A train operation plan emergency adjustment method considering passenger ticket refund and change behavior

Abstract

The application provides a train operation plan emergency adjustment method considering passenger refund and change behavior. The method comprises the following steps: obtaining an original train operation diagram, and route plan data, ticket reservation data, interruption scene data and passenger refund and change intention data; considering possible refund and change behavior of passengers under different train adjustment strategies, and constructing a train operation diagram and motor train unit route integrated adjustment model with the target of minimizing ticket revenue loss and minimizing motor train unit operation cost; inputting the data into the train operation diagram and motor train unit route integrated adjustment model, and calculating to obtain a high-speed rail train operation plan adjustment suggestion scheme and a corresponding passenger change suggestion scheme. The method accurately depicts the passenger refund and change behavior, supports the re-matching of supply and demand under passenger flow transfer loss, fully utilizes the train potential through the change suggestion scheme, provides the train operation plan adjustment scheme, and improves the scientificity, applicability and implementability of the train operation emergency adjustment method.

Description

Technical Field

[0001] This invention relates to the field of train operation management technology, and in particular to an emergency adjustment method for train operation plans that takes into account passenger refund and change behavior. Background Technology

[0002] In actual high-speed railway operation, if a small-scale, minor disturbance occurs, such as a few trains experiencing slight delays, the high-speed railway's automatic dispatching and command system can automatically adjust train operation plans. However, when train operation is severely disrupted by numerous factors, such as social security incidents and various high-speed railway transportation accidents, leading to a significant reduction in the railway's short-term throughput capacity and even temporary line interruptions, the high-speed railway dispatching and command system can no longer simply achieve automated adjustments to train operation. It is necessary to use certain human intervention measures to make adjustments in order to ensure traffic safety and reduce the impact of disturbances on normal train operation.

[0003] If rapid and accurate emergency adjustments to train operation plans can be made under conditions of high-speed railway line disruption, it can provide railway departments with a basis for emergency decision-making. Integrating adjustments to train timetables and routes can further refine the research, and to reflect the service nature of railways, operation plan adjustments can be made more humanely, with the objective function taking the passenger perspective into account. Comprehensively considering passengers' independent refund and rebooking behaviors, and generating passenger reallocation schemes after travel disruptions, can minimize the railway system's ticket revenue losses, satisfying corporate interests while better aligning with the independent choices of some passengers after the disruption, making the research more relevant to real-world scenarios.

[0004] In research on emergency adjustments to train operation plans, one existing technology, based on transformational maxima algebra and order optimization, studies train operation scheduling after delays, proposing three adjustment strategies: overtaking, stopping, and timetable rearrangement. After modeling, different scheduling methods and their resulting delay durations are generated according to corresponding algorithms. Another approach proposes a method for real-time train scheduling during major high-speed railway disruptions. This involves allowing trains to share arrival and departure tracks to simultaneously rearrange arriving and departing trains. Based on the spatiotemporal network method, an integer linear programming model minimizing train deviations from their original operating state is established. All of the above literature addresses adjustments at the single timetable level. Another approach proposes a real-time adjustment scheme for high-speed railway train operation considering EMU (Electric Multiple Unit) connections. This scheme builds an integrated adjustment model and solves it using CPLEX in scenarios with short-duration unidirectional disruptions on high-speed railway lines, involving integrated adjustments, but it does not consider the decision to activate hot standby trains or the issue of returning EMUs to the depot on the same day to ensure their use the following day. Yet another approach proposes an adjustment strategy for activating hot standby trains at the integrated adjustment level, but still does not consider the issue of returning EMUs to the depot on the same day to ensure their use the following day.

[0005] The aforementioned emergency adjustment schemes for high-speed train operation plans have the following drawbacks:

[0006] (1) Existing technical solutions fail to integrate the adjustment of train timetables and EMU routes, resulting in limited practicality and completeness of the adjustment schemes. When making emergency adjustments to high-speed railway operation plans, existing technical solutions are mostly limited to adjusting train timetables, without integrating the adjustment of train connection relationships, without considering the activation of standby trains, or without considering the return of EMUs to the depot to ensure the next day's operation. Adjustment schemes proposed using existing technologies may lead to improper EMU connection in practical applications, making them impossible to implement. The resulting adjustment schemes lack completeness, have low practicality, and cannot support the actual needs of train operation adjustments.

[0007] (2) Existing technical solutions give little consideration to passenger demand and generally use simplified methods to express demand. For example, passenger flow for canceled trains is always considered a direct loss, and for delayed trains, it is assumed that all passengers (including those who have not yet boarded) insist on traveling on the original train, ignoring passengers' independent decision-making regarding refunds and changes. The expression of passenger demand is often reflected in the objective function in the form of aggregated indicators, such as using train delay time to represent passenger delay time, lacking a precise expression of changes in passenger distribution under passengers' independent refund and change decisions. In reality, once the train operation plan changes due to a sudden operational interruption, passengers at different stages of travel and choosing trains with different attributes may make different travel adjustment decisions, resulting in differences in the effectiveness of different adjustment schemes in meeting transportation demand. The existing technology's way of expressing passenger demand fails to accurately depict passengers' travel adjustment decisions, resulting in a lack of accurate estimates of changes in passenger distribution on trains and related ticket revenue under train operation adjustment conditions, thus failing to support the effectiveness and rationality of train operation plan adjustments.

[0008] (3) Existing technical solutions fail to generate rebooking suggestions based on passengers' rebooking intentions. For example, they do not redistribute passenger flow for cancelled trains, ignore potential train transport capacity, and fail to provide a complete solution for dealing with sudden operational disruptions. Summary of the Invention

[0009] The embodiments of the present invention provide a method for emergency adjustment of train operation plans that takes into account passenger refund and change behavior, so as to effectively control the loss of ticket revenue and additional operating costs caused by sudden operation interruption and improve the emergency response level of high-speed rail.

[0010] To achieve the above objectives, the present invention adopts the following technical solution.

[0011] A method for emergency adjustment of train operation plans that takes into account passenger refund and change behavior includes:

[0012] Obtain the original train timetable, as well as route planning data, ticket booking data, interruption scenario data, and passenger refund and change intention data;

[0013] Considering the possible refund and rebooking behaviors of passengers under different train schedule adjustment strategies, an integrated adjustment model of train timetable and EMU route is constructed with the goal of minimizing ticket revenue loss and minimizing EMU operating costs.

[0014] The original train timetable, route plan data, ticket booking data, interruption scenario data, and passenger refund / rescheduling intention data are input into the integrated adjustment model of train timetable and EMU route to calculate the proposed adjustment scheme for high-speed train operation plan and the corresponding passenger rescheduling scheme.

[0015] Preferably, considering the possible refund and change behaviors of passengers under different train schedule adjustment strategies and the corresponding changes in passenger flow, an integrated adjustment model of train timetable and EMU route is constructed with the goal of minimizing ticket revenue loss and minimizing EMU operating costs, including:

[0016] Considering the possible refund and rebooking behaviors of passengers under different train adjustment strategies and the corresponding changes in passenger flow, an integrated adjustment model of train timetable and EMU route is constructed with the goal of minimizing ticket revenue loss and minimizing EMU operating costs.

[0017] Define the set and index, parameters, intermediate variables and decision variables of the integrated adjustment model of train timetable and EMU route, and set the objective function and constraints of the integrated adjustment model of train timetable and EMU route.

[0018] Preferably, the set and index, parameters, intermediate variables, and decision variables defining the integrated adjustment model of the train timetable and EMU route include:

[0019] The collection and index of the integrated adjustment model for train timetables and EMU routes include:

[0020]

[0021]

[0022] The parameters of the integrated adjustment model for train timetables and EMU routes include:

[0023]

[0024]

[0025] The intermediate variables of the integrated adjustment model for train timetables and EMU routes include:

[0026]

[0027] The decision variables of the integrated adjustment model for train timetables and EMU routes include:

[0028]

[0029] Preferably, the objective function and constraints for setting the integrated adjustment model of the train timetable and EMU route include:

[0030] When an interruption occurs, the train is delayed, and the loss of ticket revenue caused by passengers choosing to leave the railway system is calculated using formula (1); when an interruption occurs, the loss of ticket revenue caused by passengers who choose to leave the railway system without being offered rebooking services by other trains is calculated using formula (2), and the total loss of ticket revenue is expressed using formula (3).

[0031]

[0032] f1 = f in,1 +f in,2 (3)

[0033] In the formula, CAN r Q represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. x LT represents the number of people in passenger group x; x Let LC represent the probability that passenger group x will continue to wait after a train delay; x QS represents the ticket price for passenger group x; r',r,x This represents the number of passengers x in train r who are actually assigned to train r'.

[0034] Equation (4) represents the fixed cost of operating the EMU, Equation (5) represents the variable cost of operating the EMU, and Equation (6) represents the total cost of operating the EMU by multiplying the length of the overall operating line by the unit mileage cost.

[0035]

[0036] In the formula, FC represents the fixed cost of operating one EMU as a rolling stock (including crew, daily wear and tear, and maintenance); |R| represents the total number of trains in the planned operation schedule; CAN r This represents a 0-1 variable; 1 for train number r if it has not been cancelled, and 0 otherwise. r,r' 0-1 variables represent the EMU train number r that continues to serve the next train number r', and 0 otherwise; UC represents the unit mileage cost of the EMU train operation; DS r This represents the distance traveled by train number r;

[0037] The objective function for the integrated adjustment model of train timetable and EMU route is:

[0038] minf=α1×f1+α2×f2 (7)

[0039] α1 and α2 are used as weights in the objective function for passenger ticket revenue loss and EMU operating cost;

[0040] The constraints of the objective function of the integrated adjustment model of train operation diagram and EMU route include relevant constraints at the train operation diagram level. Equations (8)-(10) represent the fixed departure and arrival time constraints. If a train is not affected by the interruption ahead and it departs before the interruption ends, such trains are set as fixed trains. Equation (8) indicates that it is not canceled. Equations (9) and (10) indicate that its actual departure and arrival time is the same as the scheduled departure and arrival time.

[0041]

[0042] In the formula, R G Let r ∈ R be the set of trains in the planned operation chart that do not change their scheduled times. G J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This indicates the actual departure time of train number r at station j; This indicates the scheduled departure time of train number r at station j; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j;

[0043] Equations (11)-(14) represent the departure and arrival time change constraints, Equations (11)-(12) are the methods for handling the cancellation of train safety intervals, indicating that if the train is cancelled after interruption, its actual departure and arrival time is set to one day after the scheduled departure and arrival time; Equations (13)-(14) indicate that the actual departure and arrival time of trains that are not cancelled has a one-day timetable constraint.

[0044]

[0045] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r M1 represents a sufficiently large positive number, taken as 1440; M represents an infinitely large positive integer; CAN r The variable is 0-1; it is 1 if train number r has not been cancelled, and 0 otherwise. This indicates the actual departure time of train number r at station j; This indicates the scheduled departure time of train number r at station j; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j;

[0046] Equations (15)-(17) indicate that the constraints are not lifted for trains en route;

[0047]

[0048] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; CAN r The variable is 0-1; it is 1 if train number r has not been cancelled, and 0 otherwise. INA Indicates the start time of the line interruption; Indicates that train number r is at the station The actual departure time; Indicates that train number r is at the station The scheduled departure time is as shown in the diagram; Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is fixed on the map;

[0049] Equations (18)-(19) represent the time constraints for stopping at stations;

[0050]

[0051] In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; This represents the set of all stations through which train r passes in the planned operation diagram. j E- Indicates the preceding station index of the interrupted section; This indicates the actual departure time of train number r at station j; This indicates the actual arrival time of train r at station j; Indicates that train number r is at the station The scheduled departure time; t INA Indicates the start time of the line interruption;

[0052] Equation (20) represents the earliest departure time constraint for trains directly affected by the interruption;

[0053]

[0054] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; t INA Indicates the start time of the line interruption; t INZIndicates the end time of the line interruption; This indicates that train number r is at station J. E- The chart shows the departure time; M represents an infinite positive integer; CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise.

[0055] Equations (21)-(22) represent the interval operation constraints;

[0056]

[0057] In the formula, R UP Let R represent the set of all upbound trains in the planned operation graph, where r∈R UP ;R DN This represents the set of all downlink trains in the planned operation chart. r∈ R DN J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r ; This indicates the actual departure time of train number r at station j; This represents the fixed travel time of train r between station j and station j+1. This indicates the fixed travel time of train number r between station j-1 and station j in the southbound direction;

[0058] Equation (23) represents the train stopping time constraint;

[0059]

[0060] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r ; This indicates the actual departure time of train number r at station j; This indicates the actual arrival time of train r at station j; t MIN Indicates the shortest possible stop time for a train at the station;

[0061] Equations (24)-(29) represent safety interval constraints, and equations (26) and (29) represent that a group of up / down trains operating in the same section must have morning / evening differences;

[0062]

[0063]

[0064] In the formula, S represents the set of train operating sections, s∈S; R UPLet R represent the set of all upbound trains in the planned operation graph, where r∈R UP ;R DN Let R represent the set of all downlink trains in the planned operation graph, where r∈R DN J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r I1 represents the departure interval between adjacent trains; I2 represents the arrival interval between adjacent trains. This indicates the actual departure time of train number r at station j; Indicates the actual arrival time of train r at station j; M represents an infinite positive integer; O r,r',s This represents a 0-1 variable, where 1 is the value for train number r within interval s if it runs before r', and 0 otherwise.

[0065] Relevant constraints at the EMU (Electric Multiple Unit) route level

[0066] Equation (30) represents the variable coupling constraint;

[0067]

[0068] In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise.

[0069] Equations (31) and (32) represent uniqueness constraints. Equation (31) means that for any given train number, the EMU that serves it can be used for at most one subsequent train number. Equation (32) means that for any given train number, the EMU that serves it can be used for at most one other train number.

[0070]

[0071] In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise.

[0072] Equation (33) represents the spatial connection constraint. When there is a train connection relationship between trains, it must be ensured that the end point of the previous train and the starting point of the next train are the same.

[0073]

[0074] In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise. This represents the index of the originating station j for train number r; This represents the index of the station j to which train number r terminates;

[0075] Equation (34) represents the time continuity constraint, which means that after a train has completed one trip, it needs a certain amount of preparation time before it can start to take on the next trip.

[0076]

[0077] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; M represents an infinite positive integer; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise. Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station Actual departure time; t PR This indicates the preparation time required for the train to proceed with the next train service after it has reached the final stop of this train service.

[0078] Equation (35) indicates the vehicle type continuity constraint, which means that only vehicles of the same type can have a train route continuity.

[0079]

[0080] In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; 1 indicates that the EMU train number r is connected to train number r', and 0 indicates otherwise. NS r This indicates the train formation type for train number r in the planned operation diagram;

[0081] Equation (36) represents the initial number constraint of the vehicle undercarriage;

[0082]

[0083] In the formula, J AZ Let J represent the set of stations with originating and terminating functions in the planned operation diagram, j∈J. AZ ;r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the number of trains originating from station j and of train formation type m in the planned operation diagram, where m = 1, 2; This indicates the number of originating type m EMUs at station j in the planned operation diagram, where m = 1, 2; This represents the set of trains originating from station j and with train formation type m in the planned operation diagram.

[0084] Equation (37) represents the constraint on the number of final destination stations for the train carriages;

[0085]

[0086] In the formula, J AZ Let J represent the set of stations with originating and terminating functions in the planned operation diagram, j∈J. AZ ;r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the number of trains that terminate at station j and have train formation type m in the planned operation diagram, where m = 1, 2; This indicates the number of type m EMUs originating from station j on the next day in the planned operation diagram, where m = 1, 2; This represents the set of trains with destination station j and train formation type m in the planned operation diagram.

[0087] Constraints related to passenger flow redistribution

[0088] Equation (38) represents the variable coupling constraint;

[0089]

[0090] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; 1 represents train number r if it has not been cancelled, and 0 otherwise. ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise.

[0091] Equation (39) represents the stop constraint;

[0092]

[0093] In the formula, R represents the set of all train services in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; Represents a 0-1 variable, train number r At the station A value of 1 indicates a stop, otherwise a value of 0. Represents a 0-1 variable, train number r At the station 1 indicates a stop, 0 indicates otherwise; ME r',r,x Represents a 0-1 variable, train number r Passenger demand x is assigned as 1 by train number r', otherwise it is 0;

[0094] Equation (40) represents the time constraint:

[0095]

[0096] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; ME r',r,x J represents a 0-1 variable, where the passenger demand x for train r is assigned a value of 1 by train r', and 0 otherwise; r,x Let J represent the set of stops for passenger group x of train r in the planned operation diagram, where j∈J. r,x M represents an infinite positive integer; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j;

[0097] Equation (41) represents the uniqueness constraint:

[0098]

[0099] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise.

[0100] Equations (42)-(44) represent passenger delay acceptance constraints, and equations (42)-(43) use The actual delay time of the passenger is represented by equation (44), which represents the passenger's acceptance of the delay when the actual late time falls within a certain time period.

[0101]

[0102]

[0103] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the actual delay time of the train carried by passenger group x. Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is determined by the graph; M1 represents a sufficiently large positive number, taken as 1440; t k LT represents the right time of time period k; x This represents the probability that passenger group x will continue to wait after the train is delayed; This represents the delay tolerance of passenger x during time period k;

[0104] Equations (45)-(47) represent passenger rebooking acceptance constraints, and equations (45)-(46) use... The actual delay time caused by the passenger's rebooking is represented by equation (47), which represents the passenger's acceptance probability when the actual delay time falls within a certain time period.

[0105]

[0106] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; 1 represents train number r if it has not been cancelled, and 0 otherwise. ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise. This represents the overall actual delay time for passenger group x if they need to change trains; Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is determined by the graph; M1 represents a sufficiently large positive number, taken as 1440; t k GT represents the right time of time interval k; x This represents the probability that passenger group x agrees to rebook onto a later train. This indicates the rebooking acceptance rate for passenger x during time period k;

[0107] Formula (48) represents the number of remaining seats on the rebooked train;

[0108]

[0109] In the formula, R represents the set of all train services in the planned operation diagram, r∈R; S represents the set of train service operating sections, s∈S; CA represents the upper limit of seating capacity of the EMU (Electric Multiple Unit) serving the train service; Q x LT represents the number of people in passenger group x; x QY represents the probability that passenger group x will continue to wait after a train delay; r,s This indicates the remaining seats for train number r within the interval s;

[0110] Equation (49) represents the actual number of passengers redistributed to a single passenger group. If a certain rebooking suggestion actually serves a certain passenger group of another train that is to be cancelled, then the total number of passengers actually served is less than or equal to the total number of the original passenger group that accepted the rebooking.

[0111]

[0112] In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; Q x ME represents the number of people in passenger group x; r',r,x This represents a 0-1 variable, where the passenger demand x for train r is assigned a value of 1 by train r', and a value of 0 otherwise; GT x QS represents the probability that passenger group x agrees to rebook onto a later train; r',r,x This represents the number of passengers x in train r who are actually assigned to train r'.

[0113] Formula (50) indicates the limit on the actual number of passengers served by the rebooked train. The remaining number of seats available for rebooking should be greater than or equal to the sum of all passengers reassigned to the train to be cancelled.

[0114]

[0115] In the formula, R represents the set of all train services in the planned operation diagram, r∈R; S represents the set of train service operating intervals, s∈S; QS r',r,x QY represents the number of passengers in passenger group x of train number r who are actually assigned to train number r'. r,s This indicates the remaining seats for train number r within the interval s;

[0116] Linearization: Equations (63)-(64) are linearized expressions of equation (30):

[0117]

[0118]

[0119] Equations (65)-(66) are linearized expressions of equation (33):

[0120]

[0121] Equations (67)-(68) are linearized expressions of equation (35):

[0122]

[0123] Equations (69)-(70) are linearized expressions of equation (38):

[0124]

[0125] Equations (71)-(72) are linearized expressions of equation (39):

[0126]

[0127] Preferably, the step of inputting the original train timetable, route plan data, ticket booking data, interruption scenario data, and passenger refund / change intention data into the integrated adjustment model of the train timetable and EMU route to calculate the high-speed train operation plan adjustment proposal and the corresponding passenger change proposal includes:

[0128] In solving the integrated adjustment model of the train timetable and EMU route, the commercial solver Gurobi is used. The objective function and various constraints in the integrated adjustment model of the train timetable and EMU route are converted into the commercial solver Gurobi through a fixed code language. The original train timetable, as well as route plan data, ticket booking data, interruption scenario data, and passenger refund and change intention data are input into the commercial solver Gurobi for solving. The commercial solver Gurobi outputs the high-speed rail train operation plan adjustment suggestions and corresponding passenger change suggestions. The train operation plan adjustment suggestions include the integrated adjustment scheme of the train timetable and route and the hot standby train activation suggestion scheme, and consider the return of EMUs to the depot after the end of the day's operation to ensure the continued operation the next day.

[0129] As can be seen from the technical solutions provided by the embodiments of the present invention above, the method of the present invention ensures the reasonable continuity of the adjusted train operation line through integrated decision-making, supports the rematch of supply and demand under the transfer and loss of passenger flow by accurately depicting passenger refund and change behavior, and makes full use of the train potential through change suggestion schemes, thereby providing a complete and effective train operation plan adjustment scheme, and improving the scientificity, applicability and feasibility of the emergency adjustment method for train operation.

[0130] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of the invention. Attached Figure Description

[0131] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0132] Figure 1 This is a simplified schematic diagram of the integrated result of railway timetable and route planning provided by an embodiment of the present invention;

[0133] Figure 2 A schematic diagram of a railway station section provided in an embodiment of the present invention;

[0134] Figure 3This invention provides an original train timetable and route plan.

[0135] Figure 4 This is a diagram illustrating a proposed scheme for adjusting a high-speed train operation plan, provided as an embodiment of the present invention. Detailed Implementation

[0136] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0137] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or couplings. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items.

[0138] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as herein.

[0139] To facilitate understanding of the embodiments of the present invention, the following will provide further explanation and description with reference to the accompanying drawings and several specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0140] This invention provides an emergency adjustment method for high-speed rail train operation plans that considers passenger refund and rebooking behavior. For scenarios of sudden one-way operational disruptions on high-speed rail, it considers possible refund and rebooking behaviors and corresponding passenger flow changes under different train adjustment strategies. An integrated adjustment model of train timetable and train route planning is constructed with the goal of minimizing ticket revenue loss and train operation costs. Using original train timetable and route planning data, ticket booking data, and disruption scenario data as inputs, the constructed integrated adjustment model calculates suggested adjustments to the high-speed rail train operation plan and corresponding passenger rebooking suggestions. These suggested adjustments include an integrated adjustment scheme for the train timetable and route planning, and a suggestion for activating standby trains. The method also considers the return of trains to the depot after the end of the day's operation to ensure continued operation the following day.

[0141] The processing flow of an emergency adjustment method for high-speed train operation plans that takes into account passenger refund and change behavior provided in this embodiment of the invention is as follows: Figure 1 As shown, the processing steps include the following:

[0142] Step S1: Obtain the original train timetable and route plan data, ticket booking data, interruption scenario data, and passenger refund / change intention data, etc.

[0143] Step S2: Consider the possible refund and rebooking behaviors of passengers under different train adjustment strategies and the corresponding changes in passenger flow. With the goal of minimizing ticket revenue loss and minimizing the operating cost of EMU trains, construct an integrated adjustment model of train timetable and EMU train routes.

[0144] Define the variables and symbols for the integrated adjustment model of train timetable and EMU route.

[0145] Sets and Indexes

[0146]

[0147]

[0148] parameter

[0149]

[0150] intermediate variables

[0151]

[0152] Decision variables

[0153]

[0154] Set the objective function of the integrated adjustment model for train timetable and EMU route.

[0155] Ticket revenue loss: When an interruption occurs, trains may be canceled or delayed. There will be two types of passenger loss within the railway system. The first type is passengers who cannot accept the delay due to train delays and choose to leave the railway system. The second type is passengers who are not offered rebooking services for other trains but whose trains are to be canceled. In this case, they will also choose to leave the railway system.

[0156] From the perspective of passengers, leaving the railway system means a decrease in satisfaction, which will also directly lead to a loss of ticket revenue. Therefore, to minimize the loss of ticket revenue, Equations (1) and (2) represent the loss of ticket revenue for these two types of passengers, respectively, and Equation (3) represents their sum.

[0157]

[0158] f1 = f in,1 +f in,2 (3)

[0159] EMU operating cost: Equation (4) represents the fixed cost of operating an EMU. In a timetable with the same number of train services, each additional connection between train services will reduce the input of one train set. Therefore, the formula is to subtract the number of EMU connections from the remaining train services in the timetable, and then multiply it by the fixed operating cost of each EMU to obtain the total fixed cost. Equation (5) represents the variable cost of operating an EMU. It is calculated by multiplying the overall length of the operating line by the unit mileage cost. Equation (6) represents the total cost of operating an EMU.

[0160]

[0161] f2=f co,1 +f co,2 (6)

[0162] Overall objective function

[0163] Equation (7) represents the overall objective of the model. From the perspective of passengers, leaving the railway system represents a decrease in satisfaction and will directly lead to a loss of ticket revenue, so the goal is to minimize the loss of ticket revenue. From the perspective of the operating company, since the operation of high-speed trains requires costs, it directly leads to an increase in operating costs, so the goal is also to minimize the operating costs of high-speed trains. α1 and α2 are set as the weights of the objective function for the loss of ticket revenue and the operating costs of high-speed trains, respectively.

[0164] minf=α1×f1+α2×f2 (7)

[0165] Set constraints for the objective function

[0166] Relevant constraints at the train timetable level

[0167] Equations (8)-(10) represent fixed departure and arrival time constraints. In order to minimize the associated impact of interruptions, if a train is not affected by the interruption ahead and departs before the interruption ends, such trains are set as fixed trains. Equation (8) indicates that it is not canceled, and Equations (9) and (10) indicate that its actual departure and arrival time is the same as the scheduled departure and arrival time.

[0168]

[0169] Equations (11)-(14) represent the departure and arrival time change constraints. Equations (11)-(12) are the methods for handling the cancellation of train safety intervals, indicating that if the train is cancelled after interruption, its actual departure and arrival time is set to one day after the scheduled departure and arrival time; Equations (13)-(14) indicate that the actual arrival and departure times of trains that are not cancelled have a one-day timetable constraint.

[0170]

[0171] Equations (15)-(17) indicate that the constraints on trains in transit are not cancelled. If the train has already departed from the originating station when the interruption occurs, and it is already carrying passengers, cancellation would involve difficulties such as clearing passengers, organizing passengers on-site, and using the opposite main line for a turnaround. Therefore, for such trains, the decision is made to wait at an appropriate station and delay departure, and the arrival and departure times do not change at the originating station.

[0172]

[0173] Equations (18)-(19) represent the station stop time constraints. For through stations, trains should not have stop time. Equation (19) indicates that when the departure time of a train is before the interruption start time, it should have this constraint at through stations other than the station preceding the interruption.

[0174]

[0175]

[0176] Equation (20) represents the earliest departure time constraint for trains directly affected by the interruption. After an interruption occurs, some trains will be running in the section that is within the interruption period. If the train is not canceled, the actual departure time of the train from the station preceding it in the interruption section shall not be earlier than the end time of the interruption.

[0177]

[0178] Equations (21)-(22) represent the section operation constraints. The pure running time of the train within the section is fixed, and slow travel within the section is prohibited, as it would affect the overall train operation order.

[0179]

[0180] Equation (23) represents the train stop time constraint. Due to passenger boarding and alighting demand, the time interval between train departures and arrivals at the stopping station should not be less than the minimum stop time.

[0181]

[0182] Equations (24)-(29) represent safety interval constraints. Since trains do not overtake within a section, if a train is running before another train in a certain section, then it must be "first to arrive" and must meet the safety arrival and departure interval constraints. Equations (26) and (29) indicate that a group of up / down trains running in the same section must have morning and evening differences.

[0183]

[0184] Relevant constraints at the EMU (Electric Multiple Unit) route level

[0185] Equation (30) represents the variable coupling constraint. If two train sets are connected by a route, neither train can be cancelled.

[0186]

[0187] Equations (31) and (32) represent uniqueness constraints. Equation (31) indicates that for any given train number, the EMU that serves it can be used for at most one subsequent train number; Equation (32) indicates that for any given train number, the EMU that serves it can be used for at most one other train number.

[0188]

[0189] Equation (33) represents the spatial connection constraint. When there is a train connection relationship between trains, it must be ensured that the destination of the previous train and the starting point of the next train are the same.

[0190]

[0191] Equation (34) represents the time continuity constraint. After completing one train service, the EMU needs a certain amount of preparation time before it can start operating the next train service.

[0192]

[0193] Equation (35) represents the train model continuity constraint. Only train models can generate EMU route continuity.

[0194]

[0195] Equation (36) represents the constraint on the number of trains originating from the train set. When an interruption occurs, there is a limit to the number of trains originating from each station, which must not exceed the total number of original EMU train sets and hot standby cars at that station.

[0196]

[0197] Equation (37) represents the constraint on the number of train carriages arriving at the final station. After the interruption adjustment is completed, there is a limit to the number of train carriages existing at each station, which must not be less than the number of trains required for the next stage of departure at that station.

[0198]

[0199] Constraints related to passenger flow redistribution

[0200] Equation (38) represents the variable coupling constraint. For a train that is to be cancelled, the train that can be used as a rebooking suggestion must be a reserved train.

[0201]

[0202] Equation (39) represents the stop constraint. If a train with rebooking service serves a passenger group x of a canceled train, then the train must stop at the originating or terminating station of this passenger group.

[0203]

[0204] Equation (40) represents the time constraint. If a train service is to be cancelled, it is necessary to ensure that its passengers have arrived at the station before other train services can provide rebooking services.

[0205]

[0206] Equation (41) represents the uniqueness constraint. To facilitate unified passenger boarding and alighting arrangements, each passenger group x can only be actually assigned once and cannot be reassigned. If a passenger cannot be rebooked, it is directly considered a passenger loss.

[0207]

[0208] Equations (42)-(44) represent passenger delay acceptance constraints. Equations (42)-(43) use This indicates the actual delay time for passengers.

[0209] Equation (44) represents the passenger's acceptance of the delay when the actual late arrival time falls within a certain time period.

[0210]

[0211] Equations (45)-(47) represent passenger rebooking acceptance constraints. Equations (45)-(46) use... This represents the actual delay time caused by the passenger's rebooking. Equation (47) represents the passenger's acceptance probability when this actual delay time falls within a certain time period.

[0212]

[0213] Equation (48) represents the number of remaining seats on the rebooked train. In the event of a disruption, some passengers may leave the railway system because they cannot accept the delay. Therefore, each train has a different number of remaining seats in each section, which is represented as the total number of seats for the train minus the original number of passengers remaining in this section.

[0214]

[0215] Equation (49) represents the actual number of passengers redistributed to a single passenger group. If a suggested rebooking service actually serves a passenger group from another train that is to be cancelled, then the total number of passengers actually served is less than or equal to the total number of the original passenger group that accepted the rebooking.

[0216]

[0217] Equation (50) represents the limit on the actual number of passengers served by the rebooked train. The number of remaining seats available for rebooking should be greater than or equal to the sum of all passengers reassigned to the train to be cancelled.

[0218]

[0219] Linearization: Equations (63)-(64) are linearized expressions of equation (30):

[0220]

[0221] Equations (65)-(66) are linearized expressions of equation (33):

[0222]

[0223] Equations (67)-(68) are linearized expressions of equation (35):

[0224]

[0225] Equations (69)-(70) are linearized expressions of equation (38):

[0226]

[0227] Equations (71)-(72) are linearized expressions of equation (39):

[0228]

[0229] Step S3: Input the original train timetable and route plan data, passenger ticket booking data, and interruption scenario data into the above-mentioned integrated adjustment model of train timetable and EMU route, and calculate the proposed adjustment scheme for high-speed train operation plan and the corresponding passenger rebooking scheme. The proposed adjustment scheme for train operation plan includes the integrated adjustment scheme of train timetable and route and the proposed scheme for the activation of hot standby trains, and considers the return of EMUs to the depot after the end of the day's operation to ensure the continued use the next day.

[0230] During the model solving process, the commercial solver Gurobi is used. The objective function and various constraints in the above mathematical model are converted into a fixed code language and written into the solver. Then, the original train operation plan, route plan data, passenger ticket booking data, and interruption scenario data are input into the solver to obtain the output high-speed rail train operation plan adjustment suggestions and corresponding passenger rebooking suggestions. At this point, the solution is completed.

[0231] Example:

[0232] The method of the present invention will be described in more detail below through specific examples.

[0233] This embodiment selects a high-speed railway line with five stations: A, B, C, D, and E, and four train operating sections. Each section is 200km long, with A to E representing the up-line direction and the opposite direction representing the down-line direction. Stations A, C, and E have both originating and terminating functions, meaning trains can connect at these stations. Figure 2 As shown.

[0234] In actual operation, sudden disruptions may cause train service interruptions, and the duration of these interruptions directly affects the formulation of overall adjustment plans. If a short-term interruption occurs, such as minor delays to a few trains, the high-speed rail's automatic dispatching and command system can automatically adjust train operation plans. Conversely, if a longer interruption occurs, such as a line interruption lasting a day or more, more complex adjustments are required, involving the rerouting and cancellation of numerous trains, and overall adjustments to the operation of multiple lines.

[0235] In the adjustment scenario of this invention, it is assumed that the sudden operational disruption occurs in the upstream direction from station B to station C at 8:40 AM, with an estimated duration of 3 hours and 50 minutes and an end time of 12:30 PM. In this context, considering passenger refund and rebooking behavior, integrated adjustment of train timetables and routes is particularly reasonable. By accurately depicting passenger refund and rebooking behavior, effective management of passenger flow transfer and loss can be achieved, thereby enabling a rematch between supply and demand. Furthermore, integrated adjustment ensures the scientific validity and practicality of the adjustment plan.

[0236] The original train timetable and route plan can be found here. Figure 3As shown, the above interruption scenario data can be found in [link to data]. Figure 3 As shown in the shaded area.

[0237] The passenger ticket reservation data reflects the number of passengers on board and the number of passengers scheduled to board. Table 1 shows the passenger flow data for upbound trains by OD, and Table 2 shows the passenger flow data for downbound trains by OD.

[0238] Table 1. Passenger Flow Data by Od / O Point for Upbound Trains (persons)

[0239]

[0240] Table 2 Passenger Flow Data for Downbound Trains by Od / Od (persons)

[0241]

[0242] Passenger refund and rebooking intention data are shown in Table 3 (for example, for passengers traveling within 1 hour, if the total train delay time is between 0.5 and 1 hour, 33.78% of passengers choose to accept the delay and not leave the railway system) and Table 4 (for example, for passengers arriving after 18:00, if the rebooked train arrives within 0.5 to 1 hour, then 66.32% of passengers choose to accept the rebooking and not leave the railway system). In practical applications, this data can be obtained through historical refund and rebooking data statistics or through questionnaires and other methods.

[0243] Table 3 Passenger Delay Acceptance Rate (%)

[0244]

[0245] Table 4 Passenger Acceptance of Flight Changes (%)

[0246]

[0247] The data was input into the model, and the model was solved using Gurobi software to obtain a proposed adjustment scheme for the high-speed rail train operation plan. Figure 4 The corresponding suggested rebooking options for passengers are shown in Table 5.

[0248] When the operation plan is adjusted, the up-direction train r4 is cancelled. The remaining seats of the passengers who intend to reschedule and the subsequent trains are checked. After the passenger flow is redistributed, the rescheduling suggestions for the original train r4 are output: passengers in AC and AE of r4 are advised to reschedule to r5; passengers in CE are advised to reschedule to r9. The specific rescheduling suggestions are shown in Table 5.

[0249] Table 5 Suggested Passenger Rebooking Options

[0250]

[0251] The following table lists the comparison values ​​of the objective function under different adjustment methods, as shown in Table 6.

[0252] Table 6. Horizontal Comparison Analysis of Objective Functions

[0253]

[0254] According to the solution results, compared with the traditional strategy of restoring and adjusting as soon as possible, the integrated adjustment method proposed in this technical solution has a total target reduction of 9.3%; compared with not considering rescheduling suggestions, its total target reduction is about 4.0%; compared with simply pursuing the minimization of EMU operating costs, its total target reduction is 58.7%; compared with simply pursuing the minimization of passenger ticket revenue loss, its total target reduction is 5.9%. The actual increase in cost is the total difference between passenger ticket revenue loss (target 1) and EMU operating costs (target 2) in the two adjustment methods.

[0255] Based on the above analysis, it can be concluded that this technical solution has a practical effect of reducing costs and increasing efficiency in addressing the issue of adjusting train operation plans after interruptions. It can effectively reduce passenger ticket revenue losses and reduce the operating costs of high-speed trains, and is of great significance for the research on emergency adjustments to high-speed train operation plans.

[0256] In summary, the present invention embodiment (1) considers the integrated adjustment and optimization of the timetable and the route, which is more comprehensive than the existing research that only considers the single-level adjustment of the timetable. It comprehensively considers the activation of hot standby cars and the return of the train car to the section on the same day to ensure the use of the train car car for the starting train the next day, which is more in line with the actual adjustment needs of the railway site.

[0257] (2) This invention considers passengers' voluntary refund and rebooking behavior. Based on the patterns of passenger refund and rebooking behavior under different conditions such as train delays and cancellations, it reasonably expresses the passenger flow loss and transfer situation under different adjustment schemes, thereby realizing the operation plan adjustment that conforms to passenger flow demand and its changing patterns. Compared with operation plan adjustment studies that do not consider the demand side, the method proposed in this invention can more realistically reflect the objective laws of passenger flow loss and transfer under actual conditions.

[0258] (3) This invention takes into account the passengers’ willingness to change their tickets and the remaining seats on relevant trains, and makes a decision on the passenger change plan through passenger flow redistribution, providing a complete emergency adjustment solution.

[0259] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0260] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention, 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 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 various embodiments or some parts of the embodiments of the present invention.

[0261] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the description of the method embodiments. The apparatus and system 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 creative effort.

[0262] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for emergency adjustment of train operation plans that takes into account passenger refund and change behavior, characterized in that, include: Obtain the original train timetable, as well as route planning data, ticket booking data, interruption scenario data, and passenger refund and change intention data; Considering the possible refund and rebooking behaviors of passengers under different train schedule adjustment strategies, an integrated adjustment model of train timetable and EMU route is constructed with the goal of minimizing ticket revenue loss and minimizing EMU operating costs. The original train timetable, route plan data, ticket booking data, interruption scenario data, and passenger refund / change intention data are input into the integrated adjustment model of train timetable and EMU route to calculate the high-speed train operation plan adjustment proposal and the corresponding passenger change proposal. Considering potential refund and rebooking behaviors and corresponding passenger flow changes under different train schedule adjustment strategies, an integrated adjustment model for train timetables and EMU routes is constructed with the objectives of minimizing ticket revenue loss and minimizing EMU operating costs. This model includes: Considering the possible refund and rebooking behaviors of passengers under different train adjustment strategies and the corresponding changes in passenger flow, an integrated adjustment model of train timetable and EMU route is constructed with the goal of minimizing ticket revenue loss and minimizing EMU operating costs. Define the set and index, parameters, intermediate variables and decision variables of the integrated adjustment model of train timetable and EMU route, and set the objective function and constraints of the integrated adjustment model of train timetable and EMU route; The definition of the integrated adjustment model for train timetables and EMU routes includes the set and index, parameters, intermediate variables, and decision variables, including: The collection and index of the integrated adjustment model for train timetables and EMU routes include: The parameters of the integrated adjustment model for train timetables and EMU routes include: The intermediate variables of the integrated adjustment model for train timetables and EMU routes include: The decision variables of the integrated adjustment model for train timetables and EMU routes include: The objective function and constraints for setting the integrated adjustment model of the train timetable and EMU route include: When an interruption occurs, the train is delayed, and the loss of ticket revenue caused by passengers choosing to leave the railway system is calculated using formula (1); when an interruption occurs, the loss of ticket revenue caused by passengers who choose to leave the railway system without being offered rebooking services by other trains is calculated using formula (2), and the total loss of ticket revenue is expressed using formula (3). f1=f in,1 +f in,2 (3) In the formula, CAN r Q represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. x LT represents the number of people in passenger group x; x Let LC represent the probability that passenger group x will continue to wait after a train delay; x QS represents the ticket price for passenger group x; r',r,x This represents the number of passengers x in train r who are actually assigned to train r'. Equation (4) represents the fixed cost of operating the EMU, Equation (5) represents the variable cost of operating the EMU, and Equation (6) represents the total cost of operating the EMU by multiplying the length of the overall operating line by the unit mileage cost. f2=f co,1 +f co,2 (6) In the formula, FC represents the fixed cost of operating one EMU as its rolling stock; |R| represents the total number of train trips in the planned operation schedule; CAN r This represents a 0-1 variable; 1 for train number r if it has not been cancelled, and 0 otherwise. r,r' 0-1 variables represent the EMU train number r that continues to serve the next train number r', and 0 otherwise; UC represents the unit mileage cost of the EMU train operation; DS r This represents the distance traveled by train number r; The objective function for the integrated adjustment model of train timetable and EMU route is: minf=α1×f1+α2×f2 (7) α1 and α2 are used as weights in the objective function for passenger ticket revenue loss and EMU operating cost; The constraints of the objective function of the integrated adjustment model of train operation diagram and EMU route include relevant constraints at the train operation diagram level. Equations (8)-(10) represent the fixed departure and arrival time constraints. If a train is not affected by the interruption ahead and it departs before the interruption ends, such trains are set as fixed trains. Equation (8) indicates that it is not canceled. Equations (9) and (10) indicate that its actual departure and arrival time is the same as the scheduled departure and arrival time. In the formula, R G Let r ∈ R be the set of trains in the planned operation chart that do not change their scheduled times. G J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This indicates the actual departure time of train number r at station j; This indicates the scheduled departure time of train number r at station j; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j.

2. The method according to claim 1, characterized in that, The objective function and constraints for setting the integrated adjustment model of the train timetable and EMU route also include: Equations (11)-(14) represent the departure and arrival time change constraints, Equations (11)-(12) are the methods for handling the cancellation of train safety intervals, indicating that if the train is cancelled after interruption, its actual departure and arrival time is set to one day after the scheduled departure and arrival time; Equations (13)-(14) indicate that the actual departure and arrival time of trains that are not cancelled has a one-day timetable constraint. In the formula, R represents the set of all trains in the planned operation diagram, r∈R; J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r M1 represents a sufficiently large positive number, taken as 1440; M represents an infinitely large positive integer; CAN r The variable is 0-1; it is 1 if train number r has not been cancelled, and 0 otherwise. This indicates the actual departure time of train number r at station j; This indicates the scheduled departure time of train number r at station j; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j; Equations (15)-(17) indicate that the constraints are not lifted for trains en route; In the formula, R represents the set of all trains in the planned operation diagram, r∈R; CAN r The variable is 0-1; it is 1 if train number r has not been cancelled, and 0 otherwise. INA Indicates the start time of the line interruption; Indicates that train number r is at the station The actual departure time; Indicates that train number r is at the station The scheduled departure time is as shown in the diagram; Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is fixed on the map; Equations (18)-(19) represent the time constraints for stopping at stations; In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; This represents the set of all stations through which train r passes in the planned operation diagram. j E- Indicates the preceding station index of the interrupted section; This indicates the actual departure time of train number r at station j; This indicates the actual arrival time of train r at station j; Indicates that train number r is at the station The scheduled departure time; t INA Indicates the start time of the line interruption; Equation (20) represents the earliest departure time constraint for trains directly affected by the interruption; In the formula, R represents the set of all trains in the planned operation diagram, r∈R; t INA Indicates the start time of the line interruption; t INZ Indicates the end time of the line interruption; This indicates that train number r is at station J. E- The chart shows the departure time; M represents an infinite positive integer; CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. Equations (21)-(22) represent the interval operation constraints; In the formula, R UP Let R represent the set of all upbound trains in the planned operation graph, where r∈R UP ;R DN Let R represent the set of all downlink trains in the planned operation graph, where r∈R DN J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r ; This indicates the actual departure time of train number r at station j; This represents the fixed travel time of train r between station j and station j+1. This indicates the fixed travel time of train number r between station j-1 and station j in the southbound direction; Equation (23) represents the train stopping time constraint; In the formula, R represents the set of all trains in the planned operation diagram, r∈R; J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r ; This indicates the actual departure time of train number r at station j; This indicates the actual arrival time of train r at station j; t MIN Indicates the shortest possible stop time for a train at the station; Equations (24)-(29) represent safety interval constraints, and equations (26) and (29) represent that a group of up / down trains operating in the same section must have morning / evening differences; In the formula, S represents the set of train operating sections, s∈S; R UP Let R represent the set of all upbound trains in the planned operation graph, where r∈R UP ;R DN Let R represent the set of all downlink trains in the planned operation graph, where r∈R DN J r This represents the set of all stations along the route of train r in the planned operation diagram, where j∈J. r I1 represents the departure interval between adjacent trains; I2 represents the arrival interval between adjacent trains. This indicates the actual departure time of train number r at station j; Indicates the actual arrival time of train r at station j; M represents an infinite positive integer; O r,r',s This represents a 0-1 variable, where 1 is the value for train number r within interval s if it runs before r', and 0 otherwise. Relevant constraints at the EMU (Electric Multiple Unit) route level Equation (30) represents the variable coupling constraint; In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. Equations (31) and (32) represent uniqueness constraints. Equation (31) means that for any given train number, the EMU that serves it can be used for at most one subsequent train number. Equation (32) means that for any given train number, the EMU that serves it can be used for at most one other train number. In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise. Equation (33) represents the spatial connection constraint. When there is a train connection relationship between trains, it must be ensured that the end point of the previous train and the starting point of the next train are the same. In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise. This represents the index of the originating station j for train number r; This represents the index of the station j to which train number r terminates; Equation (34) represents the time continuity constraint, which means that after a train has completed one trip, it needs a certain amount of preparation time before it can start to take on the next trip. In the formula, R represents the set of all trains in the planned operation diagram, r∈R; M represents an infinite positive integer; r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is followed by train number r', and 0 otherwise. Indicates that train number r is at the station The actual arrival time; This indicates that train number r is at station J. r A's actual departure time; t PR This indicates the preparation time required for the train to proceed with the next train service after it has reached the final stop of this train service. Equation (35) indicates the vehicle type continuity constraint, which means that only vehicles of the same type can have a train route continuity. In the formula, R represents the set of all trains in the planned operation diagram, and r∈R; r r,r' This represents a 0-1 variable; 1 indicates that the EMU train number r is connected to train number r', and 0 indicates otherwise. NS r This indicates the train formation type for train number r in the planned operation diagram; Equation (36) represents the initial number constraint of the vehicle undercarriage; In the formula, J AZ Let J represent the set of stations with originating and terminating functions in the planned operation diagram, j∈J. AZ ;r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the number of trains originating from station j and of train formation type m in the planned operation diagram, where m = 1, 2; This indicates the number of originating type m EMUs at station j in the planned operation diagram, where m = 1, 2; This represents the set of trains originating from station j and with train formation type m in the planned operation diagram. Equation (37) represents the constraint on the number of final destination stations for the train carriages; In the formula, J AZ Let J represent the set of stations with originating and terminating functions in the planned operation diagram, j∈J. AZ ;r r,r' This represents a 0-1 variable; it is 1 if the EMU train number r is connected to train number r', and 0 otherwise. CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the number of trains that terminate at station j and have train formation type m in the planned operation diagram, where m = 1, 2; This indicates the number of type m EMUs originating from station j on the next day in the planned operation diagram, where m = 1, 2; This represents the set of trains with destination station j and train formation type m in the planned operation diagram. Constraints related to passenger flow redistribution Equation (38) represents the variable coupling constraint; In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; 1 represents train number r if it has not been cancelled, and 0 otherwise. ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise. Equation (39) represents the stop constraint; In the formula, R represents the set of all train services in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; Represents a 0-1 variable, where train number r is at the station. A value of 1 indicates a stop, otherwise a value of 0. Represents a 0-1 variable, where train number r is at the station. 1 indicates a stop, 0 indicates otherwise; ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise. Equation (40) represents the time constraint: In the formula, R represents the set of all trains in the planned operation diagram, r∈R; ME r',r,x J represents a 0-1 variable, where the passenger demand x for train r is assigned a value of 1 by train r', and 0 otherwise; r,x Let J represent the set of stops for passenger group x of train r in the planned operation diagram, where j∈J. r,x M represents an infinite positive integer; This indicates the actual arrival time of train r at station j; This indicates the scheduled arrival time of train number r at station j; Equation (41) represents the uniqueness constraint: In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise. Equations (42)-(44) represent passenger delay acceptance constraints, and equations (42)-(43) use The actual delay time of the passenger is represented by equation (44), which represents the passenger's acceptance of the delay when the actual late time falls within a certain time period. In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; it is 1 if train number r has not been cancelled, and 0 otherwise. This represents the actual delay time of the train carried by passenger group x. Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is determined by the graph; M1 represents a sufficiently large positive number, taken as 1440; t k LT represents the right time of time period k; x This represents the probability that passenger group x will continue to wait after the train is delayed; This represents the delay tolerance of passenger x during time period k; Equations (45)-(47) represent passenger rebooking acceptance constraints, and equations (45)-(46) use... The actual delay time caused by the passenger's rebooking is represented by equation (47), which represents the passenger's acceptance probability when the actual delay time falls within a certain time period. In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; CAN r This represents a 0-1 variable; 1 represents train number r if it has not been cancelled, and 0 otherwise. ME r',r,x Let x represent a 0-1 variable, where the passenger demand x for train r is assigned as 1 by train r', and 0 otherwise. This represents the overall actual delay time for passenger group x if they need to change trains; Indicates that train number r is at the station The actual arrival time; Indicates that train number r is at the station The arrival time is determined by the graph; M1 represents a sufficiently large positive number, taken as 1440; t k GT represents the right time of time interval k; x This represents the probability that passenger group x agrees to rebook onto a later train. This indicates the rebooking acceptance rate for passenger x during time period k; Formula (48) represents the number of remaining seats on the rebooked train; In the formula, R represents the set of all train services in the planned operation diagram, r∈R; S represents the set of train service operating sections, s∈S; CA represents the upper limit of seating capacity of the EMU (Electric Multiple Unit) serving the train service; Q x LT represents the number of people in passenger group x; x QY represents the probability that passenger group x will continue to wait after a train delay; r,s This indicates the remaining seats for train number r within the interval s; Equation (49) represents the actual number of passengers redistributed to a single passenger group. If a certain rebooking suggestion actually serves a certain passenger group of another train that is to be cancelled, then the total number of passengers actually served is less than or equal to the total number of the original passenger group that accepted the rebooking. In the formula, R represents the set of all trains in the planned operation diagram, r∈R; X represents the set of passenger groups, x∈X; Q x ME represents the number of people in passenger group x; r',r,x This represents a 0-1 variable, where the passenger demand x for train r is assigned a value of 1 by train r', and a value of 0 otherwise; GT x QS represents the probability that passenger group x agrees to rebook onto a later train; r',r,x This represents the number of passengers x in train r who are actually assigned to train r'. Formula (50) indicates the limit on the actual number of passengers served by the rebooked train. The remaining number of seats available for rebooking should be greater than or equal to the sum of all passengers reassigned to the train to be cancelled. In the formula, R represents the set of all train services in the planned operation diagram, r∈R; S represents the set of train service operating intervals, s∈S; QS r',r,x QY represents the number of passengers in passenger group x of train number r who are actually assigned to train number r'. r,s This indicates the remaining seats for train number r within the interval s; Linearization: Equations (63)-(64) are linearized expressions of equation (30): Equations (65)-(66) are linearized expressions of equation (33): Equations (67)-(68) are linearized expressions of equation (35): Equations (69)-(70) are linearized expressions of equation (38): Equations (71)-(72) are linearized expressions of equation (39):

3. The method according to claim 2, characterized in that, The process involves inputting the original train timetable, route plan data, ticket booking data, interruption scenario data, and passenger refund / change intention data into the integrated adjustment model of the train timetable and EMU route to calculate a suggested adjustment scheme for the high-speed train operation plan and corresponding suggested change schemes for passengers, including: In solving the integrated adjustment model of the train timetable and EMU route, the commercial solver Gurobi is used. The objective function and various constraints in the integrated adjustment model of the train timetable and EMU route are converted into the commercial solver Gurobi through a fixed code language. The original train timetable, as well as route plan data, ticket booking data, interruption scenario data, and passenger refund and change intention data are input into the commercial solver Gurobi for solving. The commercial solver Gurobi outputs the high-speed rail train operation plan adjustment suggestions and corresponding passenger change suggestions. The train operation plan adjustment suggestions include the integrated adjustment scheme of the train timetable and route and the hot standby train activation suggestion scheme, and consider the return of EMUs to the depot after the end of the day's operation to ensure the continued operation the next day.

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