Railway main type comprehensive passenger hub transfer streamline optimization method

Abstract

The application discloses a railway main type comprehensive passenger transport hub transfer flow line optimization method, studies the transfer process of passengers in the hub, proposes a transfer impedance quantitative analysis method, identifies a transfer bottleneck, optimizes a transfer flow line, and improves hub transfer efficiency and service quality. First, for hub transfer sections, the walking characteristics and impedance influencing factors of passengers on the sections are analyzed, and impedance models are constructed according to different section types. Second, for hub transfer nodes, the walking characteristics and impedance influencing factors of passengers on the nodes are analyzed, and impedance models of different node types are constructed based on queuing theory. Finally, on the basis of realizing hub transfer impedance quantitative analysis, a railway main type comprehensive passenger transport hub transfer passenger flow line optimization method is proposed, which can provide a theoretical basis for impedance analysis and flow line optimization of the railway main type comprehensive passenger transport hub, has certain theoretical significance and application value in improving hub transfer efficiency and service quality.

Description

Technical Field

[0001] This invention belongs to the technical field of transfer organization and optimization of railway integrated passenger transport hubs in transportation engineering, and specifically relates to a method for optimizing transfer flow in railway-dominated integrated passenger transport hubs. Background Technology

[0002] With the rapid advancement of high-speed rail construction, the proportion of railway passenger volume in the total passenger volume of all modes of transportation is increasing year by year, and railway transportation is playing an increasingly important role in the development of integrated transportation. Railway-led integrated passenger transport hubs, as important locations for efficiently connecting railways, highways, and urban public transportation, are key points for passengers to transfer between other modes of transportation and railway transport. With rapid economic development and the increasingly fast pace of life and work, the demands for hub transfer efficiency and service quality are rising.

[0003] The continuously growing demand for railway transportation is posing increasing challenges to integrated railway passenger hubs. Improving transfer efficiency to alleviate passenger flow pressure at these hubs is receiving increasing attention. Integrated railway passenger hubs are characterized by their large scale, complex functional spatial layout, high passenger volume, and diverse transfer types. Inefficient transfer flows are a significant factor affecting hub transfer efficiency and service quality. The rationality of transfer flows in integrated railway passenger hubs can be evaluated from aspects such as transfer distance, time, cost, and comfort. These factors can be converted into quantitative values ​​for unified analysis. Transfer impedance in integrated railway passenger hubs is a physical quantity describing the resistance encountered by passengers during transfers within the hub; it is a unified expression of transfer distance, time, and cost. Quantitative analysis of hub transfer impedance is the foundation for evaluating and optimizing the rationality of transfer flows and a key link in improving hub transfer efficiency and service quality.

[0004] Currently, the quantitative analysis and modeling of transfer impedance in railway integrated passenger transport hubs is quite complex, and the existing impedance models have limited application scope. This is because the analysis of transfer impedance in railway integrated passenger transport hubs involves not only the macroscopic characteristics of passenger flow on transfer sections between various modes of transport, but also the different arrival distributions of passengers at transfer nodes, the service time patterns of facilities, and service capabilities. Furthermore, due to the diverse types of transfer sections and nodes in railway integrated passenger transport hubs, passengers exhibit different walking characteristics and service reception processes at different sections and nodes, making it impossible for a single model to fully quantify and describe the hub's transfer impedance. In addition, focusing only on the impedance of a section or node cannot provide a holistic evaluation and optimization of the transfer passenger flow lines in railway integrated passenger transport hubs. These problems pose new requirements for the quantitative analysis of transfer impedance and flow line optimization in railway integrated passenger transport hubs. Summary of the Invention

[0005] Objective of the Invention: The technical problem to be solved by this invention is to provide a method for optimizing the transfer flow of passengers in railway-dominated integrated passenger transport hubs, analyze the transfer process of passengers in railway integrated passenger transport hubs, reveal the characteristics of the transfer process of hub passengers; establish a transfer impedance model for railway integrated passenger transport hubs to provide a theoretical basis for the quantitative analysis of hub transfer impedance; and establish an optimization model for the transfer passenger flow of railway integrated passenger transport hubs to provide a theoretical basis for the optimization of hub transfer passenger flow.

[0006] Technical solution: The present invention provides a method for optimizing transfer flow in railway-dominated integrated passenger transport hubs, comprising the following steps:

[0007] (1) Analyze the characteristics of railway integrated passenger transport hubs, obtain data elements of passenger transfer process in the hub, analyze the characteristics of passenger transfer process in the hub, and abstract the passenger transfer path in railway integrated passenger transport hub into a transfer network;

[0008] (2) Analyze the walking characteristics and impedance influencing factors of passengers in the hub transfer section, establish the impedance model of the hub transfer section, calibrate the model parameters based on the survey data, and verify the applicability and rationality of the impedance model of the hub transfer section;

[0009] (3) Analyze the walking characteristics and impedance influencing factors of passengers at hub transfer nodes, establish a hub transfer node impedance model, calibrate the model parameters based on survey data, and verify the applicability and rationality of the hub transfer node impedance model;

[0010] (4) To minimize the transfer impedance of the hub and the operating cost of the node facilities, an optimization model of the transfer passenger flow of the railway integrated passenger transport hub is established, and a solution algorithm is proposed.

[0011] (5) Calculate the hub transfer impedance and node facility operation cost before hub optimization, compare and analyze the changes in hub transfer impedance and node facility operation cost before and after optimization, as well as the hub transfer network traffic distribution before and after optimization, analyze and evaluate the optimization effect of the optimization scheme, and finally propose corresponding optimization strategies based on the optimization scheme.

[0012] Further, the data elements of the transfer process in step (1) include static data within the hub and dynamic data of the transfer process; the static data within the hub includes: static data of the hub transfer segments and static data of the hub transfer node facilities; the static data of the hub transfer segments includes segment location, segment number, starting node, ending node, segment length, segment width, segment slope, and escalator operating speed; the static data of the hub transfer nodes includes node location, node number, number of node facilities, and staff configuration; the dynamic data within the hub includes: dynamic data of passenger flow at the hub entrance, dynamic data of the hub transfer segments, and dynamic data of the hub transfer nodes; the dynamic data of passenger flow at the hub entrance includes total passenger flow and passenger flow of each mode of transportation; the dynamic data of the hub transfer segments includes segment flow and passenger segment travel time; the dynamic data of the hub transfer nodes includes node flow, passenger arrival time distribution, and facility service time distribution.

[0013] Furthermore, the process of analyzing the characteristics of passenger transfers within the hub described in step (1) is as follows:

[0014] The transfer process includes transfers within the railway network and transfers from other modes of transportation to the railway network. Transfers within the railway network are facilitated through convenient transfers, eliminating the need for procedures such as entering the station, ticket inspection, security check, and waiting. Transfers from other modes of transportation to the railway network involve the necessary procedures of arrival, ticket inspection, security check, and waiting.

[0015] The transfer facilities include: transfer plaza, transfer hall, transfer passage, transfer stairs, entrance gate facilities and security check facilities. The sections of the transfer plaza, transfer hall, transfer passage and transfer stairs are defined as hub transfer sections, and the areas where passengers receive services from entrance gate facilities and security check facilities are defined as hub transfer nodes.

[0016] Furthermore, the impedance model of the hub transfer section in step (2) is the sum of the impedances of the horizontal section, the sloping section, and the escalator section, as detailed below:

[0017]

[0018]

[0019]

[0020]

[0021] in, Impedance of the transfer section at the hub; For horizontal road sections, the impedance is... Impedance for sloping road sections; For the impedance of the escalator section; These represent the number of horizontal road sections, sloping road sections, and escalator road sections, respectively. For the first Impedance of each horizontal road segment For the first Impedance of a sloping road section; For the first The impedance of each escalator section; For the first The number of passengers on a typical horizontal road section; For the first The number of passengers on each sloping section of the road; For the first The number of passengers on each escalator section.

[0022] Furthermore, the impedance model of the hub transfer node in step (3) is the impedance model of the entrance gate node and the impedance model of the security check node. The specific process is as follows:

[0023]

[0024]

[0025]

[0026] in, Impedance of the hub transfer node; The impedance of the entrance gate; Impedance of the security checkpoint; This refers to the number of entrance gates and security checkpoints. For the first Average dwell time of each entry gate queuing system For the first Average dwell time in the queuing system at each security checkpoint; For the first The number of passengers at each entrance gate node; For the first The number of passengers at each security checkpoint.

[0027] Furthermore, the impedance model of the entrance gate node is applicable in off-peak passenger flow scenarios. Queuing systems are suitable for peak passenger flow scenarios. Queuing system;

[0028] In off-peak passenger flow scenarios, The operational metrics of the queuing system are calculated using the following formula:

[0029]

[0030]

[0031]

[0032]

[0033] in, The average waiting time for passengers at the turnstile; The average queue length at the turnstile; The average length of the turnstile; The average time passengers spend at the turnstile; This refers to the number of turnstiles; The average arrival rate of new passengers in the gate queuing system. The number of passengers arriving at the gate node within one hour; System busy rate; , The expected value and variance of the probability distribution of the service time for the turnstile; For service rate;

[0034] During peak passenger flow scenarios, The operational metrics of the queuing system are calculated using the following formula:

[0035]

[0036]

[0037]

[0038]

[0039]

[0040] in, The average arrival rate of new passengers in a single gate queuing system. This refers to the number of turnstiles arranged side-by-side. This represents the system's busy rate.

[0041] Furthermore, the impedance model of the security checkpoint is applicable in both peak and off-peak passenger flow scenarios. Queuing system This refers to the number of service stations in a single-channel queuing multi-channel service system; for systems with... A queuing system consisting of security screening machines can be broken down into... indivual system.

[0042] Furthermore, step (4), which aims to minimize hub transfer impedance and node facility operating costs, is specifically as follows:

[0043]

[0044]

[0045] St

[0046]

[0047]

[0048]

[0049]

[0050] in, For hub transfer impedance; Impedance of the transfer section at the hub; Impedance of the hub transfer node; For example, an edge in a hub transfer network; It refers to a point in the hub transfer network; For the side Traffic; For the edge The weight, i.e., the impedance on the transfer section of the hub. , ; Let be the matrix of connections between edges and points. When the edge... For point The import side, ,on the contrary, , , ; For the edge Point of view The weight on the point, i.e., the impedance at the point. , ; The operating cost of hub transfer node facilities per unit of time; This refers to the number of entrances to the hub station. The cost per unit of time for using a single entrance gate; The cost per unit of time for the use of a single security check facility; For staff operating expenses; For the first Number of staff at each entrance; For the first The number of entrance gates at each entrance; For the first The number of security checkpoints at each entrance; Starting from a certain point; For a certain endpoint; The set that starts from; The set whose endpoint is... The set of all paths; For a specific path in the path set; A set of paths; For 0-1 variables, For a point in the network; For the network Point flow direction Point traffic; For the network Point flow direction Point traffic; for Traffic along the path; for and Inter-flow; This is the correlation matrix between edges and paths.

[0051] Beneficial Effects: Compared with the prior art, the beneficial effects of this invention are as follows: This invention considers different transfer sections and node types in railway integrated passenger transport hubs, combines actual hub scenarios and factors such as the walking characteristics of hub passengers in transfer sections and nodes, different arrival distribution patterns of passengers at nodes, service time distribution patterns of transfer facilities, quantity and service capacity, etc., to conduct a more refined study on the impedance of hub transfer sections and nodes, explore a reasonable expression form of hub transfer impedance model, and apply the hub transfer impedance model to hub transfer flow optimization. Combining the mutual influence of hub transfer section impedance and transfer node impedance, the hub transfer impedance is regarded as a whole, and the operating cost of hub transfer node facilities is considered to establish a hub transfer passenger flow flow model, thereby reducing hub transfer impedance and improving hub transfer efficiency and service quality. Attached Figure Description

[0052] Figure 1 This is a flowchart of the present invention;

[0053] Figure 2 This is a schematic diagram of the three-dimensional layout of the hub in this invention.

[0054] Figure 3 This is a schematic diagram of the layout of each layer of the hub in this invention.

[0055] Figure 4 This is the location of the video survey post in the case study of this invention;

[0056] Figure 5 This is a hub transfer topology network diagram of the present invention.

[0057] Figure 6 This is a time-sharing passenger flow map of the hub in this invention. Detailed Implementation

[0058] The present invention will now be described in further detail with reference to the accompanying drawings:

[0059] like Figure 1 As shown, this invention proposes a method for optimizing transfer flow in railway-dominated integrated passenger transport hubs. This method includes the following steps:

[0060] Step 1: Analyze the characteristics of railway integrated passenger transport hubs, obtain data elements of passenger transfer processes within the hub, and the three-dimensional layout of the hub is as follows: Figure 2 As shown, the floor plans for each level are as follows: Figure 3 As shown, positions that require video surveys include... Figure 4 As shown in the figure, the transfer route network diagram is as follows: Figure 5 As shown, the passenger flow arriving at the hub at different times is as follows: Figure 6 As shown in Table 1, the speed distribution characteristics of the horizontal road sections are shown in Table 2, and the speed distribution characteristics of the stair sections are shown in Table 3.

[0061] Table 1. Transfer data of the hub

[0062]

[0063] Table 2 Speed ​​Distribution Characteristics of Horizontal Road Sections

[0064]

[0065] Table 3. Velocity distribution characteristics of stairwell sections

[0066]

[0067] Step 2: Analyze the walking characteristics and impedance influencing factors of passengers in the hub transfer section, establish the impedance model of the hub transfer section, calibrate the model parameters based on the survey data, and verify the applicability and rationality of the impedance model of the hub transfer section.

[0068] The impedance parameters for each section are as follows:

[0069] ① Impedance of horizontal road sections :

[0070]

[0071] in, The impedance for a typical horizontal road segment represents the travel time of a passenger on that segment. Impedance of horizontal road sections taking congestion into account.

[0072] ② Impedance of general horizontal road sections :

[0073]

[0074]

[0075] in, For free-flowing passengers on level sections Travel time Level road section Actual passenger flow Level road section Actual traffic capacity The congestion level influence coefficient is used to characterize the amplification effect of the ratio of actual passenger flow to traffic capacity on the walking time of a horizontal road segment. It is a nonlinear adjustment index used to characterize the nonlinear growth characteristics of walking time as passenger flow density changes; and The value can be determined by curve fitting based on actual passenger flow data. The length of the horizontal road section The average walking speed of passengers in free-flow conditions on a level road segment.

[0076] ③ Impedance of horizontal road sections considering congestion :

[0077]

[0078]

[0079] in, The time impedance increase / decrease coefficient due to congestion; Actual passenger flow on congested horizontal road sections; The actual traffic capacity of congested horizontal road sections. The congestion impact intensity coefficient is used to characterize the magnitude of the increase in walking time under congested conditions. The congestion growth index is used to adjust for the increasing trend of walking time as passenger flow exceeds capacity. This is the base time correction term, used to compensate for the base walking time under congested conditions. The value of can be determined by curve fitting based on actual passenger flow data.

[0080] ④ Impedance of sloping road sections :

[0081]

[0082]

[0083]

[0084]

[0085] in, The basic impedance for sloping road sections, To account for the time impedance of slope increase or decrease, Sloping section Length, For passengers on sloping sections walking speed, The time impedance increase / decrease coefficient due to slope slope, This is the slope influence coefficient, used to characterize the intensity of the impact of slope changes on walking time. This is a non-linear slope adjustment index, used to adjust the non-linear relationship between walking time and slope. This is a time offset correction parameter used to correct the basic walking time under slope conditions. , , The value of can be determined by curve fitting based on actual passenger flow data.

[0086] ⑤ Escalator section impedance :

[0087]

[0088] in, escalator Length, escalator The running speed.

[0089] The impedance model for transfer sections in a transportation hub is the sum of the impedances of horizontal sections, sloping sections, and escalator sections. It represents the total travel time for all passengers passing through transfer sections within the hub, as detailed below:

[0090]

[0091]

[0092]

[0093]

[0094] in, Impedance of the transfer section at the hub; For impedance of all horizontal road segments; Impedance for all sloping road sections; Impedance for all escalator sections; These represent the number of horizontal road sections, sloping road sections, and escalator road sections, respectively. For the first Impedance of each horizontal road segment For the first Impedance of a sloping road section; For the first The impedance of each escalator section; For the first The number of passengers on a typical horizontal road section; For the first The number of passengers on each sloping section of the road; For the first Passenger numbers on each escalator section

[0095] The parameters of the BPR function model were calibrated using long, straight horizontal road segments. The parameters of the horizontal road segments are shown in Table 4.

[0096] Table 4 Parameters of Horizontal Road Sections

[0097]

[0098] Time for passengers to pass through the survey section in a free state It is 15.50 Actual traffic capacity of the road section 13779 According to the different results obtained from the survey Based on the passenger travel time data under the given conditions, parameter calibration was performed, and the linear equation fitted to the scatter plot was:

[0099]

[0100] According to the above formula, -0.9147, 2.5491, by , achievable 0.1217, 2.5491. Therefore, the impedance model for a typical horizontal road section of a hub is:

[0101]

[0102] Similarly, the parameters in the formula for the time impedance increase / decrease coefficient of calibrating congested horizontal and sloping road sections are as follows:

[0103]

[0104] .

[0105] Step 3: Analyze the walking characteristics and impedance influencing factors of passengers at the hub transfer nodes, establish a hub transfer node impedance model, calibrate the model parameters based on survey data, and verify the applicability and rationality of the hub transfer node impedance model.

[0106] The impedance model for the hub transfer node is the sum of the impedance of the entrance gate and the impedance of the security checkpoint. The specific process is as follows:

[0107]

[0108]

[0109]

[0110] in, Impedance of the hub transfer node; The impedance of the entrance gate; Impedance of the security checkpoint; This refers to the number of entrance gates and security checkpoints. For the first Average dwell time of each entry gate queuing system For the first Average dwell time in the queuing system at each security checkpoint; For the first The number of passengers at each entrance gate node; For the first The number of passengers at each security checkpoint.

[0111] The impedance models used for the entrance gate nodes and security checkpoint nodes employ queuing theory, and the entrance gate nodes are suitable for off-peak passenger flow scenarios. Queuing systems are suitable for peak passenger flow scenarios. Queuing system, in which The number of turnstiles represents a queuing model where customer arrivals follow a Poisson distribution, and customer service times are independent and follow a general probability distribution.

[0112] In off-peak passenger flow scenarios, The operational metrics of a queuing system can be calculated using the following formula.

[0113]

[0114]

[0115]

[0116]

[0117] in, The average waiting time for passengers at the turnstile; The average queue length at the turnstile; The average length of the turnstile; The average time passengers spend at the turnstile; This refers to the number of turnstiles; The average arrival rate of new passengers in the gate queuing system. The number of passengers arriving at the gate node within one hour; System busy rate; , The expected value and variance of the probability distribution of the service time for the turnstile; For service rate.

[0118] During peak passenger flow scenarios, The operational metrics of a queuing system can be calculated using the following formula.

[0119]

[0120]

[0121]

[0122]

[0123]

[0124] in, The average arrival rate of new passengers in a single gate queuing system. This refers to the number of turnstiles arranged side-by-side. This represents the system's busy rate.

[0125] The probability distribution of the time passengers spend undergoing security checks follows a normal distribution, therefore Queuing models are not suitable for security check queuing systems. Considering the parallel nature of security scanners, where "one person puts their bag in while multiple people are checked," it can be abstracted into a single-path, multi-channel service system. This system is applicable to both peak and off-peak passenger flow scenarios. Queuing system This refers to the number of service stations in a single-channel queuing multi-channel service system. For systems with... A queuing system consisting of security screening machines can be broken down into: indivual system.

[0126] The queuing model for a single security screening machine is the same as the queuing model for turnstiles during off-peak hours, except that the number of turnstiles is adjusted. The number of service stations in a single-channel queuing multi-channel service system For those by A queuing system consisting of multiple security screening machines arranged in parallel has the same average waiting time and average dwell time as a queuing system with a single security screening machine. The average queue length and average queue length in this system are significantly different from those of a single security screening machine queuing system. times.

[0127] Based on the on-site investigation of the case, the parameters of the entrance gate queuing system are shown in Table 5, and the parameters of the security check queuing system are shown in Table 6.

[0128] Table 5 Parameters of the Entry Gate Queuing System

[0129]

[0130] Table 6 Parameters of Security Check Queue System

[0131]

[0132] Step 4: With the objectives of minimizing hub transfer impedance and minimizing node facility operating costs, establish an optimization model for passenger flow flow in railway integrated passenger transport hubs and propose a solution algorithm.

[0133] The first objective function can be viewed as an allocation problem under system optimality (SO), while the second optimization objective can be viewed as the optimization of transfer node facilities considering operating costs.

[0134] The objectives are to minimize hub transfer impedance and minimum node facility operating costs, as detailed below:

[0135]

[0136]

[0137] St

[0138]

[0139]

[0140]

[0141]

[0142] in, For hub transfer impedance; Impedance of the transfer section at the hub; Impedance of the hub transfer node; For example, an edge in a hub transfer network; It refers to a point in the hub transfer network; For the side Traffic; For the edge The weight, i.e., the impedance on the transfer section of the hub. , ; Let be the matrix of connections between edges and points. When the edge... For point The import side, ,on the contrary, , , ; For the edge Point of view The weight on the point, i.e., the impedance at the point. , ; The operating cost of hub transfer node facilities per unit of time; This refers to the number of entrances to the hub station. The cost per unit of time for using a single entrance gate; The cost per unit of time for the use of a single security check facility; For staff operating expenses; For the first Number of staff at each entrance; For the first The number of entrance gates at each entrance; For the first The number of security checkpoints at each entrance; Starting from a certain point; For a certain endpoint; The set that starts from; The set whose endpoint is... The set of all paths; For a specific path in the path set; A set of paths; For 0-1 variables, For a point in the network; For the network Point flow direction Point traffic; For the network Point flow direction Point traffic; for Traffic along the path; for and Inter-flow; This is the correlation matrix between edges and paths.

[0143] To solve the SO problem, the MSA algorithm is chosen for passenger flow allocation. The steps of the MSA algorithm are as follows:

[0144] Step 1: Initialization. The number of iterations is... =0, execute all-or-nothing allocation, and obtain the initial traffic allocation scheme. ;

[0145] Step 2: Update impedance and path selection probability. Based on the initial flow distribution plan and segment flow rate. and path traffic Calculate segment impedance and path impedance, and calculate the probability of each path being selected. ;

[0146] Step 3: Update path traffic. Recalculate path traffic based on the calculated path selection probabilities.

[0147] Step 4: Determine the optimal descent direction Determine the step size. ;

[0148] Step 5: Update traffic flow for the affected road segment. ;

[0149] Step 6: Convergence Check. If the convergence criteria are met, the algorithm terminates. For network traffic balance distribution schemes; otherwise, let Proceed to Step 2.

[0150] For solving the multi-objective optimization model, the PSO algorithm is used. The PSO algorithm process is as follows:

[0151] Step 1: Initialization. Initialize the particle swarm parameters, randomly initializing the position and velocity of each particle;

[0152] Step 2: Determine if the termination condition is met. If the termination condition is not met, call the MSA algorithm to allocate traffic in the hub transfer network and continue to Step 3. If the termination condition is met, the algorithm ends, and the globally optimal location is the globally optimal solution.

[0153] Step 3: Calculate the fitness value. Calculate the fitness value for each particle based on the fitness function.

[0154] Step 4: Update the optimal fitness and position of each particle. For each particle, compare its current fitness with the fitness of its historical best position. If the current fitness is higher, update the historical best position with the current position.

[0155] Step 5: Update the swarm's optimal fitness and position. For each particle, compare its current fitness with the fitness of its global best position. If the current fitness is higher, update the global best position using the current position.

[0156] Step 6: Update particle position and velocity, then proceed to Step 2.

[0157] Step 5: Calculate the hub transfer impedance and node facility operating costs before hub optimization, as shown in Tables 7 and 8. Compare and analyze the changes in hub transfer impedance and node facility operating costs before and after optimization, as well as the hub transfer network traffic distribution before and after optimization. Analyze and evaluate the optimization effect of the optimization scheme, and finally propose corresponding optimization strategies based on the optimization scheme.

[0158] Table 7 Hub transfer impedance before hub optimization

[0159]

[0160] Table 8. Node Facility Operating Costs

[0161]

[0162] The basic information of the transfer network of the case hub, passenger flow data under peak and off-peak scenarios, and transfer node facility data were substituted into the optimization model. The Pareto algorithm was used, and the model was solved using MATLAB programming. The initial population size was set to 100, and the number of iterations was 200. After solving the algorithm, the Pareto solution sets for optimizing the transfer passenger flow lines of the case hub under peak and off-peak flow scenarios were obtained, as shown in Tables 9 and 10.

[0163] Table 9. Pareto solution set for passenger transfer flow optimization at the case hub under peak traffic scenarios.

[0164]

[0165] Table 10 Pareto solution set for passenger transfer flow optimization at the case hub in off-peak traffic scenarios.

[0166]

[0167] Impedance / cost weights are set to 0.5 / 0.5, and the objective function is normalized and weighted accordingly. The optimal solutions for passenger flow optimization at the hub in peak and off-peak traffic scenarios are summarized in Table 11.

[0168] Table 11 Optimal solutions for passenger transfer flow optimization under peak and off-peak traffic scenarios.

[0169]

[0170] Introducing the ratio of hub transfer impedance to hub transfer node facility operating cost, abbreviated as impedance cost ratio, unit: Table 12 shows the comparison of the optimization degree of hub transfer impedance, and Table 13 shows the comparison of the optimization degree of hub transfer node facility operating cost and impedance cost ratio.

[0171] Table 12 Comparison of Hub Transfer Impedance Optimization Degree

[0172]

[0173] Under both high and low peak traffic scenarios, the optimal solution in the optimization model reduces the hub transfer impedance by 17.34% and 0.00% (0.0038% when rounded to four decimal places), respectively, compared to the current hub transfer impedance. Specifically, under high peak traffic scenarios, the road segment impedance increases by 0.81%, while the node impedance decreases by 39.31%; under low peak traffic scenarios, the road segment impedance decreases by 2.03%, while the node impedance increases by 7.26%.

[0174] It can be observed that the road segment impedance increases slightly under peak traffic conditions and the node impedance increases slightly under off-peak traffic conditions, while all other indicators decrease. This is because the optimization approach of this model is to redistribute transfer traffic across various flow lines, i.e., changing the traffic flow on road segments and the passenger arrival rate at each entrance, and controlling the number and cost of entrance gates and security check equipment at transfer nodes. Under the combined effect of these two factors, the optimization scheme with the minimum impedance and minimum cost is sought. Therefore, changes in the impedance of individual road segments or nodes are not the optimization objective; that is, a slight increase in road segment impedance under peak traffic conditions and node impedance under off-peak traffic conditions is reasonable.

[0175] Table 13 Comparison of the degree of optimization of the operating cost and impedance cost ratio of the New Interchange Node Facilities

[0176]

[0177] In peak traffic scenarios, the optimal solution of the optimization model increases the operating cost of hub transfer node facilities by 5.65% compared to the current situation. At the same time, in this optimal solution, the hub transfer impedance is reduced by 17.37%, and the impedance-cost ratio is reduced by 21.76%. In off-peak traffic scenarios, the optimal solution of the optimization model reduces the operating cost of hub transfer node facilities by 16.56% compared to the current situation. At the same time, in this optimal solution, the hub transfer impedance is not reduced by 0.00%, and the impedance-cost ratio is increased by 19.84%.

[0178] The optimization space varies under different traffic flow scenarios. In peak traffic scenarios, there is significant room for optimization of hub impedance. Therefore, the optimal solution obtained by the optimization model shows a slight increase in cost and a significant decrease in impedance, resulting in a negative impedance-to-cost ratio. In off-peak traffic scenarios, there is significant room for optimization of the operating costs of hub transfer node facilities. Therefore, the optimal solution obtained by the optimization model shows a significant decrease in cost and a slight decrease in impedance, resulting in a positive impedance-to-cost ratio. In summary, the optimization levels of impedance-to-cost ratios of -21.76% and 19.84% are reasonable and effective under both high and low peak traffic scenarios.

[0179] It should be understood that the embodiments and descriptions above are only the principles, main features and advantages of the present invention. Various changes and modifications can be made to the present invention without departing from the spirit and scope of the invention, and all such changes and modifications fall within the protection scope of the present invention.

Claims

1. A method for optimizing transfer flow in a railway-dominated integrated passenger transport hub, characterized in that, Includes the following steps: (1) Analyze the characteristics of railway integrated passenger transport hubs, obtain data elements of passenger transfer process in the hub, analyze the characteristics of passenger transfer process in the hub, and abstract the passenger transfer path in railway integrated passenger transport hub into a transfer network; (2) Analyze the walking characteristics and impedance influencing factors of passengers in the hub transfer section, establish the impedance model of the hub transfer section, calibrate the model parameters based on the survey data, and verify the applicability and rationality of the impedance model of the hub transfer section; (3) Analyze the walking characteristics and impedance influencing factors of passengers at hub transfer nodes, establish a hub transfer node impedance model, calibrate the model parameters based on survey data, and verify the applicability and rationality of the hub transfer node impedance model; (4) To minimize the transfer impedance of the hub and the operating cost of the node facilities, an optimization model of the transfer passenger flow of the railway integrated passenger transport hub is established, and a solution algorithm is proposed. (5) Calculate the hub transfer impedance and node facility operation cost before hub optimization, compare and analyze the changes in hub transfer impedance and node facility operation cost before and after optimization, as well as the hub transfer network traffic distribution before and after optimization, analyze and evaluate the optimization effect of the optimization scheme, and finally propose corresponding optimization strategies based on the optimization scheme.

2. The method for optimizing transfer flow in a railway-dominated integrated passenger transport hub according to claim 1, characterized in that, The data elements of the transfer process in step (1) include static data within the hub and dynamic data of the transfer process; the static data within the hub includes: static data of the hub transfer segments and static data of the hub transfer node facilities; the static data of the hub transfer segments includes segment location, segment number, starting node, ending node, segment length, segment width, segment slope, and escalator operating speed; the static data of the hub transfer nodes includes node location, node number, number of node facilities, and staff configuration; the dynamic data within the hub includes: dynamic data of passenger flow at the hub entrance, dynamic data of the hub transfer segments, and dynamic data of the hub transfer nodes; the dynamic data of passenger flow at the hub entrance includes total passenger flow and passenger flow of each mode of transportation; the dynamic data of the hub transfer segments includes segment flow and passenger travel time; the dynamic data of the hub transfer nodes includes node flow, passenger arrival time distribution, and facility service time distribution.

3. The method for optimizing transfer flow in a railway-dominated integrated passenger transport hub according to claim 1, characterized in that, The process of analyzing the characteristics of passenger transfers within the hub in step (1) is as follows: The transfer process includes transfers between train services within the railway network and transfers between other modes of transportation and the railway network. Transfers between train services within the railway network are facilitated through convenient transfers, eliminating the need for procedures such as entering the station, ticket inspection, security checks, and waiting for the train. Transferring from other modes of transportation to railway transportation involves the necessary procedures of arrival, ticket inspection and entry, security check, and waiting for the train. The transfer facilities include: transfer plaza, transfer hall, transfer passage, transfer stairs, entrance gate facilities and security check facilities. The sections of the transfer plaza, transfer hall, transfer passage and transfer stairs are defined as hub transfer sections, and the areas where passengers receive services from entrance gate facilities and security check facilities are defined as hub transfer nodes.

4. The method for optimizing transfer flow in a railway-dominated integrated passenger transport hub according to claim 1, characterized in that, The impedance model of the hub transfer section in step (2) is the sum of the impedances of the horizontal section, the sloping section, and the escalator section, as detailed below: ； ； ； ； in, Impedance of the transfer section at the hub; For horizontal road sections, the impedance is... Impedance for sloping road sections; For the impedance of the escalator section; These represent the number of horizontal road sections, sloping road sections, and escalator road sections, respectively. For the first The impedance of each horizontal road segment For the first Impedance of a sloping road section; For the first The impedance of each escalator section; For the first The number of passengers on a typical horizontal road section; For the first The number of passengers on each sloping section of the road; For the first The number of passengers on each escalator section.

5. The method for optimizing transfer flow in railway-dominated integrated passenger transport hubs according to claim 1, characterized in that, The impedance model of the hub transfer node mentioned in step (3) is the impedance model of the entrance gate node and the impedance model of the security check node. The specific process is as follows: ； ； ； in, Impedance of the hub transfer node; The impedance of the entrance gate; Impedance of the security checkpoint; This refers to the number of entrance gates and security checkpoints. For the first Average dwell time of each entry gate queuing system For the first Average dwell time in the queuing system at each security checkpoint; For the first The number of passengers at each entrance gate node; For the first The number of passengers at each security checkpoint.

6. The method for optimizing transfer flow in railway-dominated integrated passenger transport hubs according to claim 5, characterized in that, The impedance model of the entrance gate node is applicable in low-peak passenger flow scenarios. Queuing systems are suitable for peak passenger flow scenarios. Queuing system; In off-peak passenger flow scenarios, The operational metrics of the queuing system are calculated using the following formula: ； ； ； ； in, The average waiting time for passengers at the turnstile; This represents the average queue length at the turnstiles. The average length of the turnstile; The average time passengers spend at the turnstile; This refers to the number of turnstiles; The average arrival rate of new passengers in the gate queuing system. The number of passengers arriving at the gate node within one hour; System busy rate; , The expected value and variance of the probability distribution of the service time for the turnstile; For service rate; During peak passenger flow scenarios, The operational metrics of the queuing system are calculated using the following formula: ； ； ； ； ； in, The average arrival rate of new passengers in a single gate queuing system. This refers to the number of turnstiles arranged side-by-side. This represents the system's busy rate.

7. The method for optimizing transfer flow in railway-dominated integrated passenger transport hubs according to claim 5, characterized in that, The impedance model for security checkpoints is applicable under both peak and off-peak passenger flow scenarios. Queuing system This refers to the number of service stations in a single-channel queuing multi-channel service system; for systems with... A queuing system consisting of security screening machines can be broken down into... indivual system.

8. The method for optimizing transfer flow in railway-dominated integrated passenger transport hubs according to claim 1, characterized in that, Step (4) aims to minimize hub transfer impedance and node facility operating costs, specifically as follows: ； ； S.t. ; ； ； ； ； in, For hub transfer impedance; Impedance of the transfer section at the hub; Impedance of the hub transfer node; For example, an edge in a hub transfer network; It refers to a point in the hub transfer network; For the side Traffic; For the edge The weight, i.e., the impedance on the transfer section of the hub. , ; Let be the matrix of connections between edges and points. When the edge... For point The import side, ,on the contrary, , , ; For the edge Point of view The weight on the point, i.e., the impedance at the point. , ; The operating cost of hub transfer node facilities per unit of time; This refers to the number of entrances to the hub station. The cost per unit of time for using a single entrance gate; The cost per unit of time for the use of a single security check facility; For staff operating expenses; For the first Number of staff at each entrance; For the first The number of entrance gates at each entrance; For the first The number of security checkpoints at each entrance; Starting from a certain point; For a certain endpoint; The set that starts from; The set whose endpoint is... The set of all paths; For a specific path in the path set; A set of paths; For 0-1 variables, For a point in the network; For the network Point flow direction Point traffic; For the network Point flow direction Point traffic; for Traffic along the path; for and Inter-flow; This is the correlation matrix between edges and paths.

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