Automatic compilation method, system and medium for rail transit multi-route operation plan

Abstract

The present invention relates to a method, system and medium for automatically compiling a rail transit multi-route operation plan, the method comprising the following steps: step S1, identifying the selected route type based on the route path information; step S2, constructing a unified data framework for describing the input parameters of the multi-route operation plan, and performing structured recognition and data preprocessing; step S3, establishing an operation plan optimization model that is common to multiple routes and has variable input parameters according to the transport capacity configuration goals and requirements, and calculating the optimal time-sharing plan result parameters that meet the conditions; step S4, setting a custom train number, matching the relationship between the custom train number and the time-sharing plan, and automatically generating a complete operation plan. Compared with the prior art, the present invention has the advantages of simplified operation plan compilation process, easy expansion of the optimization model, and consideration of regularity and customization conditions.

Description

Technical Field

[0001] The invention relates to a rail transit signal system, and in particular to a method, system and medium for automatically compiling a rail transit multi-route operation plan. Background Art

[0002] Urban rail transit trains operate according to the route forms specified in the plan map. Common route forms include single route, large and small routes, circular routes, Y-shaped routes, connecting routes and combinations of these routes. Each line formulates a route form based on line conditions and passenger flow demand. Therefore, the route forms of different lines are different, and the same line will also adopt different route forms in different periods and time periods. A route form combined with interval parameters constitutes a train operation plan. Therefore, map editors need to frequently compile train operation plans under a variety of route conditions.

[0003] The existing method of compiling train operation plans studies different routes separately, and the existing map compilation software also divides the train operation plan into multiple independent modules such as single route, large and small routes, and circular routes. This makes the workflow of formulating train operation plans cumbersome, the data formats are multiple, and the method types are complex, which affects the improvement of map compilation and operation management efficiency.

[0004] After searching the Chinese patent publication number CN115239021A, a method for optimizing the operation plan of large and small routes of urban rail transit was disclosed. Specifically, the method aims to solve the problem of passenger congestion during the morning peak hours of urban rail transit lines, and establishes an optimization model for the operation plan of large and small routes of urban rail transit with the goal of minimizing the total waiting time cost of passengers and the number of kilometers traveled by trains; the optimization model of large and small routes of urban rail transit is solved by linear weighted sum method to obtain the optimal train operation plan and objective function value. However, the existing patent mainly models and solves the large and small route operation plan based on the minimum waiting time for passengers and the number of kilometers traveled by trains, without considering other route forms and route combinations.

[0005] With the upgrading of networked operations and the need for intelligent map compilation technology, operating units in various regions are in urgent need of universal methods and systems for automatic compilation of operation plans to solve the problem of unified compilation of operation diagrams under various route conditions. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method, system and medium for automatically compiling rail transit operation plans for multiple routes, which has a simplified operation plan compilation process, an easily expandable optimization model, and takes into account both regularity and customization conditions. Single routes, circular routes, large and small routes, Y-shaped routes, connecting routes and separated routes are integrated under an integrated model framework to achieve unified modeling and optimization calculation of operation plans for these common routes.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to a first aspect of the present invention, a method for automatically compiling multiple rail transit route operation plans is provided, the method comprising the following steps:

[0009] Step S1, identifying the selected intersection type based on the path information of the intersection;

[0010] Step S2, constructing a unified data framework for describing the input parameters of the multi-intersection operation plan, and performing structured recognition and data preprocessing;

[0011] Step S3, according to the transport capacity configuration objectives and requirements, establish a running plan optimization model that is common to multiple routes and has variable input parameters, and calculate the optimal time-sharing plan result parameters that meet the conditions;

[0012] Step S4, setting a custom train number, and matching the relationship between the custom train number and the time-sharing plan, and automatically generating a complete operation plan.

[0013] As a preferred technical solution, the intersection type of step S1 is specifically:

[0014] Single intersections and circular intersections are defined as single intersection types, and collinear intersections, connecting intersections, and separated intersections are defined as double intersection types, among which collinear intersections are further divided into large and small intersections and Y-type intersections.

[0015] As a preferred technical solution, the identification of the selected intersection type in step S1 is specifically as follows:

[0016] For single-route types, the stations at both ends of the route are identified based on whether they are the same. If they are the same, it is a circular route, and if they are different, it is a single route.

[0017] For double intersection types, they are identified based on the number of common stations between the two intersections. Intersections with two or more common stations are co-linear intersections, intersections with one common station connected end to end are connecting intersections, and intersections with no common stations are separate intersections.

[0018] As a preferred technical solution, for the co-linear intersection, identification is performed based on whether the two intersection endpoints are on the same main line. If both are on the same main line, it is a large-small intersection; if both are on the main line and the forked line, it is a Y-type intersection.

[0019] As a preferred technical solution, in step S2, a unified data framework is constructed to describe the input parameters of the multi-intersection operation plan as follows:

[0020] The input parameters of the multi-route operation plan are uniformly described as: start time, end time, route type, whether the route is circular, operation ratio, common line segment interval or total number of vehicles, average interval of each route, operation and stop scale, up or down path information of each route, turnaround method, minimum and maximum turnaround time, in and out path information, turnaround station priority, two-way staggered arrival stations and time;

[0021] The above parameters are described as a set of data fields as a unified data framework so that each intersection can be adapted. If a certain intersection does not have a certain field, it will be filled with zero or 0.

[0022] As a preferred technical solution, in step S2, the structured recognition and data preprocessing are as follows: according to the route type, the route section information is identified, and the segmented travel time is calculated.

[0023] As a preferred technical solution, the structured recognition and data preprocessing are specifically as follows:

[0024] Assume that the stations at both ends of route 1 are A and B; if there is route 2, the stations at both ends of route 2 are C and D; according to the automatic path identification of route 1 and route 2, if there is a common line segment, the stations at both ends of the common line segment are set to E and F. The two routes may have one end overlapping, in which case E and C overlap or F and D overlap; according to the running scale and stop scale used by the line, calculate the up and down travel time of the routes between A~B, C~D and the up and down travel time of the segments between E~F, A~E, C~E, B~F, and D~F respectively.

[0025] As a preferred technical solution, in step S3, establishing a running scheme optimization model that is common to multiple routes and has variable input parameters is specifically as follows:

[0026] Step S301, setting model decision variables, specifically including:

[0027] 3011) Total number of vehicles or benchmark interval: choose one of the two, when one is the decision variable, the other is the input parameter, which is applicable to single intersection, circular intersection, and collinear intersection. For connecting intersection and separated intersection, the decision variable is only the total number of vehicles;

[0028] 3012) Actual turnaround time of all turnaround stations: Under two intersection conditions, there are at most four turnaround stations;

[0029] 3013) Each route operation cycle: the sum of the two-way travel time and the return time at both ends;

[0030] 3014) Two-way start time difference: There is a start time difference in both directions of each intersection;

[0031] 3015) Auxiliary integer variable K k: k auxiliary integer variables required by the model expression, used to express multiple relationships;

[0032] Step S302, the model objective function is to minimize the weighted sum of the return time and the expected deviation of the two-way staggered arrival;

[0033] Step S303, setting model constraints, specifically including:

[0034] 3031) Interval constraint: Based on the reference interval, the conversion interval is added as an intermediate variable;

[0035] 3032) operation cycle constraints;

[0036] 3033) Apply total vehicle number constraints;

[0037] 3034) Two-way relationship constraints;

[0038] 3035) Turnaround time range constraint: The actual turnaround time of each turnaround station is between the minimum and maximum values;

[0039] 3036) Bidirectional staggered arrival constraints;

[0040] 3037) Bidirectional start time difference constraint.

[0041] As a preferred technical solution, the model objective function in step S302 is specifically:

[0042] M=min[∑(tr i ·ρ i )+∑(ΔGap j ·σ j )]

[0043] Among them, tr i is the actual return time of station i, ρ i is the return priority coefficient. The larger it is, the sooner the i-th return station should return. j is the deviation of the two-way staggered arrival time at intermediate station j, that is, the difference from the expected staggered time; σ j is the two-way staggered priority coefficient. The larger it is, the closer the i intermediate station is to the set staggered arrival time. j is any intermediate station, and any number of intermediate stations can be selected.

[0044] As a preferred technical solution, the interval constraint 3031) is specifically:

[0045] 30311) Collinear intersections: The base interval is the interval between vehicles on the collinear segments, and the conversion interval is the average interval of each intersection;

[0046] 30312) A circular or single-intersection circuit has only one interval, namely the reference interval;

[0047] 30313) There are two intervals for connecting or separating intersections: the reference interval is the interval of intersection 1, and the conversion interval is the interval of intersection 2;

[0048] The 3032) operation cycle constraints are specifically:

[0049] 30321) Non-circular routes: The operating cycle of each route is the sum of the up and down travel time between the two end stations and the return time of the two end stations;

[0050] 30322) Circular route: There are two operating cycles, which are the sum of the up or down travel time and the return time at one end station;

[0051] 30323) Each route operation cycle is also an integer multiple of the reference interval;

[0052] The total number of vehicles used in the 3033) constraint is specifically:

[0053] 30331) Single-strip route: the total number of vehicles is equal to the operating cycle divided by the reference interval;

[0054] 30332) For co-linear routes: the total number of vehicles is equal to the sum of the product of the operation ratio and the operation cycle of the two routes, divided by the conversion interval;

[0055] 30333) Ring: The total number of vehicles is equal to the sum of the operating cycles in both directions divided by the reference interval;

[0056] 30334) Connecting or separating routes: The total number of vehicles is equal to the sum of the number of vehicles on the two routes, that is, the operating cycle of route 1 divided by the reference interval plus the operating cycle of route 2 divided by the conversion interval;

[0057] The two intersection relationship constraints 3034) are specifically:

[0058] 30341) Collinear intersection: The difference in the two-way travel time of two non-collinear segments of the intersection is an integer multiple of the average headway interval;

[0059] 30342) Connecting routes: The sum of the reference interval and the return time of the two routes at the connecting station is at least staggered by two safety intervals, and the difference between the operating cycle of each route and the return time of the two routes at the connecting station is between two conversion interval multiples;

[0060] 30343) Single intersections, circular intersections and separated intersections do not have this constraint;

[0061] The bidirectional staggered arrival constraints (3036) are specifically:

[0062] The difference between the two-way travel time from any two-way staggered arrival station to any terminal station of its current route and the multiple of the "reference interval" is greater than or equal to the expected staggered time; for single route, co-line route stations and the first route station of connecting routes and separated routes, the "reference interval" is the benchmark interval, and in other cases, the conversion interval is used;

[0063] The bidirectional start time difference constraint 3037) is specifically:

[0064] 30371) Non-circular route: The difference between the start time of the uplink and downlink is equal to K times the "reference interval" minus the uplink travel time and the downlink first station return time, and the absolute value of the difference between the start times is less than the driving interval;

[0065] 30372) The "reference interval" of intersection 1 of non-circular intersections is the reference interval, and the "reference interval" of intersection 2 of non-circular intersections is the converted interval;

[0066] 30373) There is no such constraint for roundabouts.

[0067] As a preferred technical solution, the customized train numbers in step S4 include the first train, the last train, the patrol train, the debugging train, and the spare train, which need to be fixedly operated within a set time range.

[0068] As a preferred technical solution, in step S4, the relationship between matching the customized train number and the time-sharing plan is specifically as follows:

[0069] Set the start time, route, direction and attributes of several custom trains to make the time of the custom trains within the expected operating time range, and combine them with the time-sharing plan in a timely manner to form a complete operation plan based on the time and route.

[0070] According to a second aspect of the present invention, a system for automatically compiling the rail transit multiple route operation scheme is provided, the system comprising a route type identification and analysis module, a time-sharing scheme optimization module and an operation scheme management module connected in sequence;

[0071] The intersection type identification and analysis module automatically identifies the intersection type and the turnaround type at both ends based on the selected intersection path information, structures the intersection information, and normalizes the operation plan data of multiple intersections;

[0072] The time-sharing scheme optimization module establishes a linear programming model based on the identified route information and combined with the input parameters and constraints of the operation scheme, and calculates the optimal operation scheme result parameters for each time period;

[0073] The operation plan management module integrates the optimization results of the time-sharing plan for each period, and allows the simultaneous addition of custom train numbers to integrate them into a full-day operation plan.

[0074] As a preferred technical solution, the time-sharing scheme optimization module includes a unified data framework construction module, a structured data preprocessing module and a scheme solving model construction module; the operation plan management module includes a time-sharing scheme management module and a custom train number management module, and the custom train number management module is connected to the time-sharing scheme management module.

[0075] According to a third aspect of the present invention, there is provided an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the method described above is implemented when the processor executes the program.

[0076] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the program implements the method described when executed by a processor.

[0077] Compared with the prior art, the present invention has the following advantages:

[0078] 1) The present invention automatically identifies the route type based on the path information, and unifies the data structure of the operation plan under various route types, so as to simplify the plan preparation process, reduce manual calculation, and facilitate the preparation and management of multi-line and multi-version operation plans under network operation;

[0079] 2) The operation plan optimization model for multiple routes established by the present invention has variable input parameters, and the decision variables and input parameters are interchangeable. It has universal applicability and strong scalability under domestic and foreign rail transit operation modes;

[0080] 3) The present invention can not only optimize and calculate the time-divided plan with even intervals, but also support users to customize train numbers with special attributes, and can simultaneously meet the requirements of regularity and customized operation plan compilation. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is the technical roadmap of the present invention.

[0082] Figure 2 It is a system flow chart of the present invention.

[0083] Figure 3 This is a cross-path type diagram of the present invention.

[0084] Figure 4 It is a structured cross-connection diagram of the present invention. DETAILED DESCRIPTION

[0085] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0086] like Figure 1 As shown, an embodiment of the present invention provides a method for automatically compiling multiple route operation plans for urban rail transit, comprising the following steps:

[0087] Step 1: Based on the path information of the intersection, identify and determine the type of the selected intersection:

[0088] Figure 2 The intersection types are illustrated, single intersections and circular intersections are defined as single intersection types, and collinear intersections, connecting intersections, and separated intersections are defined as double intersection types, among which collinear intersections are further divided into large and small intersections and Y-type intersections.

[0089] For single-line crossings, the identification is based on whether the stations at both ends of the route are the same. If they are the same, it is a circular crossing, and if they are different, it is a single crossing. For double crossings, the identification is based on the number of common stations between the two crossings. If there are two or more common stations, it is a co-line crossing, if there is one common station connected from end to end, it is a connecting crossing, and if there is no common station, it is a separated crossing. Furthermore, for co-line crossings, the identification is based on whether the two crossing end stations are on the same main line. If they are on the same main line, it is a large-small crossing, and if they are on the main line and the forked line respectively, it is a Y-shaped crossing.

[0090] Step 2: Build a unified data framework to describe the input parameters of the multi-intersection operation plan, and perform structured recognition and data preprocessing:

[0091] The input parameters of the multi-route operation plan are uniformly described as: start time, end time, route type, whether the route is circular, operation ratio, common line segment interval (if any) or total number of vehicles, average interval of each route, operation and stop scale, up / down path information of each route, turnaround method, minimum and maximum turnaround time, in and out path information, turnaround station priority, two-way staggered arrival stations and time. These parameters are described as a set of data fields as a unified data framework so that each route can be adapted. If a certain route does not have a certain field, fill it with None or 0. Examples of input parameters are shown in Table 1:

[0092] Table 1

[0093]

[0094]

[0095] According to the route type, the route section information is identified and the segment travel time is calculated. Figure 3 An example of a structured collinear intersection diagram is given. Assume that the two end stations of intersection 1 are A and B, and calculate the up and down travel time between A and B; if there is intersection 2, the two end stations of intersection 2 are C and D, and calculate the up and down travel time between C and D; according to the automatic identification of the paths of intersections 1 and 2, if there is a collinear segment, the two end stations of the collinear segment are set to E and F. The two intersections may have one end overlapped, in which case E and C overlap or F and D overlap, and calculate the up and down travel time between E and F, between A and E, between C and E, between B and F, and between D and F; if there is no collinear segment, calculate the travel time for each intersection separately.

[0096] Step 3: According to the transport capacity configuration goals and requirements, establish a running plan optimization model that is common to multiple routes and has variable input parameters, and calculate the optimal time-sharing plan result parameters that meet the conditions:

[0097] Create the following model:

[0098] 1. Model decision variables include:

[0099] ①Total number of vehicles or benchmark interval: choose one of the two. When one is a decision variable, the other is an input parameter. This is applicable to single intersections, circular intersections, and collinear intersections. The decision variable for connecting intersections and separating intersections is only the total number of vehicles.

[0100] ② The actual turning time of all turning stations: Under the two route conditions, there are at most four turning stations.

[0101] ③ Each route operation cycle: the sum of the two-way travel time and the return time at both ends.

[0102] ④ Two-way starting time difference: There is a starting time difference in the two directions of each intersection.

[0103] ⑤Auxiliary integer variable K k : k auxiliary integer variables required by the model to express multiple relationships.

[0104] 2. The objective function of the model is to minimize the weighted sum of the return time and the expected deviation of the two-way staggered arrival:

[0105] M=min[∑(tr i ·ρ i )+∑(ΔGap j ·σ j )]

[0106] Among them, tr i is the actual return time of station i. i is the return priority coefficient. The larger it is, the sooner the i return station should return. jis the deviation of the two-way staggered arrival time at intermediate station j, that is, the difference from the expected staggered time. j is the two-way staggered priority coefficient. The larger it is, the closer the i intermediate station is to the set staggered arrival time. j can be any intermediate station, and any number of intermediate stations can be selected.

[0107] 3. Model constraints include:

[0108] 1) Interval constraint: Based on the benchmark interval, add the conversion interval as an intermediate variable:

[0109] ① Collinear intersections: The benchmark interval is the driving interval of the collinear segment, and the converted interval is the average interval of each intersection.

[0110] ② A circular or single-intersection circuit has only one interval, namely the reference interval.

[0111] ③ There are two intervals for connecting or separating intersections: the reference interval is the interval of intersection 1, and the conversion interval is the interval of intersection 2.

[0112] 2) Operation cycle constraints:

[0113] ① Non-circular routes: The operation cycle of each route is the sum of the up and down travel time between the two end stations and the return time of the two end stations;

[0114] ② Circular route: There are two operating cycles, which are the sum of the up or down travel time and the return time at one end station.

[0115] ③ Each route operation cycle is also an integer multiple of the benchmark interval.

[0116] 3) Use total vehicle number constraints:

[0117] ① Single route: The total number of vehicles is equal to the operating cycle divided by the reference interval.

[0118] ② Co-linear routes: The total number of vehicles is equal to the sum of the product of the operation ratio and the operation cycle of the two routes, divided by the conversion interval.

[0119] ③ Ring: The total number of vehicles is equal to the sum of the operating cycles in both directions divided by the reference interval.

[0120] ④ Connecting or separating routes: The total number of vehicles is equal to the sum of the number of vehicles on the two routes, that is, the operating cycle of route 1 divided by the benchmark interval plus the operating cycle of route 2 divided by the conversion interval.

[0121] 4) Two-intersection relationship constraints: Only collinear and connecting intersections exist:

[0122] ① Collinear intersection: The difference in the two-way travel time of two non-collinear segments of the intersection is an integer multiple of the average driving interval;

[0123] ② Connecting routes: The sum of the base interval and the turnaround time of the two routes at the connecting station is staggered by at least two safety intervals, and the difference between the operating cycle of each route and the turnaround time of the two routes at the connecting station is between two conversion interval multiples;

[0124] ③Single intersections, circular intersections and separated intersections do not have this constraint.

[0125] 5) Turnaround time range constraint: The actual turnaround time of each turnaround station is between the minimum and maximum values.

[0126] 6) Two-way staggered arrival constraints:

[0127] The difference between the two-way travel time from any two-way staggered arrival station to any end station of its current route and the multiple of the "reference interval" is greater than or equal to the expected staggered time. For single route, co-line route stations and the first route station of connecting routes and separated routes, the "reference interval" is the benchmark interval, and in other cases, the conversion interval is used.

[0128] 7) Bidirectional start time difference constraint:

[0129] ① Non-circular route: The difference between the uplink and downlink start times is equal to K times the "reference interval" minus the uplink travel time and the downlink first stop return time, and the absolute value of the difference in start time is less than the driving interval.

[0130] ② The “reference interval” of intersection 1 of a non-circular intersection is the reference interval, and the “reference interval” of intersection 2 of a non-circular intersection is the converted interval.

[0131] ③There is no such constraint for circular intersections.

[0132] The optimization tool is called to solve the above model and obtain the optimal result of the decision variables. Table 1 shows an example of the decision variable results for a period of time.

[0133] Step 4: Set up custom train numbers, match the relationship between custom train numbers and time-sharing plans, and generate a complete operation plan:

[0134] Customized trains include the first train, the last train, patrol trains, debugging trains, spare trains, etc., which need to be operated within a certain time range. Set the start time, route, direction, and attributes of several customized trains, and make the time of the customized trains within the expected operating time range. According to the time and route, it is combined with the time-sharing plan in a time sequence to form a complete operation plan. See Table 2 for examples of customized trains:

[0135] Table 2

[0136]

[0137] The above is an introduction to the method embodiment. The following is a further explanation of the solution of the present invention through a system embodiment.

[0138] like Figure 2 As shown, the present invention also provides a system for automatically compiling multiple route operation plans for rail transit, the system comprising a route type identification and analysis module, a time-sharing plan optimization module and an operation plan management module connected in sequence;

[0139] The intersection type identification and analysis module automatically identifies the intersection type and the turnaround type at both ends based on the selected intersection path information, structures the intersection information, and normalizes the operation plan data of multiple intersections;

[0140] The time-sharing scheme optimization module establishes a linear programming model based on the identified route information and combined with the input parameters and constraints of the operation scheme, and calculates the optimal operation scheme result parameters for each time period;

[0141] The operation plan management module integrates the optimization results of the time-sharing plan for each period, and allows the simultaneous addition of custom train numbers to integrate them into a full-day operation plan.

[0142] The time-sharing scheme optimization module includes a unified data framework construction module, a structured data preprocessing module and a scheme solution model construction module; the operation scheme management module includes a time-sharing scheme management module and a custom train number management module, and the custom train number management module is connected to the time-sharing scheme management module.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0144] The embodiment of the present invention also provides an electronic device including a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or computer program instructions loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0145] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0146] The processing unit performs the various methods and processes described above, such as the method of the present invention. For example, in some embodiments, the method of the present invention can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the method of the present invention described above can be performed. Alternatively, in other embodiments, the CPU can be configured to perform the method of the present invention by any other appropriate means (e.g., by means of firmware).

[0147] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0148] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0149] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0150] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for automatically compiling a rail transit multi-route operation plan, characterized in that: The method comprises the following steps: Step S1, identifying the selected intersection type based on the path information of the intersection; Step S2, constructing a unified data framework for describing the input parameters of the multi-intersection operation plan, and performing structured recognition and data preprocessing; Step S3, according to the transport capacity configuration objectives and requirements, establish a running plan optimization model that is common to multiple routes and has variable input parameters, and calculate the optimal time-sharing plan result parameters that meet the conditions; Step S4, setting a custom train number, matching the relationship between the custom train number and the time-sharing plan, and automatically generating a complete operation plan; In step S3, the establishment of a running scheme optimization model common to multiple routes and with variable input parameters is specifically as follows: Step S301, setting model decision variables, specifically including: 3011) Total number of vehicles or benchmark interval: choose one of the two, when one is the decision variable, the other is the input parameter, which is applicable to single intersection, circular intersection, and collinear intersection. For connecting intersection and separated intersection, the decision variable is only the total number of vehicles; 3012) Actual turnaround time of all turnaround stations: Under two intersection conditions, there are at most four turnaround stations; 3013) Each route operation cycle: the sum of the two-way travel time and the return time at both ends; 3014) Two-way start time difference: There is a start time difference in both directions of each intersection; 3015) Auxiliary integer variable K k : k auxiliary integer variables required by the model expression, used to express multiple relationships; Step S302, the model objective function is to minimize the weighted sum of the return time and the expected deviation of the two-way staggered arrival; Step S303, setting model constraints, specifically including: 3031) Interval constraint: Based on the reference interval, the conversion interval is added as an intermediate variable; 3032) operation cycle constraints; 3033) Apply total vehicle number constraints; 3034) Two-way relationship constraints; 3035) Turnaround time range constraint: The actual turnaround time of each turnaround station is between the minimum and maximum values; 3036) Bidirectional staggered arrival constraints; 3037) Bidirectional start time difference constraint.

2. According to claim 1, a method for automatically compiling a rail transit multi-route operation plan is characterized in that: The specific intersection type of step S1 is: Single intersections and circular intersections are defined as single intersection types, and collinear intersections, connecting intersections, and separated intersections are defined as double intersection types, among which collinear intersections are further divided into large and small intersections and Y-type intersections.

3. According to claim 1, a method for automatically compiling a rail transit multi-route operation plan is characterized in that: The identification of the selected route type in step S1 is specifically as follows: For single-route types, the stations at both ends of the route are identified based on whether they are the same. If they are the same, it is a circular route, and if they are different, it is a single route. For double intersection types, they are identified based on the number of common stations between the two intersections. Intersections with two or more common stations are co-linear intersections, intersections with one common station connected end to end are connecting intersections, and intersections with no common stations are separate intersections.

4. According to claim 3, a method for automatically compiling a rail transit multi-route operation plan is characterized in that: For the collinear intersection, identification is performed based on whether the two intersection endpoint stations are on the same main line. If both are on the same main line, it is a large-small intersection; if both are on the main line and the bifurcated line, it is a Y-type intersection.

5. According to claim 1, a method for automatically compiling a rail transit multi-route operation plan is characterized in that: In step S2, a unified data framework is constructed to describe the input parameters of the multi-intersection operation plan: The input parameters of the multi-route operation plan are uniformly described as: start time, end time, route type, whether the route is circular, operation ratio, common line segment interval or total number of vehicles, average interval of each route, operation and stop scale, up or down path information of each route, turnaround method, minimum and maximum turnaround time, in and out path information, turnaround station priority, two-way staggered arrival stations and time; The above parameters are described as a set of data fields as a unified data framework so that each intersection can be adapted. If a certain intersection does not have a certain field, it will be filled with zero or 0.

6. According to claim 1, a method for automatically compiling a rail transit multi-route operation plan is characterized in that: In the step S2, the structured recognition and data preprocessing are as follows: according to the route type, the route section information is recognized, and the segment travel time is calculated.

7. The method for automatically compiling a rail transit multi-route operation plan according to claim 6, characterized in that: The structured recognition and data preprocessing are specifically as follows: Assume that the stations at both ends of route 1 are A and B; if there is route 2, the stations at both ends of route 2 are C and D; according to the automatic path identification of route 1 and route 2, if there is a common line segment, the stations at both ends of the common line segment are set to E and F. The two routes may have one end overlapping, in which case E and C overlap or F and D overlap; according to the running scale and stop scale used by the line, calculate the up and down travel time of the routes between A~B, C~D and the up and down travel time of the segments between E~F, A~E, C~E, B~F, and D~F respectively.

8. The method for automatically compiling a rail transit multi-route operation plan according to claim 1, characterized in that: The model objective function in step S302 is specifically: M=min[∑(tr i ·r i )+∑(ΔGap j ·s j )] Among them, tr i is the actual return time of station i, ρ i is the return priority coefficient. The larger it is, the sooner the i-th return station should return. j is the deviation of the two-way staggered arrival time at intermediate station j, that is, the difference from the expected staggered time; σ j is the two-way staggered priority coefficient. The larger it is, the closer the i intermediate station is to the set staggered arrival time. j is any intermediate station, and any number of intermediate stations can be selected.

9. The method for automatically compiling a rail transit multi-route operation plan according to claim 1, characterized in that: The 3031) interval constraints are specifically: 30311) Collinear intersections: The base interval is the interval between vehicles on the collinear segments, and the conversion interval is the average interval of each intersection; 30312) A circular or single-intersection circuit has only one interval, namely the reference interval; 30313) There are two intervals for connecting or separating intersections: the reference interval is the interval of intersection 1, and the conversion interval is the interval of intersection 2; The 3032) operation cycle constraints are specifically: 30321) Non-circular routes: The operating cycle of each route is the sum of the up and down travel time between the two end stations and the return time of the two end stations; 30322) Circular route: There are two operating cycles, which are the sum of the up or down travel time and the return time at one end station; 30323) Each route operation cycle is also an integer multiple of the reference interval; The total number of vehicles used in the above 3033) is specifically as follows: 30331) Single-strip route: the total number of vehicles is equal to the operating cycle divided by the reference interval; 30332) For co-linear routes: the total number of vehicles is equal to the sum of the product of the operation ratio and the operation cycle of the two routes, divided by the conversion interval; 30333) Ring: The total number of vehicles is equal to the sum of the operating cycles in both directions divided by the reference interval; 30334) Connecting or separating routes: The total number of vehicles is equal to the sum of the number of vehicles on the two routes, that is, the operating cycle of route 1 divided by the reference interval plus the operating cycle of route 2 divided by the conversion interval; The two intersection relationship constraints 3034) are specifically: 30341) Collinear intersection: The difference in the two-way travel time of two non-collinear segments of the intersection is an integer multiple of the average headway interval; 30342) Connecting routes: The sum of the reference interval and the return time of the two routes at the connecting station is at least staggered by two safety intervals, and the difference between the operating cycle of each route and the return time of the two routes at the connecting station is between two conversion interval multiples; 30343) Single intersections, circular intersections and separated intersections do not have this constraint; The bidirectional staggered arrival constraints (3036) are specifically: The difference between the two-way travel time from any two-way staggered arrival station to any terminal station of its current route and the multiple of the "reference interval" is greater than or equal to the expected staggered time; for single route, co-line route stations and the first route station of connecting routes or separated routes, the "reference interval" is the benchmark interval, and in other cases, the converted interval is used; The bidirectional start time difference constraint 3037) is specifically: 30371) Non-circular route: The difference between the start time of the uplink and downlink is equal to K times the "reference interval" minus the uplink travel time and the downlink first station return time, and the absolute value of the difference between the start times is less than the driving interval; 30372) The "reference interval" of intersection 1 of non-circular intersections is the reference interval, and the "reference interval" of intersection 2 of non-circular intersections is the converted interval; 30373) There is no such constraint on circular intersections.

10. The method for automatically compiling a rail transit multi-route operation plan according to claim 1, characterized in that: The customized train numbers in step S4 include the first train, the last train, the patrol train, the debugging train, and the spare train, which need to be fixedly operated within the set time range.

11. The method for automatically compiling a rail transit multi-route operation plan according to claim 10, characterized in that: In step S4, the relationship between matching the customized train number and the time-sharing plan is specifically as follows: Set the start time, route, direction and attributes of several custom trains to make the time of the custom trains within the expected operating time range, and combine them with the time-sharing plan in a timely manner to form a complete operation plan based on the time and route.

12. A system for automatically compiling the method for operating multiple rail transit routes according to claim 1, characterized in that: The system includes a route type identification and analysis module, a time-sharing scheme optimization module and a running scheme management module connected in sequence; The intersection type identification and analysis module automatically identifies the intersection type and the turnaround type at both ends based on the selected intersection path information, structures the intersection information, and normalizes the operation plan data of multiple intersections; The time-sharing scheme optimization module establishes a linear programming model based on the identified route information and combined with the input parameters and constraints of the operation scheme, and calculates the optimal operation scheme result parameters for each time period; The operation plan management module integrates the optimization results of the time-sharing plan for each period, and allows the simultaneous addition of custom train numbers to integrate them into a full-day operation plan.

13. The system according to claim 12, characterized in that: The time-sharing scheme optimization module includes a unified data framework construction module, a structured data preprocessing module and a scheme solution model construction module; the operation scheme management module includes a time-sharing scheme management module and a custom train number management module, and the custom train number management module is connected to the time-sharing scheme management module.

14. An electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: When the processor executes the program, the method according to any one of claims 1 to 11 is implemented.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

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