Method and system for calculating time impedance in high-speed rail comprehensive passenger transport junction station

Abstract

The invention discloses a method and a system for calculating time impedance in a high-speed rail comprehensive passenger transport junction station. The method specifically comprises the following steps of: summarizing static information and passenger activity characteristic information of each gate in a junction; constructing a pull-in gate-security check combined impedance model and a ticket check gate impedance model; performing system parameter calibration on the pull-in gate-security check combined impedance model and the ticket check gate impedance model; based on the system parameters of the pull-in gate-security check combined impedance model, obtaining queuing indexes of the pull-in gate-security check combined impedance model; obtaining a queuing index of the ticket checking gate impedance model based on the system parameters of the ticket checking gate impedance model; all queuing indexes and system parameters are analyzed, bottleneck links that traffic capacity is redundant and service capacity is not matched with passenger demands are found, a targeted scheme is made accordingly, and hub design and management are optimized. The built transfer impedance model in the high-speed rail junction station can represent the internal impedance of the high-speed rail junction station building area with high accuracy.

Description

Technical Field

[0001] This invention belongs to the field of transportation engineering and railway passenger hub optimization technology, and in particular relates to a method and system for calculating time impedance within a high-speed rail integrated passenger hub station. Background Technology

[0002] Time impedance analysis within high-speed rail hubs is a crucial step in evaluating and optimizing transfer efficiency at integrated high-speed rail passenger transport hubs, significantly impacting passenger travel experience and hub operation management. While existing hub transfer research has established a relatively complete theoretical framework, systematic research on transfer impedance within integrated high-speed rail passenger transport hubs remains insufficient, hindering effective support for the refined design and operation management of these hubs. This is manifested in the following aspects:

[0003] ① There is a lack of systematic identification and analysis of key nodes in the passenger entry process, and the core links affecting transfer time costs have not been effectively identified;

[0004] ② There is a lack of in-depth analysis of passenger behavior characteristics at the nodes, and the specific influencing factors of time impedance at each stage are not clearly identified;

[0005] ③ There is a lack of methods for modeling the service process of each node based on queuing theory and other theories, making it difficult to quantify and dynamically evaluate the time impedance within the hub. Summary of the Invention

[0006] Purpose of the invention: In order to solve the problems existing in the prior art, the present invention provides a method and system for calculating time impedance in a high-speed rail integrated passenger transport hub.

[0007] Technical solution: This invention discloses a method for calculating time impedance within a high-speed rail integrated passenger transport hub station, specifically as follows:

[0008] Summarize the static information and passenger activity characteristics of each gate within the hub;

[0009] Construct a joint impedance model of the entrance gate and security checkpoint, and construct an impedance model of the ticket gate.

[0010] System parameter calibration was performed on the combined impedance model of the entrance gate and security checkpoint.

[0011] System parameter calibration is performed on the impedance model of the ticket gate;

[0012] Based on the system parameters of the joint impedance model of the entrance gate and security check, the queuing index of the joint impedance model of the entrance gate and security check is obtained;

[0013] Based on the system parameters of the ticket gate impedance model, the queuing index of the ticket gate impedance model is obtained.

[0014] Analyze all queuing indicators and system parameters to identify bottlenecks where throughput capacity is redundant and service capacity does not match passenger demand. Based on this, develop targeted solutions to optimize hub design and management.

[0015] Furthermore, the construction of the entrance gate-security check joint impedance model specifically involves: the entrance gate-security check joint impedance model being a continuous queuing system consisting of two service stations; each service station includes several sub-service counters, which are entrance gates or security check nodes; based on the time interval between adjacent customers continuously leaving the same entrance gate... Assuming the passenger arrival process follows an exponential distribution, and that the arrival processes at entrance gates and security checkpoints follow the same distribution, then for any service station corresponding to either the entrance gate or the security checkpoint, we denote either type of service station as having an exponential distribution. Single-channel parallel connection of individual service counters A queuing system, where M represents a Poisson distribution. The probability distributions of passenger arrival and service time are both Poisson distributions.

[0016] Furthermore, the system parameters of the entrance gate-security check joint impedance model include: the number of related facilities, the arrival passenger flow, the average arrival rate, the passage time, the service rate, the queue length, the average queue length, and the service intensity of the queuing system.

[0017] Furthermore, the system parameters of the entrance gate queuing system and the security gate queuing system in the system are calculated separately using the joint impedance model of the entrance gate and the security gate.

[0018] The expression for the service intensity of a queuing system is: :

[0019] ;

[0020] in, For passenger arrival rate, The average service rate of the service desk;

[0021] The average queue length, which is the total number of passengers waiting in the queue in the system, is expressed as:

[0022] ;

[0023] in, Let be the probability that the number of passengers in the queuing system is 0. The expression is:

[0024] ;

[0025] in, The number of passengers in the system;

[0026] The average queue length, which is the total number of passengers receiving service and those waiting in the queue in the system, is expressed as follows:

[0027] .

[0028] Furthermore, the impedance model of the ticket gate is constructed as follows: based on the input process, queuing rules, and service mode of the ticket gate, the impedance model of the ticket gate is described as follows: A parallel Queuing system The probability distributions of passenger arrival and service time are both general distributions.

[0029] Furthermore, the system parameters of the ticket gate impedance model include the number of ticket gates, the system passenger flow, the average arrival rate, the mean of the passenger arrival time interval, the variance of the passenger arrival time interval, the mean of the ticket check service time, the variance of the ticket check service time, the system service intensity, the average waiting time, the average consumption time, the average queue length, and the average queue length.

[0030] Furthermore, the expressions for the system parameters of the ticket gate impedance model are as follows:

[0031] The service intensity of the queuing system is :

[0032] ;

[0033] in, The arrival rate of passengers at the ticket gates. The average service rate of the ticket gate service counter;

[0034] The expression for average waiting time is:

[0035] ;

[0036] in, The average waiting time, , These represent the average passenger arrival interval and the average system service duration, respectively. , These represent the deviation coefficients for passenger arrival interval and system service duration, respectively.

[0037] The expression for average duration is:

[0038] ;

[0039] The expression for average queue length is:

[0040] ;

[0041] Average team leader:

[0042] .

[0043] Furthermore, the queuing index of the entrance gate-security check joint impedance model and the queuing index of the ticket gate impedance model both include: the number of people queuing, the total number of people in the system, the queuing time, and the passage time impedance.

[0044] The queueing number in the joint impedance model of the entrance gate and security check is the sum of the queueing numbers in the entrance gate queuing system and the security check queuing system; the total number of people in the joint impedance model of the entrance gate and security check is the sum of the total number of people in the entrance gate queuing system and the total number of people in the security check queuing system; the passage time impedance in the joint impedance model of the entrance gate and security check is the sum of the passage time impedance in the entrance gate queuing system and the passage time impedance in the security check queuing system; the queuing time in the joint impedance model of the entrance gate and security check is the sum of the queuing time in the entrance gate queuing system and the queuing time in the security check queuing system.

[0045] Queuing time for entry gate queuing system or security check queuing system The expression is:

[0046] ;

[0047] Through-time impedance of entrance gate queuing system or security check queuing system for:

[0048] ;

[0049] in, This represents the average queue length of the corresponding queuing system. This represents the average service rate of the corresponding queuing system.

[0050] A time impedance calculation system for a high-speed rail integrated passenger transport hub station includes:

[0051] Information aggregation module: used to aggregate static information and passenger activity characteristics of each gate within the hub;

[0052] The impedance model construction module is used to construct the joint impedance model of the entrance gate and security checkpoint, as well as the impedance model of the ticket gate; the system parameter calibration module is used to calibrate the system parameters of the joint impedance model of the entrance gate and security checkpoint, and the impedance model of the ticket gate.

[0053] The queuing index calculation module is used to calculate the queuing index of the entrance gate-security check joint impedance model and the ticket gate impedance model.

[0054] The decision-making module is used to analyze queuing indicators and system parameter calibration parameters to identify bottlenecks where there is redundancy in throughput capacity or a mismatch between service capacity and passenger demand. Based on this, targeted solutions are developed to optimize hub design and management.

[0055] A computer device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to implement the steps of the time impedance calculation method within a high-speed rail integrated passenger transport hub station.

[0056] Beneficial Effects: This invention first outlines the entire process of passengers arriving at a high-speed rail hub and boarding a high-speed train, identifying three key nodes affecting the internal impedance of the hub: the entrance gate, security checkpoint, and ticket gate. Then, it analyzes the behavioral characteristics of passengers at these three nodes. Next, it summarizes queuing theory, explaining its main components and representation methods, and analyzes the rationality of using queuing theory to describe the impedance of key nodes within the hub. Then, based on factors such as passenger arrival patterns, queuing methods, and flow characteristics at each node, queuing models are established for each node. Considering the continuous passage of passengers at the entrance gate and security checkpoints, these two nodes are treated as a single system, described using a continuous multi-level queuing system. It is proven that the passenger input distribution at the security checkpoint is the same as that at the entrance gate. For the special characteristics of passenger arrival and service time distribution at the ticket gate, N parallel queuing systems are used... A queuing system is used to depict the queuing situation at the ticket gate node. Then, impedance models for the joint entry-security check node and the ticket gate node are established by combining the queuing models of each node. This invention identifies three nodes—entry gate, security check, and ticket gate—based on the passenger entry process within a high-speed rail hub. By systematically analyzing passenger behavior and process characteristics at each node, it constructs a realistic time impedance model, effectively supporting the refined design and operation management needs of high-speed rail hubs. The high-speed rail hub transfer impedance model established by this invention can accurately characterize the internal impedance of the high-speed rail hub station area. Attached Figure Description

[0057] Figure 1 This is a flowchart of the method of the present invention.

[0058] Figure 2 This is a structural diagram of the combined impedance model of the entrance gate and security checkpoint of the present invention.

[0059] Figure 3Figure (a) shows the comparison between the calculated and actual values ​​obtained using this method, while Figure (b) shows the comparison between the calculated and actual values ​​in the entrance gate queuing system, and Figure (c) shows the comparison between the calculated and actual values ​​in the security check queuing system. Detailed Implementation

[0060] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0061] like Figure 1 As shown, the method of this invention establishes a joint impedance model of the entrance gate and security checkpoint, as well as an impedance model of the ticket gate, by summarizing information on the internal nodes of a high-speed rail hub and analyzing the characteristics of the components of the passenger queuing system, such as the entrance gate, security checkpoint, and ticket gate. The impedance of each internal node is then calculated and analyzed. The specific steps are as follows:

[0062] (1) Summary of information on internal nodes of the high-speed rail hub. Based on the survey results, the static information and passenger activity characteristics of each node within the hub were determined. Static information includes the number of facilities, their layout, the number of service counters, etc.; passenger activity characteristics include the time characteristics of passenger arrival and service reception.

[0063] (2) Calibration of impedance model parameters for each node. Based on the summary results in step (1), calculate the parameters in the queuing impedance model of each node in the high-speed rail hub station, including arrival rate, mean and variance of service time, service intensity, number of service stations, etc.

[0064] (3) Calculation of impedance model indicators for each node. Based on the indicator calculation results in step (2), calculate the impedance of each characteristic indicator in the model and the transfer time value under the passenger flow during the survey period, and compare it with the actual survey value of the service duration received by passengers at each node. Finally, determine the applicability of the model based on the error comparison results and analyze the impedance calculation results of each node.

[0065] Step 1: Compile information on the internal nodes of the high-speed rail hub.

[0066] This embodiment takes Nanjing South Railway Station as the research object.

[0067] (1.1) An example of the static information survey results of each node within the hub is shown in Table 1.

[0068] Table 1

[0069]

[0070] (1.2) Passenger activity characteristics information at the entrance gate node

[0071] The process of passengers arriving at the entrance gate node is a stochastic dynamic process. Passengers arriving at the security check area in each non-overlapping time interval are independent, and both the entrance gate and the arrival follow a Poisson distribution.

[0072] Passengers at the entrance gates are served on a first-come, first-served basis, and there is a waiting system. Passengers can choose the shorter queue to receive service based on the queue situation at the gate.

[0073] If there are available and unused entrance gates when a passenger arrives at the node, they can receive service directly; otherwise, they will need to queue and wait for service. After receiving service, the passenger will leave the node area. Even if the entrance area is crowded and chaotic, it will not prevent passengers from entering the node.

[0074] (1.3) Passenger activity characteristics information at security checkpoints and entrance gates

[0075] In order to find the input distribution of the security checkpoint (the time interval distribution of passengers arriving at the security checkpoint, that is, the time interval distribution of two adjacent passengers arriving at the security checkpoint), it is necessary to find the output distribution of the entrance gate node (the time interval distribution of passengers leaving the entrance gate node, that is, the time interval between two adjacent passengers leaving the same entrance gate).

[0076] Assume there exists a common Each service desk The queuing system is in a steady state. Indicates the time after the previous customer left. The number of customers in the system at that time is... At any time, the system has The probability of a customer is:

[0077]

[0078] Let random variable The time difference (i.e., the interval) between consecutive departures of adjacent customers from the system exists:

[0079]

[0080] in, Indicates in The time system has 100 customers, and Less than the interval time The joint probability of the random variable is the probability that the next customer has not yet left after the previous customer has left. The expression for the cumulative distribution function As shown below:

[0081] In order to obtain First, we need to obtain The expression, about The difference equation is shown below:

[0082]

[0083] Will Move each equation from the right side to the left side, and divide by... and take The limit of is obtained as follows:

[0084]

[0085] According to the formula The boundary conditions are as follows:

[0086]

[0087] Based on the boundary conditions, we can solve for... The solution is:

[0088]

[0089] Substitute the above expression into the formula. The interval time can be obtained. The cumulative distribution function is:

[0090]

[0091] The time interval between consecutive departures of adjacent customers from the previous system Following an exponential distribution, it can be proven that in a two-stage, multi-service continuous queuing system, both the passenger input distribution (describing the probability distribution of the time intervals between customer arrivals, e.g., the time interval between each customer's arrival at the next system is random and follows an exponential distribution) and the output distribution follow a parameter of . The exponential distribution follows. Therefore, the passenger arrival process at the entrance gate and security checkpoint follows the same distribution.

[0092] (1.4) Joint node of entrance gate and security check

[0093] Passengers must pass through the entrance gates and security checkpoints in sequence to enter the station. Skipping any step or changing the order of steps is not permitted.

[0094] Based on (1.1), (1.2), and (1.3), the entrance gate-security check queuing system of a high-speed rail station is a continuous queuing system consisting of two service stations.

[0095] Generally, the waiting space between two adjacent service stations in a continuous queuing system (in this embodiment, all entrance gates are considered as one service station, and all security gates are considered as one service station) usually has capacity limitations, leading to downstream service stations often being regarded as queuing systems with limited customer sources. However, the waiting areas between entrance gate nodes and security checkpoint nodes in high-speed rail stations have relatively ample space and large capacity, making it less likely that the number of customers in the waiting areas between nodes will exceed the passenger capacity of the waiting areas.

[0096] Therefore, each sub-service station (which is either an entrance gate or a security checkpoint) in the entrance gate-security check joint queuing system complies with... Queuing theory model, Where M represents the Poisson distribution. The probability distributions of passenger arrival and service time are both Poisson distributions.

[0097] (1.5) Passenger activity characteristics information at the boarding gate nodes

[0098] Some passengers begin queuing before the boarding announcement is issued, while others proceed from various locations in the waiting hall to their respective boarding gates after receiving the announcement. Based on this, this paper argues that passenger input at the boarding gates follows a general distribution.

[0099] Passengers wait in line at the ticket gate to receive service, and are served on a first-come, first-served basis according to the rules.

[0100] The ticket gate node contains multiple parallel service counters (the service counters here are ticket gates), and the service time for passenger ticket checking follows a normal distribution.

[0101] This embodiment, based on an on-site investigation of the ticket gate nodes at Nanjing South Railway Station, found that each ticket gate at the station has four independently operating ticket gates, resulting in minimal passenger queue changes. Therefore, the ticket gate nodes in this invention are designed as four independently operating gates. The queuing system. The probability distributions of passenger arrival and service time are both general.

[0102] Step 2: Calibrate the impedance model parameters of each node.

[0103] (2.1) Calibration of impedance model parameters of the entrance gate-security check joint node

[0104] The structure of the impedance model of the entrance gate-security check joint node is as follows: Figure 2 As shown;

[0105] For a single-channel parallel connection with C sub-service counters Queueing and sequencing, passenger arrival rate is recorded as... The average service rate of each service desk is recorded as follows: The average service rate of the entire queuing system is:

[0106] ;

[0107] in, This indicates the number of customers in the queuing system.

[0108] The system service strength is:

[0109] ;

[0110] When the system is in a steady state (in this embodiment) (The system is considered to be in a steady state). The queuing system has a total of... The probability of 1 passenger for:

[0111] ;

[0112] Among them, the probability that the number of passengers in the queuing system is 0. for:

[0113] ;

[0114] The average queue length of the queuing system (the total number of passengers waiting in the queue) is:

[0115] ;

[0116] The average queue length (the total number of passengers receiving service and those waiting in the queue) of a queuing system is:

[0117] ;

[0118] The average customer wait time in the system (including only queue time) is:

[0119] ;

[0120] The average customer dwell time in the system (including queuing time and service time) is:

[0121] ;

[0122] The parameter results of the Nanjing calibrated entrance gate node and the parameter results of the security check node queuing system can be filled into the table. The parameters of the entrance gate node queuing system are shown in Table 2, and the parameters of the security check gate node queuing system are shown in Table 3.

[0123] Table 2:

[0124]

[0125] Table 3:

[0126]

[0127] (2.2) Calibration of impedance model parameters of ticket gate nodes

[0128] right A queuing system, assuming its passenger arrival rate is The average service rate of the service desk The system's service strength is:

[0129] ;

[0130] The average waiting time for passengers in this system is:

[0131] ;

[0132] in, , These represent the average passenger arrival interval and the average system service duration, respectively. , These represent the deviation coefficients for passenger arrival intervals and system service duration, respectively.

[0133] The average time passengers spend in this system is:

[0134] ;

[0135] According to Little's law, the average queue length of the system is:

[0136] ;

[0137] The average length of the system is:

[0138] ;

[0139] The results of calibrating the parameters of the queuing system at the boarding gate nodes are shown in Table 4 below:

[0140] Table 4

[0141]

[0142] Step 3: Calculate the impedance model indicators for each node: Based on the calculation results of indicators (2.1) and (2.2), calculate the impedance of each characteristic indicator in the model and the transfer time value impedance under the passenger flow during the survey period. Analyze the impedance calculation results of each node. The construction steps are as follows:

[0143] (3.1) Impedance of the joint node between the entrance gate and the security checkpoint

[0144] Based on the parameter calibration results of the entrance gate node and security check node in (2.1), the queuing index and time impedance of each part of the entrance-security check joint queuing system are calculated. The queuing index includes the number of people queuing, the total number of people in the system, and the queuing time.

[0145] Queuing time at any service counter in the turnstile-security check queuing system and time impedance The expression is:

[0146] ;

[0147] ;

[0148] The overall queuing index and time impedance of the combined queuing system can be obtained by summing the operating indicators of the two service counters.

[0149] The queuing parameters and time impedance of the entrance gate queuing system are shown in Table 5:

[0150] Table 5

[0151]

[0152] The queuing parameters and time impedance of the security gate queuing system are shown in Table 6:

[0153] Table 6

[0154]

[0155] The calculation results of queuing index and time impedance of the entrance gate-security check joint node are shown in Table 7:

[0156] Table 7

[0157]

[0158] (3.2) Impedance of the ticket gate node

[0159] Based on the parameter calibration results in (2.2), the queuing index and time impedance of the ticket checking queuing system were calculated. The above index data are summarized in Table 8:

[0160] Table 8

[0161]

[0162] (3.3) Analyze the impedance calculation results of each node.

[0163] By analyzing impedance characteristics such as queuing time and queuing length at nodes, bottlenecks with redundant capacity and mismatch between service capacity and passenger demand can be identified, and targeted solutions can be developed to optimize hub design and management.

[0164] Figure 3 This is a comparison chart between the calculated values ​​and actual values ​​obtained using this method. Figure 3 It can be seen that, except for the large queuing time error caused by the small number of people queuing at the entrance gate, the operating indicators of the other queuing systems are all below 15%. Therefore, the joint impedance model of entrance gate and security check proposed in this paper can accurately describe the passage of passengers at the entrance gate and security check.

[0165] This invention studies the time impedance of the high-speed rail hub's internal and external service areas based on the different characteristics exhibited by passengers during transfers within and outside the hub. This chapter primarily focuses on the internal impedance of the high-speed rail hub. First, the entire process of passengers arriving at the high-speed rail hub station and boarding the train is outlined, identifying three key nodes affecting the hub's internal impedance: the entrance gate, security checkpoint, and ticket gate. Then, the behavioral characteristics of passengers at these three nodes are analyzed. Next, queuing theory is summarized, explaining its main components and representation methods, and analyzing the rationality of using queuing theory to describe the impedance of each important node within the hub. Finally, based on factors such as passenger arrival patterns, queuing methods, and flow characteristics at each node, queuing models are established for each node. Considering the continuous passage of passengers at the entrance gate and security checkpoint, these two nodes are treated as a single system. A continuous multi-level queuing system is used to describe this system, and it is proven that the passenger input distribution at the security checkpoint is the same as that at the entrance gate. Addressing the unique characteristics of passenger arrival and service time distribution at the ticket checkpoint, N parallel queues are used... A queuing system was used to depict the queuing situation at the ticket gate node. Then, impedance models were established for the joint entry-security check node and the ticket check node, based on the queuing models of each node. Finally, Nanjing South Railway Station was used as a case study high-speed rail hub. Model parameters were calibrated based on survey data, and the time impedance of each node was calculated. A comparison and analysis of the calculated time impedance results with the actual survey results showed that the relative error between the calculated results and the survey results did not exceed 15%. Finally, analysis of the time impedance calculation results for each node revealed that the security check node is a significant bottleneck in the entry process within the hub.

[0166] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

Claims

1. A method for calculating time impedance within a high-speed railway integrated passenger transport hub station, characterized in that, Specifically: Summarize the static information and passenger activity characteristics of each gate within the hub; Construct a joint impedance model of the entrance gate and security checkpoint, and construct an impedance model of the ticket gate. System parameter calibration was performed on the combined impedance model of the entrance gate and security checkpoint. System parameter calibration is performed on the impedance model of the ticket gate; Based on the system parameters of the joint impedance model of the entrance gate and security check, the queuing index of the joint impedance model of the entrance gate and security check is obtained; Based on the system parameters of the ticket gate impedance model, the queuing index of the ticket gate impedance model is obtained. Analyze all queuing indicators and system parameters to identify bottlenecks where throughput capacity is redundant and service capacity does not match passenger demand. Based on this, develop targeted solutions to optimize hub design and management.

2. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 1, characterized in that, The construction of the entrance gate-security check joint impedance model specifically involves: the entrance gate-security check joint impedance model being a continuous queuing system consisting of two service stations; each service station includes several sub-service counters, which are entrance gates or security check nodes; based on the time interval between adjacent customers leaving the same entrance gate consecutively. Assuming the passenger arrival process follows an exponential distribution, and that the arrival processes at entrance gates and security checkpoints follow the same distribution, then for any service station corresponding to either the entrance gate or the security checkpoint, we denote either type of service station as having an exponential distribution. Single-channel parallel connection of individual service counters A queuing system, where M represents a Poisson distribution. The probability distributions of passenger arrival and service time are both Poisson distributions.

3. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 1, characterized in that, The parameters of the entrance gate-security check joint impedance model system include: the number of related facilities, the arrival passenger flow, the average arrival rate, the passage time, the service rate, the queue length, the average queue length, and the service intensity of the queuing system.

4. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 2, characterized in that, The system parameters of the entrance gate queuing system and the security gate queuing system in the system are calculated separately using the joint impedance model of the entrance gate and the security gate. The expression for the service intensity of a queuing system is: : ； in, For passenger arrival rate, The average service rate of the service desk; The average queue length, which is the total number of passengers waiting in the queue in the system, is expressed as: ； in, Let be the probability that the number of passengers in the queuing system is 0. The expression is: ； in, The number of passengers in the system; The average queue length, which is the total number of passengers receiving service and those waiting in the queue in the system, is expressed as follows: 。 5. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 1, characterized in that, The specific steps for constructing the ticket gate impedance model are as follows: Based on the input process, queuing rules, and service mode of the ticket gate, the ticket gate impedance model is described as follows: A parallel Queuing system The probability distributions of passenger arrival and service time are both general distributions.

6. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 1, characterized in that, The system parameters of the ticket gate impedance model include the number of ticket gates, the system passenger flow, the average arrival rate, the mean of the passenger arrival time interval, the variance of the passenger arrival time interval, the mean of the ticket check service time, the variance of the ticket check service time, the system service intensity, the average waiting time, the average consumption time, the average queue length, and the average queue length.

7. The method for calculating time impedance within a high-speed rail integrated passenger transport hub station according to claim 6, characterized in that, The expressions for the system parameters of the ticket gate impedance model are as follows: The service intensity of the queuing system is : ； in, The arrival rate of passengers at the ticket gates. The average service rate of the ticket gate service counter; The expression for average waiting time is: ； in, The average waiting time, , These represent the average passenger arrival interval and the average system service duration, respectively. , These represent the deviation coefficients for passenger arrival interval and system service duration, respectively. The expression for average duration is: ； The expression for average queue length is: ； Average team leader: 。 8. The method for calculating time impedance within a high-speed rail integrated passenger transport hub according to claim 1, characterized in that, The queuing index of the joint impedance model of the entrance gate and security check and the queuing index of the ticket gate impedance model both include: the number of people queuing, the total number of people in the system, the queuing time, and the passage time impedance. The queueing number in the joint impedance model of the entrance gate and security check is the sum of the queueing numbers in the entrance gate queuing system and the security check queuing system; the total number of people in the joint impedance model of the entrance gate and security check is the sum of the total number of people in the entrance gate queuing system and the total number of people in the security check queuing system; the passage time impedance in the joint impedance model of the entrance gate and security check is the sum of the passage time impedance in the entrance gate queuing system and the passage time impedance in the security check queuing system; the queuing time in the joint impedance model of the entrance gate and security check is the sum of the queuing time in the entrance gate queuing system and the queuing time in the security check queuing system. Queuing time for entry gate queuing system or security check queuing system The expression is: ； Through-time impedance of entrance gate queuing system or security check queuing system for: ； in, This represents the average queue length of the corresponding queuing system. This represents the average service rate of the corresponding queuing system.

9. A time impedance calculation system for a high-speed railway integrated passenger transport hub station, characterized in that, include: Information aggregation module: used to aggregate static information and passenger activity characteristics of each gate within the hub; The impedance model construction module is used to construct the joint impedance model of the entrance gate and security checkpoint, as well as the impedance model of the ticket gate; the system parameter calibration module is used to calibrate the system parameters of the joint impedance model of the entrance gate and security checkpoint, and the impedance model of the ticket gate. The queuing index calculation module is used to calculate the queuing index of the entrance gate-security check joint impedance model and the ticket gate impedance model. The decision-making module is used to analyze queuing indicators and system parameter calibration parameters to identify bottlenecks where there is redundancy in throughput capacity or a mismatch between service capacity and passenger demand. Based on this, targeted solutions are developed to optimize hub design and management.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the time impedance calculation method within a high-speed rail integrated passenger transport hub as described in any one of claims 1 to 8.

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