A full-reservation travel od control method for peak-hour subway single-line

Abstract

The application discloses a high-peak subway single-line full-reservation travel OD control method, comprising the following steps: collecting the expected arrival time period and the start and end points of each passenger during the peak period through a reservation platform on the previous day; establishing a precise passenger flow control model, which is a linear programming model, and the constraints of the model include the constraints of the number of delayed passengers, passenger service constraints and variable range constraints; solving the above model by Gurobi through the built-in branch and bound algorithm, and Gurobi outputs the arrival time period of the passenger reservation success; the arrival time period of the passenger reservation success output by Gurobi is output by the reservation platform, and the reservation platform also outputs the passenger reservation access code, and passengers who do not participate in the subway reservation on the previous day can perform the second round of reservation. The application can obtain precise full-passenger flow space-time distribution information through full-reservation travel service, and the information can be used to conveniently perform precise passenger flow control, effectively solve the platform congestion during the peak period, and solve the problem of long passenger waiting time cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rail transit, in particular to a full-reservation travel OD control method for a subway single line during peak hours. BACKGROUND

[0002] Due to the imbalance of urban development, there is often a problem of prominent contradiction between supply and demand during peak hours in the operation of rail transit, and the scale and carrying capacity of some subway lines and stations cannot meet the passenger flow demand and need to be controlled. At present, the main control is to control the number of passengers entering the station, which leads to queuing of passengers entering the station, poor passenger experience, and affected subway operation efficiency. Since reservation travel can effectively improve the queuing situation and improve the overall efficiency of the system, it has been widely concerned.

[0003] Most current researches are based on the mode of partial passenger reservation and non-reservation of passengers entering the station. This leads to the inability to fully grasp and control the full passenger flow information. Due to the great uncertainty of non-reservation passengers, it is difficult to accurately control them, which greatly reduces the effect of current passenger flow control and timetable optimization. SUMMARY

[0004] The purpose of the present application is to overcome the shortcomings and deficiencies of the prior art, and to provide a full-reservation travel OD control method for a subway single line during peak hours, which breaks through the limitations of partial passenger reservation or partial station reservation. During peak hours, all stations and all passengers on the subway line need to be reserved to enter the station and take the train. The reservation platform can accurately obtain the spatio-temporal distribution of passenger travel demand at each station on the line, provide a comprehensive data basis for adjusting the passenger flow control scheme, and help to achieve accurate matching of train supply and passenger demand using appropriate models. At the same time, passengers at all stations can make reservations, and passengers can enter the station and take the train according to the reservation arrival time period, which can effectively reduce the invalid queuing time outside the station and reduce the pressure of subway peak passenger flow control outside the station.

[0005] To achieve the above purpose, the technical scheme provided by the present application is as follows: a full-reservation travel OD control method for a subway single line during peak hours, comprising the following steps:

[0006] S1: collecting the estimated arrival time period and origin-destination (OD) point of each passenger during peak hours through a reservation platform on the previous day, wherein the origin point is O and the destination point is D;

[0007] S2: establishing a precise passenger flow control model using the estimated arrival time period and OD point of each passenger collected and the train timetable, which is a linear programming model, and the constraints of the model include the constraints of the number of delayed passengers, passenger service constraints and variable range constraints;

[0008] S3: The above precise passenger flow control model is solved by a commercial optimization solver Gurobi through its built-in branch and bound algorithm, and Gurobi outputs the passenger reservation success arrival time period;

[0009] S4: The passenger reservation success arrival time period output by Gurobi is output by the reservation platform, and the reservation platform also outputs the passenger reservation access code. Passengers who do not participate in the subway reservation of the previous day can perform the second round of reservation.

[0010] Further, in step S1, during the peak period, all passengers in all stations of the subway line need to enter the reservation platform for reservation. Passengers reserve subway travel services according to their own travel needs during the peak period from 12:00 to 20:00 the previous day, and input their expected arrival time period and origin-destination point in the reservation platform.

[0011] Further, the specific steps of step S2 are as follows:

[0012] S21: Before model construction, make assumptions about the influencing factors of the model: a, the train stop time length at all stations is the same, without considering the train overtaking and skipping behavior, all trains maintain the same running speed, and the time spent when driving through two stations with the same distance is the same; b, in the reservation platform, the optimal boarding sequence is adopted for the reservation success boarding time period of different passenger ODs, that is, the optimal solution of the objective function is selected in all passenger OD boarding schemes, and for passengers with the same OD, the earlier the expected arrival time period, the earlier the reservation success boarding time period feedback by the reservation platform; c, the operation cost generated by each train from the starting station to the terminal station is fixed and consistent; d, all passengers participating in the first round of reservation of the platform need to input their expected arrival time period and origin-destination point, and all passengers can receive the reservation success boarding time period feedback by the platform, and all participating reservation passengers OD will receive the reservation success boarding time period; e, within the implementation range of the reservation entry, the number of train carriages is sufficient;

[0013] S22: The decision variable of the model is the delay queuing quantity of passengers expected to arrive before time j but not yet assigned to the reservation success boarding time period and q uvj , the two variables are integer decision variables;

[0014] is the delay cross-section passenger quantity of the origin-destination point of passengers expected to arrive before time j but not yet assigned to the reservation success boarding time period through the station s;

[0015] q uvjTo express the OD quantity of the delayed passengers whose origin and destination are station u and station v, and who are expected to arrive at the station before time j, but have not been assigned to the reserved boarding time period with success yet;

[0016] S23: Propose the constraint condition of the model:

[0017] a. The constraint of the delayed passenger quantity:

[0018]

[0019]

[0020] Equation (1) and equation (2) express that at the initial time 0, the delayed section passenger quantity of all stations and the passenger OD quantity of each type of delay are zero;

[0021]

[0022] Equation (3) expresses the relationship between the delayed section passenger quantity and the train capacity; at time j, for the station s, if the train does not depart at time j, the delayed section passenger quantity of the station s at time j is equal to the sum of the delayed section passenger quantity of the station s at time [j-1] and the delayed section passenger quantity of the passengers expected to arrive and pass through the station s in the time period [j-1, j]; if the train departs at time j, the delayed section passenger quantity of the station s at time j is not less than the sum of the delayed section passenger quantity of the station s at time [j-1] and the delayed section passenger quantity of the passengers expected to arrive and pass through the station s in the time period [j-1, j] minus the difference between the train capacity;

[0023]

[0024] Equation (4) expresses the relationship between the delayed passenger OD quantity and the expected arrival passenger OD quantity; the delayed quantity of the passengers whose origin and destination are u and v at time j is not more than the sum of the delayed quantity at time j-1 and the passenger OD quantity of the passengers expected to arrive and whose origin and destination are u and v in the time period [j-1, j];

[0025]

[0026] Equation (5) expresses the relationship between the delayed section passenger quantity of the station and the delayed passenger OD quantity; the delayed section passenger quantity of the station s at time j-1 is equal to the sum of the delayed passenger OD quantities passing through the station s;

[0027] In the above equation, ε:={1, 2, …, E} represents the set of station numbers;

[0028] s, u, and v respectively represent the numbers of stations,

[0029] respectively represent the upstream and downstream station sets of station s;

[0030] j represents the time point sequence number within the operation time range,

[0031] represent the set of time points;

[0032] q 0s represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0033] q uv0 represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0034] represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet; represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet; and want to go to station ;

[0035] q uv,j-1 represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0036] a uvj represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0037] c represents the maximum number of passengers that the train can accommodate;

[0038] x js represents a 0-1 variable, equal to 1 if the train departs from station s at time j; equal to 0 if departure is not considered;

[0039] b, passenger service constraints:

[0040]

[0041] Equation (6) represents that all passengers participating in the first round of reservation can board within the operation time range of the reserved trip, i.e. the last operation time J of the reserved trip, the number of passengers of the origin-destination pair u and v is zero, and all passenger ODs receive a successful boarding time period;

[0042] c, variable range constraints:

[0043]

[0044]

[0045] Equation (7) and Equation (8) represent that the section delay queue of the station and the delay quantity of the passenger OD are integers greater than or equal to zero;

[0046] S24: The total delay time cost of the passenger is selected as the objective function, the delay time cost is equal to the product of the delay time of all passenger ODs and the unit delay time cost, and the delay time of all passenger ODs is equal to the product of the delay queue passenger OD number at all time points in the operation time range and the time length of a single time period, therefore, the objective function is represented as:

[0047]

[0048] w represents the time cost generated by a single passenger delaying a reservation time period;

[0049] δ represents the time interval length of a reservation time period.

[0050] Further, the specific steps of S3 are as follows:

[0051] S31: Set the type and value range of the decision variable;

[0052] S32: Update the variable space;

[0053] S33: Set the objective function according to the decision variable and the related coefficient;

[0054] S34: Add the constraint condition;

[0055] S35: Set the parameters of the optimization calculation, and execute the optimization calculation;

[0056] S36: Output the optimization result.

[0057] Further, the specific steps of S4 are as follows:

[0058] S41: The reservation platform opens two rounds of reservation: step S1 is the first round of reservation, the reservation platform outputs the arrival time period of each passenger according to the travel demand provided by all passengers and the basic situation of the train line, in combination with historical OD data, according to the optimization result of passenger flow OD control in steps S2 and S3, the passengers who successfully reserve the arrival time period arrive at the station within the reservation time period returned by the reservation platform, can generate a reservation access code, do not need to queue, and can directly scan the code to enter the station and board the train;

[0059] S42: The second round of appointment is opened from 21:00 of the previous day to the peak period of the appointment day, the passengers who do not participate in the first round of appointment can participate in this round of appointment, the appointment platform finds the time period that can meet the entry condition according to the result of the first round of appointment and returns to the passengers of the second round of appointment, the passengers who successfully make an appointment arrive at the station within the appointment time period returned by the appointment platform, can generate an appointment access code, do not need to queue, and can directly scan the code to enter the station and get on the vehicle.

[0060] Further, the appointment access code returned by the appointment platform has a time requirement limit and can only be used within the appointment successful time range, the passengers who arrive too early or too late cannot enter the station, wherein the passengers who arrive too early need to queue until the appointment successful time period, the passengers who arrive too late need to submit an appointment application to the appointment platform again, participate in the second round of appointment, and wait for the appointment successful arrival time period returned by the appointment platform, the passengers who successfully make an appointment but cancel the travel plan can cancel the appointment on the appointment platform.

[0061] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0062] 1. The present application can realize comprehensive control and control of full passenger flow information through the appointment form of all passengers in the peak period.

[0063] 2. The present application designs a two-round appointment mode, which can reduce platform congestion and enable passengers to travel efficiently.

[0064] In summary, the present application can obtain accurate full passenger flow space-time distribution information through the full appointment mode, and the information can be used to conveniently control the accurate passenger flow, effectively solve the problem of platform congestion and long waiting time cost of passengers in the peak period. BRIEF DESCRIPTION OF DRAWINGS

[0065] Figure 1 is a subway full appointment service flowchart in the peak period.

[0066] Figure 2 is a construction flowchart of the subway accurate passenger flow control scheme in the peak period.

[0067] Figure 3 is a schematic diagram of the first round of appointment operation steps in the embodiment.

[0068] Figure 4 is a schematic diagram of the second round of appointment operation steps in the embodiment. DETAILED DESCRIPTION

[0069] The present application will be further described in detail below in combination with the embodiments and the drawings, but the embodiments of the present application are not limited thereto.

[0070] As Figure 1As shown, the embodiment discloses a high-peak subway single-line full-reservation travel OD control method, which comprises the following steps:

[0071] S1: collecting the expected arrival time period and the origin-destination point (OD point, the origin point is O, and the destination point is D) of each passenger during the peak period through the reservation platform on the previous day;

[0072] During the peak period, all passengers at all stations on the subway line need to make reservations on the reservation platform. Passengers make reservations for subway travel services from 12:00 to 20:00 on the previous day according to their travel needs during the peak period, and input their expected arrival time period and origin-destination point on the reservation platform;

[0073] S2: establishing a precise passenger flow control model by using the collected expected arrival time period and origin-destination point of each passenger and the train timetable;

[0074] As shown, the construction process of the high-peak subway precise passenger flow control scheme is shown, which comprises the following steps: Figure 2

[0075] S21: Before the model is constructed, the following assumptions are made for the relevant influencing factors of the model: a, the stopping time length of the train at all stations is the same, the train's overtaking and skipping behaviors are not considered, all trains maintain the same running speed, and the time taken to travel through two stations with the same distance is the same; b, in the reservation platform, the optimal boarding sequence is adopted for the reservation successful boarding time period of different passenger ODs, that is, the optimal scheme of the objective function is selected from all passenger OD boarding schemes, and for passengers with the same OD, the earlier the expected arrival time period, the earlier the reservation successful boarding time period fed back by the reservation platform; c, the operation cost generated by each train from the starting station to the terminal station is fixed and consistent; d, all passengers participating in the first round of reservation need to input their expected arrival time period and origin-destination point, and all passengers participating in the reservation can receive the reservation successful boarding time period fed back by the platform; e, within the operation range of the reservation entry station, the number of train carriages is sufficient;

[0076] S22: The decision variable of the model is the delay queuing amount of passengers expected to arrive before time j but not yet assigned to the reservation successful boarding time period and q uvj , which are integer decision variables;

[0077] is the delay cross-section passenger number of the origin-destination point of passengers expected to arrive before time j but not yet assigned to the reservation successful boarding time period passing through the station s;

[0078] q uvj ​To express the OD quantity of the delayed passengers whose origin and destination are station u and station v, and who are expected to arrive at the station before time j, but have not been assigned to the reserved boarding time period with success yet;

[0079] S23: Propose the constraint conditions of the model:

[0080] a. The constraint of the delayed passenger quantity:

[0081]

[0082]

[0083] Equation (1) and equation (2) represent that at the initial time 0, the delayed section passenger quantity of all stations and the passenger OD quantity of each type of delay are zero;

[0084]

[0085] Equation (3) represents the relationship between the delayed section passenger quantity and the train capacity; at time j, for the station s, if the train does not depart at time j, the delayed section passenger quantity of the station s at time j is equal to the sum of the delayed section passenger quantity of the station s at time [j-1] and the delayed section passenger quantity of the passengers expected to arrive and pass through the station s in the time period [j-1, j]; if the train departs at time j, the delayed section passenger quantity of the station s at time j is not less than the sum of the delayed section passenger quantity of the station s at time [j-1] and the delayed section passenger quantity of the passengers expected to arrive and pass through the station s in the time period [j-1, j] minus the difference between the train capacity;

[0086]

[0087] Equation (4) represents the relationship between the delayed passenger OD quantity and the expected arrival passenger OD quantity, the delayed quantity of the passengers whose origin and destination are u and v at time j is not greater than the delayed quantity at time j-1 and the sum of the passenger OD quantity of the passengers expected to arrive and whose origin and destination are u and v in the time period [j-1, j];

[0088]

[0089] Equation (5) represents the relationship between the delayed section passenger quantity of the station and the delayed passenger OD quantity, the delayed section passenger quantity of the station s at time j-1 is equal to the sum of the delayed passenger OD quantity passing through the station s;

[0090] In the above equation, ε:={1, 2, …, E} represents the set of station numbers;

[0091] s, u, and v respectively represent the numbers of stations,

[0092] respectively represent the upstream and downstream station sets of station s;

[0093] j represents the time point sequence number within the operation time range,

[0094] represent the set of time points;

[0095] q 0s represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0096] q uv0 represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0097] represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet; represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet; and want to go to station ;

[0098] q uv,j-1 represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0099] a uvj represents the number of passengers of the origin-destination pair u and v who are expected to arrive at station s before time 0 but have not been assigned a successful boarding time period yet;

[0100] c represents the maximum number of passengers that the train can accommodate;

[0101] x js represents a 0-1 variable, equal to 1 if the train departs from station s at time j; equal to 0 if the departure is not considered;

[0102] b, passenger service constraints:

[0103]

[0104] Equation (6) represents that all passengers participating in the first round of reservation can board within the operation time range of the reserved trip, i.e. the number of passengers of the origin-destination pair u and v is zero at the last operation time J of the reserved trip, and all passenger ODs receive a successful boarding time period;

[0105] c, variable range constraints:

[0106]

[0107]

[0108] Equation (7) and equation (8) represent that the cross-sectional delay queue of the station and the delay number of the passenger OD are integers greater than or equal to zero;

[0109] S24: The total delay time cost of the passenger is selected as the objective function, the delay time cost is equal to the product of the delay time of all passenger ODs and the unit delay time cost, and the delay time of all passenger ODs is equal to the product of the delay queue passenger OD number at all time points in the operation time range and the time length of a single time period, therefore, the objective function can be represented as:

[0110]

[0111] w represents the time cost generated by a single passenger delaying a reservation time period;

[0112] δ represents the time interval length of a reservation time period.

[0113] S3: The above-mentioned accurate passenger flow control model is solved by a commercial optimization solver Gurobi through a built-in branch and bound algorithm, and the Gurobi outputs the arrival time period of the passenger reservation success, and the specific steps are as follows:

[0114] S31: The decision variable type and value range are set;

[0115] S32: The variable space is updated;

[0116] S33: The objective function is set according to the decision variable and the related coefficient;

[0117] S34: The constraint condition is added;

[0118] S35: The parameters of the optimization calculation are set, and the optimization calculation is executed;

[0119] S36: The optimization result is output.

[0120] S4: The arrival time period of the passenger reservation success output by the Gurobi is output by the reservation platform, and the reservation platform also outputs the passenger reservation access code, and the passenger who does not participate in the subway reservation of the previous day can perform the second round of reservation, and the specific steps are as follows:

[0121] S41: The reservation platform opens two rounds of reservation: Step S1 is the first round of reservation. The reservation platform outputs the arrival time period of each passenger according to the travel demand provided by all passengers and the basic situation of the train line, in combination with historical OD data, the optimization results of passenger flow OD control in steps S2 and S3, and the passengers who successfully reserve the arrival station arrive at the station within the reservation time period returned by the reservation platform, can generate a reservation pass code, do not need to queue, and can directly scan the code to enter the station and board the train;

[0122] S42: The second round of reservation is opened from 21:00 of the previous day to the peak period of the reservation day. The passengers who do not participate in the first round of reservation can participate in this round of reservation. The reservation platform finds the time period that can meet the station entry condition according to the results of the first round of reservation and returns it to the passengers of the second round of reservation. The passengers who successfully reserve the arrival station arrive at the station within the reservation time period returned by the reservation platform, can generate a reservation pass code, do not need to queue, and can directly scan the code to enter the station and board the train.

[0123] The reservation pass code returned by the reservation platform has a time requirement limit and can only be used within the reservation successful time range. The passengers who arrive early or late cannot enter the station. The passengers who arrive early need to queue until the reservation successful time period. The passengers who arrive late need to submit a reservation application to the reservation platform again, participate in the second round of reservation, and wait for the reservation successful arrival time period returned by the reservation platform. The passengers who successfully reserve but cancel the travel plan can cancel the reservation on the reservation platform.

[0124] As shown in Figure 3 , the first round of reservation operation steps of the full reservation of the present embodiment are as follows:

[0125] S1: The passengers who have travel demand in the peak period enter the reservation platform to make the first round of reservation from 12:00-20:00 of the previous day. The passengers input the expected arrival time period and the origin-destination point;

[0126] S2: According to the expected arrival time period and the origin-destination point input by the passengers, the platform outputs the reservation successful arrival time period and the passenger reservation pass code;

[0127] S3: If the passengers arrive at the station on time according to the reservation successful arrival time period output by the platform, then scan the code to enter the station;

[0128] S4: If the passengers arrive at the station earlier than the reservation successful arrival time period output by the platform, then wait for the reservation successful time period and then scan the code to enter the station;

[0129] S5: If the passengers arrive at the station later than the reservation successful arrival time period output by the platform, then need to make the second round of reservation.

[0130] As shown in Figure 4 , the second round of reservation operation steps of the full reservation of the present embodiment are as follows:

[0131] S1: The passenger enters the platform for the second round of reservation from 21:00 of the previous day to the end of the peak period of the reservation day, and inputs the expected arrival time period and the starting and ending points;

[0132] S2: According to the starting and ending points and the expected arrival time period input by the passenger, the platform outputs the successful reservation arrival time period and the passenger reservation access code;

[0133] S3: If the passenger arrives on time according to the successful reservation arrival time period output by the platform, the passenger scans the code to enter the station;

[0134] S4: If the passenger arrives earlier than the successful reservation arrival time period output by the platform, the passenger waits until the successful reservation time period and then scans the code to enter the station;

[0135] S5: If the passenger arrives later than the successful reservation arrival time period output by the platform, the passenger needs to make another reservation.

[0136] The above embodiment is the preferred embodiment of the present application, but the embodiment of the present application is not limited by the above embodiment, and any change, modification, substitution, combination, simplification made without departing from the spirit and principle of the present application should be an equivalent replacement method, which is included in the protection scope of the present application.

Claims

1. A full reservation travel OD control method for peak-hour subway single-line routes, characterized in that, Comprising the following steps: S1: Collect the expected arrival time period and origin-destination (OD) point of each passenger during peak hours through a reservation platform on the previous day, wherein the origin point is O and the destination point is D; S2: Establish a precise passenger flow control model using the collected expected arrival time period and OD point of each passenger and train timetable, which is a linear programming model, and the constraints of the model include delay passenger quantity constraint, passenger service constraint and variable range constraint, and the specific steps are as follows: S21: Before model construction, initialize the relevant influencing factors of the model: a, the stop time length of the train at all stations is the same, and the train does not consider overrunning and skipping behavior, all trains run at a stable and same speed, and the time spent when passing through two stations with the same distance is the same; b, in the reservation platform, the optimal boarding sequence is adopted for the reservation success boarding time period of different passenger ODs, that is, in all passenger OD boarding schemes, the scheme with the optimal objective function is selected, and for passengers with the same OD, the earlier the expected arrival time period, the earlier the reservation success boarding time period fed back by the reservation platform; c, the operation cost of each train from the starting station to the terminal station is fixed and consistent; d, all passengers participating in the first round of reservation need to input their expected arrival time period and OD point, and all passengers can receive the reservation success boarding time period fed back by the platform, and all participating passenger ODs will receive the reservation success boarding time period; e, within the operation range of the reservation arrival station, the number of trains is sufficient; S22: The decision variable of the model is the expected number of passengers who arrive before time j but have not been assigned to a successful pick-up time slot, which contains two variables and q uvj , both of which are integer decision variables; the number of passengers at the origin and destination of the passenger who is expected to arrive before time j but has not been assigned to a successful reservation boarding time period yet, passing through the station s; q uvj OD number of passengers expected to arrive at station u and station v respectively before time j, but not yet assigned to the reservation successful boarding time period delay. S23: Propose the constraint conditions of the model: a, delay passenger quantity constraint: Equation (1) represents the delay section passenger quantity of all stations at initial time 0, and equation (2) represents the passenger OD quantity of each type of delay at initial time 0, which is zero; Equation (3) represents the relationship between the delay section passenger quantity and the train capacity; at time j, for the delay section passenger quantity of station s, if the train does not depart at time j, it is equal to the sum of the delay section passenger quantity of station s at time [j-1] and the delay section passenger quantity of the passengers expected to arrive and pass through station s within the time period [j-1, j]; if the train departs at time j, the delay section passenger quantity of station s is not less than the sum of the delay section passenger quantity of station s at time [j-1] and the delay section passenger quantity of the passengers expected to arrive and pass through station s within the time period [j-1, j] minus the difference between the train compartment capacity; Equation (4) represents the relationship between the delay passenger OD quantity and the expected arrival passenger OD quantity, and the OD points of the passengers are u and v, respectively, and the delay quantity at time j is not greater than the sum of the delay quantity at time j-1 and the passenger OD quantity of the passengers expected to arrive and with OD points u and v within the time period [j-1, j]; Equation (5) represents the relationship between the delay section passenger quantity of the station and the delay passenger OD quantity, and the delay section passenger quantity of station s at time j-1 is equal to the sum of the delay passenger OD quantities passing through station s; In the above equation: ε:={1, 2,..., E} represents the set of station numbers; s, u, v respectively represent the serial number of the station, u, v ∈ ε; respectively denote the upstream and downstream station sets of station s; j denotes the time point sequence number within the operating time range, a set representing the sequence number of all time points within the operating time range; q 0s the number of passengers expected to arrive at the station s before time 0 but not yet assigned to a successful boarding time interval; q uv0 OD number of passengers who are expected to arrive at station before time 0 but have not been assigned to the reservation successful boarding time period delay with the start and end points being stations u and v, respectively; represents the number of passengers expected to arrive at the station s before time j-1 but not yet assigned to a successful reservation boarding time period; represents the number of passengers expected to arrive at the upstream station and to go to the station in the reservation time period [j-1, j]. q uv,j-1 OD number of passengers who are expected to arrive at station before time j-1 and have not been assigned to the reservation successful boarding time period delay with the start and end points being stations u and v, respectively; a uvj denotes the number of passengers expected to arrive in the reservation period [j-1, j] and to have their origin and destination stations at stations u and v, respectively; c represents the maximum number of passengers that the train can accommodate; x js denotes a 0-1 variable, equal to 1 if the train departs from station s at time j; equal to 0 if departure is not considered; b, passenger service constraints: Equation (6) represents that all passengers participating in the first round of reservation can get on the train within the operating time range of the reserved trip, i.e., the last operating time J of the reserved trip, the number of delays of passengers OD u and v is zero, and all passenger ODs receive the reserved successful boarding time period; c, variable range constraints: Equation (7) represents that the cross-sectional delay queue of the station is an integer greater than or equal to zero; Equation (8) represents that the number of delays of passengers OD is an integer greater than or equal to zero; S24: Select the total delay time cost of passengers as the objective function, the delay time cost is equal to the product of the delay time of all passengers OD and the unit delay time cost, and the delay time of all passengers OD is equal to the product of the number of delay queue passengers OD at all time within the operating time range and the time length of a single time period, therefore, the objective function is represented as: w represents the time cost generated by a single passenger delaying a reservation time period; δ represents the time interval length of a reservation time period; S3: The above precise passenger flow control model is solved by a commercial optimization solver Gurobi through an embedded branch and bound algorithm, and Gurobi outputs the arrival time period of the passenger reservation success; S4: The arrival time period of the passenger reservation success output by Gurobi is output by the reservation platform, and the reservation platform also outputs the passenger reservation access code, and passengers who do not participate in the subway reservation the day before can participate in the second round of reservation.

2. The full reservation travel OD control method for peak-hour subway single-line routes according to claim 1, characterized in that, In step S1, all passengers at all stations in the subway line need to enter the reservation platform for reservation during the peak period, passengers reserve subway travel services according to their own travel needs during the peak period from 12:00 to 20:00 the day before, and input their expected arrival time period and origin-destination point on the reservation platform.

3. The full reservation travel OD control method for a peak-hour subway single-line route according to claim 2, characterized in that, The specific steps of S3 are as follows: S31: Set the type and value range of the decision variable; S32: Update the variable space; S33: Set the objective function according to the decision variable and related coefficients; S34: Add constraint conditions; S35: Set the parameters of optimization calculation and execute optimization calculation; S36: Output the optimization result.

4. The full reservation travel OD control method for peak-hour subway single-line routes according to claim 3, characterized in that, The specific steps of S4 are as follows: S41: The reservation platform opens two rounds of reservation: step S1 is the first round of reservation, the reservation platform outputs the arrival time period of each passenger according to the travel needs provided by all passengers and the basic situation of the train line, combines historical OD data, and according to the optimization result of passenger flow OD control in steps S2 and S3, the passengers who successfully arrive at the station in the reservation time period returned by the reservation platform can generate a reservation access code, do not need to queue, and can directly scan the code to enter the station and get on the train; S42: The second round of reservation is opened from 21:00 the day before to the peak period of the reservation day, passengers who do not participate in the first round of reservation can participate in this round of reservation, the reservation platform finds time periods that can meet the entry conditions according to the results of the first round of reservation and returns them to the passengers of the second round of reservation, the passengers who successfully arrive at the station in the reservation time period returned by the reservation platform can generate a reservation access code, do not need to queue, and can directly scan the code to enter the station and get on the train.

5. The full reservation travel OD control method for peak-hour subway single-line routes according to claim 4, characterized in that, The appointment pass returned by the appointment platform is time-limited and can only be used within the appointment success time range, and passengers who arrive too early or too late cannot enter the station, wherein passengers who arrive too early need to wait in line until the appointment success time period, passengers who arrive too late need to submit an appointment application to the appointment platform again, participate in the second round of appointment, and wait for the appointment success entry time period returned by the appointment platform, and passengers who have successfully appointed but cancelled the travel plan can cancel the appointment on the appointment platform.

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