Urban rail train operation adjusting method and system for coping with interruption of one-way operation long section

Abstract

The invention provides an urban rail train operation adjustment method and system coping with interruption of a long unidirectional operation section, belongs to the technical field of urban rail train operation control, and aims at a scene with a long interruption length and with the minimum total waiting time of passengers as an optimization target, a train operation adjustment model is constructed; and solving the train operation adjustment model by adopting a double-layer simulated annealing-genetic algorithm, establishing an elitist retention strategy, and adding a solution checking process in crossover and mutation operation in the double-layer simulated annealing-genetic algorithm. According to the method, the line transportation capacity is effectively improved, and the flexibility and timeliness of train operation adjustment are improved; the train capacity and the line capacity can be more effectively utilized, the waiting time of opposite passengers is shortened, the departure interval of the two-way trains is shortened, and the traffic capacity under the long-section interruption condition is effectively improved; passengers in an interruption section are effectively relieved, detention is reduced, and the operation flexibility and stability of the rail transit system under the emergency situation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban rail train operation control, and in particular to an urban rail train operation adjustment method and system using virtual marshaling technology to cope with interruptions of a long section of one-way operation. Background Art

[0002] When there is a line interruption in urban rail transit operations, the short-circuit strategy, single-line two-way, reverse driving strategy or a combination of strategies can generally be used for adjustment. The short-circuit strategy means that the train turns back at the stations with the ability to turn back on both sides of the interrupted section, and then turns back to the line in the other direction. The short-circuit strategy is more suitable for the situation of two-way line interruption. When a one-way interruption occurs in the section, the short-circuit strategy needs to be combined with the single-line two-way driving strategy or the reverse driving strategy. The "short-circuit + single-line two-way" strategy means that only one train is operated in the one-way section to provide two-way operation service, and the two-way sections on both sides are operated in the way of short-circuit turning back; the reverse driving strategy means using facilities such as crossovers, stop lines and turn-back lines to organize the train in the interrupted direction to run in the opposite direction of the opposite track for a distance, and then return to the original line to continue running.

[0003] The existing train operation adjustment is mainly based on the traditional train organization method, and the adjustment efficiency is relatively low when facing a long section interruption. Virtual marshaling technology refers to the use of wireless communication instead of mechanical coupling. The rear car obtains the operating status of the front car through car-to-car wireless communication, and realizes real-time and rapid reconnection or disassembly during the train operation. Compared with traditional fixed marshaling trains, virtual marshaling trains are not connected by mechanical coupling devices, and the number of train marshaling can be dynamically adjusted. Flexible scheduling can be achieved by setting appropriate driving intervals, thereby matching different transport capacities and achieving a good match between passenger flow and vehicle flow.

[0004] In summary, in the study of adjustment strategies in response to interruptions, existing research focuses more on the adjustment of train operation by small-circuit strategies, and there are relatively few studies on train operation adjustment for scenarios with long interruption sections on one-way lines. In addition, the efficiency of train operation adjustment under existing strategies is low. In terms of virtual marshaling technology, current research mainly focuses on the concept, advantages, train control technology and driving strategies under virtual marshaling technology, but lacks a model expression of train operation adjustment strategies under virtual marshaling technology. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for adjusting the operation of urban rail trains using virtual marshaling technology to cope with the interruption of a long section of one-way operation, establish an optimization model for adjusting the operation of trains using virtual marshaling technology in the scenario of a long interruption section, realize the mathematical modeling expression of the strategy of selecting the right time to turn back when reconnecting two-way trains by crossing the line, and propose a solution method for the model, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for adjusting the operation of an urban rail train in response to a long-section interruption of one-way operation, comprising:

[0008] For scenarios with long interruption lengths, a train operation adjustment model is constructed with the minimum total waiting time of passengers as the optimization goal. Among them, the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers.

[0009] A double-layer simulated annealing-genetic algorithm is used to solve the train operation adjustment model to obtain a train operation adjustment plan; an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0010] As a further limitation of the first aspect, the arrival time of a train at the station s it serves is the sum of the departure time of train i at station s-1 and the interval running time between station s-1 and station s; the departure time of train i at the station s it serves is the sum of the arrival time of train i at station s and the stop time; when the coupled train consisting of the up train i and the down train l is coupled, the running direction is upward, and the down train enters the coupled station first vs i Clear passengers and change ends, so the up train i is at the reconnection station vs i The arrival time of the station and the down train l in vs i The difference in arrival time of the down train l at vs i The time for clearing passengers and changing terminals at the station; after the reconnecting station, the down train reconnected with it changes its running direction, and its arrival time after the reconnecting station is consistent with the arrival time of the up train, and the departure time of the reconnecting station and the subsequent service station is consistent with the departure time of the up train.

[0011] As a further limitation of the first aspect, when the combined train consisting of the up train i and the down train l is running in the down direction after being combined, the down train enters the combined station first vs. i Clear passengers and change terminals, so the arrival time of down train l at the reconnection station vsi is the same as that of up train i at vsi. i The difference in arrival time of the station should be greater than the arrival time of the up train i in vs i The passenger clearing and terminal changing time of the station. After the reconnecting station, the up train reconnected with it changes its running direction, and its arrival time after the reconnecting station is consistent with the arrival time of the down train. The departure time of the reconnecting station and the subsequent service station is consistent with the departure time of the down train.

[0012] As a further limitation of the first aspect, when the combined train consisting of the up train i and the down train l is combined and runs in the upward direction, the up train i serves all trains in the up station set. At the station served by both the up train i+1 and the up train i, the departure interval must meet the minimum running interval. Due to the uniqueness of the single-line section occupancy, in this case, the time when the down train l+1 arrives at the 2X+1-n station and the time when the combined train leaves the 2X+1-n station must meet the safety interval time;

[0013] When the coupled train composed of the up train i and the down train l runs downward after being coupled, since the up train i+1 must enter the single-track section some time after the coupled train of the up train i and the down train leaves the 2X+1-m station, the departure interval between the up train i+1 and the up train i only needs to meet the minimum departure interval before m stations, and the time when the up train i+1 arrives at the 2X+1-m station and the time when the coupled train leaves the 2X+1-m station must meet the safety interval time.

[0014] As a further limitation of the first aspect, the interruption study period is refined into N time units of 1 minute granularity. The number of passengers arriving during the departure interval of up train i and up train i-1 is the sum of the number of passengers arriving during all time units contained in the departure interval of the two trains. The number of waiting passengers of the first train needs to be calculated separately, which is the number of arriving passengers of train i. Except for the first train, the number of passengers going to station s' among the waiting passengers of up train i is the number of passengers staying at station s waiting to go to station s' of up train i, v i,s,s' , plus the departure interval between train i and the adjacent preceding train k The number of arriving passengers in the upstream train i at the reconnection station vs i The number of passengers cleared for the up train i in vs i The number of passengers on board at station s minus the number of passengers getting off; the number of passengers getting off at station s of the upward train i is the sum of the number of passengers getting on the train starting from the station before station s and ending at station s.

[0015] As a further limitation of the first aspect, the number of passengers on board the up train i leaving station s is the passenger capacity of the up train i arriving at station s-1, minus the number of passengers getting off at station s, plus the number of passengers getting on at station s; the remaining capacity of the up train i at station s is the train capacity minus the number of passengers on board the up train i leaving station s-1 plus the number of passengers getting off at station s; the number of passengers getting on board the up train i at station s is the number of waiting passengers W i,s and the remaining capacity of the train r i,s The smaller value between the two; the number of passengers of the up train i staying at station s and the destination of station s' v i,s,s' is the number of passengers waiting at the platform W i,s,s' Number of passengers on board difference.

[0016] In a second aspect, the present invention provides an urban rail train operation adjustment system for coping with a long section interruption of one-way operation, comprising:

[0017] A construction module is used to construct a train operation adjustment model for scenarios with long interruption lengths, with the minimum total waiting time of passengers as the optimization goal; wherein the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers;

[0018] The solution module is used to solve the train operation adjustment model by using a double-layer simulated annealing-genetic algorithm to obtain a train operation adjustment plan; wherein an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0019] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with interruptions of long sections of one-way operation as described in the first aspect is implemented.

[0020] In a fourth aspect, the present invention provides a computer device comprising a memory and a processor, wherein the processor and the memory communicate with each other, the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with interruptions of long sections of one-way operation as described in the first aspect.

[0021] In a fifth aspect, the present invention provides an electronic device, comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing the method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with interruptions of long sections of one-way operation as described in the first aspect.

[0022] Terminology explanation:

[0023] Virtual marshaling technology: Use car-to-car wireless communication instead of traditional mechanical couplers to enable the rear car to obtain the operating status of the front car through wireless communication, thereby realizing the coordinated operation of multiple trains at the same speed and extremely small intervals, and being able to achieve real-time and rapid reconnection or de-marshaling during train operation.

[0024] Train operation adjustment: When external interference causes the train operation to deviate from the original plan, under the premise of ensuring driving safety, take corresponding measures according to the actual train operation situation to ensure that the train runs as far as possible according to the schedule or restore the transportation order.

[0025] The beneficial effects of the present invention are as follows: it can more effectively reduce the total waiting time of passengers, the waiting time of stranded passengers, reduce the number of stranded passengers, effectively improve the line transportation capacity, and improve the flexibility and timeliness of train operation adjustment; it can shorten the running interval of trains, more effectively utilize the train capacity and line capacity, serve more passengers, reduce the waiting time of oncoming passengers, and shorten the departure interval of trains in both directions, effectively improving the traffic capacity under long section interruption conditions; it can more effectively relieve passengers in the interrupted section, reduce detention, and improve the operational flexibility and stability of the rail transit system under emergency situations.

[0026] Additional advantages of the present invention will be more clearly given in the following description or learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0028] Figure 1 This is a schematic diagram of a two-way train reconnection using a crossover to return to the upward direction at an appropriate time according to an embodiment of the present invention.

[0029] Figure 2 This is a schematic diagram of a two-way train reconnection using a crossover to turn back to the downward direction at an appropriate time according to an embodiment of the present invention.

[0030] Figure 3 This is a schematic diagram of a scenario in which the interruption segment length is relatively long according to an embodiment of the present invention.

[0031] Figure 4 It is a schematic diagram of the constraint relationship between passenger flow division and train departure time according to an embodiment of the present invention.

[0032] Figure 5 This is a flow chart of solving a model using a double-layer simulated annealing-genetic algorithm as described in an embodiment of the present invention.

[0033] Figure 6 This is a schematic diagram of the initial solution of the outer algorithm in the double-layer simulated annealing-genetic algorithm described in an embodiment of the present invention.

[0034] Figure 7 This is a schematic diagram of chromosome encoding of the inner algorithm in the double-layer simulated annealing-genetic algorithm described in an embodiment of the present invention.

[0035] Figure 8 Schematic diagram of the crossover operation in the inner algorithm of the double-layer simulated annealing-genetic algorithm described in an embodiment of the present invention.

[0036] Fig. 9 A schematic diagram of the mutation operation in the inner algorithm of the double-layer simulated annealing-genetic algorithm described in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below by the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0038] It should be understood by those skilled in the art that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0039] It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have a meaning consistent with that in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless as defined herein.

[0040] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or groups thereof.

[0041] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. Different embodiments or examples described in this specification and features of different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

[0042] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings, and the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0043] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0044] The present invention aims at the scenario where the interruption section of a one-way urban rail transit line is long (the interruption length is greater than four intervals), and constructs a train operation adjustment model by combining virtual marshaling technology with a reverse driving strategy. The present invention solves the problems of large necessary safety interval for driving in this scenario, the inability to occupy intervals for non-vehicle-to-vehicle communication at the same time, low adjustment efficiency, and digital modeling of train operation adjustment strategies. The partial traffic capacity of the interrupted section is improved, the total waiting time of passengers and the waiting time of stranded passengers are effectively reduced, the number of stranded passengers is reduced, the flexibility and timeliness of train operation adjustment are improved, and the stability of the operation of the urban rail transit system is improved.

[0045] Example 1

[0046] In this embodiment 1, firstly, a system for adjusting the operation of urban rail trains to cope with the interruption of a long section of one-way operation is provided, including: a construction module, for constructing a train operation adjustment model for a long interruption length scenario with the minimum total waiting time of passengers as the optimization goal; wherein the constraints include train operation constraints and passenger boarding constraints, the train operation constraints include the relationship between train arrival and departure time, the train stop time at the station needs to meet the maximum and minimum stop time constraints and the train operation interval constraints; the passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers. A solution module, for solving the train operation adjustment model using a double-layer simulated annealing-genetic algorithm to obtain a train operation adjustment plan; wherein an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0047] In this embodiment, the above-mentioned system is used to implement a method for adjusting the operation of urban rail trains in response to interruptions in long one-way operation sections. For scenarios with long interrupted sections, a reverse driving strategy based on virtual marshaling is proposed in this embodiment: the two-way trains are reconnected and turn back at an appropriate time using the crossover. Assuming that a one-way interruption occurs in the upward direction, if the upward train is connected to the downward train and the running direction is upward after the connection is completed, the upward train is switched to the downward direction at the station closest to the interrupted section through the crossover and other wiring, and the downward train runs normally, and the upward train and the downward train enter the single-track section at the same time. Based on the virtual marshaling car-to-car communication technology, the two trains can share train information in real time, estimate the train running trajectory, consider the real-time passenger flow, and select stations with relatively close train arrival times as reconnection stations. The down train first enters the virtual reconnection station and stops steadily, and then clears passengers and changes terminals, and passengers board and alight. The up train enters the station and reconnects with the down train. After passengers board and alight, it continues to run along the single-track section as a large train, then returns to the up direction through the crossover, and runs to the terminal station as a reconnection train. Figure 1 If the running direction of the multiple train is down, the up train will enter the station first and stop steadily, clear passengers and change ends, and the down train will enter the station to form a large train, and then leave the single track section in the down direction and continue running. Figure 2 In addition, the train reconnection at the station requires the platform to meet the length requirement for two trains to stop at the same time. If the platform length cannot meet the requirement, the middle of the platform is used as the basis for the front and rear trains to stop, and the extra part is parked outside the platform for passengers to get on and off. Passengers choose the nearest platform door to get off, and passengers who get on the train can move to the carriage parked outside the platform after getting on the train from the platform door.

[0048] In this embodiment, a train operation adjustment model is constructed for the scenario with a long interruption length. The interruption scenario is assumed to occur in the upward direction of the line, and the interruption section is a plurality of intervals, between station m and station n, such as Figure 3 As shown in the figure, the strategy adopted is: the trains in both directions are reconnected and turn back at the right time by using the crossover. The up train i and the down train l enter the single-track section at the same time, that is, between the 2X+1-m station and the 2X+1-n station. The reconnection point vs is determined according to the train arrival situation and passenger flow situation. i If the running direction of the combined train is upward, the down train l arrives at the combined station first vs i After the passengers are cleared and the terminal is changed, the up train enters the station to reconnect with it, continues to run along the single-line section, and then returns to the up line through the crossover. If the running direction of the reconnected train is down, the up train i arrives at the reconnected station first vs i After the passengers are cleared and the terminal is changed, the down train enters the station and reconnects with it, running along the down direction.

[0049] In such Figure 3 In the urban rail transit line shown in the figure, when the operating section is interrupted in one direction, the set of upward stations is denoted as S u ={1,2,...,m-1}∪{2X+1-m,2X-m,...,2X+1-n}∪{n+1,n+2,...,X}, the set of downlink stations is denoted as S d ={X+1,X+2,...,2X}.

[0050] In order to facilitate the construction of the model, some complex factors are simplified in this embodiment, and the following assumptions are made:

[0051] (1) Trains are not allowed to overtake other trains at any point on the line, regardless of train skipping.

[0052] (2) The interval operating time will not be adjusted, but the stop time can be adjusted appropriately.

[0053] (3) Taking into account the platform length factor, a maximum of two trains are allowed to be coupled at the station, and it is assumed that all station platforms can accommodate the length of the coupled trains; the train can choose to couple or not at the station before entering the single-track section, namely, the m-1 station and the 2X-n station.

[0054] (4) Ignoring the situation where passengers turn to other modes of transportation or give up rail transit travel due to long waiting times.

[0055] (5) It is assumed that the undercarriage resources are sufficient to meet the needs of train operation adjustments.

[0056] The relevant parameters and variables in the model are defined and explained, as shown in Table 1.

[0057] Table 1 Description of model parameters and variables

[0058]

[0059]

[0060]

[0061] In this embodiment, the objective function of the optimization model is:

[0062] After the operation interruption occurs, in order to ensure the transportation service level and minimize the safety hazards caused by passengers staying at the station for a long time, the model takes the minimum total waiting time of passengers as the optimization goal. The total waiting time of passengers is composed of the waiting time of passengers at the station, the waiting time of stranded passengers, and the waiting time for passengers to be cleared at the reconnection station, as shown in formula (1).

[0063] minT=min(T1+T2+T3) (1)

[0064] (1) Passenger waiting time at the station

[0065] The waiting time of passengers at the station is the difference between the arrival time of passengers and the departure time of trains. The passenger flow time granularity of the present invention is 1 minute and passengers arrive evenly within each time granularity. Therefore, it can be divided into two parts for calculation: the first part is that each arriving passenger needs to wait for an average of 0.5 minutes because they arrive evenly within each time granularity; the second part is that passengers who arrive within each time granularity and wait to get on the train need to continue waiting until the train arrives, as shown in formula (2).

[0066]

[0067] (2) Waiting time for stranded passengers

[0068] The waiting time of stranded passengers is the product of the number of stranded passengers and their waiting time. The waiting time of stranded passengers of up train i is the difference between the departure time of train k and its adjacent preceding train i at station s. The waiting time of stranded passengers is shown in formula (3).

[0069]

[0070] (3) Waiting time for clearing passengers

[0071] The waiting time for the passengers of the up train i to clear is the time for the up train k2 to arrive at the reconnection station vs i Arrives at the reconnection station with the up train i vs i The waiting time for cleared passengers is the product of the number of cleared passengers and their waiting time. As shown in formula (4).

[0072]

[0073] Consider the constraints of the reconnection site and the running direction after reconnection:

[0074] The constraints of the model include train operation constraints and passenger boarding constraints. The constraints of the up train are explained as an example. The constraints of the down train are basically the same as those of the up train.

[0075] (1) Train operation constraints

[0076] 1) Train arrival and departure time relationship

[0077] The arrival time of the up train i at the station s it serves is the sum of the departure time of the up train i at s' station and the interval running time between s' station and s station, as shown in formula (5).

[0078]

[0079] The departure time of the up train i at the station s it serves is the sum of the arrival time and the stop time of the up train i at station s, as shown in formula (6).

[0080]

[0081] In addition, when the up train i and the down train l form a combined train, the running direction is upward, and the down train enters the combined station first vs i Clear passengers and change ends, so the up train i is at the reconnection station vs i The arrival time of the station and the down train l in vs i The difference in arrival time of the down train l at vs i The time for clearing passengers and changing terminals at the station is shown in formula (7). After the reconnection station, the arrival and departure times of the up train i at the station s it serves are calculated according to (5) to (6). However, the down train reconnected with it changes its running direction, and its arrival time after the reconnection station is consistent with the arrival time of the up train, and its departure time at the reconnection station and the subsequent service station is consistent with the departure time of the up train, as shown in formulas (8) to (9).

[0082]

[0083]

[0084] When the combined train consisting of the up train i and the down train l is running in the down direction after being combined, the down train enters the combined station first vs i Clear passengers and change ends, so the down train l is at the reconnection station vs i The arrival time of the station and the up train i in vs i The difference in arrival time of the station should be greater than the arrival time of the up train i in vs iThe time for clearing passengers and changing terminals at the station is shown in formula (10). After the reconnection station, the arrival time and departure time of the down train l at the station s it serves are calculated according to the down direction formulas corresponding to (5) to (6). However, the up train reconnected with it changes its running direction, and its arrival time after the reconnection station is consistent with the arrival time of the down train, and its departure time at the reconnection station and the subsequent service station is consistent with the departure time of the down train, as shown in formulas (11) to (12).

[0085]

[0086] 2) Train stop time relationship

[0087] The train's stop time at the station needs to meet the maximum and minimum stop time constraints, as shown in formula (13).

[0088]

[0089] 3) Train running interval constraints

[0090] When the combined train consisting of the up train i and the down train l is combined and runs in the up direction, the up train i serves all the trains in the up station set. At the station served by both the up train i+1 and the up train i, its departure interval must meet the minimum running interval, as shown in formula (14). Due to the uniqueness of the single-line section occupancy, in this case, the time when the down train l+1 arrives at the 2X+1-n station and the time when the combined train leaves the 2X+1-n station must meet the safety interval time, as shown in formula (15).

[0091]

[0092] When the combined train consisting of the up train i and the down train l is combined and runs in the down direction, since the up train number i+1 must enter the single-track section some time after the combined train of the up train i and the down train leaves the 2X+1-m station, the departure interval between the up train number i+1 and the up train number i only needs to meet the minimum departure interval before m stations, as shown in formula (16). The time when the up train i+1 arrives at the 2X+1-m station and the time when the combined train leaves the 2X+1-m station must meet the safety interval time, as shown in formula (17).

[0093]

[0094] (2) Passenger Restrictions

[0095] 1) Number of arriving passengers

[0096] In order to describe the arrival of passenger flow during the study period, the interruption study period is refined into 1-minute granularity time units to characterize the real-time changes of passenger flow.i,s,n represents the departure time of train i at station s and the time nodes t1, t2, …, t N relationship, if Greater than time node t n , then λ i,s,n =1; otherwise, λ i,s,n =0, as shown in formula (18).

[0097]

[0098] With the help of the 0-1 variable introduced above, the number of passengers arriving during the departure interval of up train i and up train i-1 is the sum of the number of passengers arriving during all time units contained in the departure interval of the two trains, as shown in formula (19). Figure 4 As shown, if the departure interval of the up train i and the train i-1 includes time units 4, 5, and 6, then the number of passengers arriving at train i is the sum of the number of passengers arriving within these three time units.

[0099]

[0100] The number of arriving passengers of the first train needs to be calculated separately, which is the sum of the number of arriving passengers in all time units from the beginning of the study period to the departure of train i from the station, as shown in formula (20).

[0101]

[0102] The number of passengers arriving in each time unit of the first train on the uplink is shown in formula (21).

[0103]

[0104] Except for the first train, the number of arriving passengers of the upstream train i is the sum of the number of arriving passengers in all time units contained in the departure interval between train i and the adjacent preceding train k, as shown in formula (22).

[0105]

[0106] The number of passengers arriving in each time unit between the departure interval of the upstream train i and the adjacent preceding train k is shown in formula (23).

[0107]

[0108] 2) Number of waiting passengers

[0109] The number of waiting passengers for the first train needs to be calculated separately, which is the number of arriving passengers of train i. The number of passengers going to station s' among the waiting passengers of the first train is shown in formula (24).

[0110]

[0111] The total number of waiting passengers for the first train at station s is shown in formula (25).

[0112]

[0113] Excluding the first train, the number of passengers waiting for the up train i to go to station s' is the number of passengers v of the up train i waiting for the up train i to go to station s' i,s,s' , plus the departure interval between train i and the adjacent preceding train k The number of arriving passengers within is shown in formula (26).

[0114]

[0115] The total number of waiting passengers for the up train i at station s is shown in formula (27).

[0116]

[0117] 3) Number of passengers cleared

[0118] Up train i at the reconnection station vs i The number of passengers cleared for the up train i in vs i The number of passengers on board at the station minus the number of passengers getting off is also the OD in the up train, which is vs. i The passengers before and after the station are shown in equations (28) to (29).

[0119]

[0120] 4) Number of passengers getting off the bus

[0121] The number of passengers getting off the up train i at station s is the sum of the number of passengers getting on the train starting from the station before station s and ending at station s. At the starting station of the reconnection, the number of passengers clearing out also needs to be added, as shown in formula (30).

[0122]

[0123] 5) Number of passengers on board

[0124] The number of passengers on board when the up train i leaves station s is the passenger capacity of the up train i arriving at station s-1, minus the number of passengers getting off at station s, plus the number of passengers getting on at station s, as shown in formula (31).

[0125]

[0126] 6) Train remaining capacity

[0127] The remaining capacity of the up train i at station s is the train capacity minus the number of passengers on board when the train i leaves station s-1 plus the number of passengers getting off at station s. When the running direction of the reconnected train is the same as the original running direction of the up train i, since the train numbers of the up and down trains do not change after the up train i is reconnected with the down train l, the up train at the reconnected station vs i The train capacity is then updated to 2C. i = 0, the up train will be at the reconnection station vs i The train capacity is then updated to 0, as shown in formula (32).

[0128]

[0129] 7) Number of passengers on board

[0130] The number of passengers boarding the up train i at station s is the number of waiting passengers W i,s and the remaining capacity of the train r i,s The smaller value between , as shown in formula (33). The proportion of passengers who board the up train i at station s and go to station s' is the ratio of the number of passengers departing from station s and going to station s' to the number of passengers departing from station s, as shown in formula (34). The number of passengers who board the up train i at station s and go to station s' is shown in formula (35).

[0131]

[0132] 8) Number of stranded passengers

[0133] The number of passengers on the up train i who are stranded at station s and whose destination is station s' v i,s,s' is the number of passengers waiting at the platform W i,s,s' Number of passengers on board The difference is shown in formula (36). The stranded passengers of the up train i at station s are shown in formula (37).

[0134]

[0135] In the nonlinear constraint (33), is the minimum value of the two. Introduce a 0-1 auxiliary variable u i,s , as shown in formula (38) to formula (42):

[0136]

[0137]

[0138] u i,s ∈{0,1}(42)

[0139] After the introduction of 0-1 variables, the above model is a mixed integer nonlinear model. As the scale of the problem increases, the number of variables shows a significant growth trend. The time consumption of directly using the solution tool to solve large-scale cases increases dramatically. On this basis, in order to verify the rationality and effectiveness of the model, an optimization algorithm is designed to solve the model. Since the mutual influence relationship between the decision variables in the model is relatively complex, in order to further solve the model efficiently, in this embodiment, a two-layer simulated annealing-genetic algorithm is used for solution. Based on the traditional genetic algorithm, this algorithm establishes an elite retention strategy and adds a solution checking process to the crossover and mutation operations in the genetic algorithm. The algorithm flow chart is shown below. Figure 5 shown.

[0140] For the double-layer heuristic algorithm design, this embodiment uses a two-stage method to adjust the three stages of the interruption response stage, the interruption continuation stage and the recovery stage. The interruption response stage and the interruption continuation stage are regarded as one stage. First, the trains in the interruption stage (interruption response stage + interruption continuation stage) are adjusted. Secondly, in the recovery stage, each train in the interruption stage is judged to determine the set of adjusted trains in the recovery stage, and then the train operation adjustment in the three stages is realized. Since the train operation adjustment in the recovery stage is relatively simple and the train operation adjustment in the interruption stage is relatively complex, the algorithm of the present invention is explained by taking the interruption stage as an example. The decision variables of the model are the running direction of the reconnected train, the reconnected station of the train in the single-line section, the arrival time of the train at the first station and the stop time at each station.

[0141] In this embodiment, for the outer layer algorithm - simulated annealing algorithm, its specific algorithm steps are as follows:

[0142] Step 1: Generate initial solution

[0143] The decision variables of the outer algorithm are the 0-1 variable running direction vd of the reconnected train and the integer variable reconnected stations vs of each train in the single-line section. If the running direction of the reconnected train is the same as that of the original train, then vd is 1, otherwise it is 0. That is, when the running direction of the reconnected train is upward, the vd of the upward train is 1, and the vd of the downward train is 0. The train randomly selects the reconnected station vs in the station range of the single-line section, which is the initial solution of the outer layer, such as Figure 6 shown.

[0144] Step 2: Calculate the objective function value

[0145] Since the selection of the reconnection site has a great impact on the timetable, the passenger flow distribution will change accordingly, which in turn affects the final objective function. Therefore, the present invention uses the outer algorithm to decide the reconnection site and the direction of the reconnection train, and then calls the inner genetic algorithm to obtain the optimal timetable and the minimum passenger waiting time based on the outer parameters. The inner algorithm feeds the result back to the outer algorithm as the objective function value under the reconnection scheme.

[0146] Step 3: Update solution

[0147] Generate a new solution through random perturbations, and then calculate the objective function value of the new solution through the method of Step 2.

[0148] Step 4: Accept the new solution

[0149] Calculate the difference between the objective function values ​​of the new solution and the current optimal solution, and determine whether to accept the new solution based on the Metropolis criterion: if ΔN≤0, accept the new reconnected train direction vd(i+1) and train reconnection site vs(i+1) as the new optimal solution; otherwise, calculate the acceptance probability p=exp(-N / α), randomly generate a random number r between [0,1), if p>r, still accept vd(i+1) and vs(i+1) as the new current solution, otherwise retain the original solution as the current solution.

[0150] Step 5: Termination criteria

[0151] The termination of the algorithm is determined by the end temperature. If the current temperature does not reach the end temperature, the iteration continues; once the end temperature is reached, the operation is terminated.

[0152] For the inner algorithm - genetic algorithm, the specific steps are as follows:

[0153] Step 1: Generate initial solution

[0154] The decision variables in the second stage are the arrival time of the train at the first station and the stop time at each station. The chromosomes are coded with real numbers, such as Figure 7 The outer parameters are input into the inner algorithm, and the constraints related to train stops, interval operation and train interval are considered. Chromosomes are randomly generated to ensure the feasibility of the initial solution and accelerate the convergence speed.

[0155] The arrival time of the first station and the stop time at each station are generated according to the following rules:

[0156]

[0157]

[0158] Step 2: Fitness function calculation

[0159] The fitness function in the genetic algorithm is a key indicator for evaluating the quality of individuals and guides the search direction of the algorithm. Generally, the larger the value, the better the performance of the individual. However, this embodiment uses the total waiting time of passengers as the objective function. The smaller the total waiting time of passengers, the better. Therefore, the negative value of the objective function is used as the fitness function F=-T.

[0160] Step 3: Select

[0161] The roulette wheel method is used for selection. Assume that the population size is N, the fitness of individual n is nf, and the probability of being selected np is proportional to its fitness value. At the same time, the elite retention strategy is adopted to replace the 10% individuals with the lowest fitness in the offspring with the 10% individuals with the highest fitness in the parent generation, so as to maintain the stability of the population and improve the solution efficiency.

[0162] Step 4: Cross

[0163] Select two individuals from the population with a crossover probability pm for crossover. Break the chromosome at a certain point, keep the first half unchanged, cross the second half, and form a new individual, such as Figure 8 The new individuals are adjusted according to constraints (7) to (12) and (15) and (17), and then it is determined whether they meet the constraints such as stop time and train interval. If they meet the constraints, a new chromosome is obtained; if not, crossover is performed again.

[0164] Step 5: Mutation

[0165] Given a point that can be mutated, a mutation point is randomly selected with a set mutation probability pc, such as Fig. 9 As shown, the new individuals are adjusted according to constraints (7) to (12) and (15) and (17), and then it is determined whether the constraints such as stop time and train interval are met. If so, a new chromosome is obtained; if not, a new mutation operation is performed.

[0166] Step 6: Termination criteria

[0167] The termination condition of the algorithm is the number of iterations. If the number of iterations is not met, the iteration continues; if it is met, the operation is terminated.

[0168] Example 2

[0169] This embodiment 2 provides a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the above-mentioned method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with the interruption of a long section of one-way operation is implemented, and the method includes:

[0170] For scenarios with long interruption lengths, a train operation adjustment model is constructed with the minimum total waiting time of passengers as the optimization goal. Among them, the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers.

[0171] A double-layer simulated annealing-genetic algorithm is used to solve the train operation adjustment model to obtain a train operation adjustment plan; an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0172] Example 3

[0173] This embodiment 3 provides a computer device, including a memory and a processor, the processor and the memory communicate with each other, the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the above-mentioned method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with the interruption of a long section of one-way operation, the method comprising:

[0174] For scenarios with long interruption lengths, a train operation adjustment model is constructed with the minimum total waiting time of passengers as the optimization goal. Among them, the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers.

[0175] A double-layer simulated annealing-genetic algorithm is used to solve the train operation adjustment model to obtain a train operation adjustment plan; an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0176] Example 4

[0177] This embodiment 4 provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing the above-mentioned method for adjusting the operation of urban rail trains using virtual marshaling technology to cope with the interruption of a long section of one-way operation, the method comprising:

[0178] For scenarios with long interruption lengths, a train operation adjustment model is constructed with the minimum total waiting time of passengers as the optimization goal. Among them, the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers.

[0179] A double-layer simulated annealing-genetic algorithm is used to solve the train operation adjustment model to obtain a train operation adjustment plan; an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

[0180] In summary, the key point of the present invention is to achieve efficient train operation adjustment for the situation where the length of the interrupted section of the one-way line of urban rail transit is long by establishing an optimization model and using virtual marshaling technology. Taking the minimum total waiting time of passengers as the objective function, the virtual marshaling is integrated into the constraints such as train operation and passenger boarding, and the mathematical modeling expression of the strategy of reconnecting two-way trains and turning back at the right time by crossing the line is realized, and a solution method for the model is proposed. Compared with the existing train operation adjustment method under the same scenario, the present invention can more effectively reduce the total waiting time of passengers, the waiting time of stranded passengers, reduce the number of stranded passengers, effectively improve the line transportation capacity, and improve the flexibility and timeliness of train operation adjustment. Under the traditional reverse driving strategy, only one direction of the train can occupy the entire single-line section, and the opposite train needs to wait at the station outside the single-line section. The technical solution proposed by the present invention can shorten the train running interval. In the same time as a one-way train passing through a single-line section, the present invention can more effectively utilize the train capacity and line capacity, serve more passengers, reduce the waiting time of passengers in the opposite direction, and shorten the departure interval of two-way trains, effectively improving the traffic capacity under long section interruption conditions. When two-way trains are reconnected at the station before the interruption section and pass through the single-line section in a large formation, due to the significant increase in train capacity, the present invention can more effectively relieve passengers in the interruption section, reduce detention, and improve the operational flexibility and stability of the rail transit system under emergency conditions. The traditional reverse driving strategy and single-line two-way strategy can also complete the train operation adjustment under one-way interruption, but the adjustment effect is limited. The single-line two-way strategy usually needs to be used in combination with the small route strategy, and the number of passenger transfers is relatively large. Although the reverse driving strategy can serve all stations and passengers can reach their destination without transfer, due to the long length of the interruption section and the one-way section cannot be occupied by trains in both directions at the same time, the line capacity will be significantly reduced in this case, and the waiting time of passengers will be greatly extended. The present invention is based on virtual marshaling technology, which allows trains in both directions to be reconnected and turn back at an appropriate time by using crossing lines. Trains in both directions can enter the single-track section at the same time. When the up train occupies the single-track section, the down train can also enter the single-track section to provide services to some stations while ensuring safety. The line transportation capacity can be greatly improved, so the driving adjustment strategy of the present invention has better effects.

[0181] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0182] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0183] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0184] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0185] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative work on the basis of the technical solution disclosed in the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for adjusting the operation of urban rail trains in response to the interruption of a long section of one-way operation, characterized in that: include: For scenarios with long interruption lengths, a train operation adjustment model is constructed with the minimum total waiting time of passengers as the optimization goal. Among them, the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers. A double-layer simulated annealing-genetic algorithm is used to solve the train operation adjustment model to obtain a train operation adjustment plan; an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

2. The method for adjusting the operation of urban rail trains in response to interruptions of long sections of one-way operation according to claim 1, characterized in that: The arrival time of a train at the station s it serves is the sum of the departure time of train i at station s-1 and the interval running time between stations s-1 and s; The departure time of train i at the station s it serves is the sum of the arrival time and the stop time of train i at station s; when the up train i and the down train l form a combined train, the running direction is upward, and the down train enters the combined station first vs i Clear passengers and change ends, so the up train i is at the reconnection station vs i The arrival time of the station and the down train l in vs i The difference in arrival time of the down train l at vs i The station clearing and terminal change time; After the reconnection station, the down train reconnected with it changes its running direction, and its arrival time after the reconnection station is consistent with the arrival time of the up train, and its departure time at the reconnection station and subsequent service stations is consistent with the departure time of the up train.

3. The method for adjusting the operation of urban rail trains in response to interruptions of long sections of one-way operation according to claim 2, characterized in that: When the combined train consisting of the up train i and the down train l is running in the down direction after being combined, the down train enters the combined station first vs i Clear passengers and change ends, so the down train l is at the reconnection station vs i The arrival time of the station and the up train i in vs i The difference in arrival time of the station should be greater than the arrival time of the up train i in vs i The passenger clearing and terminal changing time of the station. After the reconnecting station, the up train reconnected with it changes its running direction, and its arrival time after the reconnecting station is consistent with the arrival time of the down train. The departure time of the reconnecting station and the subsequent service station is consistent with the departure time of the down train.

4. The method for adjusting the operation of urban rail trains in response to interruptions of long sections of one-way operation according to claim 3, characterized in that: When the combined train consisting of the up train i and the down train l is combined and runs in the up direction, the up train i serves all the trains in the up station set. At the station served by both the up train i+1 and the up train i, the departure interval must meet the minimum running interval. Due to the uniqueness of the single-line section occupancy, in this case, the time when the down train l+1 arrives at the 2X+1-n station and the time when the combined train leaves the 2X+1-n station must meet the safety interval time; When the coupled train composed of the up train i and the down train l runs downward after being coupled, since the up train i+1 must enter the single-track section some time after the coupled train of the up train i and the down train leaves the 2X+1-m station, the departure interval between the up train i+1 and the up train i only needs to meet the minimum departure interval before m stations, and the time when the up train i+1 arrives at the 2X+1-m station and the time when the coupled train leaves the 2X+1-m station must meet the safety interval time.

5. The method for adjusting the operation of urban rail trains in response to the interruption of a long section of one-way operation according to claim 4, characterized in that: The interruption study period is divided into N time units of 1 minute granularity. The number of passengers arriving during the departure interval of up train i and up train i-1 is the sum of the number of passengers arriving in all time units contained in the departure interval of the two trains. The number of waiting passengers of the first train needs to be calculated separately, which is the number of arriving passengers of train i. Except for the first train, the number of passengers going to station s' among the waiting passengers of up train i is the number of passengers v that are stranded at station s waiting to go to station s' of up train i. i,s,s' , plus the departure interval between train i and the adjacent preceding train k The number of arriving passengers in the upstream train i at the reconnection station vs i The number of passengers cleared for the up train i in vs i The number of passengers on board at station s minus the number of passengers getting off; the number of passengers getting off at station s of the upward train i is the sum of the number of passengers getting on the train starting from the station before station s and ending at station s.

6. The method for adjusting the operation of urban rail trains in response to interruptions of long sections of one-way operation according to claim 5, characterized in that: The number of passengers on board when the up train i leaves station s is the passenger capacity of the up train i arriving at station s-1, minus the number of passengers getting off at station s, plus the number of passengers getting on at station s; The remaining capacity of the up train i at station s is the train capacity minus the number of passengers on board when train i leaves station s-1 plus the number of passengers getting off at station s; The number of passengers boarding the up train i at station s is the number of waiting passengers W i,s and the train remaining capacity r i,s The smaller value between the two; the number of passengers of the up train i staying at station s and the destination of station s' v i,s,s' is the number of passengers waiting at the platform W i,s,s' Number of passengers on board difference.

7. An urban rail train operation adjustment system for coping with the interruption of a long section of one-way operation, characterized in that: include: A construction module is used to construct a train operation adjustment model for scenarios with long interruption lengths, with the minimum total waiting time of passengers as the optimization goal; wherein the constraints include train operation constraints and passenger boarding constraints. Train operation constraints include the relationship between train arrival and departure times, the train stop time at the station must meet the maximum and minimum stop time constraints and the train operation interval constraints; passenger boarding constraints include the number of arriving passengers, the number of waiting passengers, the number of cleared passengers, the number of disembarking passengers, the number of passengers on board, the remaining capacity of the train, the number of boarding passengers and the number of stranded passengers; The solution module is used to solve the train operation adjustment model by using a double-layer simulated annealing-genetic algorithm to obtain a train operation adjustment plan; wherein an elite retention strategy is established, and a solution checking process is added to the crossover and mutation operations in the double-layer simulated annealing-genetic algorithm.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the urban rail train operation adjustment method for coping with the interruption of a long section of one-way operation as described in any one of claims 1-6 is implemented.

9. A computer device, characterized in that: It includes a memory and a processor, the processor and the memory communicate with each other, the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the urban rail train operation adjustment method for coping with the interruption of a long section of one-way operation as described in any one of claims 1-6.

10. An electronic device, characterized in that: include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the method for adjusting the operation of an urban rail train in response to the interruption of a long section of one-way operation as described in any one of claims 1 to 6.

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