An optimization method and system for shuttle bus scheduling in case of urban rail transit interruption

Abstract

The present invention belongs to the technical field of urban rail transit planning, and provides a method and system for optimizing the dispatching of shuttle buses for urban rail transit interruptions, including: obtaining the interrupted stations of urban rail transit; considering the passenger flow at the interrupted stations, determining the parking points of shuttle buses with the goal of minimizing the total site selection cost of the parking points of shuttle buses; according to the determined parking points of shuttle buses, considering the turning-back stations upstream and downstream of the interrupted stations of urban rail transit, and determining the routes of shuttle buses with the goal of minimizing the sum of the transportation cost of shuttle buses and the passenger delay cost, so as to complete the optimization of shuttle buses.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban rail transit planning, and particularly relates to a method and system for optimizing the dispatching of shuttle buses for urban rail transit interruptions. Background Art

[0002] The statements in this part only provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] Urban rail transit has become an important part of the public transportation system, providing passengers with efficient and convenient travel experiences. However, in recent years, with the occurrence of major natural disasters (such as earthquakes, typhoons, floods, etc.), urban rail transit has suffered huge losses. Reasonable and effective planning and construction of emergency transfer stations in the rail transit network are effective ways to reduce the harm and losses caused by disaster events and are also important links in urban and rural planning and construction. At the same time, the passenger flow of rail transit is relatively large. Once an urban rail transit line is interrupted due to an accident caused by a sudden disaster, a large number of passengers will inevitably be stranded at each interrupted station. When the number of stranded passengers reaches a certain scale and emergency transfer buses need to be used for transfer and evacuation, optimizing the evacuation route of the transfer buses and minimizing the impact of the line interruption on passengers' travel is the current research focus.

[0004] Regarding the problem of the location selection of emergency transfer buses under the condition of sudden subway interruptions, there are relevant studies on the optimal layout of emergency service facilities; for example: the three key aspects of accessibility, economy, and facility utilization efficiency can be comprehensively considered to construct a two-layer multi-objective refuge location-allocation model to solve the location-allocation problem; based on the vulnerable nodes in the transportation network, with the minimization of operating costs and the maximization of accessibility as the objectives, a two-objective optimization model is established to allocate backup emergency facility points for demand points to ensure the coverage allocation problem; considering the characteristic that the capacity of the site changes with time, a model is constructed with the objectives of maximizing the number of refuge victims accommodated and minimizing the number of refuge sites activated to minimize the impact of the disaster situation; according to the distribution of key waters of accidents in the jurisdiction, a mathematical model for the location selection of emergency rescue stations can be established to ensure the safety of the distribution of key waters of accidents in the jurisdiction.

[0005] The prior art can enrich and improve the site selection model by combining the demand characteristics of shelters; for example: by constructing an optimization model for the location selection of emergency facilities and material allocation based on coverage satisfaction and economy to solve the problem of balancing coverage and cost; proposing a site selection strategy for emergency shelters aiming at minimizing the perceived cost of victims' pain to minimize the losses of victims; quantifying the bounded rational choice behavior of residents through a multinomial logit model and introducing a utility function to describe the regret value, and analyzing the behavior tendency of residents with this as the site selection goal; considering the impact of secondary disasters on the needs of victims and proposing a three-stage site selection planning model to minimize the impact of disasters on victims as much as possible.

[0006] Most of the existing research on the site selection planning of emergency shelters focuses on the real situation during disasters, providing favorable theoretical support and practical guidance for the optimal layout of emergency service facilities; for example: deeply studying the method of systematically identifying and evaluating the location of shelters by combining factors such as flood risk and traffic evacuation; considering the uncertainty of road network damage during disasters, calculating the road damage rate to construct a model with the goal of minimizing the total area of shelters and the total evacuation distance, and optimizing the road network during disasters.

[0007] Generally speaking, in terms of site selection, most of the existing emergency rescue connection site selection models take construction cost, distance, arrival time, etc. as the objectives and constraints, but do not fully consider factors such as line passenger flow, line risk level, and line network planning; in terms of line optimization, the existing research mainly focuses on the design of connection lines and model optimization, rarely considering the coordination between buses and subway trains and the possible large passenger flow situation at subway stations, and even less related to the analysis of passengers' behavior. Summary of the Invention

[0008] To solve the above problems, the present invention proposes a method and system for optimizing the dispatching of connection vehicles for urban rail transit interruptions. In terms of site selection, it fully considers the passenger flow situation of the line and the overall line network planning, comprehensively considers the entire transportation line network, and establishes a planning model with the minimum site selection cost by taking the construction cost of parking points and the purchase cost of connection vehicles as the objectives for solution; in terms of line optimization, it optimizes the lines of connection buses by combining the analysis of passengers' behavior, fully considering the impact of subway trains and the possible large passenger flow situation, establishes a model with the goal of minimizing the vehicle evacuation cost and the passenger waiting cost, and combines it with the site selection cost for solution calculation, in order to provide theoretical support for the urban rail transit industry.

[0009] According to some embodiments, the first solution of the present invention provides a method for optimizing the dispatching of connection vehicles for urban rail transit interruptions, adopting the following technical solutions:

[0010] A method for optimizing the dispatching of connection vehicles for urban rail transit interruptions, comprising:

[0011] Obtain the interrupted stations of urban rail transit;

[0012] Considering the passenger flow of the interrupted stations, determine the pick-up and drop-off points of the shuttle buses with the goal of minimizing the total site selection cost of the pick-up and drop-off points;

[0013] According to the determined pick-up and drop-off points of the shuttle buses, considering the turning-back stations upstream and downstream of the interrupted stations of urban rail transit, determine the routes of the shuttle buses with the goal of minimizing the sum of the transportation cost of the shuttle buses and the passenger delay cost, and complete the optimization of the shuttle buses.

[0014] As a further technical limitation, the total site selection cost of the pick-up and drop-off points of the shuttle buses includes the site selection and construction cost of the pick-up and drop-off points and the purchase cost of the shuttle buses ; that is ; ; where represents the pick-up and drop-off point, represents the set of pick-up and drop-off points; represents whether a shuttle bus is set at the pick-up and drop-off point , when it means a shuttle bus is set at the pick-up and drop-off point , when it means no shuttle bus is set at the pick-up and drop-off point ; represents the fixed cost of the site selection of the pick-up and drop-off point , represents the purchase cost of the vehicle, is the number of standby vehicles at the pick-up and drop-off point .

[0015] As a further technical limitation, the transportation cost of the shuttle buses at least includes the transportation cost of the shuttle buses to evacuate passengers and the dispatch cost of the shuttle buses before arriving at the interrupted stations; that is ; where represents the expected value of the scenario ; represents the probability of the scenario occurring, represents the set of scenarios; represents the interrupted station; represents the rated passenger capacity of the shuttle bus; 、 、 respectively represent the number of passengers that can be evacuated by the shuttle bus per unit time on the three routes under the scenario ; 、 、 respectively represent the number of passengers that can be evacuated by the shuttle bus per unit time on the three routes under the scenario from the interrupted station To the return station The time required for a round trip; Indicates the number of vehicles dispatched from the parking point To the interruption station ; Indicates the travel time of the feeder bus from the parking point To the interruption station ; Indicates the fixed cost of the feeder bus per vehicle per unit time, Indicates the operating time cost of the feeder bus per vehicle.

[0016] Furthermore, the passenger delay cost Is ; Among them, Indicates the per capita waiting cost of passengers; Indicates the scenario The number of people choosing to go to the upstream return station ; Indicates the scenario The number of people choosing to go to the downstream return station ; Indicates the scenario The number of people choosing to go to the off-site collection and distribution point ; Indicates the number of passengers detained at the interruption station, and ; Indicates whether the feeder bus parking point Provides services to the interruption station When Indicates that the feeder bus parking point Is the interruption station Provides services, when Indicates that the feeder bus parking point Is not the interruption station Provides services; Indicates the unit cost of government-dispatched vehicles; Indicates the number of feeder buses dispatched by the government to the interruption station when there are not enough feeder buses at the parking point.

[0017] Furthermore, in the process of determining the feeder bus route, the feeder bus transportation cost and the passenger delay cost form an EOQ equilibrium, that is, under the vehicle transportation cost and the passenger delay cost, determine the number of feeder buses to minimize the sum of the vehicle transportation cost and the passenger delay cost; through the number of passengers evacuated by the feeder bus per unit time Under the scenario Get the scenario The number of feeder buses From the interruption station To different return stations The constraints are as follows:

[0018] ;

[0019] ;

[0020] Among them, ; represents the passenger flow transported to the turning-back station and the off-station evacuation point; represents the shuttle bus from the interruption station to the turning-back station for a round trip time; j represents the turning-back station; represents from the parking point sent to the interruption station the number of vehicles.

[0021] Furthermore, the number of passengers evacuated by the shuttle bus per unit time in the said scenario needs to satisfy . .

[0022] According to some embodiments, the second solution of the present invention provides a shuttle bus scheduling optimization system for urban rail transit interruption, adopting the following technical solution:

[0023] A shuttle bus scheduling optimization system for urban rail transit interruption, comprising:

[0024] An acquisition module configured to acquire the urban rail transit interruption station;

[0025] A site selection module configured to determine the shuttle bus parking point with the goal of minimizing the total site selection cost of the shuttle bus parking point considering the passenger flow at the interruption station;

[0026] An optimization module configured to determine the route of the shuttle bus with the goal of minimizing the sum of the shuttle bus transportation cost and the passenger delay cost considering the turning-back stations upstream and downstream of the urban rail transit interruption station, and complete the optimization of the shuttle bus.

[0027] According to some embodiments, the third solution of the present invention provides a computer-readable storage medium, adopting the following technical solution:

[0028] A computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, it implements the steps in the shuttle bus scheduling optimization method for urban rail transit interruption as described in the first solution of the present invention.

[0029] According to some embodiments, the fourth solution of the present invention provides an electronic device, adopting the following technical solution:

[0030] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps in the shuttle bus scheduling optimization method for urban rail transit interruption described in the first solution of the present invention.

[0031] According to some embodiments, the fifth solution of the present invention provides a computer program product, adopting the following technical solution:

[0032] A computer program product includes software code, and the program in the software code executes the steps in the shuttle bus scheduling optimization method for urban rail transit interruption described in the first solution of the present invention.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0034] The present invention conducts relevant research on the location selection of shuttle stops and personnel evacuation in the case of urban rail transit interruption. In terms of location selection, it fully considers the passenger flow situation of the line and the overall network planning of the line network, takes overall consideration of the entire traffic line network, and establishes a planning model with the minimum location selection cost as the goal to solve the problem by taking the construction cost of the parking point and the purchase cost of shuttle vehicles as the target; in terms of route optimization, it optimizes the routes of shuttle buses by combining passenger behavior analysis, fully considers the influence of subway trains and the possible large passenger flow situation, establishes a model with the minimum vehicle evacuation cost and passenger waiting cost as the goal, and combines it with the location selection cost for solution calculation, in order to provide theoretical support for the urban rail transit industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The schematic diagrams in the specification forming a part of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments and descriptions thereof of this embodiment are used to explain this embodiment and do not constitute an improper limitation to this embodiment.

[0036] Figure 1 It is a flowchart of a shuttle bus scheduling optimization method for urban rail transit interruption in Embodiment 1 of the present invention;

[0037] Figure 2 It is a schematic diagram of the shuttle evacuation process in Embodiment 1 of the present invention;

[0038] Figure 3(a) is a schematic diagram of the curve of passengers leaving for the upstream turning-back station in Embodiment 1 of the present invention;

[0039] Figure 3(b) is a schematic diagram of the curve of passengers leaving for the downstream turning-back station in Embodiment 1 of the present invention;

[0040] Figure 3(c) is a schematic diagram of the curve of passengers leaving for the out-of-station turning-back station in Embodiment 1 of the present invention;

[0041] Figure 4 It is a schematic structural diagram of a 49-node road network in the first embodiment of the present invention;

[0042] Figure 5 It is a schematic diagram of the interruption range of the breakpoint in the first embodiment of the present invention;

[0043] Figure 6 It is a schematic diagram of the coverage range of the parking point in the first embodiment of the present invention;

[0044] Figure 7 It is a structural block diagram of a shuttle bus scheduling optimization system for urban rail transit interruption in the second embodiment of the present invention. Detailed implementation manners

[0045] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0046] It should be noted that the following detailed descriptions are all exemplary and are intended to provide further descriptions of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0047] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary implementation manners according to the present invention. As used herein, unless otherwise clearly specified in the context, the singular form is also intended to include the plural form. In addition, it should also be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0048] In the present invention, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only relational terms determined for the convenience of describing the structural relationship of each component or element of the present invention and do not specifically refer to any component or element of the present invention. It cannot be understood as a limitation of the present invention.

[0049] In the case of no conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0050] Embodiment 1

[0051] The first embodiment of the present invention introduces a shuttle bus scheduling optimization method for urban rail transit interruption.

[0052] As Figure 1 shown, a shuttle bus scheduling optimization method for urban rail transit interruption includes:

[0053] Obtain the urban rail transit interruption site;

[0054] Consider the passenger flow at the interrupted stations, and determine the pick-up and drop-off points of the shuttle buses with the goal of minimizing the total site selection cost of the pick-up and drop-off points of the shuttle buses;

[0055] Based on the determined pick-up and drop-off points of the shuttle buses, consider the turning-back stations upstream and downstream of the interrupted stations of the urban rail transit, and determine the routes of the shuttle buses with the goal of minimizing the sum of the transportation cost of the shuttle buses and the passenger delay cost, so as to complete the optimization of the shuttle buses.

[0056] Due to their randomness, temporariness and urgency, emergencies pose a major challenge to the urban rail transit system. Therefore, the emergency management department must formulate effective emergency plans to mitigate their negative impacts. When a certain section of an urban rail transit line is interrupted due to some reasons, in order to reduce the impact caused by the line interruption, this embodiment adopts the Figure 2 shown shuttle evacuation plan to carry out the evacuation and transfer of passengers. After an accident occurs on the urban rail transit, the pick-up and drop-off points first send shuttle vehicles to the interrupted stations for evacuation. According to the different destinations of the passengers (whether the destination is within the interrupted section), the passengers are transported to the relevant turning-back stations or off-station evacuation points, and the vehicles shuttle back and forth between the interrupted stations, turning-back stations, and evacuation points until all passengers are evacuated. Since the traffic demand inside the interrupted section of the rail transit is generally relatively small, conventional buses, taxis, online car-hailing services, shared bicycles, walking, etc. can be used to complete the journey.

[0057] It should be noted that this embodiment only considers the demand for passengers to be transported between the rail transit turning-back stations, interrupted stations and turning-back stations, and does not consider the passengers who leave on their own.

[0058] In this embodiment, the emergency bus shuttle plan under the condition of urban rail transit interruption is as follows: the set of pick-up and drop-off points within the line network is , the number of emergency shuttle buses in the pick-up and drop-off points is , the set of rail transit interrupted stations is , the set of turning-back stations is , the passenger flow to be transported at the interrupted stations is , the section between the two nearest turning-back stations on both sides of the interrupted point is called the interrupted section. The interrupted section is evacuated by means of emergency bus shuttles to evacuate the passengers stranded at the interrupted point. For the two normal sections on the left and right outside the interrupted section, the trains continue to operate normally in a short-turn mode. After the accident occurs, the shuttle buses depart from the pick-up and drop-off points and go to the rail interrupted stations to pick up passengers. According to the different destinations of the passengers, they evacuate the passengers to the corresponding stations until all passengers are evacuated.

[0059] This embodiment is mainly divided into two major stages: The first stage focuses on the location selection of parking points, aiming to minimize the costs of parking point location selection and vehicle acquisition; the second stage focuses on vehicle evacuation, striving to reduce the costs of vehicle evacuation and passenger waiting. Finally, considering the probability of risk occurrence in a random scenario, the expected cost is obtained. All stranded passengers at interrupted stations are evacuated using emergency shuttle buses, and the parking points are scientifically set in the rail transit network, thereby formulating an optimal dispatching plan.

[0060] Before optimizing the shuttle buses, the following assumptions are made in this embodiment:

[0061] 1) Do not consider the passenger travel demand between interrupted stations.

[0062] 2) Do not consider the time spent by passengers getting on and off at each station.

[0063] 3) After an accident, passengers will no longer enter each interrupted station.

[0064] 4) All shuttle buses have the same rated passenger capacity, and all subway trains have the same rated passenger capacity.

[0065] 5) Determine the average empty running speed and operating speed of the emergency shuttle buses based on the historical average road conditions.

[0066] 6) The emergency shuttle buses will not be interfered by unexpected events during driving.

[0067] After the rail transit operation is interrupted, passengers with different destinations are evacuated in an orderly manner. For passengers whose destinations are within the interrupted section, they are guided by the staff to take local buses directly to their respective destinations. For those passengers whose destinations are outside the interrupted section, the emergency shuttle bus system is immediately activated. This system includes two types of shuttle vehicles: one is the reserve buses parked at normal bus stations, and the other is the school buses scattered in each school. These shuttle vehicles are quickly dispatched to the scene to transport passengers to the nearest turning-back station. Subsequently, passengers can choose a suitable rail transit route according to their destinations at the turning-back station and continue to move forward.

[0068] The total location selection cost of the shuttle bus parking points includes the construction cost of parking point location selection and the acquisition cost of shuttle vehicles ; that is ; ; where represents a parking point, represents the set of parking points; represents whether a shuttle bus is set at the parking point , when it means a shuttle bus is set at the parking point , when Indicates the parking point There is no shuttle bus set up at this location; Indicates the parking point The fixed cost of site selection, Indicates the vehicle acquisition cost, Is the parking point The number of standby vehicles.

[0069] Vehicle dispatching and evacuation refer to the process in which, after it is determined to adopt emergency bus shuttles when an accident occurs, emergency buses are dispatched from various parking points to the interruption station and then to the turnaround station. After it is confirmed to adopt the emergency bus shuttle plan to deal with the accident, the vehicle dispatching and evacuation work will be carried out immediately. This process involves the rapid dispatching of emergency buses from each preset parking point to the interruption site, and continuing to the designated turnaround station after completing the passenger transfer. The vehicle dispatching stage ends with the vehicle successfully arriving at the corresponding turnaround station, and then enters the vehicle evacuation link. Vehicle evacuation refers to the process of orderly dispatching vehicles between each interruption site and the turnaround site to transfer and evacuate the stranded passengers. These two stages are closely linked and jointly constitute the core implementation steps of the emergency bus shuttle plan.

[0070] Due to the uncertainty of human behavior, within the time range of passenger waiting and loss, analyze the passenger behavior characteristics, obtain the passenger loss ratio, and obtain the number of passengers remaining at the interruption station waiting for rescue. Then, combined with data investigation, select 3 turnaround stations for evacuating passengers: the upstream turnaround station (i.e., ), the downstream turnaround station (i.e., ), outside the station (i.e., ), and then calculate the passenger waiting time in this scenario respectively. Assume the interruption scenario is , the set of all scenarios that occur is , and the objective function of this stage is to minimize the vehicle and passenger delay costs under the entire scenario.

[0071] Indicates the scenario The transportation cost of the shuttle vehicle under, Indicates the scenario The passenger delay cost under. Scenario The transportation cost under Is composed of the transportation cost during the evacuation process of the shuttle vehicle and the dispatching cost before the shuttle vehicle arrives at the interruption point under the scenario , where, Indicates the fixed cost of the shuttle bus per vehicle per unit time, Indicates the operating time cost of the shuttle bus per vehicle, that is, we get .

[0072] As shown in Figure 3(a), the upstream return station The waiting time of passengers is the area enclosed by the quadrilateral OABC and the triangle BCD. As shown in Figure 3(b), the downstream return station The waiting time of passengers is the area enclosed by the quadrilateral OEFG and the triangle EFG. As shown in Figure 3(c), the off-site gathering point The waiting time of passengers is the area enclosed by the quadrilateral OPQR and the triangle QRS; represents the number of stranded passengers, represents the scenario The number of people who choose to go to the upstream return station (i.e., ), represents the scenario The number of people who choose to go to the downstream return station (i.e., ), represents the scenario The number of people who choose to go to the off-site gathering point (i.e., ), where, .

[0073] represents the time when the feeder vehicle arrives at the interruption point, , , respectively represent the times when all passengers on the three lines are evacuated. The slopes , , respectively represent the number of passengers that the feeder vehicle can evacuate per unit time on the three lines in the scenario . If the number of feeder vehicles is insufficient, the government will dispatch additional vehicles to evacuate the passengers. Denote the waiting time of passengers in this process as ; that is, the waiting time of passengers during the transportation process is

[0074] ;

[0075] ;

[0076] ;

[0077] ;

[0078] .

[0079] It can be obtained that the passenger delay cost in the scenario is

[0080] .

[0081] Constraints are imposed on the vehicle evacuation cost and the passenger waiting cost for the three lines respectively, that is

[0082] ;

[0083] ;

[0084] .

[0085] Slope represents the calculation of the number of evacuated passengers per unit time. Another representation is .

[0086] By synthesizing the vehicle evacuation cost and the passenger waiting cost, it is found that the two can form an EOQ equilibrium. Through conducting the EOQ equilibrium, substituting into the inequality from can respectively obtain the constraints on the number of feeder vehicles for the three lines in the scenario as follows:

[0087] ;

[0088] ;

[0089] .

[0090] In summary, for all lines in a scenario the vehicle evacuation cost and the passenger delay cost are as follows:

[0091] ;

[0092] ;

[0093] .

[0094] Once a disaster occurs, decision-makers must quickly and resolutely formulate and implement location and route plans. However, in the context of lacking accurate demand information, directly applying a deterministic demand model is obviously impractical. Although decision-makers can try to formulate coping strategies by estimating demand values, the actual demand in practice often deviates from the estimated values. Therefore, instead of relying on a single demand estimate here, a set of demand scenarios covering various possibilities is constructed, and each scenario is accompanied by its specific occurrence probability. This method can consider uncertainty more comprehensively and provide more flexible and robust decision support for decision-makers. For the rail transit lines under different random scenarios, the variable is introduced, representing a scenario Lower parking point The number of shuttle vehicles dispatched. Substituting the variable yields the vehicle transportation cost in one scenario and the passenger waiting cost .

[0095] Suppose represents the probability of a scenario occurring. Given an expected value to solve for the probability of a random interruption occurring in all scenarios. Note that in multiple interruption scenarios, the passenger waiting cost for waiting for a shuttle vehicle at the interruption point is relatively small and is chosen to be ignored in this problem. In all possible cases, the expected total vehicle transportation cost and the passenger waiting cost are as follows:

[0096] ;

[0097] ;

[0098] .

[0099] In summary, during the shuttle station site selection stage, the objective function is to minimize the total site selection cost of the shuttle station and maximize the line network coverage level; during the vehicle transportation stage, the objective function is to minimize the vehicle transportation cost and the passenger waiting cost; finally, the probability of risk occurrence in a random scenario is analyzed overall to obtain the expected cost. In summary, the overall objective function for minimizing the total cost of the entire shuttle station site selection and transportation is:

[0100] ;

[0101] The constraints are:

[0102] Set the parking point constraint at : ; Only set the parking point at so that the interruption station can accept the constraint of shuttle vehicle service: ;

[0103] The constraint that each interruption point is served by at least one parking point: ;

[0104] The maximum vehicle reserve capacity limit of the emergency shuttle parking point. The area occupied by the vehicles at the parking point does not exceed the vehicle reserve capacity of the parking point constraint: ; Among them, represents the vehicle scale of a single shuttle vehicle, represents the parking point The maximum vehicle capacity.

[0105] Constraint on the minimum number of evacuation passengers for the feeder vehicles at the parking point: ; where represents the interruption point Average coefficient of passengers with evacuation.

[0106] Constraint that the number of vehicles dispatched from the parking point to the interruption point is equal to the preset number of vehicles at the parking point: .

[0107] When the number of vehicles dispatched from the parking point to the interruption point is insufficient, the government will allocate vehicles to the interruption point for support. The number of vehicles from both sides needs to meet the demand for the number of feeder vehicles at the interruption point to different turn-back points Constraint on the demand for the number of feeder vehicles: .

[0108] Constraint that the number of feeder vehicles needs to meet the passenger requirements: ;

[0109] Constraint for the balance between the number of passengers going to different turn-back points and the total passenger flow: ;

[0110] Constraint for the capacity limit of the turn-back point: ; where represents the capacity of different turn-back stations.

[0111] Constraint on the decision variables: ;

[0112] Constraint on continuous integer variables: ; where represents a positive integer.

[0113] The model constructed in this embodiment is a precise integer linear programming model. Due to its structural rigor and high efficiency in solving, this type of model has extensive application value in the field of optimization decision-making. To solve this complex model, there are two main approaches: one is to use the commercial solver CPLEX, and the other is to use Python combined with libraries such as Numpy, PULP, and Pandas for solving.

[0114] As a leading commercial solver in the industry, CPLEX is well-known for its powerful solving engine, high stability, and wide applicability. It can quickly and accurately handle complex problems such as large-scale linear programming and integer programming, providing precise optimal solutions or high-quality approximate solutions. The algorithms of CPLEX are carefully designed and optimized to handle various constraint conditions and objective functions, ensuring the efficiency of the solving process and the reliability of the results.

[0115] However, to fully utilize the programming flexibility and data processing capabilities of Python, this embodiment adopts the method of Python calling the Numpy, PULP, and Pandas libraries for solution. Numpy is a fundamental library for scientific computing in Python. It provides efficient multi-dimensional array objects, making data processing and matrix operations extremely simple. PULP is a modeling library for linear programming problems. It provides a concise API to define problems, add constraints, and solve them, making the construction and solution process of integer linear programming models more intuitive and easy to understand. Pandas is a powerful data processing and analysis library. It provides rich data structures and functions, making data cleaning, transformation, and analysis effortless.

[0116] By combining the solution capabilities of CPLEX with the data processing and modeling flexibility of Python and its libraries, the integer linear programming model established in this embodiment can be comprehensively and effectively solved. This not only provides scientific decision-making support for the parking point location and vehicle evacuation problems of emergency shuttle buses but also demonstrates the complementarity and synergy between different solution methods.

[0117] Case Study

[0118] This embodiment uses the actual road network test model with 49 nodes as shown in Figure 4 and analyzes in detail the optimization results of the road network with 49 nodes. Conduct sensitivity analysis on some key parameters in the model to clarify the impact of these parameters on the optimization plan and put forward corresponding management suggestions.

[0119] Select the urban rail transit in a certain area as the background of case analysis. Assume that the fixed cost per unit of shuttle vehicle per unit time is 50,000 yuan / vehicle, the operating time cost per unit of shuttle vehicle is 1,000 yuan / vehicle, the average waiting cost per passenger is 100 yuan / person, the nuclear load capacity per unit vehicle is 50 people, the volume occupied by per unit vehicle is 60 / , the average coefficient of passengers to be evacuated at the station is 0.05. The fixed cost of parking point location and the purchase cost of shuttle vehicles are and respectively, the maximum vehicle capacity of the shuttle station is 1000 vehicles, and the average driving speed of the vehicle is 30 km / h. The number of nodes in each road network is shown in Table 1, and the node distribution of each road network is as shown in Figure 4 .

[0120] Table 1 Number of Nodes in the Experimental Road Network

[0121]

[0122] In this embodiment, taking a 47-node road network as an example, the specific implementation effects of the optimization scheme are deeply analyzed. From Figure 4 it can be seen that the parking points in this road network are quite evenly distributed, while the interrupted lines are mainly concentrated in Lines 1, 2, 3, 4, and 7 with dense passenger flow. When selecting a turning-back station, key transfer stations with relatively large passenger flow or line intersections are given priority.

[0123] This embodiment comprehensively reviews the accidents caused by natural disasters (such as floods) and problems of the subway system itself (such as derailment or train collision) in the history of urban rail transit, and combines rich historical data to carefully construct a diversified disaster scenario model. This embodiment designs 10 representative scenarios, and each scenario represents different passenger flow demands and line damage conditions. These scenarios cover complex situations from the interruption of a single station to the almost simultaneous interruption of multiple stations, as shown in Table 2 specifically. Given the uncertainty of passenger behavior after a disaster, this embodiment widely collects and sorts out the data of passenger behavior choices in different disaster situations. When setting the number of interrupted passengers at a station, according to a certain ratio, passengers are reasonably allocated to the upstream and downstream turning-back stations and the evacuation points outside the station, and this ratio is set to 4:4:2. It should be noted that although the probabilities assigned to these scenarios are intended to match the historical characteristics of subway line interruptions in this area, they should be regarded as simplified example values for assisting in explaining the problem. Table 3 gives the total costs and other key experimental results under 10 scenarios, and Tables 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13 give the specific evacuation processes under 10 scenarios.

[0124] Table 2 Scenario Definitions and Occurrence Probabilities

[0125]

[0126] Table 3 Calculation Results of the Experimental Road Network

[0127]

[0128] Table 4 Solutions under Scenario 1

[0129]

[0130] Table 5 Solutions under Scenario 2

[0131]

[0132] Table 6 Solutions under Scenario 3

[0133]

[0134] Table 7 Solutions under Scenario 4

[0135]

[0136] Table 8 Solutions under Scenario 5

[0137]

[0138] Table 9 Solutions under Scenario 6

[0139]

[0140] Table 10 Solutions under Scenario 7

[0141]

[0142] Table 11 Solutions under Scenario 8

[0143]

[0144] Table 12 Solutions under Scenario 9

[0145]

[0146] Table 13 Solutions under Scenario 10

[0147]

[0148] Through in-depth analysis of Table 2, Table 3, Table 4, Table 5, Table 6, Table 7, Table 8, Table 9, Table 10, Table 11, Table 12 and Table 13, it can be clearly observed that in the entire connection and evacuation network covering 10 different scenarios, the 1st, 3rd, 11th, 12th and 13th parking points are finally selected. In most cases, the vehicles stored at the parking points can be fully utilized in the connection and evacuation network. These vehicles dispatch the vehicles to the required break points according to the actual distance and evacuation needs, and flexibly schedule between the parking points and the break points, ensuring the smooth progress of the evacuation work. For some break points, the number of passengers to be evacuated is small, so the selected parking points can meet the corresponding needs; for some break points, the number of passengers to be evacuated is large, so when the vehicles at the selected parking points cannot meet the evacuation needs, the government will respond quickly and dispatch corresponding vehicles for rescue. Although this measure can ensure the continuous progress of the evacuation work, it will also bring additional transportation costs and site selection costs. Therefore, when planning the connection and evacuation network, it is necessary to fully consider the number and location of the parking points, as well as the vehicle storage and dispatching strategies, in order to reduce costs and improve evacuation efficiency.

[0149] Figure 4Intuitively shows the range of interruption at the breakpoint. In this experiment, most of the selected test scenarios involve interruptions occurring simultaneously at two breakpoints, and also include scenarios where a single breakpoint interrupts alone. Overall, the coverage of these breakpoints is quite uniform, and it can comprehensively and effectively simulate and evaluate the impact on the rail transit system under different interruption situations. Figure 5 Clearly shows the coverage of the five parking points selected in this experiment. It can be intuitively seen from the figure that the layout of the 1st, 3rd, 11th, 12th, and 13th parking points almost covers the entire rail transit line network. This indicates that among the 16 alternative points, these five parking points are the best choices after careful screening and optimization. The selection of these five parking points not only fully meets the connection and evacuation needs of the rail transit line network, ensuring efficient and rapid evacuation of people in case of emergencies, but also takes into account cost-effectiveness. Among all possible site selection schemes, this combination has the lowest cost and is the most cost-effective and economical choice among all alternative schemes.

[0150] In addition, the passenger selection at the breakpoint is also an important factor affecting vehicle allocation. Different passengers will make different choices according to their own needs and destinations, thus requiring the dispatch of corresponding connecting vehicles. This requires that when conducting vehicle deployment, the needs and distribution of passengers should be fully considered to ensure that the vehicles can reach the designated evacuation points accurately and in a timely manner. It can also be seen from the table that although the number of people allocated to the off-station evacuation points is relatively small, because two or three breakpoints may share one evacuation point, these evacuation points are relatively far away. Therefore, the number of vehicles required is also relatively large. When planning the evacuation network, the location and coverage of the evacuation points should be fully considered to ensure the comprehensiveness and effectiveness of the evacuation work. Of course, the actual situation is often much more complex than that shown in the table. Therefore, when conducting specific cost calculations and vehicle deployments, more actual factors need to be considered. These factors may include road conditions, traffic congestion, weather conditions, etc. Only by comprehensively considering these factors can a more reasonable and effective evacuation plan and deployment strategy be formulated.

[0151] This embodiment deeply analyzes the site selection of connecting stations and the personnel evacuation strategy for urban rail transit in case of interruption. Based on the goal of minimizing the total cost, a scenario-based mixed-integer stochastic optimization model is constructed, considering the site selection cost of parking points, the purchase cost of connecting vehicles, and the vehicle evacuation cost, passenger waiting cost, and government vehicle deployment cost generated during the vehicle evacuation process under different disaster scenarios. To solve the optimization model, the Python programming language is used and the PULP library is called; the aim is to provide strong auxiliary decision-making support for managers when formulating emergency material supply plans.

[0152] To verify the effectiveness of the model, in this embodiment, a rail transit network in a certain area with 49 nodes was selected for experimental comparison. The experimental results show that the layouts of the 1st, 3rd, 11th, 12th, and 13th parking points almost cover the entire rail transit network, not only fully meeting the connection and evacuation requirements of the rail transit network, but also being the most cost-effective and economical choice among all the solutions.

[0153] Embodiment II

[0154] Embodiment II of the present invention introduces an optimized shuttle bus scheduling system for urban rail transit interruptions.

[0155] As Figure 7 shown, an optimized shuttle bus scheduling system for urban rail transit interruptions includes:

[0156] An acquisition module, which is configured to acquire the interrupted site of urban rail transit;

[0157] A site selection module, which is configured to consider the passenger flow of the interrupted site and determine the shuttle bus parking point with the minimum total site selection cost of the shuttle bus parking points;

[0158] An optimization module, which is configured to determine the route of the shuttle bus with the minimum sum of the shuttle bus transportation cost and the passenger delay cost, considering the turning-back sites upstream and downstream of the interrupted site of urban rail transit, based on the determined shuttle bus parking points, and complete the optimization of the shuttle bus.

[0159] The detailed steps are the same as those of the optimized shuttle bus scheduling method for urban rail transit interruptions provided in Embodiment I, and will not be elaborated here.

[0160] Embodiment III

[0161] Embodiment III of the present invention provides a computer-readable storage medium.

[0162] A computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, it implements the steps in the optimized shuttle bus scheduling method for urban rail transit interruptions as described in Embodiment I of the present invention.

[0163] The detailed steps are the same as those of the optimized shuttle bus scheduling method for urban rail transit interruptions provided in Embodiment I, and will not be elaborated here.

[0164] Embodiment IV

[0165] Embodiment IV of the present invention provides an electronic device.

[0166] An electronic device includes a memory, a processor, and a program stored on the memory and running on the processor. When the processor executes the program, it implements the steps in a method for optimizing the dispatching of shuttle buses for urban rail transit interruptions as described in Embodiment 1 of the present invention.

[0167] The detailed steps are the same as those provided in the method for optimizing the dispatching of shuttle buses for urban rail transit interruptions in Embodiment 1, and will not be elaborated here.

[0168] Embodiment 5

[0169] Embodiment 5 of the present invention provides a computer program product.

[0170] A computer program product includes software code, and the program in the software code executes the steps in a method for optimizing the dispatching of shuttle buses for urban rail transit interruptions as described in Embodiment 1 of the present invention.

[0171] The detailed steps are the same as those provided in the method for optimizing the dispatching of shuttle buses for urban rail transit interruptions in Embodiment 1, and will not be elaborated here.

[0172] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0173] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0174] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in one or more of the flow Figure 1 acts or a plurality of acts and / or boxes Figure 1 specified in one box or a plurality of boxes.

[0175] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the flow Figure 1 acts or a plurality of acts and / or boxes Figure 1 specified in one box or a plurality of boxes.

[0176] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made by those skilled in the art once they learn of the basic inventive concept. Therefore, the appended claims are intended to be construed to cover the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0177] It is apparent that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

[0178] The above description is only the preferred embodiments of this example and is not intended to limit this example. For those skilled in the art, this example can have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of this example shall be included within the protection scope of this example.

Claims

1. A shuttle bus scheduling optimization method for urban rail transit interruption, characterized in that: include: Get the interrupted stations of urban rail transit; Considering the passenger flow at the interruption station, the shuttle bus parking point is determined with the goal of minimizing the total location cost of the shuttle bus parking point; According to the determined shuttle bus parking points, the turnaround stations upstream and downstream of the urban rail transit interruption stations are considered, and the shuttle bus route is determined with the goal of minimizing the sum of the shuttle bus transportation cost and the passenger delay cost, thus completing the optimization of the shuttle bus; The shuttle transportation cost At least it includes the transportation cost of the shuttle bus to evacuate passengers and the dispatch cost before the shuttle bus arrives at the interruption site; that is, ;in, Representation scene Expected value; Representation scene The probability of occurrence, Represents a collection of scenes; Indicates the interruption site; Indicates the number of passengers that the shuttle bus can carry; , , Representing scenes The number of passengers that can be evacuated by the shuttle bus per unit time on the following three routes; , , Representing scenes Shuttle buses on the next three routes will depart from the interruption station To the turnaround point Time required for a round trip; From the parking spot Dispatched to outage site The number of vehicles; Indicates that the shuttle bus is leaving from the parking spot To the interruption site travel time; represents the fixed cost of connecting buses per vehicle per unit time, represents the operating time cost of the unit vehicle shuttle; Delay costs for passengers for: ;in, represents the average waiting cost per passenger; Representation scene Next, select Go to the upstream turnaround station Number of people, Representation scene Next, select Go to the downstream turnaround station Number of people, Representation scene Next, select Go to an off-site distribution point Number of people; represents the number of passengers stranded at the interruption station, and ; Indicates shuttle bus parking spot Is it an interruption site? Provide services when The shuttle bus parking spot For interruption site Provide services when The shuttle bus parking spot Not an interruption site Provide services; represents the unit cost of the government deployed vehicles; It indicates the number of shuttle buses that the government deploys to the interruption station when there are not enough shuttle buses at the parking point; In the process of determining the shuttle bus route, the shuttle bus transportation cost and the passenger delay cost constitute the EOQ equilibrium, that is, under the vehicle transportation cost and the passenger delay cost, the number of shuttle buses is determined so that the sum of the vehicle transportation cost and the passenger delay cost is minimized; through the scenario Number of passengers evacuated by shuttle bus within the next unit time Get the scene Lower interruption site To different turnaround points Number of shuttle vehicles The constraints are: ； ； in, ; Indicates transport to the return station and passenger flow at evacuation points outside the station; Indicates that the shuttle bus is leaving the interruption station To the turnaround point The time for a round trip; j Indicates a reentry site; From the parking spot Dispatched to outage site The number of vehicles.

2. A shuttle bus scheduling optimization method for urban rail transit interruption as described in claim 1, characterized in that: The total site selection cost of the shuttle bus parking point includes the site selection and construction cost of the parking point and shuttle vehicle purchase costs ;Right now ; ;in, Indicates parking point. Indicates a parking point collection; Indicates parking spot Is there a shuttle bus? Indicates parking point Shuttle buses are set up at Indicates parking point There is no shuttle bus at the location; Indicates parking spot Fixed costs of site selection, represents the purchase cost of the vehicle, For parking spot The number of spare vehicles.

3. A shuttle bus scheduling optimization method for urban rail transit interruption as described in claim 1, characterized in that: The scenario Number of passengers evacuated by shuttle bus within the next unit time Need to meet .

4. A shuttle bus scheduling optimization system for urban rail transit interruption, using a shuttle bus scheduling optimization method for urban rail transit interruption as described in any one of claims 1 to 3, characterized in that: include: An acquisition module, which is configured to acquire interrupted urban rail transit stations; A site selection module is configured to determine the shuttle bus parking point with the goal of minimizing the total site selection cost of the shuttle bus parking point by considering the passenger flow of the interruption station; The optimization module is configured to determine the route of the shuttle bus based on the determined shuttle bus parking point, taking into account the turnaround stations upstream and downstream of the urban rail transit interruption station, with the goal of minimizing the sum of the shuttle bus transportation cost and the passenger delay cost, and complete the optimization of the shuttle bus.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of a method for optimizing shuttle bus scheduling for urban rail transit interruptions as described in any one of claims 1 to 3 are implemented.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of a method for optimizing shuttle bus scheduling for urban rail transit interruptions as described in any one of claims 1-3 are implemented.

7. A computer program product comprising software code, characterized in that The program in the software code executes the steps of a method for optimizing shuttle bus scheduling for urban rail transit interruptions as described in any one of claims 1-3.

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