Analysis method and system for reducing redundancy and controlling cost based on full period of rail transit line

Abstract

The invention discloses an analysis method and system for reducing redundancy and controlling cost in a full period based on a rail transit line, and the method comprises the steps: carrying out the virtualization of a to-be-constructed station, generating a simulated station, and obtaining the people flow information in the simulated station, the people flow information comprises uplink and downlink peak hour cross-section passenger flow volume and peak hour one-way cross-section passenger flow volume of a certain line; and respectively setting threshold values of uplink and downlink peak hour cross-section passenger flow volumes and peak hour one-way cross-section passenger flow volumes of a certain line, and optimizing the simulated station according to comparison results of the peak hour cross-section passenger flow volumes and the threshold values so as to finish construction of the final station according to an optimization result.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit design optimization, and more specifically, relates to an analysis method and system for reducing redundant control costs based on the full cycle of a rail transit line. Background Art

[0002] Compared with traditional infrastructure, high-quality development of infrastructure has the following changes: from strips to systems, from government to market, from traditional to new, from links to the entire life cycle, and from cities to urban circles. The current engineering consulting standard system is difficult to adapt to and support the transformation of high-quality development of infrastructure. It is urgently needed to optimize and improve in order to achieve the transformation of high-quality development of infrastructure and accelerate the construction of an adaptive engineering consulting standardization system.

[0003] Currently, there is no intelligent technical solution for rail transit construction that can automatically assess the location of stations and evaluate the stations, thereby adjusting the station plan. Summary of the invention

[0004] In order to solve the above technical problems, the present invention proposes an analysis method for reducing the redundancy control cost based on the full cycle of rail transit lines, including:

[0005] Virtualize the station to be constructed, generate a simulated station, and obtain passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the up and down peak hours, and the passenger flow of a certain line in a one-way direction during the peak hours;

[0006] Thresholds for the up and down peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line are set respectively, and the simulated station is optimized based on the comparison results with the thresholds, so as to complete the construction of the final station based on the optimization results.

[0007] Furthermore, it also includes setting up transfer stations, including:

[0008] When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

[0009] Furthermore, it includes: when the difference in the upstream and downstream peak hour section passenger flow exceeds a threshold and the maximum section passenger flow ratio exceeds 1.5:1, optimizing the direction of small passenger flow.

[0010] Furthermore, it also includes: when the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, taking peak-cutting measures.

[0011] Furthermore, it also includes: using the peak hour passenger and alighting volume of single-line stations as a classification indicator, the stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

[0012] The present invention also proposes an analysis system based on reducing redundant control costs of rail transit lines throughout the entire cycle, comprising:

[0013] An information acquisition module is used to virtualize the station to be constructed, generate a simulated station, and obtain passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream sections during peak hours, and the passenger flow of a certain line during peak hours in one direction;

[0014] The optimization module is used to set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line respectively, and optimize the simulated station according to the comparison results with the thresholds, so as to complete the construction of the final station according to the optimization results.

[0015] Furthermore, it also includes setting up transfer stations, including:

[0016] When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

[0017] Furthermore, it includes: when the difference in the upstream and downstream peak hour section passenger flow exceeds a threshold and the maximum section passenger flow ratio exceeds 1.5:1, optimizing the direction of small passenger flow.

[0018] Furthermore, it also includes: when the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, taking peak-cutting measures.

[0019] Furthermore, it also includes: using the peak hour passenger and alighting volume of single-line stations as a classification indicator, the stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

[0020] Compared with the prior art, the above technical solution conceived by the present invention has the following beneficial effects:

[0021] The present invention can optimize the setting of stations and lines according to relevant passenger flow data, and can complete the design of high-quality stations and lines in a highly efficient and energy-saving manner, which has guiding significance for subsequent construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0023] Figure 2 is a system structure diagram of Embodiment 2 of the present invention;

[0024] Figure 3 This is a schematic diagram of differentiated grading of stations according to Example 1 of the present invention. DETAILED DESCRIPTION

[0025] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0026] The method provided by the present invention can be implemented in the following terminal environment, and the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, and the instruction is loaded and executed by the processor to implement the method described in the following embodiment.

[0027] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[0028] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets or instructions.

[0029] The display is used to show the interactive cross-section of each application.

[0030] All subscripts in the formulas of the present invention are only used to distinguish parameters and have no actual meaning.

[0031] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal may include more or fewer components, or combine certain components, or arrange the components differently. For example, the terminal also includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, and a power supply, which will not be described in detail here.

[0032] Example 1

[0033] like Figure 1 As shown, an embodiment of the present invention provides an analysis method based on reducing redundancy control costs of a rail transit line throughout a full cycle, including:

[0034] Step 101, virtualizing the station to be constructed, generating a simulated station, and obtaining passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream sections during peak hours, and the passenger flow of the peak hour one-way sections of a certain line;

[0035] Step 102, respectively set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line, and optimize the simulated station based on the comparison results with the thresholds, so as to complete the construction of the final station based on the optimization results.

[0036] For example, the core contents proposed for the technical characteristics of each line of the Shenzhen Metro Phase 5 project include the following aspects:

[0037] (1) Accurately grasp the characteristics of passenger flow: Through data analysis and market research, understand and describe the characteristics and behavior patterns of customer groups in detail in order to better meet their needs and improve the operational efficiency of rail transit. It is also a data-based method to improve the accuracy and efficiency of construction decisions through in-depth analysis and understanding of customer behavior. It can include in-depth research on data collection and analysis, customer segmentation, behavior pattern recognition, personalized services, marketing strategy optimization, and continuous monitoring and adjustment, and propose professional measures and suggestions based on key data such as the line's full-day passenger flow, peak hour section passenger flow, peak hour boarding and alighting passenger flow, and peak hour transfer volume. The specific contents are as follows:

[0038] (1.1) Daily passenger flow

[0039] Due to the high cost of station construction, operation and maintenance, if the passenger flow of the station is too low, its overall investment and benefits are seriously mismatched. Therefore, when planning and designing, the predicted passenger volume of the station should be combined to deepen the research on the line station plan. Combining the reasonable demonstration and optimization of the line station setting with the long-term full-day passenger volume of the station is conducive to controlling the scale of construction investment and improving operational efficiency. Therefore, for stations with a long-term full-day passenger volume of less than 10,000 people / day, it is possible to consider further comprehensive demonstration of the necessity and economy of station setting.

[0040] The construction and operation costs of transfer stations are high. If the transfer passenger flow is too low, it will cause a serious imbalance between investment and benefits. By demonstrating the reasonable optimization of unnecessary transfer nodes, it is conducive to the control of construction scale and investment costs. Therefore, it can be considered that when the long-term daily transfer volume of the transfer station is less than 10,000 people / day, the necessity and economy of the transfer setting should be further demonstrated.

[0041] In the era of network operation, it is necessary to optimize the design of line connection and transfer from the perspective of network demand. When the transfer passenger flow between two lines is large, it is necessary to combine the transfer passenger flow in different directions and reasonably design the interconnection and transfer on the same platform from the perspective of improving the convenience of passenger travel, which is conducive to improving the network passenger flow service level and improving the efficiency of operation organization. Therefore, it is possible to consider optimizing the network operation organization and station transfer design from the perspective of improving the convenience of passenger transfer. When the full-day transfer volume between the two lines at the transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer design should give priority to interconnection or transfer on the same platform.

[0042] (1.2) Peak hour passenger flow

[0043] There are obvious tidal characteristics in the morning and evening peaks of local subway passenger flow. The imbalance of the two-way sections of the radial lines connecting the central city and the periphery is particularly prominent. The two-way balanced driving plan is likely to cause serious waste of capacity in the direction of small passenger flow. Combined with the differences in the two-way passenger flow sections during peak hours of the line, the redundant capacity in the direction of small passenger flow can be compressed on the basis of ensuring the basic service level, and precise capacity deployment can be achieved, thereby improving the utilization rate of the entire line's transportation capacity during peak hours and saving operating costs. Therefore, when the difference in the passenger flow levels of the sections during peak hours of the upstream and downstream is large and the maximum section passenger flow ratio exceeds 1.5:1, the operation organization of the direction of small passenger flow should be optimized in combination with the passenger flow characteristics of the sections during peak hours.

[0044] The peak section passenger flow of rail lines is generally unevenly distributed, and some lines have a few sections that are significantly higher than other sections. For such lines with significant sharpening characteristics, if the maximum section of the line during peak hours is used as the standard for capacity design, it is easy to cause serious waste of transportation capacity in most sections of the line. Therefore, peak-cutting measures should be reasonably formulated in combination with the peak section distribution characteristics to optimize the capacity deployment and vehicle configuration. Formulating peak-cutting measures based on the peak section sharpening of the line can effectively and reasonably reduce the waste of transportation capacity and control the scale of vehicle configuration in the design stage, thereby reducing operating costs and initial investment. Therefore, it can be considered that when the peak hour one-way section passenger flow of a line is less than 3 sections exceeding 90% of the maximum section passenger flow in that direction, the capacity design should formulate reasonable peak-cutting measures in combination with the section distribution.

[0045] The passenger flow levels in different forecast years are an important basis for transport capacity design and vehicle configuration. When designing, the design capacity should be determined by fully considering the characteristics of passenger flow changes from the initial to long-term. Within the scope allowed by relevant standards, the design capacity margins of different years should be reasonably controlled according to the difference between the initial and long-term passenger flow levels, and the design and investment scale of each stage should be effectively controlled to a certain extent. Therefore, it is possible to consider reasonably designing transport capacity according to the characteristics of passenger flow changes in different forecast years. When the ratio of the maximum cross-section in the long-term to the initial peak hour is greater than 3:1, the transport capacity margin should be reasonably optimized in combination with the difference.

[0046] (1.3) Peak hour passenger flow

[0047] Rail stations have different passenger flow scales due to differences in location, network relationships, and the degree of development along the line. If all stations are designed as standard stations, some stations may become too large and require increased investment. Determining the building scale, design standards, station stop time, and facility equipment configuration based on the passenger and alighting volume of different stations can better guarantee station passenger services and reasonably control construction scale and costs. Therefore, it is possible to consider using the peak hour passenger and alighting volume of single-line stations as a classification indicator to divide stations into three categories: small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h), and large stations (20,000 passengers / h or more); e.g. Figure 3 As shown, stations should be graded and classified according to the peak hour passenger and alighting volumes to determine the scale and design standards of different stations.

[0048] The initial passenger flow of some lines is significantly lower than that of the long-term, indicating that there is a big difference between the land use planning around the station and the current situation, and the uncertainty of the future passenger flow of the station is high. If the station facilities and equipment are designed according to the long-term passenger flow scale, it will lead to a serious mismatch between the long-term investment cost and the actual benefit. By configuring station equipment based on the difference between the initial and long-term peak hour passenger flow and making a phased implementation plan, we can better control the initial equipment scale and station civil engineering scale, reduce the initial construction investment, and better deal with the impact of passenger flow uncertainty on the scale of environmental control facilities. Therefore, it is possible to consider the reasonable configuration of station facilities and equipment based on the characteristics of passenger flow changes in different forecast years. When the ratio of the long-term and initial peak hour passenger flow is greater than 5:1, the necessity of phased implementation of station environmental control equipment should be studied and a phased implementation plan should be reasonably formulated.

[0049] (1.4) Peak hour transfer volume

[0050] Due to differences in the number of lines and line relationships, the transfer volume of each transfer station is different. If the transfer station is designed according to a unified standard, some stations will be too large and the investment will increase. Determining the scale and design standards according to the transfer volume of different stations can better guarantee the station transfer service and reasonably control the construction scale and cost. Therefore, it is possible to consider using the peak hour transfer volume of the station as a classification indicator to divide the transfer station into three categories: small transfer stations (0-10,000 passengers / h), medium transfer stations (10,000-20,000 passengers / h), and large transfer stations (more than 20,000 passengers / h). The transfer station should be classified according to the peak hour transfer volume and reasonably determine the scale and design standards.

[0051] (2) Accurately allocate transport capacity: scientifically and reasonably arrange and adjust the supply of rail transit transportation resources according to market demand and passenger flow characteristics to optimize transportation efficiency. This is also a scientific management method. Through accurate grasp of market demand and reasonable allocation of transportation resources, it aims to improve transportation efficiency, reduce costs, enhance service quality, and ultimately maximize the benefits of rail transit construction and operation. In-depth research can be conducted through market demand analysis, transportation resource scheduling, service quality assurance, cost-effectiveness considerations, dynamic adjustment capabilities, and technical support. Specifically, targeted professional measures such as uneven density driving, peak shaving measures, reducing transportation capacity redundancy, control system capabilities, and non-stopping in the direction of small passenger flow can be proposed. The specific contents are as follows;

[0052] (2.1) Peak capacity shaving design

[0053] The system capacity should be reasonably designed according to the sharpness of the passenger flow section. When the number of sections exceeding 90% of the maximum section during peak hours is no more than 3, peak-shaving design should be considered. The maximum section reduced by 10% or the third section value should be used as the basis for calculation, and the capacity should be configured at 5 people / square meter with a 10% margin. The highest standing density of the entire line should not exceed 6 people / square meter, the number of sections exceeding 5 people / square meter should not be more than 3, and the train running time should not exceed 10 minutes.

[0054] Usually, the capacity design of rail transit lines is based on individual maximum sections as the controlling standard for full-line adaptation. It is easy for individual prominent large sections to cause excessive capacity supply and waste of capacity on the entire line, especially in the current context of slowing down urbanization and high risk of passenger flow fluctuation prediction. For this reason, a peak-cutting design concept that takes comfort into consideration is proposed. Based on 0.9 times the maximum section value, when there are less than 3 interval sections, it can be determined that the section sharpening degree is high, and 10% of the driving pairs are reduced to save costs. At the same time, the number of sections with a congestion degree of more than 5 people / square meter and the riding time are checked to avoid too long congested sections. The goal is to reduce the number of driving pairs by more than 10% and save 10% of the number of vehicles in use.

[0055] (2.2) Unbalanced density driving

[0056] When the ratio of the two-way controlled passenger flow section of the line exceeds 1.5, the traffic density in the direction of small passenger flow should be reduced on the basis of ensuring the service level, and an asymmetric operation mode should be adopted. The number of reductions in one direction should be greater than 4 trains / h.

[0057] The rail transit service customer group is mainly commuter traffic. The commuting characteristics determine that the majority of passenger traffic is tidal travel, and the two-way passenger traffic of the line varies greatly. On the basis of ensuring the supply of capacity in the direction of large passenger traffic and the basic service level in the direction of small passenger traffic, reducing the density of traffic in the direction of small passenger traffic through the traffic organization method can effectively save operating costs. When the line has a high passenger flow and the ratio of large and small sections is more than 1.5 times, it is proposed to reduce the traffic volume in the direction of small passenger traffic, and reduce the number of pairs by no less than 4 trains / h, so as to save more than 10% of the number of vehicles in use and reduce the number of kilometers traveled by more than 3% per day.

[0058] (2.3) Reduce transportation capacity redundancy

[0059] When the initial peak hour section is higher than 25,000 people / h and the future growth rate is less than 50% compared with the initial period, the initial transport capacity margin should be controlled at 5% (calculated at 5 people / square meter); when the future peak hour section is more than 3 times that of the initial period, the future transport capacity margin should be controlled at 5% (calculated at 5 people / square meter). At the same time, the transport capacity margin after the spare vehicle is put into operation should reach 10%.

[0060] By referring to the changes in passenger flow in the initial and long term, the risks of the passenger flow forecast value of the route can be predicted, and then the reserve of transport capacity can be accurately reserved to achieve the purpose of saving the number of vehicles in the initial allocation and the scale of the system in the long term. From the general rule of experience, when the long-term passenger flow section is smaller than the initial growth ratio (0.5 times), it can be judged that the initial development along the line has reached a high degree of maturity, and the risk of upward fluctuation of the initial passenger flow is basically controllable. It is recommended to reduce the transport capacity by 5%; when the ratio reaches more than 3 times, combined with the support of the initial passenger flow intensity for the necessity of construction, it can be judged that the risk of upward fluctuation of the long-term passenger flow is controllable, and it is recommended to reduce the transport capacity by 5%; at the same time, combined with the configuration of the number of spare vehicles, it is ensured that the surplus can still reach 10% after the spare vehicles are put into operation, which matches the corresponding national standards. The goal is to reduce the number of vehicles in the initial allocation by more than 5%.

[0061] (2.4) Control system capabilities

[0062] This method is mainly aimed at the practice of designing system capacity of 30 pairs / h for a single route in rail transit, and aims to accurately reserve capacity according to project characteristics to avoid over-investment. System capacity should be determined by comprehensive transportation capacity reserve and civil engineering system cost ratio, and the rationality of the reservation condition of 30 pairs / h should be checked, especially for lines with long-term expansion of marshaling; when the peak hour section of the peripheral line is lower than 1 / 2 of the highest section (or after peak shaving) and the length is more than 5km, the system capacity should be designed in sections; the system capacity of the low section area should be configured according to 2 / 3 of the highest system capacity of the whole line, and should not be lower than 15 pairs / h, to reserve flexibility for development.

[0063] The specific method is to reduce the system scale index of large passenger flow areas, such as 24 pairs / h and 20 pairs / h. Secondly, based on the changes in passenger flow, the system scale of small passenger flow areas such as peripherals and branches should be determined according to demand. The goal is to reduce the scale of the yard, reduce the interval ventilation shaft, reduce the number of traction stations and transformer capacity, and optimize the wiring conditions such as return.

[0064] (2.5) No stopping and slow driving in the direction of small passenger flow to save energy

[0065] When the ratio of two-way passenger flow cross-section is greater than 2:1, some trains can skip and slow down in the direction of small passenger flow to reduce the number of starts and stops and lower energy consumption. The number of trains skipping and stopping should be greater than 5 pairs per hour.

[0066] The characteristics of rail transit tidal passenger flow determine that there is surplus capacity in the direction of small passenger flow. Under the condition of ensuring the basic service level in the direction of small passenger flow, the goal of saving energy consumption can be achieved by controlling the running speed of trains and reducing train starts and stops by allowing some trains to not stop at stations and running at normal travel speed. The energy saving ratio is >3%.

[0067] (2.6) New functions of the main line parking line improve economy and flexibility

[0068] On the premise of meeting the requirement of turning back passage for nighttime operation vehicles, the parking lines at the starting and ending stations or intermediate stations far from the vehicle base should have the function of parking trains at night and be counted in the number of parking rows on the entire line; the parking rows at the starting and ending stations should all be counted, the double parking lines at the intermediate stations should be counted as one row, and the single parking lines may not be counted. Stations with parking conditions should provide conditions for crew members to rest at night. At the same time, the parking line design should focus on the parking function of hot standby vehicles, provide conditions for clearing passengers at stations with large passenger flow, and be located near high-section stations with large passenger flow, with "four-leg" access conditions. If the conditions cannot be met, the parking line should face the direction of large passenger flow.

[0069] With the current extended train inspection cycle and fully automatic operation level, parking at the mainline parking line can effectively reduce the scale of vehicle bases and trains running empty; the parking line at the intermediate station is counted as one less train position to avoid the inability to park when it is used as a return line. By providing hot standby car parking conditions on the main line and setting parking lines near sudden passenger flow points, the backlog of passengers in the station can be quickly cleared when the passenger flow exceeds expectations, thus improving the flexibility of line operation and risk resistance.

[0070] (3) Refined station classification: This refers to the practice of classifying stations into different levels based on the basic demand characteristics of passenger flow, combined with factors such as station functions, service scope, and importance in the transportation network, so as to rationally allocate resources, optimize service quality, and improve operational efficiency. This will not only help improve the service quality and management efficiency of stations, but also promote the overall optimization of the transportation network, better guide the construction and renovation of stations, and ensure the rationality of investment and maximize benefits. In-depth research can be conducted through multiple dimensions such as passenger flow demand, business functions, service scope, network status, facility scale, information level, station safety management and emergency response capabilities, and comprehensive evaluation indicators. Specifically, targeted professional measures and suggestions can be proposed, such as a station classification system based on predicted passenger flow, differentiated public area facility layout standards, and phased implementation of civil engineering and equipment layout standards.

[0071] Specifically, it also includes: calculating the passenger flow distribution density of a certain line of the simulated station during peak hours according to the passenger flow information, and setting the passenger flow distribution density optimization threshold and the passenger flow distribution density line setting threshold. Only when the passenger flow distribution density of a certain line of the simulated station during peak hours exceeds the passenger flow distribution density line setting threshold, the line will be built when the station is built later. When the passenger flow distribution density of a certain line of the simulated station during peak hours is greater than the passenger flow distribution density line setting threshold and less than the passenger flow distribution density optimization threshold, the line is optimized. The optimization includes: increasing the interval time of each vehicle. The passenger flow distribution density of a certain line of the simulated station during peak hours is calculated as follows:

[0072]

[0073] Among them, suppose the total length of a certain line is L, which is divided into n intervals, and the length of the i-th interval is l i , f(x) is the predicted passenger flow distribution density at the position x along the route during the peak hour, l i-1 is the length of the i-1th interval, f′(x) is the current passenger flow distribution density, ε i is the random disturbance term of the peak hour section passenger flow in the ith interval, k i is the degree of deviation of the passenger flow in the ith interval from the average level, g is the function used to characterize the shape of the predicted passenger flow distribution density f(x) in the ith interval, σ i is the standard deviation parameter of the i-th interval, which controls the width of the kernel function. i is the first shape parameter of the ith interval, βi 为 The second shape parameter of the ith interval, α i and β i Together they control the shape of the kernel function's tail. is iThe mean is 0 and the standard deviation is The normal distribution of i is the center position of the ith interval.

[0074] Example 2

[0075] like Figure 2 As shown, the embodiment of the present invention further proposes an analysis system based on reducing redundancy control costs of rail transit lines throughout the entire cycle, including:

[0076] An information acquisition module is used to virtualize the station to be constructed, generate a simulated station, and obtain passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream sections during peak hours, and the passenger flow of a certain line during peak hours in one direction;

[0077] The optimization module is used to set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line respectively, and optimize the simulated station according to the comparison results with the thresholds, so as to complete the construction of the final station according to the optimization results.

[0078] Specifically, it also includes setting up transfer stations, including:

[0079] When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

[0080] Specifically, it includes: when the difference in the upstream and downstream section passenger flow during peak hours exceeds a threshold and the maximum section passenger flow ratio exceeds 1.5:1, the direction of small passenger flow is optimized.

[0081] Specifically, it also includes: when the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, taking peak-cutting measures.

[0082] Specifically, it also includes: using the peak hour passenger and alighting volume of single-line stations as a classification indicator, the stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

[0083] Specifically, it also includes: calculating the passenger flow distribution density of a certain line of the simulated station during peak hours according to the passenger flow information, and setting the passenger flow distribution density optimization threshold and the passenger flow distribution density line setting threshold. Only when the passenger flow distribution density of a certain line of the simulated station during peak hours exceeds the passenger flow distribution density line setting threshold, the line will be built when the station is built later. When the passenger flow distribution density of a certain line of the simulated station during peak hours is greater than the passenger flow distribution density line setting threshold and less than the passenger flow distribution density optimization threshold, the line is optimized. The optimization includes: increasing the interval time of each vehicle. The passenger flow distribution density of a certain line of the simulated station during peak hours is calculated as follows:

[0084]

[0085] Among them, suppose the total length of a certain line is L, which is divided into n intervals, and the length of the i-th interval is l i , f(x) is the predicted passenger flow distribution density at the position x along the route during the peak hour, l i-1 is the length of the i-1th interval, f′(x) is the current passenger flow distribution density, ε i is the random disturbance term of the peak hour section passenger flow in the ith interval, k i is the degree of deviation of the passenger flow in the ith interval from the average level, g is the function used to characterize the shape of the predicted passenger flow distribution density f(x) in the ith interval, σ i is the standard deviation parameter of the i-th interval, which controls the width of the kernel function. i is the first shape parameter of the ith interval, β i is the second shape parameter of the ith interval, α i and β i Together they control the shape of the kernel function's tail. is i The mean is 0 and the standard deviation is The normal distribution of μ i is the center position of the ith interval.

[0086] Example 3

[0087] An embodiment of the present invention further proposes a storage medium storing a plurality of instructions, wherein the instructions are used to implement the analysis method for reducing redundancy control costs based on the full cycle of a rail transit line.

[0088] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0089] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: Step 101, virtualizing the station to be constructed, generating a simulated station, and obtaining passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream peak hour sections, and the passenger flow of the peak hour one-way sections of a certain line;

[0090] Step 102, respectively set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line, and optimize the simulated station based on the comparison results with the thresholds, so as to complete the construction of the final station based on the optimization results.

[0091] Specifically, it also includes setting up transfer stations, including:

[0092] When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

[0093] Specifically, it includes: when the difference in the upstream and downstream section passenger flow during peak hours exceeds a threshold and the maximum section passenger flow ratio exceeds 1.5:1, the direction of small passenger flow is optimized.

[0094] Specifically, it also includes: when the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, taking peak-cutting measures.

[0095] Specifically, it also includes: using the peak hour passenger and alighting volume of single-line stations as a classification indicator, the stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

[0096] Specifically, it also includes: calculating the passenger flow distribution density of a certain line of the simulated station during peak hours according to the passenger flow information, and setting the passenger flow distribution density optimization threshold and the passenger flow distribution density line setting threshold. Only when the passenger flow distribution density of a certain line of the simulated station during peak hours exceeds the passenger flow distribution density line setting threshold, the line will be built when the station is built later. When the passenger flow distribution density of a certain line of the simulated station during peak hours is greater than the passenger flow distribution density line setting threshold and less than the passenger flow distribution density optimization threshold, the line is optimized. The optimization includes: increasing the interval time of each vehicle. The passenger flow distribution density of a certain line of the simulated station during peak hours is calculated as follows:

[0097]

[0098] Among them, suppose the total length of a certain line is L, which is divided into n intervals, and the length of the i-th interval is l i, f(x) is the predicted passenger flow distribution density at the position x along the route during the peak hour, l i-1 is the length of the i-1th interval, f′(x) is the current passenger flow distribution density, ε i is the random disturbance term of the peak hour section passenger flow in the ith interval, k i is the degree of deviation of the passenger flow in the ith interval from the average level, g is the function used to characterize the shape of the predicted passenger flow distribution density f(x) in the ith interval, σ i is the standard deviation parameter of the i-th interval, which controls the width of the kernel function. i is the first shape parameter of the ith interval, β i is the second shape parameter of the ith interval, α i and β i Together they control the shape of the kernel function's tail. is i The mean is 0 and the standard deviation is The normal distribution of i is the center position of the ith interval.

[0099] Example 4

[0100] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, and the instructions can be loaded and executed by the processor to enable the processor to execute an analysis method based on reducing redundant control costs throughout the entire cycle of a rail transit line.

[0101] Specifically, the electronic device of this embodiment may be a computer terminal, and the computer terminal may include: one or more processors, and a storage medium.

[0102] Among them, the storage medium can be used to store software programs and modules, such as an analysis method for reducing the redundancy control cost of a rail transit line throughout the entire cycle in an embodiment of the present invention, and the corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned analysis method for reducing the redundancy control cost of a rail transit line throughout the entire cycle. The storage medium may include a high-speed random storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include a storage medium remotely arranged relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0103] The processor can call the information and application stored in the storage medium through the transmission system to execute the following steps: Step 101, virtualize the station to be constructed, generate a simulated station, and obtain the passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream peak hours, and the passenger flow of the peak hour one-way section of a certain line;

[0104] Step 102, respectively set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line, and optimize the simulated station based on the comparison results with the thresholds, so as to complete the construction of the final station based on the optimization results.

[0105] Specifically, it also includes setting up transfer stations, including:

[0106] When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

[0107] Specifically, it includes: when the difference in the upstream and downstream section passenger flow during peak hours exceeds a threshold and the maximum section passenger flow ratio exceeds 1.5:1, the direction of small passenger flow is optimized.

[0108] Specifically, it also includes: when the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, taking peak-cutting measures.

[0109] Specifically, it also includes: using the peak hour passenger and alighting volume of single-line stations as a classification indicator, the stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

[0110] Specifically, it also includes: calculating the passenger flow distribution density of a certain line of the simulated station during peak hours according to the passenger flow information, and setting the passenger flow distribution density optimization threshold and the passenger flow distribution density line setting threshold. Only when the passenger flow distribution density of a certain line of the simulated station during peak hours exceeds the passenger flow distribution density line setting threshold, the line will be built when the station is built later. When the passenger flow distribution density of a certain line of the simulated station during peak hours is greater than the passenger flow distribution density line setting threshold and less than the passenger flow distribution density optimization threshold, the line is optimized. The optimization includes: increasing the interval time of each vehicle. The passenger flow distribution density of a certain line of the simulated station during peak hours is calculated as follows:

[0111]

[0112] Among them, suppose the total length of a certain line is L, which is divided into n intervals, and the length of the i-th interval is l i, f(x) is the predicted passenger flow distribution density at the position x along the route during the peak hour, l i-1 is the length of the i-1th interval, f′(x) is the current passenger flow distribution density, ε i is the random disturbance term of the peak hour section passenger flow in the ith interval, k i is the degree of deviation of the passenger flow in the ith interval from the average level, g is the function used to characterize the shape of the predicted passenger flow distribution density f(x) in the ith interval, σ i is the standard deviation parameter of the i-th interval, which controls the width of the kernel function. i is the first shape parameter of the ith interval, β i is the second shape parameter of the ith interval, α i and β i Together they control the shape of the kernel function's tail. is i The mean is 0 and the standard deviation is The normal distribution of μ i is the center position of the ith interval.

[0113] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0114] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0116] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0118] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0119] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. An analysis method for reducing redundancy control costs based on the full cycle of rail transit lines, characterized in that: include: Virtualize the station to be constructed, generate a simulated station, and obtain passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the up and down peak hours, and the passenger flow of a certain line in a one-way direction during the peak hours; Thresholds for the up and down peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line are set respectively, and the simulated station is optimized based on the comparison results with the thresholds, so as to complete the construction of the final station based on the optimization results.

2. The analysis method for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 1 is characterized in that: It also includes the setting up of transfer stations, including: When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

3. The analysis method for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 1 is characterized in that: include: When the difference in the upstream and downstream peak hour section passenger flow exceeds the threshold and the maximum section passenger flow ratio exceeds 1.5:1, the direction with small passenger flow is optimized.

4. The method for analyzing the cost of reducing redundant control based on the full cycle of rail transit lines as claimed in claim 1, characterized in that: Also includes: When the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, peak reduction measures are taken.

5. The analysis method for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 1 is characterized in that: Also includes: Based on the peak hour passenger volume of single-line stations, stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

6. An analysis system for reducing redundant control costs based on the full cycle of rail transit lines, characterized in that: include: An information acquisition module is used to virtualize the station to be constructed, generate a simulated station, and obtain passenger flow information in the simulated station, wherein the passenger flow information includes: the passenger flow of the upstream and downstream sections during peak hours, and the passenger flow of a certain line during peak hours in one direction; The optimization module is used to set the thresholds of the upstream and downstream peak hour section passenger flow and the peak hour one-way section passenger flow of a certain line respectively, and optimize the simulated station according to the comparison results with the thresholds, so as to complete the construction of the final station according to the optimization results.

7. The analysis system for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 6, characterized in that: It also includes the setting up of transfer stations, including: When the daily transfer volume between two lines at a transfer station is greater than 60,000 passengers / day and the one-way transfer volume is greater than 30,000 passengers / day, the transfer station shall adopt interconnection or same-platform transfer.

8. The analysis system for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 6, characterized in that: include: When the difference in the upstream and downstream peak hour section passenger flow exceeds the threshold and the maximum section passenger flow ratio exceeds 1.5:1, the direction with small passenger flow is optimized.

9. The analysis system for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 6, characterized in that: Also includes: When the one-way cross-sectional passenger flow of a certain line during peak hours is less than 3 sections and exceeds 90% of the maximum cross-sectional passenger flow in the direction of the certain line, peak reduction measures are taken.

10. The analysis system for reducing redundant control costs based on the full cycle of rail transit lines as claimed in claim 6, characterized in that: Also includes: Based on the peak hour passenger volume of single-line stations, stations are divided into small stations (0-10,000 passengers / h), medium stations (10,000-20,000 passengers / h) and large stations (more than 20,000 passengers / h).

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