Rail transit passenger flow scheduling method and device

Abstract

The application provides a rail transit passenger flow scheduling method and device, the method comprises the following steps: obtaining a passenger flow scheduling period; in the case that the passenger flow scheduling period is a current day middle period, in each first scheduling period in the passenger flow scheduling period, based on the transport capacity data and the first passenger flow data of the first scheduling period, a first optimization model is solved to determine a train operation frequency increase scheme and a first flow limiting scheme; or in the case that the passenger flow scheduling period is a subsequent day middle period, in each second scheduling period in the passenger flow scheduling period, based on the transport capacity data and the second passenger flow data of the second scheduling period, a second optimization model is solved to determine a second flow limiting scheme and at least one operation scheme. By distinguishing whether the passenger flow scheduling period is a current day middle period or a subsequent day middle period, the current day passenger flow scheduling and the subsequent day passenger flow scheduling can be processed according to different scheduling periods, and a suitable passenger flow scheduling scheme for the current day and the subsequent day can be determined.

Description

Technical Field

[0001] This invention relates to the field of rail transit technology, and in particular to a method and apparatus for rail transit passenger flow scheduling. Background Technology

[0002] Urban rail transit passenger flow exhibits strong spatiotemporal imbalance and random fluctuations, often resulting in large numbers of passengers stranded in stations and a mismatch between capacity supply and passenger demand during peak hours. To ensure operational safety and passenger service levels, subway operators frequently implement passenger flow control measures both inside and outside stations to alleviate large passenger flows. Extensive research exists on coordinated passenger flow control across single lines and networks, typically aiming to minimize differences in service levels among stations, the number of stations subject to flow control, and the time passengers spend outside stations and on platforms. However, these studies only control the demand side and do not optimize capacity supply. To achieve the best possible match between passenger demand and capacity supply, some studies have integrated passenger flow control with capacity allocation, using factors such as train tracking intervals and departure intervals as constraints to construct a coordinated optimization model for train operation plans and passenger flow control plans.

[0003] However, passenger flow scheduling for the current day differs from that for subsequent days (e.g., tomorrow or some future day). Compared to subsequent days, passenger flow scheduling for the current day requires a higher frequency of scheduling. Furthermore, considering that train routes cannot be arbitrarily changed once a train is already in operation, passenger flow scheduling for the current day cannot alter train routes or timetables. However, for passenger flow scheduling for a future day (e.g., tomorrow), train routes and timetables can be changed. Determining appropriate passenger flow scheduling schemes for the current day and subsequent days is a pressing issue that the industry needs to address. Summary of the Invention

[0004] To address the problems existing in the prior art, embodiments of the present invention provide a method and apparatus for scheduling passenger flow in rail transit.

[0005] In a first aspect, the present invention provides a method for scheduling passenger flow in rail transit, comprising:

[0006] Obtain passenger flow scheduling time periods;

[0007] When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, the first optimization model is solved to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle;

[0008] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0009] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0010] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, the first capacity optimization sub-model includes: a first capacity allocation objective function and a first capacity allocation constraint, wherein the first capacity allocation objective function takes the train operation frequency of each route as the decision variable and the minimum train travel distance as the optimization objective;

[0011] The first flow restriction optimization sub-model includes: a first flow restriction objective function and a first flow restriction constraint condition. The first flow restriction objective function takes the flow restriction station set and the flow restriction intensity of each flow restriction station as decision variables, and takes the maximum passenger flow in the first scheduling cycle and the minimum variance of the flow restriction intensity of the flow restriction station set as optimization objectives.

[0012] The train frequency increase scheme includes: increasing the train frequency configuration for each route; the first flow restriction scheme includes: a first flow restriction station set and the flow restriction intensity of each first flow restriction station;

[0013] The first optimization model, based on capacity data and first passenger flow data of the first scheduling period, is solved to determine the train frequency increase scheme and the first passenger flow restriction scheme for the first scheduling period, including:

[0014] Based on the first capacity allocation constraint, the capacity data, and the first passenger flow data, the first capacity allocation objective function is solved to determine the train frequency of each route, and based on the capacity data and the train frequency of each route, the configuration for increasing the train frequency of each route is determined.

[0015] Based on the first flow restriction constraint, the transport capacity data, and the first passenger flow data, the first flow restriction objective function is solved to determine the first set of flow restriction stations and the flow restriction intensity of each first flow restriction station.

[0016] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the capacity data includes: a first preset maximum cross-sectional load factor, a preset maximum train frequency on the line, a preset maximum number of trains on the line, a total number of stations on the line, an entry gate throughput capacity index, a platform capacity index, and a maximum transport capacity index for each section; the first passenger flow data includes: the maximum cross-sectional passenger flow for each section;

[0017] The first capacity allocation constraints include: maximum cross-sectional load factor constraints, section train frequency constraints, route train frequency constraints, maximum train frequency constraints, and number of vehicles in use constraints.

[0018] The maximum cross-sectional load factor constraint condition is used to constrain the maximum cross-sectional load factor of the section to be less than or equal to the first preset maximum cross-sectional load factor.

[0019] The train frequency constraint condition for each section is used to constrain the relationship between the train frequency of each section and the maximum cross-sectional passenger flow of each section.

[0020] The aforementioned train frequency constraint is used to constrain the relationship between the train frequency of a section and the train frequency of the section.

[0021] The maximum train frequency constraint is used to constrain the relationship between the train frequency of the section route and the preset maximum train frequency of the line.

[0022] The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route.

[0023] The first flow restriction constraints include: flow restriction intensity constraints, flow restriction station number constraints, station capacity constraints, and interval transport capacity constraints;

[0024] The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength;

[0025] The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line;

[0026] The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index.

[0027] The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

[0028] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, before solving the first flow restriction objective function based on the first flow restriction constraint, the capacity data, and the first passenger flow data, and determining the first set of flow restriction stations and the flow restriction intensity of each first flow restriction station, the method further includes:

[0029] The train frequency configuration for each route has been increased, and the maximum transport capacity indicators for each section have been updated.

[0030] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, the at least one second capacity optimization sub-model includes the following sub-models: single route operation scheme optimization sub-model, large and small route operation scheme optimization sub-model, and connecting route operation scheme optimization sub-model;

[0031] The second capacity optimization sub-model includes a second capacity allocation objective function and a second capacity allocation constraint condition;

[0032] The second capacity allocation objective function of the single-route operation scheme optimization sub-model uses the single-route train operation frequency as the decision variable and the minimum passenger waiting time and the minimum train travel distance as the optimization objectives.

[0033] The second capacity allocation objective function of the optimization sub-model of the large and small route operation scheme takes the small route train frequency, the first ratio, the first small route turnaround station and the second small route turnaround station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives. The first ratio is the ratio between the large route train frequency and the small route train frequency.

[0034] The second capacity allocation objective function of the optimization sub-model of the connecting route operation scheme takes the train operation frequency of the first route, the train operation frequency of the second route, and the connecting station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives.

[0035] The second flow restriction optimization sub-model includes: a second flow restriction objective function and a second flow restriction constraint. The second flow restriction objective function uses the set of flow-restricted stations and the flow restriction intensity of each flow-restricted station as decision variables, and takes the maximum passenger flow entering the station and the minimum variance of the flow restriction intensity of the set of flow-restricted stations within the second scheduling cycle as optimization objectives.

[0036] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the at least one operation scheme includes: a single route operation scheme, a combined long and short route operation scheme, and a connecting route operation scheme; the second flow restriction scheme includes: a third flow restriction scheme for each flow restriction period, the third flow restriction scheme including a set of second flow restriction stations and the flow restriction intensity of each second flow restriction station, wherein the flow restriction period is a period in the second scheduling cycle;

[0037] The second optimization model is solved based on capacity data and second passenger flow data of the second scheduling period to determine the second flow restriction scheme and at least one operation scheme for the second scheduling period, including:

[0038] Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the single route operation scheme optimization sub-model, the second capacity allocation objective function of the single route operation scheme optimization sub-model is solved to determine the single route operation scheme.

[0039] Based on the transport capacity data, the second passenger flow data, and the second transport capacity allocation constraints of the optimized sub-model of the large and small route operation scheme, the second transport capacity allocation objective function of the optimized sub-model of the large and small route operation scheme is solved to determine the large and small route operation scheme;

[0040] Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the connecting route operation scheme optimization sub-model, the second capacity allocation objective function of the connecting route operation scheme optimization sub-model is solved to determine the connecting route operation scheme.

[0041] Based on the second flow restriction constraint, the capacity data, and the second passenger flow data, the second flow restriction objective function is solved to determine the third flow restriction scheme for each flow restriction period.

[0042] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the capacity data includes: the preset minimum train frequency of the line, the preset maximum train frequency of the line, the preset maximum number of trains used on the line, the second preset maximum cross-section full load rate, the total number of stations on the line, the entry gate throughput capacity index, the platform capacity index, and the maximum transport capacity index of each section.

[0043] The second capacity allocation constraints include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints.

[0044] The minimum train frequency constraint is used to constrain the relationship between the train frequency of the route and the preset minimum train frequency of the line.

[0045] The maximum train frequency constraint is used to constrain the relationship between the train frequency of the route and the maximum train frequency of the preset line.

[0046] The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route.

[0047] The maximum cross-section full load rate constraint condition is used to constrain the maximum cross-section full load rate of the line to be less than or equal to the second preset maximum cross-section full load rate.

[0048] The second flow restriction constraint conditions include: flow restriction intensity constraint conditions, flow restriction station number constraint conditions, station capacity constraint conditions, and interval transport capacity constraint conditions;

[0049] The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength;

[0050] The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line;

[0051] The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index.

[0052] The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

[0053] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, before solving the second flow restriction objective function based on the second flow restriction constraint, the capacity data, and the second passenger flow data, and determining the third flow restriction scheme for each flow restriction period, the method further includes:

[0054] Based on preset evaluation indicators, the single route operation plan, the large and small route operation plan, and the connecting route operation plan are evaluated to obtain the first evaluation result of each operation plan;

[0055] Based on the first evaluation results of each operation plan, one of the following operation plans is determined as the target operation plan: the single route operation plan, the large and small route operation plan, and the connecting route operation plan.

[0056] Based on the target train operation plan, update the maximum transport capacity index for each section.

[0057] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, when the passenger flow scheduling period is the current midday period, after solving the first optimization model based on the capacity data and the first passenger flow data of the first scheduling period to determine the train frequency increase scheme and the first flow restriction scheme of the first scheduling period, the method further includes:

[0058] Based on preset evaluation indicators, the train frequency increase scheme and the first flow restriction scheme are evaluated to obtain a second evaluation result.

[0059] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, after solving the second optimization model based on the capacity data and the second passenger flow data of the second scheduling cycle to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle, the method further includes:

[0060] Based on the preset evaluation indicators, the second flow restriction scheme and the at least one operation scheme are evaluated to obtain a third evaluation result.

[0061] Secondly, the present invention also provides a rail transit passenger flow scheduling device, comprising:

[0062] The acquisition module is used to obtain passenger flow scheduling time periods;

[0063] The determination module is used to, when the passenger flow scheduling period is the current midday period, solve the first optimization model based on the capacity data and the first passenger flow data of the first scheduling period in each first scheduling cycle of the passenger flow scheduling period, and determine the train frequency increase scheme and the first flow restriction scheme of the first scheduling cycle;

[0064] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0065] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0066] The rail transit passenger flow scheduling method and apparatus provided by this invention, by distinguishing whether the passenger flow scheduling period is the current midday period or a subsequent midday period, can determine the passenger flow scheduling scheme according to a first scheduling cycle when the passenger flow scheduling period is the current midday period, and according to a second scheduling cycle when the passenger flow scheduling period is a subsequent midday period. A first scheduling cycle shorter than a second scheduling cycle can meet the scheduling demand for higher frequencies on the current day. When the passenger flow scheduling period is the current midday period, by solving the first capacity optimization sub-model and the first flow restriction optimization sub-model, the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle can be determined. The train frequency increase scheme and the first flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure the first scheduling... The capacity supply and passenger demand are matched in the second scheduling cycle, and the increased train frequency scheme is a scheme that increases the train frequency based on the current train operation scheme, which can avoid changing the train operation routes. When the passenger flow scheduling period is the midday period of the following day, by solving the second flow restriction optimization sub-model and at least one second capacity optimization sub-model, the second flow restriction scheme and at least one operation scheme can be determined. At least one operation scheme and the second flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply and passenger demand are matched in the second scheduling cycle. The train operation routes of the following days can be changed, and at least one operation scheme can be used to change the train operation routes of the following days to meet the capacity supply, which can realize the determination of a suitable passenger flow scheduling scheme for the current day and the following days. Attached Figure Description

[0067] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0068] Figure 1 This is one of the flowcharts of the rail transit passenger flow scheduling method provided by the present invention;

[0069] Figure 2 This is the second flowchart of the rail transit passenger flow scheduling method provided by the present invention;

[0070] Figure 3 This is a schematic diagram of the first optimization model provided by the present invention;

[0071] Figure 4 This is a schematic diagram of the train frequency increase scheme provided by the present invention;

[0072] Figure 5 This is a schematic diagram of the second optimization model provided by the present invention;

[0073] Figure 6 This is a schematic diagram of the single-route operation scheme provided by the present invention;

[0074] Figure 7 This is a schematic diagram of the large and small route operation scheme provided by the present invention;

[0075] Figure 8 This is a schematic diagram of the connecting route operation scheme provided by the present invention;

[0076] Figure 9 This is a schematic diagram of the structure of the rail transit passenger flow scheduling device provided by the present invention;

[0077] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0078] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0079] Figure 1 This is one of the flowcharts illustrating the rail transit passenger flow scheduling method provided by the present invention, such as... Figure 1 As shown, the executing entity of the rail transit passenger flow scheduling method can be an electronic device, such as a server. The method includes:

[0080] Step 101: Obtain passenger flow scheduling time periods.

[0081] Specifically, in order to achieve passenger flow scheduling for rail transit, passenger flow scheduling time periods can be obtained, and then corresponding passenger flow scheduling schemes can be determined for the passenger flow scheduling time periods.

[0082] Optionally, if based on passenger flow forecast data, it is predicted that a large passenger flow will occur during a certain period of the current day, then that period can be determined as the passenger flow scheduling period.

[0083] Optionally, if based on passenger flow forecast data, it is predicted that a large passenger flow will occur at a certain time on a subsequent day, then that time period can be determined as the passenger flow scheduling period.

[0084] Optionally, the current day's preset scheduling period can be determined as the passenger flow scheduling period, or the preset scheduling period of subsequent days can be determined as the passenger flow scheduling period.

[0085] Step 102: When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, solve the first optimization model to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle.

[0086] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0087] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0088] Specifically, by distinguishing between the current midday period and the subsequent midday period, the passenger flow scheduling plan can be determined according to the first scheduling cycle when the passenger flow scheduling period is the current midday period, and according to the second scheduling cycle when the passenger flow scheduling period is the subsequent midday period. The first scheduling cycle being shorter than the second scheduling cycle can meet the scheduling needs of the current day at a higher frequency.

[0089] Optionally, the first scheduling cycle can be 15 minutes, and the second scheduling cycle can be 1 hour.

[0090] Specifically, when the passenger flow scheduling period is the current midday period, by solving the first capacity optimization sub-model and the first flow restriction optimization sub-model, the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle can be determined. The train frequency increase scheme and the first flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply and passenger flow demand in the first scheduling cycle are matched. Moreover, the train frequency increase scheme is a scheme that increases the train frequency based on the current train operation scheme, which can avoid changing the train operation routes.

[0091] It is understandable that both the increased train frequency plan and the first flow restriction plan are passenger flow scheduling plans, and dispatchers can choose between the increased train frequency plan and / or the first flow restriction plan to carry out passenger flow scheduling.

[0092] Specifically, when the passenger flow scheduling period is the midday period of the following day, by solving the second flow restriction optimization sub-model and at least one second capacity optimization sub-model, the second flow restriction scheme and at least one operation scheme can be determined. The at least one operation scheme and the second flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand. Furthermore, the train operation routes of the following day can be changed, and the at least one operation scheme can be used to change the train operation routes of the following day to meet the capacity supply.

[0093] It is understandable that the second flow restriction plan and at least one operation plan are both passenger flow scheduling plans. The dispatchers can select one or more plans from the second flow restriction plan and at least one operation plan to carry out passenger flow scheduling.

[0094] The rail transit passenger flow scheduling method provided by this invention distinguishes between the current daytime and subsequent daytime periods for passenger flow scheduling. It can handle passenger flow scheduling for the current day and subsequent days according to different scheduling cycles. A first scheduling cycle shorter than a second scheduling cycle can meet the higher frequency scheduling needs of the current day. When the passenger flow scheduling period is the current daytime, by determining a train frequency increase scheme and a first flow restriction scheme, it can ensure that the capacity supply of the first scheduling cycle matches the passenger flow demand and avoids changes to train routes. When the passenger flow scheduling period is subsequent daytime, by determining at least one operation scheme and a second flow restriction scheme, it can ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand. Furthermore, at least one operation scheme can be used to change the train routes of subsequent days to meet capacity supply needs, thus enabling the determination of appropriate passenger flow scheduling schemes for both the current day and subsequent days.

[0095] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, the first capacity optimization sub-model includes: a first capacity allocation objective function and a first capacity allocation constraint, wherein the first capacity allocation objective function takes the train operation frequency of each route as the decision variable and the minimum train travel distance as the optimization objective;

[0096] The first flow restriction optimization sub-model includes: a first flow restriction objective function and a first flow restriction constraint condition. The first flow restriction objective function takes the flow restriction station set and the flow restriction intensity of each flow restriction station as decision variables, and takes the maximum passenger flow in the first scheduling cycle and the minimum variance of the flow restriction intensity of the flow restriction station set as optimization objectives.

[0097] The train frequency increase scheme includes: increasing the train frequency configuration for each route; the first flow restriction scheme includes: a first flow restriction station set and the flow restriction intensity of each first flow restriction station;

[0098] The first optimization model, based on capacity data and first passenger flow data of the first scheduling period, is solved to determine the train frequency increase scheme and the first passenger flow restriction scheme for the first scheduling period, including:

[0099] Based on the first capacity allocation constraint, the capacity data, and the first passenger flow data, the first capacity allocation objective function is solved to determine the train frequency of each route, and based on the capacity data and the train frequency of each route, the configuration for increasing the train frequency of each route is determined.

[0100] Based on the first flow restriction constraint, the transport capacity data, and the first passenger flow data, the first flow restriction objective function is solved to determine the first set of flow restriction stations and the flow restriction intensity of each first flow restriction station.

[0101] Specifically, when the passenger flow scheduling period is the current midday period, by solving the first capacity allocation objective function, the train frequency of each route can be determined. Then, based on the capacity data and the train frequency of each route, the configuration for increasing the train frequency of each route can be determined. By solving the first flow restriction objective function, the set of first flow restriction stations and the flow restriction intensity of each first flow restriction station can be determined. The configuration for increasing the train frequency of each route and the flow restriction intensity of each first flow restriction station can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply and passenger flow demand match in the first scheduling cycle. Moreover, the configuration for increasing the train frequency of each route is to increase the train frequency based on the current train operation plan, which can avoid changing the train operation routes.

[0102] Therefore, when the passenger flow scheduling period is the current midday period, by increasing the configuration of train operation frequency for each route and the intensity of flow restriction at each first-limit station, it is possible to ensure that the capacity supply in the first scheduling cycle matches the passenger flow demand and avoid changing the train operation routes.

[0103] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the capacity data includes: a first preset maximum cross-sectional load factor, a preset maximum train frequency on the line, a preset maximum number of trains on the line, a total number of stations on the line, an entry gate throughput capacity index, a platform capacity index, and a maximum transport capacity index for each section; the first passenger flow data includes: the maximum cross-sectional passenger flow for each section;

[0104] The first capacity allocation constraints include: maximum cross-sectional load factor constraints, section train frequency constraints, route train frequency constraints, maximum train frequency constraints, and number of vehicles in use constraints.

[0105] The maximum cross-sectional load factor constraint condition is used to constrain the maximum cross-sectional load factor of the section to be less than or equal to the first preset maximum cross-sectional load factor.

[0106] The train frequency constraint condition for each section is used to constrain the relationship between the train frequency of each section and the maximum cross-sectional passenger flow of each section.

[0107] The aforementioned train frequency constraint is used to constrain the relationship between the train frequency of a section and the train frequency of the section.

[0108] The maximum train frequency constraint is used to constrain the relationship between the train frequency of the section route and the preset maximum train frequency of the line.

[0109] The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route.

[0110] The first flow restriction constraints include: flow restriction intensity constraints, flow restriction station number constraints, station capacity constraints, and interval transport capacity constraints;

[0111] The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength;

[0112] The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line;

[0113] The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index.

[0114] The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

[0115] Specifically, when the passenger flow scheduling period is the current midday period, under the constraints of the maximum cross-sectional full load rate, the section train frequency, the route train frequency, the maximum train frequency, and the number of vehicles in use, the train frequency of each route can be determined by solving the first capacity allocation objective function. Then, based on the capacity data and the train frequency of each route, the configuration of increasing the train frequency of each route can be determined.

[0116] Specifically, when the passenger flow scheduling period is the current midday period, the first set of stations subject to flow restriction and the flow restriction intensity of each station can be determined by solving the first flow restriction objective function under constraints such as flow restriction intensity, number of stations subject to flow restriction, station capacity, and section transport capacity. The area between adjacent stations is considered a section, and the line can be divided into different sections according to the current route configuration; a section can include multiple sections.

[0117] Optionally, the objective function for the first capacity allocation takes minimizing the train travel distance Z1 as the optimization objective, and the objective function for the first capacity allocation can be expressed by the following formula:

[0118] MinZ1=2·∑f j ·L j j = 1, 2, 3…j max ;

[0119] The first constraint on capacity allocation may include: the maximum cross-sectional load factor constraint, the section train frequency constraint, the route train frequency constraint, the maximum train frequency constraint, and the number of vehicles in use constraint.

[0120] The first preset maximum cross-sectional load factor can be 100%, and the maximum cross-sectional load factor constraint can be expressed by the following formula:

[0121]

[0122]

[0123] The frequency of trains operating in each section should be able to guarantee the passenger flow demand of that section. The constraint on the frequency of trains operating in a section can be expressed by the following formula:

[0124]

[0125] The sum of the operating frequencies of all sections should meet the operating frequency requirements of that section. The operating frequency constraint of the train routes can be expressed by the following formula:

[0126] ∑x ij ·f j ≥D i j = 1, 2, 3…j max ;

[0127] The train frequency for each section cannot exceed the section's capacity. The maximum train frequency constraint can be expressed by the following formula:

[0128] ∑x ij ·f j ≤f mj = 1, 2, 3…j max ;

[0129] The total number of vehicles used on all routes cannot exceed the number of available vehicles. The constraint on the number of vehicles used can be expressed by the following formula:

[0130] Z 运用 ≤Z 可用 ;

[0131] Z 运用 =∑f j ·n,j=1,2,3…j max ;

[0132] The decision variable for the primary capacity allocation objective function can be the train frequency f on each route. j ;

[0133] Among them, f j Let j be the train frequency for route j. max Indicates the total number of routes; L j P is the length of intersection j; i,max Let i be the maximum cross-sectional passenger flow of segment i. max Indicates the total number of segments; C 定员 n represents the passenger capacity per train formation; n represents the number of cars in the train formation; x represents the passenger capacity per train formation. ij The relationship between intersection j and segment i is defined as follows: if intersection j includes segment i, the value is 1; otherwise, it is 0. i f is the train frequency for segment i; m The maximum train frequency for the preset line is subject to capacity limitations; Z 运用 Z represents the total number of vehicles used across all routes. 可用 This is the preset maximum number of vehicles for a route (the number of vehicles available for the route).

[0134] Understandably, heuristic algorithms such as genetic algorithms can be used to solve the above-mentioned first transportation capacity allocation objective function.

[0135] Optionally, the first flow restriction objective function takes the maximum inbound passenger flow Z1 and the minimum flow restriction intensity variance Z2 of the set of flow-restricted stations within the first scheduling period as its optimization objectives. The first flow restriction objective function can be expressed by the following formula:

[0136]

[0137]

[0138] The first flow restriction constraint may include: flow restriction intensity constraint, flow restriction number of stations constraint, station capacity constraint, and interval transport capacity constraint.

[0139] To ensure the service level of the station, the flow restriction intensity cannot be too high or too low. The constraint condition of the flow restriction intensity can be expressed by the following formula:

[0140]

[0141] The constraint on the number of stations implementing flow control measures is that the number of stations implementing flow control measures should not be too large, and the number of stations with flow control measures should not exceed 20% of the total number of stations on the line. This constraint can be expressed by the following formula:

[0142]

[0143]

[0144] The station capacity constraint, which states that the passenger flow entering the station cannot exceed the throughput capacity of the entrance gates and the platform capacity, can be expressed by the following formula:

[0145]

[0146]

[0147] The constraint on the transport capacity of a section, namely that the passenger flow through any section should not exceed the maximum transport capacity of that section, firstly requires determining whether each traffic origin-destination (OD) in the inbound traffic passes through section dm. The OD volumes passing through section dm are then accumulated to determine the station's passenger flow contribution to section dm. The ratio of this passenger flow contribution to the station's inbound traffic is the station's passenger flow contribution rate to section dm. The maximum transport capacity of the section is then considered. The constraints on the transport capacity of a section, which are related to the frequency of train operations, the number of cars in a train formation, and the train's passenger capacity, can be expressed by the following formula:

[0148]

[0149]

[0150]

[0151]

[0152]

[0153] The decision variable of the first flow restriction objective function can be the set of flow-restricted stations, s of each flow-restricted station. i Current limiting intensity

[0154] Where T is the scheduling period; t iFor each flow restriction period (e.g., 15 minutes), if the passenger flow scheduling period is during the current midday period, T can include only one t. i S represents the set of stations; DM represents the set of cross-sections. S after rate limiting i Standing at t i Passenger flow entering the station during a specific time period; For S i Standing at t i Demand for station entry volume during a specific time period; CR aver N is the average of the rate limiting intensity across all sites. S n is the total number of stations on the line. Si For S i A 0-1 variable indicating whether the station will implement traffic control measures; For S i Standing at t i The throughput capacity of the entrance gates during a specific time period; For S i Standing at t i The platform's capacity during different time periods; For S i The contribution of station entry passenger flow to the up-direction section dm is determined by whether each OD in the entry flow passes through section dm and the ODs that pass through the up-direction section dm are accumulated. For S i The contribution of station entry passenger flow to the downstream cross-section dm; For S i The contribution rate of station entry passenger flow to the upstream cross-section dm, that is, the ratio of the contribution to the station entry passenger flow. For S i The contribution rate of station entry passenger flow to the downstream cross-section dm; For t i Within a given time interval, the transport capacity of dm; The train frequency for the line to which section dm belongs; n is the number of cars in the train formation; C 定员 The number of passengers is set for each train set.

[0155] Understandably, the first current-limiting objective function mentioned above can be solved using machine learning algorithms such as reinforcement learning.

[0156] Therefore, when the passenger flow scheduling period is the current midday period, under the constraints of the first capacity allocation constraint and the first flow restriction constraint, by determining the increased configuration of train operation frequency for each route and the flow restriction intensity of each first flow restriction station, it is possible to ensure that the capacity supply of the first scheduling cycle matches the passenger flow demand and avoid changing the train operation routes.

[0157] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, before solving the first flow restriction objective function based on the first flow restriction constraint, the capacity data, and the first passenger flow data, and determining the first set of flow restriction stations and the flow restriction intensity of each first flow restriction station, the method further includes:

[0158] The train frequency configuration for each route has been increased, and the maximum transport capacity indicators for each section have been updated.

[0159] Specifically, in order to make the first flow restriction scheme compatible with the train frequency increase scheme, after determining the train frequency increase configuration for each route, the maximum transport capacity index of each section can be updated based on the train frequency increase configuration for each route. Then, under the constraints of flow restriction intensity constraints, flow restriction station number constraints, station capacity constraints, and updated section transport capacity constraints, the first flow restriction objective function can be solved to determine the first flow restriction station set and the flow restriction intensity of each first flow restriction station.

[0160] For example, if the original frequency was 4 pairs of trains per 15 minutes, with 6 train sets and a capacity of 240 passengers per car, then the maximum transport capacity of the section was 4 × 6 × 240 = 5760 passengers per 15 minutes. After updating the maximum transport capacity of each section based on the increased train frequency of each route, the capacity can be increased to 5 pairs of trains per 15 minutes. Therefore, when solving the first flow restriction objective function, the maximum transport capacity of the section is 7200 passengers per 15 minutes.

[0161] Therefore, by increasing the configuration of train operating frequencies based on each route and updating the maximum transport capacity indicators of each section, the first flow restriction scheme can be adapted to the train operating frequency increase scheme, thereby improving the passenger flow scheduling effect of the first flow restriction scheme.

[0162] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, the at least one second capacity optimization sub-model includes the following sub-models: single route operation scheme optimization sub-model, large and small route operation scheme optimization sub-model, and connecting route operation scheme optimization sub-model;

[0163] The second capacity optimization sub-model includes a second capacity allocation objective function and a second capacity allocation constraint condition;

[0164] The second capacity allocation objective function of the single-route operation scheme optimization sub-model uses the single-route train operation frequency as the decision variable and the minimum passenger waiting time and the minimum train travel distance as the optimization objectives.

[0165] The second capacity allocation objective function of the optimization sub-model of the large and small route operation scheme takes the small route train frequency, the first ratio, the first small route turnaround station and the second small route turnaround station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives. The first ratio is the ratio between the large route train frequency and the small route train frequency.

[0166] The second capacity allocation objective function of the optimization sub-model of the connecting route operation scheme takes the train operation frequency of the first route, the train operation frequency of the second route, and the connecting station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives.

[0167] The second flow restriction optimization sub-model includes: a second flow restriction objective function and a second flow restriction constraint. The second flow restriction objective function uses the set of flow-restricted stations and the flow restriction intensity of each flow-restricted station as decision variables, and takes the maximum passenger flow entering the station and the minimum variance of the flow restriction intensity of the set of flow-restricted stations within the second scheduling cycle as optimization objectives.

[0168] Specifically, when the passenger flow scheduling period is during the midday period of the following day, multiple operation schemes can be determined by solving the second capacity allocation objective function of the single route operation scheme optimization sub-model, the second capacity allocation objective function of the large and small route operation scheme optimization sub-model, and the second capacity allocation objective function of the connecting route operation scheme optimization sub-model. By solving the second flow restriction objective function, the second flow restriction scheme can be determined. Multiple operation schemes and the second flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply and passenger flow demand in the second scheduling cycle are matched. Moreover, the train operation routes of the following days can be changed, and multiple operation schemes can be used to change the train operation routes of the following days to meet the capacity supply.

[0169] Therefore, when the passenger flow scheduling period is during the midday period of the following day, by determining the second flow restriction plan and multiple operation plans, it is possible to ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand, and to change the train operation routes of the following day to meet the capacity supply.

[0170] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the at least one operation scheme includes: a single route operation scheme, a combined long and short route operation scheme, and a connecting route operation scheme; the second flow restriction scheme includes: a third flow restriction scheme for each flow restriction period, the third flow restriction scheme including a set of second flow restriction stations and the flow restriction intensity of each second flow restriction station, wherein the flow restriction period is a period in the second scheduling cycle;

[0171] The second optimization model is solved based on capacity data and second passenger flow data of the second scheduling period to determine the second flow restriction scheme and at least one operation scheme for the second scheduling period, including:

[0172] Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the single route operation scheme optimization sub-model, the second capacity allocation objective function of the single route operation scheme optimization sub-model is solved to determine the single route operation scheme.

[0173] Based on the transport capacity data, the second passenger flow data, and the second transport capacity allocation constraints of the optimized sub-model of the large and small route operation scheme, the second transport capacity allocation objective function of the optimized sub-model of the large and small route operation scheme is solved to determine the large and small route operation scheme;

[0174] Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the connecting route operation scheme optimization sub-model, the second capacity allocation objective function of the connecting route operation scheme optimization sub-model is solved to determine the connecting route operation scheme.

[0175] Based on the second flow restriction constraint, the capacity data, and the second passenger flow data, the second flow restriction objective function is solved to determine the third flow restriction scheme for each flow restriction period.

[0176] Specifically, when the passenger flow scheduling period is during the midday period of the following day, by solving the second capacity allocation objective function of the single route operation scheme optimization sub-model, the large and small route operation scheme optimization sub-model, and the connecting route operation scheme optimization sub-model, the single route operation scheme, the large and small route operation scheme, and the connecting route operation scheme can be determined. By solving the second flow restriction objective function, the third flow restriction scheme for each flow restriction period can be determined. Multiple operation schemes (including single route operation scheme, large and small route operation scheme, and connecting route operation scheme) and the second flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply and passenger flow demand in the second scheduling cycle are matched. Moreover, the train operation routes of the following day can be changed, and multiple operation schemes can be used to change the train operation routes of the following day to meet the capacity supply.

[0177] Understandably, the determination of whether to implement major / minor routes and connecting routes depends on whether the line has the capability to operate such routes. At least one operating plan includes: single route operation plan, major / minor route operation plan, and connecting route operation plan, which can be understood as the line's specific capability to operate major / minor routes and connecting routes.

[0178] Therefore, when the passenger flow scheduling period is during the midday period of the following day, by determining the second flow restriction plan and multiple operation plans (including single route operation plan, large and small route operation plan and connecting route operation plan), it is possible to ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand, and to change the train operation routes of the following day to meet the capacity supply.

[0179] Optionally, according to a rail transit passenger flow scheduling method provided by the present invention, the capacity data includes: the preset minimum train frequency of the line, the preset maximum train frequency of the line, the preset maximum number of trains used on the line, the second preset maximum cross-section full load rate, the total number of stations on the line, the entry gate throughput capacity index, the platform capacity index, and the maximum transport capacity index of each section.

[0180] The second capacity allocation constraints include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints.

[0181] The minimum train frequency constraint is used to constrain the relationship between the train frequency of the route and the preset minimum train frequency of the line.

[0182] The maximum train frequency constraint is used to constrain the relationship between the train frequency of the route and the maximum train frequency of the preset line.

[0183] The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route.

[0184] The maximum cross-section full load rate constraint condition is used to constrain the maximum cross-section full load rate of the line to be less than or equal to the second preset maximum cross-section full load rate.

[0185] The second flow restriction constraint conditions include: flow restriction intensity constraint conditions, flow restriction station number constraint conditions, station capacity constraint conditions, and interval transport capacity constraint conditions;

[0186] The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength;

[0187] The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line;

[0188] The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index.

[0189] The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

[0190] Specifically, when the passenger flow scheduling period falls within the subsequent midday hours, under constraints such as minimum train frequency, maximum train frequency, number of operating vehicles, and maximum cross-sectional load factor, the single-route operation scheme, the large-small-small-routes operation scheme, and the connecting-route operation scheme optimization sub-model can be determined by solving the second capacity allocation objective function of each sub-model.

[0191] Specifically, when the passenger flow scheduling period is during the midday period of the following day, under the constraints of the flow restriction intensity, the number of stations with flow restriction, the station capacity, and the section transport capacity, the third flow restriction scheme for each flow restriction period can be determined by solving the second flow restriction objective function. Multiple operation schemes (including single route operation schemes, large and small route operation schemes, and connecting route operation schemes) and the second flow restriction scheme can be used to allocate transport capacity and restrict passenger flow to ensure that the transport capacity supply in the second scheduling cycle matches the passenger flow demand. Furthermore, the train operation routes of the following days can be changed, and multiple operation schemes can be used to change the train operation routes of the following days to meet the transport capacity supply.

[0192] Optionally, the second capacity allocation objective function of the single-route operation scheme optimization sub-model can take minimizing passenger waiting time Z1 and train travel distance Z2 as optimization objectives, which can be expressed by the following formula:

[0193]

[0194] MinZ2=2·L 1N ·f1·n;

[0195] MinM1=w1·Z1+w2·Z2;

[0196] The second capacity allocation constraints of the single-route operation scheme optimization sub-model may include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints.

[0197] Minimum train frequency constraints: To ensure a high level of service, the maximum headway for urban rail trains should not be too large; generally, the preset minimum train frequency f for the line is taken. min The minimum train frequency constraint, which is 10 pairs / hour, can be expressed by the following formula:

[0198] f1≥f min ;

[0199] The maximum train frequency constraint, which is subject to the minimum train headway and the turnaround capacity of the turnaround station, stipulates that the maximum frequency should not exceed the preset maximum train frequency f for the line. max (For example, 30 pairs / hour), the maximum train frequency constraint can be expressed by the following formula:

[0200] f1≤f max ;

[0201] The constraint on the number of vehicles used, namely that the number of vehicles used in the train operation plan cannot exceed the preset maximum number of vehicles used on the line (the number of available vehicles), can be expressed by the following formula:

[0202] Z 运用 ≤Z 可用 ;

[0203]

[0204]

[0205] The maximum cross-sectional load factor constraint condition, i.e., the cross-sectional load factor cannot be too large, the second preset maximum cross-sectional load factor can be 120%, and the maximum cross-sectional load factor constraint condition can be expressed by the following formula:

[0206] γ max ≤120%;

[0207]

[0208]

[0209]

[0210] The objective function for the second capacity allocation of the single-route operation scheme optimization sub-model can use the train frequency f1 as a decision variable.

[0211] Among them, T k The second scheduling cycle (e.g., 1 hour); f1 is the train frequency for a single route; Q is the total passenger flow entering the station on this line; Q in To bring in passenger traffic to other lines; L 1N The total length of the entire line is n; the number of cars in the train formation is n; w1 and w2 are the weights of the objective function; f min The minimum train frequency for the preset line; f max Z is the preset maximum train frequency for the line; 运用 Z represents the number of vehicles used in the capacity allocation plan. 可用 T1 represents the maximum number of trains that can be used on the preset line; T1 represents the turnaround time for a single route; N represents the total number of stations on the line; R iS represents the train travel time in interval i; j t represents the train's dwell time at station j; 折 γ represents the turnaround time of the train at the turnaround station. max This represents the maximum cross-sectional load factor. Let i be the load factor of section i in the upward direction; Let i be the load factor of section i in the upward direction; The passenger flow at section i in the upward direction; C represents the passenger flow at section i in the downhill direction; 定员 The number of passengers is set for each train set.

[0212] Optionally, the second capacity allocation objective function of the sub-model for optimizing the operation of both long and short routes can be optimized by minimizing passenger waiting time Z1 and train travel distance Z2, which can be expressed by the following formula:

[0213]

[0214] MinZ2=2·L 1N ·f1·n+2·L ab ·f2·n;

[0215] MinM1=w1·Z1+w2·Z2;

[0216] The second capacity allocation constraints of the sub-model for optimizing the operation scheme of large and small routes may include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints.

[0217] The ratio m of the operating frequencies of long-distance trains to short-distance trains is a positive integer, and m can be a positive integer from 1 to 3. The relationship between the operating frequencies of long-distance trains and short-distance trains can be expressed by the following formula:

[0218] m = 1 or 2 or 3;

[0219] f1 = m·f2;

[0220] Minimum train frequency constraints: To ensure a high level of service, the maximum headway for urban rail trains should not be too large; generally, the preset minimum train frequency f for the line is taken. min The minimum train frequency constraint, which is 10 pairs / hour, can be expressed by the following formula:

[0221] f1≥f min ;

[0222] The maximum train frequency constraint, which is subject to the minimum train headway and the turnaround capacity of the turnaround station, stipulates that the maximum frequency should not exceed the preset maximum train frequency f for the line. max(For example, 30 pairs / hour), the maximum train frequency constraint can be expressed by the following formula:

[0223] (f1+f2)≤f max ;

[0224] The constraint on the number of vehicles used, namely that the number of vehicles used in the train operation plan cannot exceed the preset maximum number of vehicles used on the line (the number of available vehicles), can be expressed by the following formula:

[0225] Z 运用 ≤Z 可用 ;

[0226]

[0227]

[0228]

[0229] The maximum cross-sectional load factor constraint condition, i.e., the cross-sectional load factor cannot be too large, the second preset maximum cross-sectional load factor can be 120%, and the maximum cross-sectional load factor constraint condition can be expressed by the following formula:

[0230] γ max ≤120%;

[0231]

[0232]

[0233]

[0234] The objective function of the second capacity allocation in the sub-model for optimizing the operation of short-route and long-route trains can take the train frequency f2, the first ratio m, the first short-route turnaround station a, and the second short-route turnaround station b as decision variables;

[0235] Among them, T k For the second scheduling cycle (e.g., 1 hour), f1 is the train frequency of the long route; f2 is the train frequency of the short route; the line can be divided into different sections according to the route pattern. Q1 is the passenger flow whose origin or destination is in the non-overlapping section of the long and short routes, that is, the passenger flow taking the long route train; Q2 is the passenger flow whose origin and destination are both in the short route section, that is, passengers who can take either the long or short route train. For passengers whose origin or destination is in a non-overlapping section of the major and minor routes, the passenger flow is transferred to other lines; This refers to passenger traffic originating and terminating in short-distance routes that are being transferred to other lines; L 1N L represents the total length of the entire line. abT1 is the total length of the short-route train; T2 is the turnaround time of the long-route train; n is the number of cars in the train; w1 and w2 are the weights of the objective function; f min The minimum train frequency for the preset line; f max Z is the preset maximum train frequency for the line; 运用 Z represents the number of vehicles used in the capacity allocation plan. 可用 R represents the maximum number of vehicles that can be used on the preset line; N represents the total number of stations on the line; R represents the maximum number of vehicles that can be used on the preset line. i S represents the train travel time in interval i; j t represents the train's dwell time at station j; 折 γ represents the turnaround time of the train at the turnaround station. max This represents the maximum cross-sectional load factor. Let i be the load factor of section i in the upward direction; Let i be the load factor of section i in the upward direction; The passenger flow at section i in the upward direction; C represents the passenger flow at section i in the downhill direction; 定员 The number of passengers is set for each train set.

[0236] Optionally, the second capacity allocation objective function of the connecting route operation scheme optimization sub-model can take minimizing passenger waiting time Z1 and train travel distance Z2 as optimization objectives, which can be expressed by the following formula:

[0237]

[0238] MinZ2=2·L 1c ·f1·n+2·L cN ·f2·n;

[0239] MinM1=w1·Z1+w2·Z2;

[0240] The second capacity allocation constraints of the sub-model for optimizing the operation plan of connecting routes may include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints.

[0241] Minimum train frequency constraints: To ensure a high level of service, the maximum headway for urban rail trains should not be too large; generally, the preset minimum train frequency f for the line is taken. min The minimum train frequency constraint, which is 10 pairs / hour, can be expressed by the following formula:

[0242] f1≥f min ;

[0243] f2≥f min ;

[0244] The maximum train frequency constraint, which is subject to the minimum train headway and the turnaround capacity of the turnaround station, stipulates that the maximum frequency should not exceed the preset maximum train frequency f for the line. max (For example, 30 pairs / hour), the maximum train frequency constraint can be expressed by the following formula:

[0245] f1≤f max ;

[0246] f2≤f max ;

[0247] The constraint on the number of vehicles used, namely that the number of vehicles used in the train operation plan cannot exceed the preset maximum number of vehicles used on the line (the number of available vehicles), can be expressed by the following formula:

[0248] Z 运用 ≤Z 可用 ;

[0249]

[0250]

[0251]

[0252] The maximum cross-sectional load factor constraint condition, i.e., the cross-sectional load factor cannot be too large, the second preset maximum cross-sectional load factor can be 120%, and the maximum cross-sectional load factor constraint condition can be expressed by the following formula:

[0253] γ max ≤120%;

[0254]

[0255]

[0256]

[0257] The objective function of the second capacity allocation in the sub-model for optimizing the operation plan of connecting routes can take the train frequency f1 of the first route, the train frequency f2 of the second route, and the connecting station c as decision variables;

[0258] Among them, T k For the second scheduling cycle (e.g., 1 hour), f1 is the train frequency of the first route; f2 is the train frequency of the second route; Q1 is the passenger flow with both origin and destination on the first route, i.e., the passenger flow taking the trains on the first route; Q2 is the passenger flow with both origin and destination on the second route, i.e., the passenger flow taking the trains on the second route; Q3 is the passenger flow with origin and destination not on the same route. This is to transfer passenger traffic from other lines where the origin and destination are both on the first route; This is to transfer passenger traffic from other lines where both the origin and destination are on the second route; For passengers whose origin and destination are not on the same route, transfer them to another line; L 1c L is the total length of the first intersection route; cN T1 is the total length of the second route; T2 is the turnaround time of the first route; T3 is the turnaround time of the second route; n is the number of cars in the train; w1 and w2 are the weights of the objective function; f min The minimum train frequency for the preset line; f max Z is the preset maximum train frequency for the line; 运用 Z represents the number of vehicles used in the capacity allocation plan. 可用 R represents the maximum number of vehicles that can be used on the preset line; N represents the total number of stations on the line; R represents the maximum number of vehicles that can be used on the preset line. i S represents the train travel time in interval i; j t represents the train's dwell time at station j; 折 γ represents the turnaround time of the train at the turnaround station. max This represents the maximum cross-sectional load factor. Let i be the load factor of section i in the upward direction; Let i be the load factor of section i in the upward direction; The passenger flow at section i in the upward direction; C represents the passenger flow at section i in the downhill direction; 定员 The number of passengers is set for each train set.

[0259] It is understandable that heuristic algorithms such as genetic algorithms can be used to solve the above-mentioned second transportation capacity allocation objective function.

[0260] Optionally, the second flow restriction objective function takes the maximum inbound passenger flow Z1 and the minimum flow restriction intensity variance Z2 of the set of restricted stations within the second scheduling cycle as its optimization objectives. The second flow restriction objective function can be expressed by the following formula:

[0261]

[0262]

[0263] The second flow restriction constraint may include: flow restriction intensity constraint, flow restriction station number constraint, station capacity constraint, and interval transport capacity constraint;

[0264] To ensure the service level of the station, the flow restriction intensity cannot be too high or too low. The constraint condition of the flow restriction intensity can be expressed by the following formula:

[0265]

[0266] The constraint on the number of stations implementing flow control measures is that the number of stations implementing flow control measures should not be too large, and the number of stations with flow control measures should not exceed 20% of the total number of stations on the line. This constraint can be expressed by the following formula:

[0267]

[0268]

[0269] The station capacity constraint, which states that the passenger flow entering the station cannot exceed the throughput capacity of the entrance gates and the platform capacity, can be expressed by the following formula:

[0270]

[0271]

[0272] The constraint on the transport capacity of a section is that the passenger flow through any section should not exceed the maximum transport capacity of that section. First, it is necessary to determine whether each originating point (OD) in the inbound traffic passes through section dm. The ODs that pass through section dm are accumulated to determine the station's passenger flow contribution to section dm. The ratio of this contribution to the station's inbound traffic is the station's passenger flow contribution rate to section dm. The maximum transport capacity of the section is then considered. The constraints on the transport capacity of a section, which are related to the frequency of train operations, the number of cars in a train formation, and the train's passenger capacity, can be expressed by the following formula:

[0273]

[0274]

[0275]

[0276]

[0277]

[0278] The decision variable for the second flow restriction objective function can be the set of flow-restricted stations, s of each flow-restricted station. i Current limiting intensity

[0279] Where T is the scheduling period (e.g., 1 hour) t i For each flow restriction period (e.g., 15 minutes), if the passenger flow scheduling period is a subsequent midday period, T can include multiple t. i (For example, if T is 1 hour and the flow restriction period is 15 minutes, then T can include 4 t's.) i S represents the set of stations; DM represents the set of cross-sections. S after rate limitingi Standing at t i Passenger flow entering the station during a specific time period; For S i Standing at t i Demand for station entry volume during a specific time period; CR aver N is the average of the rate limiting intensity across all sites. S n is the total number of stations on the line. Si For S i A 0-1 variable indicating whether the station will implement traffic control measures; For S i Standing at t i The throughput capacity of the entrance gates during a specific time period; For S i Standing at t i The platform's capacity during different time periods; For S i The contribution of station entry passenger flow to the up-direction section dm is determined by whether each OD in the entry flow passes through section dm and the ODs that pass through the up-direction section dm are accumulated. For S i The contribution of station entry passenger flow to the downstream cross-section dm; For S i The contribution rate of station entry passenger flow to the upstream cross-section dm, that is, the ratio of the contribution to the station entry passenger flow. For S i The contribution rate of station entry passenger flow to the downstream cross-section dm; For t i Within a given time interval, the transport capacity of dm; The train frequency for the line to which section dm belongs; n is the number of cars in the train formation; C 定员 The number of passengers is set for each train set.

[0280] Understandably, the second current-limiting objective function mentioned above can be solved using machine learning algorithms such as reinforcement learning.

[0281] Therefore, when the passenger flow scheduling period is during the midday period of the following day, under the constraints of the second capacity allocation condition and the second flow restriction condition, by determining the second flow restriction scheme and multiple operation schemes (including single route operation scheme, large and small route operation scheme and connecting route operation scheme), it is possible to ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand, and to change the train operation routes of the following day to meet the capacity supply.

[0282] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, before solving the second flow restriction objective function based on the second flow restriction constraint, the capacity data, and the second passenger flow data, and determining the third flow restriction scheme for each flow restriction period, the method further includes:

[0283] Based on preset evaluation indicators, the single route operation plan, the large and small route operation plan, and the connecting route operation plan are evaluated to obtain the first evaluation result of each operation plan;

[0284] Based on the first evaluation results of each operation plan, one of the following operation plans is determined as the target operation plan: the single route operation plan, the large and small route operation plan, and the connecting route operation plan.

[0285] Based on the target train operation plan, update the maximum transport capacity index for each section.

[0286] Specifically, in order to ensure that the third traffic restriction scheme is compatible with the operation scheme, after determining the single-route operation scheme, the large-small-small-routes operation scheme, and the connecting-route operation scheme, the single-route operation scheme, the large-small-small-routes operation scheme, and the connecting-route operation scheme can be evaluated based on preset evaluation indicators to obtain the first evaluation result of each operation scheme. Then, based on the first evaluation result of each operation scheme, the target operation scheme can be determined, and then based on the target operation scheme, the maximum transport capacity indicator of each section can be updated.

[0287] Optionally, the first evaluation result may include the score of the operation plan, and the target operation plan may be determined based on the score of each operation plan. The target operation plan may be the one with the highest score among multiple operation plans.

[0288] Specifically, after updating the maximum transport capacity index of each section, the second flow restriction scheme can be determined by solving the second flow restriction objective function under the constraints of flow restriction intensity, flow restriction station number, station capacity, and updated section transport capacity. The second flow restriction scheme includes the third flow restriction scheme for each flow restriction period. The third flow restriction scheme includes the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station. The flow restriction period is the time period in the second scheduling cycle.

[0289] Therefore, by updating the maximum transport capacity index of each section based on the target operation plan, the second flow restriction plan can be adapted to the target operation plan, thereby improving the passenger flow scheduling effect of the second flow restriction plan.

[0290] Optionally, according to the rail transit passenger flow scheduling method provided by the present invention, when the passenger flow scheduling period is the current midday period, after solving the first optimization model based on the capacity data and the first passenger flow data of the first scheduling period to determine the train frequency increase scheme and the first flow restriction scheme of the first scheduling period, the method further includes:

[0291] Based on preset evaluation indicators, the train frequency increase scheme and the first flow restriction scheme are evaluated to obtain a second evaluation result.

[0292] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, after solving the second optimization model based on the capacity data and the second passenger flow data of the second scheduling cycle to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle, the method further includes:

[0293] Based on the preset evaluation indicators, the second flow restriction scheme and the at least one operation scheme are evaluated to obtain a third evaluation result.

[0294] Specifically, when the passenger flow scheduling period is the current midday period, the train frequency increase plan and the first flow restriction plan can be evaluated based on preset evaluation indicators to obtain a second evaluation result. The second evaluation result can provide a reference for the dispatchers, so that the dispatchers can select the train frequency increase plan and / or the first flow restriction plan for passenger flow scheduling based on the second evaluation result.

[0295] Optionally, a first combined scheme can be determined based on the train frequency increase scheme and the first flow restriction scheme. The evaluation of the train frequency increase scheme and the first flow restriction scheme can include the evaluation of the first combined scheme. Correspondingly, the second evaluation result can include the evaluation result of the first combined scheme.

[0296] Specifically, when the passenger flow scheduling task is for the subsequent midday period, the second flow restriction plan and at least one operation plan can be evaluated based on preset evaluation indicators to obtain a third evaluation result. The third evaluation result can provide a reference for the dispatchers, making it convenient for them to select one or more plans from the second flow restriction plan and at least one operation plan for passenger flow scheduling.

[0297] Optionally, a second combined scheme can be determined based on the second flow restriction scheme and a train operation scheme (such as the target train operation scheme mentioned above). Evaluating the second flow restriction scheme and at least one train operation scheme may include evaluating the second combined scheme. Accordingly, the third evaluation result may include the evaluation result of the second combined scheme.

[0298] Therefore, after determining one or more passenger flow scheduling schemes, the passenger flow scheduling schemes can be evaluated based on preset evaluation indicators to obtain evaluation results. The evaluation results can provide a reference for dispatchers, making it easier for them to select appropriate scheduling schemes based on the evaluation results.

[0299] Optionally, Figure 2 This is the second flowchart of the rail transit passenger flow scheduling method provided by the present invention, as shown below. Figure 2As shown, the method includes steps 201 to 203.

[0300] Step 201: Obtain the data required to solve the optimization model.

[0301] Specifically, the data required to solve the optimization model can include passenger flow data and transportation capacity data.

[0302] For example, if the passenger flow scheduling period is during the current midday period, the data required to solve the first optimization model may include capacity data and first passenger flow data for the first scheduling cycle, which may be 15 minutes. The first passenger flow data may include passenger OD data, cross-sectional passenger flow, demand for entry, and passenger arrival rate. Capacity data may include: train operation data (e.g., the departure interval of the current operation plan), vehicle data, the preset maximum number of vehicles on the line (the number of available trains), and operational capacity limit data. Vehicle data may include the number of cars in a train formation and the number of passengers per vehicle, while operational capacity limit data may include: the preset maximum train frequency on the line and the first preset maximum cross-sectional load factor.

[0303] For example, when the passenger flow scheduling period is during the subsequent midday hours, the data required to solve the second optimization model can include capacity data and second passenger flow data for the second scheduling cycle, where the first scheduling cycle can be 1 hour. The second passenger flow data can include passenger flow origin-destination (OD) data, cross-sectional passenger flow, and demand for station entry, etc. Capacity data can include: train operation data, vehicle data, the preset maximum number of trains on the line (number of available trains), and operational capacity limit data. Train operation data can include interval running time, stop time, and turnaround time; vehicle data can include the number of cars in a train formation and the number of passengers per car, etc.; and operational capacity limit data can include: the preset maximum train frequency on the line, the preset minimum train frequency on the line, and the second preset maximum cross-sectional load factor, etc.

[0304] Step 202: Solve the first optimization model to obtain the train frequency increase scheme and the first flow restriction scheme; or solve the second optimization model to obtain the second flow restriction scheme and at least one train operation scheme.

[0305] Optionally, such as Figure 2 As shown, the first combined scheme may include a train frequency increase scheme obtained by the first optimization model and a first flow restriction scheme, and the second combined scheme may include a train operation scheme and a second flow restriction scheme.

[0306] Step 203: Based on preset evaluation indicators, evaluate the train frequency increase scheme, the first flow restriction scheme, and the first combination scheme to obtain a second evaluation result; or, based on preset evaluation indicators, evaluate the second flow restriction scheme and at least one operation scheme and the second combination scheme to obtain a third evaluation result.

[0307] Optionally, the preset evaluation indicators may include: passenger waiting time, train travel distance, number of vehicles in use, maximum cross-sectional load factor and average cross-sectional load factor. These indicators can be used to evaluate the train frequency increase plan and at least one other operation plan.

[0308] Optionally, the preset evaluation indicators may include: the number of people subject to flow restriction, the number of stations subject to flow restriction, the maximum cross-sectional full load rate, and the average cross-sectional full load rate. These indicators can be used to evaluate the first flow restriction scheme and the second flow restriction scheme.

[0309] Optionally, the preset evaluation indicators may include: train travel kilometers, number of vehicles in use, maximum cross-sectional load factor, average cross-sectional load factor, number of passengers subject to flow restriction, and number of stations subject to flow restriction. These indicators can be used to evaluate the first combination scheme and the second combination scheme.

[0310] Optionally, Figure 3 This is a schematic diagram of the first optimization model provided by the present invention, as shown below. Figure 3 As shown, the first optimization model may include a first capacity optimization sub-model and a first flow restriction optimization sub-model; the first capacity optimization sub-model may include a first capacity allocation objective function and a first capacity allocation constraint, the first capacity allocation constraint may include a maximum cross-sectional full load rate constraint, a section train frequency constraint, a route train frequency constraint, a maximum train frequency constraint, and a number of operating vehicles constraint; the first flow restriction optimization sub-model may include a first flow restriction objective function and a first flow restriction constraint, the first flow restriction constraint may include a flow restriction intensity constraint, a flow restriction station number constraint, a station capacity constraint, and a section transport capacity constraint.

[0311] Optionally, such as Figure 3 As shown, by solving the objective function of the first capacity allocation, a train frequency increase plan can be obtained. This plan includes the frequency increase configuration for each route and the time slots for adding trains. The first scheduling cycle can be divided into several time slots, with the time slot with the highest passenger flow designated as the time slot for adding trains.

[0312] For example, if the line operates both long and short routes, with routes 1 and 2 both operating at a frequency of 3 pairs / 15 minutes, the line can be divided into two sections based on the coverage area of ​​each route. Figure 4 This is a schematic diagram of the train frequency increase scheme provided by the present invention, as shown below. Figure 4As shown, section 1 is only covered by route 1, while section 2 is covered by both routes 1 and 2. Based on the maximum cross-sectional passenger flow of each section, the required operating frequency for section 1 is 3 pairs / 15min, and the required operating frequency for section 2 is 7 pairs / 15min. To ensure the capacity demand of each section and minimize train travel distance, the required operating frequency for route 1 is 3 pairs / 15min, and for route 2 it is 4 pairs / 15min. Therefore, one additional pair of trains should be added to route 2. The train frequency increase plan is shown in Table 1, including the original line operation plan, the train frequency increase configuration, and evaluation indicators.

[0313] Table 1. Configuration Table for Increased Train Frequency

[0314]

[0315] Optionally, such as Figure 3 As shown, by solving the first flow restriction objective function, the first flow restriction scheme can be obtained. The first flow restriction scheme includes the first flow restriction station set and the flow restriction intensity of each first flow restriction station.

[0316] For example, if we solve the objective function of the first flow restriction for the line from 8:00 to 8:15, the first flow restriction scheme obtained is shown in Table 2, which includes the set of stations with the first flow restriction and the flow restriction intensity and evaluation index of each station with the first flow restriction.

[0317] Table 2. Flow restriction intensity of each first-level flow restriction station

[0318]

[0319] Optionally, such as Figure 3 As shown, by solving the first capacity allocation objective function, the train frequency increase configuration for each route can be obtained. Based on the train frequency increase configuration for each route, the maximum transport capacity index of each section is updated. Then, under the constraints of flow restriction intensity constraints, flow restriction station number constraints, station capacity constraints, and updated section transport capacity constraints, by solving the first flow restriction objective function, the first flow restriction station set and the flow restriction intensity of each first flow restriction station can be determined, and the first combination scheme can be determined. The first combination scheme includes the train frequency increase configuration for each route, the time period for adding trains, the first flow restriction station set, and the flow restriction intensity of each first flow restriction station.

[0320] For example, the first combination scheme obtained can be as shown in Table 3, including the original line operation scheme, the configuration of increased train operation frequency, the set of first flow restriction stations, the flow restriction intensity and evaluation index of each first flow restriction station.

[0321] Table 3: Increased Train Frequency and Intensity of Current Restriction

[0322]

[0323]

[0324] Optionally, Figure 5 This is a schematic diagram of the second optimization model provided by the present invention, as shown below. Figure 5 As shown, the second optimization model may include at least one second capacity optimization sub-model and a second flow restriction optimization sub-model; the second capacity optimization sub-model may include a second capacity allocation objective function and a second capacity allocation constraint, the second capacity allocation constraint may include a minimum train frequency constraint, a maximum train frequency constraint, a number of operating vehicles constraint, and a maximum cross-sectional load factor constraint; the second flow restriction optimization sub-model may include a second flow restriction objective function and a second flow restriction constraint, the second flow restriction constraint may include a flow restriction intensity constraint, a flow restriction station number constraint, a station capacity constraint, and an interval transport capacity constraint.

[0325] Optionally, such as Figure 5 As shown, at least one second capacity optimization sub-model includes the following sub-models: single route operation scheme optimization sub-model, large and small route operation scheme optimization sub-model, and connecting route operation scheme optimization sub-model.

[0326] Optionally, such as Figure 5 As shown, the single-route operation scheme can be obtained by solving the single-route operation scheme optimization sub-model.

[0327] Optionally, such as Figure 5 As shown, the large and small route operation schemes can be obtained by solving the optimization sub-model of the large and small route operation schemes.

[0328] Optionally, such as Figure 5 As shown, the connecting route operation scheme can be obtained by solving the optimization sub-model of the connecting route operation scheme.

[0329] For example, the second scheduling cycle can be 1 hour, and the determined single route operation plan, large and small route operation plan and connecting route operation plan can be shown in Table 4. Figure 6 This is a schematic diagram of the single-route operation scheme provided by the present invention, as shown below. Figure 6 The diagram shows a single-route train operation plan. Figure 7 This is a schematic diagram of the large and small route operation scheme provided by the present invention, as shown below. Figure 7 The diagram shows the operation plan for both long and short routes; Figure 8 This is a schematic diagram of the connecting route operation scheme provided by the present invention, as shown below. Figure 8 The diagram shows the connecting route operation plan.

[0330] Table 4 Configuration Table of Multiple Train Operation Schemes

[0331]

[0332] Optionally, such as Figure 5 As shown, by solving the second flow restriction optimization sub-model, the second flow restriction scheme can be obtained. The second flow restriction scheme includes the third flow restriction scheme for each flow restriction period. The third flow restriction scheme includes the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station. The flow restriction period is a period in the second scheduling cycle.

[0333] For example, the second flow restriction optimization sub-model can be solved for the line from 7:30 to 8:30 to obtain the second flow restriction scheme, as shown in Table 5, which includes the third flow restriction scheme and evaluation index for each flow restriction period.

[0334] Table 5 Configuration Table of Second Current Limiting Scheme

[0335]

[0336]

[0337] Optionally, such as Figure 5 As shown, after determining the single-route operation plan, the large-small-small-routes operation plan, and the connecting-route operation plan, the single-route operation plan, the large-small-small-routes operation plan, and the connecting-route operation plan are evaluated based on preset evaluation indicators to obtain the first evaluation result of each operation plan. Then, based on the first evaluation result of each operation plan, the target operation plan can be determined. Then, based on the target operation plan, the maximum transport capacity index of each section can be updated. After updating the maximum transport capacity index of each section, under the constraints of the flow restriction intensity constraint, the flow restriction station number constraint, the station capacity constraint, and the updated section transport capacity constraint, the second flow restriction plan can be determined by solving the second flow restriction objective function. Then, the second combined plan can be determined. The second combined plan includes the target operation plan and the second flow restriction plan.

[0338] For example, the second combination scheme obtained can be as shown in Table 6, including the target train operation scheme, the second flow restriction scheme, and evaluation indicators.

[0339] Table 6 Configuration Table for the Second Combination Scheme

[0340]

[0341]

[0342] The rail transit passenger flow scheduling method provided by this invention distinguishes between the current daytime and subsequent daytime periods for passenger flow scheduling. It can handle passenger flow scheduling for the current day and subsequent days according to different scheduling cycles. A first scheduling cycle shorter than a second scheduling cycle can meet the higher frequency scheduling needs of the current day. When the passenger flow scheduling period is the current daytime, by determining a train frequency increase scheme and a first flow restriction scheme, it can ensure that the capacity supply of the first scheduling cycle matches the passenger flow demand and avoids changes to train routes. When the passenger flow scheduling period is subsequent daytime, by determining at least one operation scheme and a second flow restriction scheme, it can ensure that the capacity supply of the second scheduling cycle matches the passenger flow demand. Furthermore, at least one operation scheme can be used to change the train routes of subsequent days to meet capacity supply needs, thus enabling the determination of appropriate passenger flow scheduling schemes for both the current day and subsequent days.

[0343] The rail transit passenger flow scheduling device provided by the present invention is described below. The rail transit passenger flow scheduling device described below can be referred to in correspondence with the rail transit passenger flow scheduling method described above.

[0344] Figure 9 This is a schematic diagram of the structure of the rail transit passenger flow scheduling device provided by the present invention, as shown below. Figure 9 As shown, the device includes: an acquisition module 901 and a determination module 902, wherein:

[0345] Module 901 is used to obtain passenger flow scheduling time periods;

[0346] The determination module 902 is used to, when the passenger flow scheduling period is the current midday period, solve the first optimization model based on the capacity data and the first passenger flow data of the first scheduling period in each first scheduling cycle of the passenger flow scheduling period, and determine the train frequency increase scheme and the first flow restriction scheme of the first scheduling cycle;

[0347] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0348] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0349] The rail transit passenger flow scheduling device provided by this invention, by distinguishing whether the passenger flow scheduling period is the current midday period or a subsequent midday period, can determine the passenger flow scheduling plan according to a first scheduling cycle when the passenger flow scheduling period is the current midday period, and according to a second scheduling cycle when the passenger flow scheduling period is a subsequent midday period. The first scheduling cycle being shorter than the second scheduling cycle can meet the scheduling demand for higher frequencies on the current day. When the passenger flow scheduling period is the current midday period, by solving the first capacity optimization sub-model and the first flow restriction optimization sub-model, the train frequency increase plan and the first flow restriction plan for the first scheduling cycle can be determined. The train frequency increase plan and the first flow restriction plan can be used to allocate capacity and restrict passenger flow to ensure the first scheduling. The cyclical capacity supply matches passenger demand, and the increased train frequency scheme is based on the existing train operation scheme, which avoids changing train routes. When the passenger flow scheduling period is during the midday period of the following day, by solving the second flow restriction optimization sub-model and at least one second capacity optimization sub-model, the second flow restriction scheme and at least one operation scheme can be determined. At least one operation scheme and the second flow restriction scheme can be used to allocate capacity and restrict passenger flow to ensure that the capacity supply of the second scheduling cycle matches passenger demand. Furthermore, the train routes of the following days can be changed, and at least one operation scheme can be used to change the train routes of the following days to meet the capacity supply, thus enabling the determination of appropriate passenger flow scheduling schemes for the current day and the following days.

[0350] Figure 10 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 10 As shown, the electronic device may include: a processor 1010, a communication interface 1020, a memory 1030, and a communication bus 1040, wherein the processor 1010, the communication interface 1020, and the memory 1030 communicate with each other through the communication bus 1040. The processor 1010 can call logical instructions in the memory 1030 to execute a rail transit passenger flow scheduling method, which includes:

[0351] Obtain passenger flow scheduling time periods;

[0352] When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, the first optimization model is solved to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle;

[0353] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0354] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0355] Furthermore, the logical instructions in the aforementioned memory 1030 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0356] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is able to execute the rail transit passenger flow scheduling method provided by the above methods, the method comprising:

[0357] Obtain passenger flow scheduling time periods;

[0358] When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, the first optimization model is solved to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle;

[0359] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0360] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0361] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the rail transit passenger flow scheduling method provided by the above methods, the method comprising:

[0362] Obtain passenger flow scheduling time periods;

[0363] When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, the first optimization model is solved to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle;

[0364] Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle;

[0365] The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; the first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; the second optimization model includes at least one second capacity optimization sub-model for determining the at least one operation scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme.

[0366] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0367] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0368] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for scheduling passenger flow in rail transit, characterized in that, include: Obtain passenger flow scheduling time periods; When the passenger flow scheduling period is the current midday period, in each first scheduling cycle of the passenger flow scheduling period, based on the capacity data and the first passenger flow data of the first scheduling cycle, the first optimization model is solved to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle; Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle; The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; The first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; The second optimization model includes at least one second capacity optimization sub-model for determining the at least one departure scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme; The step of solving the first optimization model to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle includes: firstly, solving the first capacity optimization sub-model to determine the train frequency increase configuration for each route; secondly, updating the maximum transport capacity index for each section based on the train frequency increase configuration for each route; and thirdly, solving the first flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the first flow restriction station set and the flow restriction intensity of each first flow restriction station. The step of solving the second optimization model to determine the second flow restriction scheme and at least one operation scheme for the second scheduling period includes: first solving the at least one second capacity optimization sub-model to determine the target operation scheme; based on the target operation scheme, updating the maximum transport capacity index of each section; and then solving the second flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station for each flow restriction period.

2. The rail transit passenger flow scheduling method according to claim 1, characterized in that, The first capacity optimization sub-model includes: a first capacity allocation objective function and a first capacity allocation constraint. The first capacity allocation objective function uses the train frequency of each route as the decision variable and the minimum train travel distance as the optimization objective. The first flow restriction optimization sub-model includes: a first flow restriction objective function and a first flow restriction constraint condition. The first flow restriction objective function takes the flow restriction station set and the flow restriction intensity of each flow restriction station as decision variables, and takes the maximum passenger flow in the first scheduling cycle and the minimum variance of the flow restriction intensity of the flow restriction station set as optimization objectives. The train frequency increase scheme includes: increasing the train frequency configuration for each route; the first flow restriction scheme includes: a first flow restriction station set and the flow restriction intensity of each first flow restriction station; The process of solving the first capacity optimization sub-model to determine the increased train frequency configuration for each route includes: Based on the first capacity allocation constraint, the capacity data, and the first passenger flow data, the first capacity allocation objective function is solved to determine the train frequency of each route, and based on the capacity data and the train frequency of each route, the configuration for increasing the train frequency of each route is determined. The step of solving the first flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the first flow restriction station set and the flow restriction intensity of each first flow restriction station includes: Based on the first flow restriction constraint, the updated maximum transport capacity index, the transport capacity data, and the first passenger flow data, the first flow restriction objective function is solved to determine the first set of flow-restricted stations and the flow restriction intensity of each first flow-restricted station.

3. The rail transit passenger flow scheduling method according to claim 2, characterized in that, The capacity data includes: the first preset maximum cross-sectional load factor, the preset maximum train frequency on the line, the preset maximum number of trains used on the line, the total number of stations on the line, the entry gate throughput capacity index, the platform capacity index, and the maximum transport capacity index of each section; the first passenger flow data includes: the maximum cross-sectional passenger flow of each section; The first capacity allocation constraints include: maximum cross-sectional load factor constraints, section train frequency constraints, route train frequency constraints, maximum train frequency constraints, and number of vehicles in use constraints. The maximum cross-sectional load factor constraint condition is used to constrain the maximum cross-sectional load factor of the section to be less than or equal to the first preset maximum cross-sectional load factor. The train frequency constraint condition for each section is used to constrain the relationship between the train frequency of each section and the maximum cross-sectional passenger flow of each section. The aforementioned train frequency constraint is used to constrain the relationship between the train frequency of a section and the train frequency of the section. The maximum train frequency constraint is used to constrain the relationship between the train frequency of the section route and the maximum train frequency of the preset line. The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route. The first flow restriction constraints include: flow restriction intensity constraints, flow restriction station number constraints, station capacity constraints, and interval transport capacity constraints; The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength; The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line; The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index. The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

4. The rail transit passenger flow scheduling method according to claim 1, characterized in that, The at least one second capacity optimization sub-model includes the following sub-models: single route operation scheme optimization sub-model, large and small route operation scheme optimization sub-model, and connecting route operation scheme optimization sub-model; The second capacity optimization sub-model includes a second capacity allocation objective function and a second capacity allocation constraint condition; The second capacity allocation objective function of the single-route operation scheme optimization sub-model uses the single-route train operation frequency as the decision variable and the minimum passenger waiting time and the minimum train travel distance as the optimization objectives. The second capacity allocation objective function of the optimization sub-model of the large and small route operation scheme takes the small route train frequency, the first ratio, the first small route turnaround station and the second small route turnaround station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives. The first ratio is the ratio between the large route train frequency and the small route train frequency. The second capacity allocation objective function of the optimization sub-model of the connecting route operation scheme takes the train operation frequency of the first route, the train operation frequency of the second route, and the connecting station as decision variables, and takes the minimum passenger waiting time and the minimum train travel distance as optimization objectives. The second flow restriction optimization sub-model includes: a second flow restriction objective function and a second flow restriction constraint. The second flow restriction objective function uses the set of flow-restricted stations and the flow restriction intensity of each flow-restricted station as decision variables, and takes the maximum passenger flow entering the station and the minimum variance of the flow restriction intensity of the set of flow-restricted stations within the second scheduling cycle as optimization objectives.

5. The rail transit passenger flow scheduling method according to claim 4, characterized in that, The at least one operation scheme includes: a single route operation scheme, a combined route operation scheme and a connecting route operation scheme; the second flow restriction scheme includes: a third flow restriction scheme for each flow restriction period, the third flow restriction scheme includes the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station, and the flow restriction period is a period in the second scheduling cycle; The process of solving the at least one second capacity optimization sub-model to determine the target operating scheme includes: Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the single route operation scheme optimization sub-model, the second capacity allocation objective function of the single route operation scheme optimization sub-model is solved to determine the single route operation scheme. Based on the transport capacity data, the second passenger flow data, and the second transport capacity allocation constraints of the optimized sub-model of the large and small route operation scheme, the second transport capacity allocation objective function of the optimized sub-model of the large and small route operation scheme is solved to determine the large and small route operation scheme; Based on the capacity data, the second passenger flow data, and the second capacity allocation constraint of the connecting route operation scheme optimization sub-model, the second capacity allocation objective function of the connecting route operation scheme optimization sub-model is solved to determine the connecting route operation scheme. The process of solving the second flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station during each flow restriction period includes: Based on the second flow restriction constraint, the updated maximum transport capacity index, the transport capacity data, and the second passenger flow data, the second flow restriction objective function is solved to determine the third flow restriction scheme for each flow restriction period.

6. The rail transit passenger flow scheduling method according to claim 5, characterized in that, The capacity data includes: the minimum train frequency of the preset line, the maximum train frequency of the preset line, the maximum number of trains used on the preset line, the full load rate of the second preset maximum cross-section, the total number of stations on the line, the throughput capacity index of the entrance gate, the platform capacity index, and the maximum transport capacity index of each section. The second capacity allocation constraints include: minimum train frequency constraints, maximum train frequency constraints, number of vehicles in use constraints, and maximum cross-sectional load factor constraints. The minimum train frequency constraint is used to constrain the relationship between the train frequency of the route and the preset minimum train frequency of the line. The maximum train frequency constraint is used to constrain the relationship between the train frequency of the route and the maximum train frequency of the preset line. The vehicle number constraint is used to constrain the relationship between the number of vehicles used on the route and the maximum number of vehicles used on the preset route. The maximum cross-section full load rate constraint condition is used to constrain the maximum cross-section full load rate of the line to be less than or equal to the second preset maximum cross-section full load rate. The second flow restriction constraint conditions include: flow restriction intensity constraint conditions, flow restriction station number constraint conditions, station capacity constraint conditions, and interval transport capacity constraint conditions; The current limiting strength constraint condition is used to constrain the range of values ​​for the current limiting strength; The constraint on the number of stations with flow restriction is used to constrain the proportional relationship between the number of stations with flow restriction and the total number of stations on the line; The station capacity constraints are used to constrain the relationship between the passenger flow entering the station and the throughput capacity index of the entrance gate, as well as to constrain the relationship between the passenger flow entering the station and the platform capacity index. The interval transport capacity constraint is used to constrain the relationship between the passenger flow through each interval and the maximum transport capacity index of each interval.

7. The rail transit passenger flow scheduling method according to claim 6, characterized in that, Before determining the third flow restriction scheme for each flow restriction period by solving the second flow restriction objective function based on the second flow restriction constraint, the updated maximum transport capacity index, the transport capacity data, and the second passenger flow data, the method further includes: Based on preset evaluation indicators, the single route operation plan, the large and small route operation plan, and the connecting route operation plan are evaluated to obtain the first evaluation result of each operation plan; Based on the first evaluation results of each operation plan, one of the following operation plans is determined as the target operation plan: the single route operation plan, the large and small route operation plan, and the connecting route operation plan.

8. The rail transit passenger flow scheduling method according to any one of claims 1-7, characterized in that, When the passenger flow scheduling period is the current midday period, after solving the first optimization model based on the capacity data and the first passenger flow data of the first scheduling cycle to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle, the method further includes: Based on preset evaluation indicators, the train frequency increase scheme and the first flow restriction scheme are evaluated to obtain a second evaluation result. Alternatively, if the passenger flow scheduling task is for a subsequent midday period, after solving the second optimization model based on the capacity data and the second passenger flow data of the second scheduling cycle to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle, the method further includes: Based on the preset evaluation indicators, the second flow restriction scheme and the at least one operation scheme are evaluated to obtain a third evaluation result.

9. A rail transit passenger flow scheduling device, characterized in that, include: The acquisition module is used to obtain passenger flow scheduling time periods; The determination module is used to, when the passenger flow scheduling period is the current midday period, solve the first optimization model based on the capacity data and the first passenger flow data of the first scheduling period in each first scheduling cycle of the passenger flow scheduling period, and determine the train frequency increase scheme and the first flow restriction scheme of the first scheduling cycle; Alternatively, if the passenger flow scheduling task is for a subsequent midday period, in each second scheduling cycle during the passenger flow scheduling period, based on the capacity data and the second passenger flow data of the second scheduling cycle, a second optimization model is solved to determine the second flow restriction scheme and at least one operation scheme for the second scheduling cycle; The duration of the first scheduling cycle is shorter than the duration of the second scheduling cycle; The first optimization model includes a first capacity optimization sub-model for determining the train frequency increase scheme and a first flow restriction optimization sub-model for determining the first flow restriction scheme; The second optimization model includes at least one second capacity optimization sub-model for determining the at least one departure scheme and a second flow restriction optimization sub-model for determining the second flow restriction scheme; The step of solving the first optimization model to determine the train frequency increase scheme and the first flow restriction scheme for the first scheduling cycle includes: firstly, solving the first capacity optimization sub-model to determine the train frequency increase configuration for each route; secondly, updating the maximum transport capacity index for each section based on the train frequency increase configuration for each route; and thirdly, solving the first flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the first flow restriction station set and the flow restriction intensity of each first flow restriction station. The step of solving the second optimization model to determine the second flow restriction scheme and at least one operation scheme for the second scheduling period includes: first solving the at least one second capacity optimization sub-model to determine the target operation scheme; based on the target operation scheme, updating the maximum transport capacity index of each section; and then solving the second flow restriction optimization sub-model based on the updated maximum transport capacity index to determine the set of second flow restriction stations and the flow restriction intensity of each second flow restriction station for each flow restriction period.

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