment may be combined in any combination to form a further embodiment.

The invention is described in detail below with reference to the figures and specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.

According to one aspect of the invention, a late point online recovery method of a rail transit system is provided, which is used for realizing the late point online recovery of a plurality of trains on a single running line, wherein the single running line comprises a plurality of stations. Although the present invention is written with a single line as an object, it can be understood by those skilled in the art that when there are a plurality of operation lines, the late on-line restoration of a train on the single operation line can be performed on a per-operation-line basis, respectively.

In one embodiment, as shown in FIG. 1, the late point online restoration method 100 includes steps S110-S130.

Wherein, step S110 is: the method comprises the steps of judging the operation scene of the connected late train based on the same degree of the residual running path of the current late train and the residual running path of the connected late train of the current late train, wherein the operation scene comprises non-traffic operation and traffic operation, and the connected late train is a train influenced by the current late train and at a late point.

In a rail transit system, a train generally circulates on the same route, and the current journey of a train refers to a one-way journey running route of the route on which the train runs, namely a process from a starting station to a terminal station of the train running route. However, there may also be situations of a loop, such as the Shanghai subway number 4 line, where for a looped line of travel, a trip of a rail train may refer to the process of the train starting from a station and returning to the station. The remaining travel route refers to a route from the current position of a train to a planned terminal of the train, and may be represented as all stations that the train will pass through in the future when completing the current trip. The single running line is divided by the longest traversable path.

Cross-track operation may generally refer to the fact that all trains traveling in the same direction on the same operating line pass through different stations during a trip. The non-intersection operation generally means that all trains running in the same direction on one operation line pass through the same station in the course of one trip. Assuming that a travel route includes N stations in total, a cross-over operation means that there are some trains (not all trains) passing through only M of the N stations (N and M are integers, and N > M), and a non-cross-over operation means that all trains pass through the N stations. Whether the N sites or the M sites are passed through, the N sites or the M sites are sequentially passed through according to the arrangement sequence of the sites on the operation line.

For example, the longest route is from Jinhai road to seven shen road, and the route for Shanghai subway number 12 is from Jinhai road to seven shen road, which includes 32 stations. But train operation schedules of Shanghai subway number 12 lines in peak hours and flat hours are not the same. For example, in the peak period, a part of trains operate by taking a huge peak road as a starting station and taking an rainbow road as a terminal station, that is, the part of trains only pass through 24 stations and do not pass through all 32 stations of the operating line; meanwhile, a part of the train runs by taking the Jinhai road as an initial station and taking the seven roads as a terminal station, and then the part of the train passes through all 32 stations of the running line. Thus, during rush hour, the train on line 12 is in cross-track operation. In the peak balancing period, all trains on line 12 run with the Jinhai road as the starting station and the seven sea roads as the destination station. I.e. during the peak-off period, the train on line 12 is in non-intersection operation.

However, the non-intersection operation according to the present invention means that all stations on the remaining travel route of the train (the current late train) located at the front are sequentially passed by the train (the train with the late train) located at the back, and the intersection operation means that a part of stations on the remaining route of the train (the current late train) located at the front are not passed by the train (the train with the late train) located at the back.

Still, by taking the sea subway 12 as an example, assume that the current journey of one train takes the golden sea station as the starting station and the rainbow plum station as the terminal station, and the current journey of another train takes the huge peak station as the starting station and the rainbow plum station as the terminal station. The two trains are in a cross-road running state from the general concept of the running environment. However, if one train is located at a bank and treasure station and the other train is located at a dragon and bank station, because the bank and treasure station is closer to the rainbow station of the terminal station than the dragon and bank station, the train located at the big connecting station is the train located at the front position, and the train located at the dragon and bank station is the train located at the back position. Obviously, the train that the position leaned on ahead can pass through Guilin park station and rainbow groove way station in proper order and reach the rainbow plum way station, and the train that the position leaned on back can pass through the treasure way station of troughing, Guilin park station and rainbow groove way station in proper order and reach the rainbow plum way station, and obviously, the train that the position leaned on back can pass through all stations Guilin park station, rainbow groove way and reach the rainbow plum way station on the surplus route of the train that the position leaned on ahead, therefore, these two trains are in no traffic road operation state in fact.

Based on the above definitions of traffic operation and non-traffic operation, as shown in fig. 2, step S110 can be defined as steps S111-S112.

Step S111 is: and responding to the fact that all stations on the remaining running path of the current late train are completely the same as the stations on the remaining running path of the connected late train in sequence, and judging that the running scenes of the current late train and the connected late train are in non-traffic running.

Step S112 is: and in response to that any station on the remaining running path of the current late train is different from all stations on the remaining running path of the connected late train, judging that the running scene of the current late train and the connected late train is traffic running.

Although the station on the remaining travel route is taken as an example to serve as a criterion for determining whether the remaining travel routes of two trains are the same, it can be understood by those skilled in the art that the essential meaning of the fact that the remaining travel routes are completely the same means that a train located behind will travel along the travel route of a train located ahead.

Step S120 is: and in response to the fact that the running scene of the current late train and the associated late train is non-traffic running, inputting the current late station to the terminal station of the current late train serving as a late recovery station into a late recovery algorithm to determine the time adjustment amount of the current late train and the associated late train at each late recovery station.

The late point recovery algorithm is composed of a late point model and a solving method of the late point model. The delay model takes the arrival time and departure time of a delay recovery station of the train as adjustment objects, takes a plan operation schedule of the train for recovering input as an adjustment target, and finally outputs the time adjustment quantity of each delay recovery station of each input train. The time adjustment may be a specific arrival time and departure time, or the time adjustment may be an offset in time late relative to the scheduled arrival time and an offset in time late relative to the scheduled departure time. Wherein, the arrival time refers to the time when the train arrives at a station and stops; the departure time refers to the time when the train departs from a station; the late time offset refers to a time difference with respect to a time. The planned operation schedule at least comprises planned arrival time and planned departure time of all trains on the operation line.

And when the current late train and the running scene of the associated late train are in non-traffic running, all the stations on the remaining running path of the current late train can be used as late recovery stations. The time difference with the planned operation schedule is shortened by adjusting the arrival time and departure time of the late recovery station.

It can be understood that the time difference between the arrival time and departure time of a train at a station is the stop time of the train at the station, i.e. the time of residence at the station; the time difference between the departure time of a train at the previous station and the arrival time of the train at the next station is the running time of the train from the previous station to the next station; the time difference between the departure time of one train at a station and the departure time of another train at the same station is the departure interval of the two trains at the station.

Obviously, the time parameters related to train operation can be obtained through the operation schedules of all trains on one operation line, and the late model can enable the input operation schedule of the trains to continuously approach the planned operation schedule by adjusting parameters such as stop time, departure interval, time consumed by the trains to travel from one station to another station and the like. Then, by setting an appropriate solving method, the optimal solution of the late model can be found.

Step S130 is: and in response to the fact that the running scene of the current late train and the train with the late train is cross-road running, inputting the current late station of the current late train to a truncation station of the current late train and the train with the late train as late recovery stations into a late recovery algorithm so as to determine the time adjustment amount of the current late train and the train with the late train at each late recovery station.

Under the traffic-free operation scene, the train with the late point passes through all stations on the remaining travel path of the current train with the late point, so that the operation of all stations of the train with the late point on the remaining travel path of the current train with the late point is influenced by the train with the late point, and all stations on the remaining travel path of the current train with the late point can be used as adjustment objects.

In a traffic operation scene, the train with the late point passes through a part of stations on the remaining travel path of the current train with the late point, so that the operation of the train with the late point on the part of stations on the remaining travel path of the current train with the late point is influenced by the current train with the late point, and the stations on the remaining travel path of the current train with the late point, namely the stations which are passed by the train with the late point on the remaining travel path of the current train with the late point, can be used as an adjustment object.

And the cut-off station is a station which is not passed by the first train with the late point on the remaining driving path of the current late point train. That is, all stations from the current late station to the cutoff station on the remaining travel route of the current late train are passed by the associated late train, and therefore the current late station to the cutoff station on the remaining travel route of the current late train is set as the adjustment target.

Further, when the cut-off station is judged, the stations on the remaining travel path of the current late train and the current late train can be compared in sequence from the first station on the remaining travel path of the associated late train, which is the same as any station on the remaining travel path of the current late train, and the first different station judged is the cut-off station.

Still further, the late on-line restoration method 100 may further include the step of determining a current late train.

The rail transit system is generally provided with an Automatic Train Supervision (ATS) system for realizing a centralized monitoring function of the Train operation. The main functions of the ATS system include operation schedule management and night statistics, etc. Therefore, the relevant information of the late train can be acquired by the ATS system of the rail transit system.

Correspondingly, to implement the determination of the current late train, the late on-line restoration method 100 may further include steps S140-S160, as shown in fig. 3.

Specifically, step S140 is: and acquiring the late point information of all late point trains from the actual operation timetables of all the stations.

The ATS system can count the train number of the late train, the late time of the late train and the like based on the time deviation between the actual operation schedule and the planned operation schedule of all the trains. Therefore, the late information can be acquired from the ATS system. The late point statistics of the ATS system is to facilitate passengers to know the actual operation schedule of a train of personal interest, and thus the counted late point information generally includes at least a train number and an arrival time. The train number is the number of the late train, and the arrival time of the late train at each station is a problem related to passengers, and the number can be used for calculating the late time of the late train.

Step S150 is: and acquiring the driving direction and the planned arrival time of each late train from a planned operation schedule based on the train number of each late train.

And after the late information of all trains is acquired from the ATS system, classifying all the late trains based on the driving direction. For a travel route, two travel directions, an outward travel and a return travel, are generally involved. The late trains are classified into two categories based on the two directions of travel.

The planned arrival time of the late train can be combined with the actual arrival time to determine the linked late train in the late train.

Step S160 is: and determining the first late train in each driving direction as the current late train in the driving direction.

The first late train in the direction of travel can be considered to be the late train at the lead position in the direction of travel. It will be appreciated that the late of a subsequent late train may be due to the late of the lead late train, so that first performing a late recovery from the lead position late train may solve the late problem from the source of the late phenomenon. Thus, the first late train in the direction of travel is determined as the current late train in the direction of travel.

Further, the associated late train of the current late train is determined based on the degree of influence of the current late train. The current late train and the associated late train are taken as an integral adjustment object to solve the associated late problem. Then, as shown in fig. 3, the late point online restoration method 100 may further include step S170.

Step S170 is: and determining the linked late train of the current late train based on the arrival time of the current late train.

In particular, the associated late train may be determined based on the late propagation depth of the current late train. As shown in fig. 4, the step of determining the associated late train includes steps S171 to S172.

Step S171 is: and determining the delay propagation depth of the current delay train based on the delay time deviation of the current delay train, wherein the delay propagation depth represents the delay degree of the current delay train.

The late time deviation is the time deviation of the actual operation schedule of the train relative to the planned operation schedule. The influence of the current late train on the trains driving to the position of the current late train within a certain time after the current late train can be determined by using the late time deviation of the current late train, namely the trains with the late trains.

In particular embodiments, the late propagation depth may refer to the number of trains affected by the current late train. When the late point propagation depth of the current late point train is determined, the late point time deviation can be determined based on the difference value between the arrival time of the current late point train and the planned arrival time of the current late point train. And because the departure interval of the rail transit train is almost fixed in theory, especially for convenient traffic of cities such as subways, the delay propagation depth can be determined based on the relationship between the delay time deviation and the departure interval. Specifically, the time offset of the current time offset of the train at the departure interval can be used, and the quotient of the time offset of the current time offset and the departure interval can be understood as the number of affected trains within the time offset of the current time offset, i.e., the propagation depth of the time offset.

Step S172 is: and determining the associated late train of the current late train based on the late propagation depth.

And after the late train propagation depth is determined, determining trains which run in the same direction as the current late train and are located behind the current late train as associated late trains. Taking 6 trains in the traveling direction shown in fig. 5 as an example, the positions of the trains in the traveling direction are the 6 train numbers 1 to 6. Assuming that 2 trains are at the current late point and the late point propagation depth is 3, the 3-5 trains behind the 2 trains are associated late point trains.

Further, the rail transit system may have the latest operation time, for example, each operation line of the subway system has the latest operation time. There may be a situation where the late train's current late propagation depth is greater than the number of trains present thereafter. Taking 3 trains shown in fig. 6 as an example, assuming that the train 1 is the current late train and only 2 trains exist thereafter, when the late propagation depth determined based on the late time deviation of the train 1 is greater than 2, the trains 2 and 3 exist behind the train 1, and therefore the trains at late are the train 2 and the train 3.

Correspondingly, step S172 may further include: responding to the situation that the number of trains behind the current late train is smaller than the late propagation depth, and determining all trains behind the current late train in the same direction and in sequence as the associated late train.

It can be understood that when the delay propagation depth determined based on the delay time deviation of the current delay train is greater than the number of trains behind the current delay train, the delay propagation depth of the current delay train can be modified based on the need. That is, when the delay spread depth of the current delay train is determined, the smaller value between the delay spread depth calculated based on the delay time deviation and the number of trains located after the current delay train may be determined as the delay spread depth of the current delay train.

Furthermore, after the time adjustment amount of the current late train and the associated late train is calculated, the actual operation schedule needs to be correspondingly adjusted according to the time adjustment amount output by the late recovery algorithm. Specifically, the late online recovery method 100 may further include: and updating the actual operation timetable of the current late train and the associated late trains at each station based on the time adjustment quantity of the current late train and the associated late trains at each late recovery station.

It will be appreciated that by adjusting the time of operation of the late train at the late recovery site, the time gap between the actual operation schedule of the late train relative to the planned operation schedule can be reduced, and a change in the operation schedule of any one site on the remaining travel paths may cause a change in the operation schedules of all sites following that site. Therefore, the actual operation schedules of the remaining travel route of the current late train and all the stations on the remaining travel route of the associated late train need to be updated based on the time adjustment amount of the current late train and the associated late train at each late recovery station, so that the passengers can know the actual operation schedule on the travel route.

Correspondingly, after the actual operation schedule is determined, the current late train and the associated late trains thereof need to be controlled to operate based on the actual operation schedule.

Further, the results after recovery through one round of delay may be different for the current delay train and its associated delay trains in both the traffic and non-traffic operating environments.

After the time adjustment amount of the current late train and the associated late train is determined by the one-time late recovery algorithm, the current late train may or may not recover the planned operation schedule.

For the current late train and the associated late trains thereof in the traffic-free running environment, all stations on the remaining running path of the current late train are late recovery stations, so that even if the current late train does not recover the planned operation schedule, the current late train reaches the terminal station after passing through all the late recovery stations, the current late train cannot influence other trains. Therefore, the late recovery for the current late train is finished.

For the current late train and the associated late trains thereof in the traffic operation environment, because only part of stations on the remaining travel path of the current late train are late recovery stations, if the current late train passing through the late recovery stations is not recovered to the planned operation schedule, the current late recovery stations still influence other trains behind the current late train. In this case, the train which has not been restored to the planned operation schedule after the one round of the late trains is restored and still has the remaining travel route may be set as the late train, and the process returns to the step S140 to determine the current late train of the new round.

Still further, the late point online restoration method 100 may further include the step of building a late point model. Specifically, as shown in FIG. 7, the method includes steps S710-S720.

Step S710 is: and establishing a train late model by taking the minimum total late time of the input train as an objective function and the arrival time and departure time of the input train at each late recovery station as regulating variables.

The objective function of the late model can be described as equation (1).

Wherein N is the sum of the number of the current late trains and the associated late trains, M is the number of the late recovery sites, and x_ijRepresents the time offset of the late point when the late train i arrives at the jth station, y_ijIndicating the delay time offset for the delay train i to leave the station j.

Step S720 is: and establishing a constraint condition of the train rear model based on the safe running condition of the front and rear trains of the rail transit system.

Specifically, according to the conditions for safe operation of the front and rear trains of the rail transit system, the following constraint conditions can be established:

(1) establishing minimum stop time constraints of stations along the train according to line operation requirements;

(2) establishing minimum train operation time constraints among all sections along the line according to station setting conditions on the operation line and train characteristics;

(3) establishing train departure interval constraints of the same station according to the signal system safety tracking interval;

(4) according to the operation requirement, a departure constraint that the train cannot be sent earlier than the planned departure time is established.

After the delay model is established, in step S120 and step S130, the planned operation schedule of the current delay train and associated delay trains and the determined delay recovery site may be input into the delay model so that the delay model is in accordance with reality.

Further, the late model can be converted into a convex optimization problem, and an interior point method can be adopted to solve the convex optimization problem. The interior point method is a common algorithm for solving the convex optimization problem, and is not described in detail.

While, for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more embodiments, occur in different orders and/or concurrently with other acts from that shown and described herein or not shown and described herein, as would be understood by one skilled in the art.

According to another aspect of the invention, a late on-line recovery device of a rail transit system is also provided.

In one embodiment, as shown in FIG. 8, late online recovery device 800 includes a memory 810 and a processor 820.

The memory 810 is used to store computer programs.

A processor 820 is coupled to the memory 810 for executing the computer program stored on the memory 810, the processor 820 being configured to implement the steps of the late point online restoration method of the track transportation system as in any of the embodiments described above.

According to another aspect of the present invention, there is also provided a computer storage medium having stored thereon a computer program which, when executed, implements the steps of the late online restoration method of a track transportation system as in any one of the preceding embodiments.

Those of skill in the art would understand that information, signals, and data may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits (bits), symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

If implemented in software as a computer program product, the functions described may be stored on or transmitted by a computer readable medium, including both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.

The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. It is to be understood that the scope of the invention is to be defined by the appended claims and not by the specific constructions and components of the embodiments illustrated above. Those skilled in the art can make various changes and modifications to the embodiments within the spirit and scope of the present invention, and these changes and modifications also fall within the scope of the present invention.