Train working diagram multi-level supply and demand matching degree evaluation method and device based on actual passenger flow data

Abstract

The invention provides a train working diagram multi-level supply and demand matching degree evaluation method and device based on actual passenger flow data, and relates to the technical field of passenger railway transportation optimization, and the method comprises the steps: obtaining target index data needed by a supply and demand matching degree evaluation index of each level in a plurality of levels; the plurality of layers comprise a line layer, an interval layer, a station layer and a train layer; calculating the evaluation index of each level by using an evaluation method corresponding to each level in the plurality of levels to obtain a supply and demand matching degree evaluation result corresponding to each level; the evaluation method corresponding to the line layer is a comparative analysis method, the evaluation method of the interval layer and the train layer is a grouping analysis method, and the evaluation method corresponding to the station layer is an Euclidean distance method. The method and device for evaluating the multi-level supply and demand matching degree of the train working diagram based on the actual passenger flow data are used for evaluating the multi-level supply and demand matching degree of the train working diagram based on the actual passenger flow data, and a scientific basis is provided for adjustment of the train working diagram.

Description

Technical Field

[0001] The present application relates to the technical field of passenger railway transportation optimization, and in particular to a method and device for evaluating multi-level supply-demand matching of a train operation diagram based on actual passenger flow data. Background Art

[0002] With the development of high-speed railways, the supply and demand relationship in the high-speed railway passenger market has changed from an overall shortage to a basic balance in total volume, but it still faces the problem of excess ineffective supply and structural shortage of effective supply, and it is difficult to adapt to the passenger flow demand with further enhanced temporal and spatial heterogeneity.

[0003] In related technologies, the train operation diagram, as the "baton" of resource allocation, directly affects the matching degree of supply and demand in the railway passenger transport market. At present, after the operation diagram is compiled, the evaluation of the matching degree of supply and demand of the new diagram based on actual passenger flow data still relies on manual experience and lacks the systematic and scientific nature of the evaluation method, which not only consumes a lot of manpower and time costs, but also has low efficiency.

[0004] Based on this, a supply-demand matching evaluation method is urgently needed to analyze the contradictions in supply-demand matching and provide a scientific basis for optimizing and adjusting the operation diagram in the next stage. Summary of the invention

[0005] The purpose of this application is to provide a method and device for evaluating the multi-level supply and demand matching of a train operation diagram based on actual passenger flow data, which is used to evaluate the multi-level supply and demand matching of the train operation diagram based on actual passenger flow data, and provide a scientific basis for adjusting the train operation diagram.

[0006] The present application provides a multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data, including: Obtain target indicator data required for supply-demand matching evaluation indicators at each level in multiple levels; the multiple levels include: line level, section level, station level and train level; based on the target indicator data, use the evaluation method corresponding to each level in the multiple levels to calculate the evaluation indicators of each level, and obtain the supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line level is the comparative analysis method, the evaluation methods corresponding to the section level and the train level are the grouping analysis method, and the evaluation method corresponding to the station level is the Euclidean distance method.

[0007] Optionally, the evaluation indicators of the line layer include: the average passenger occupancy rate of the line and the standard deviation rate of the line; based on the target indicator data, the evaluation indicators of each level are calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply and demand matching evaluation results corresponding to each level, including: based on the target indicator data, calculating the average passenger occupancy rate of the line and the standard deviation rate of the line; the average passenger occupancy rate of the line is calculated based on the ratio of the actual passenger turnover volume completed by the train and the sum of the passenger seat kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of passenger occupancy rates in various sections of the line; based on the average passenger occupancy rate of the line and the standard deviation rate of the line, generate target comparison result data, and use the comparative analysis method to compare and analyze the changes in the supply and demand matching of the line layer to obtain the supply and demand matching evaluation results corresponding to the line layer; wherein, the target comparison result data includes any one of the following: the average passenger occupancy rate and the standard deviation rate of the same line in different periods, and the average passenger occupancy rate and the standard deviation rate of different lines in the same period.

[0008] Optionally, the evaluation indicators of the interval layer include: the average occupancy rate of the interval; based on the target indicator data, the evaluation indicators of each level are calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply and demand matching evaluation results corresponding to each level, including: based on the target indicator data, the average occupancy rate of the trains running in each interval of the line is calculated to obtain the average occupancy rate of the interval; the average occupancy rate of the interval is: calculated based on the ratio of the actual passenger turnover completed by the train in each interval to the sum of the passenger seat-kilometers provided by the train; based on the average occupancy rate of the interval, the maximum and minimum values ​​of the average occupancy rate of the trains running in each interval are determined, and based on the maximum and minimum values ​​of the average occupancy rate of the trains running in each interval, the average occupancy rate of each interval is grouped according to the first preset group distance to generate an average occupancy rate distribution map for all intervals of the line; based on the average occupancy rate distribution map, the supply and demand matching evaluation results corresponding to the interval layer are obtained.

[0009] Optionally, the evaluation indicators of the station layer include: a first data sequence and a second data sequence; based on the target indicator data, the evaluation method corresponding to each layer in the multiple layers is used to calculate the evaluation indicators of each layer to obtain the supply and demand matching evaluation result corresponding to each layer, including: based on the target indicator data, obtaining the first data sequence and the second data sequence; the first data sequence is used to indicate: the number of stops at the station in different time periods; the second data sequence is used to indicate: the number of passengers getting on and off the station in different time periods; the Euclidean distance method is used to calculate the target similarity of the first data sequence and the second data sequence in trend and morphological fluctuations, and based on the target similarity, the supply and demand matching evaluation result corresponding to the station layer is obtained; wherein the supply and demand matching corresponding to the station layer is positively correlated with the target similarity.

[0010] Optionally, the evaluation indicators of the train layer include: the average occupancy rate of the route and the proportion of cross-line train passenger flow; based on the target indicator data, the evaluation method corresponding to each level in the multiple levels is used to calculate the evaluation indicators of each level, and the supply and demand matching evaluation result corresponding to each level is obtained, including: based on the target indicator data, calculating the average occupancy rate of the route and the proportion of cross-line train passenger flow; the average occupancy rate of the route is: obtained by the ratio of the sum of the actual passenger turnover volume completed by each train in the route to the sum of the passenger seat-kilometers provided by each train in the route; the proportion of cross-line train passenger flow is: based on the cross-line passenger flow of cross-line trains, The passenger flow of the cross-line train's own line and the passenger flow of the cross-line train's external line are calculated; based on the average passenger occupancy rate of the route and the passenger flow proportion of the cross-line train, the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of the cross-line train within the route are determined; based on the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of the cross-line train within the route, the average passenger occupancy rate within the route and the passenger flow proportion of the cross-line train within the route are grouped according to the second preset group distance to generate a cross-line train and passenger flow distribution map; based on the cross-line train and passenger flow distribution map, the supply and demand matching evaluation result corresponding to the train layer is obtained.

[0011] The present application also provides a multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data, comprising: An acquisition module is used to acquire target indicator data required for supply-demand matching evaluation indicators of each level in multiple levels; the multiple levels include: line level, section level, station level and train level; an evaluation module is used to calculate the evaluation indicators of each level based on the target indicator data using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line level is the comparative analysis method, the evaluation methods corresponding to the section level and the train level are the grouping analysis method, and the evaluation method corresponding to the station level is the Euclidean distance method.

[0012] Optionally, the evaluation indicators of the line layer include: the average occupancy rate of the line and the standard deviation rate of the line; the evaluation module is specifically used to calculate the average occupancy rate of the line and the standard deviation rate of the line based on the target indicator data; the average occupancy rate of the line is calculated based on the ratio of the actual passenger turnover of the train and the sum of the passenger seat-kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of the occupancy rate in each section of the line; the evaluation module is specifically used to generate target comparison result data based on the average occupancy rate of the line and the standard deviation rate of the line, and use a comparative analysis method to compare and analyze the changes in the supply and demand matching degree of the line layer to obtain the supply and demand matching evaluation result corresponding to the line layer; wherein, the target comparison result data includes any one of the following items: the average occupancy rate and the standard deviation rate of the same line in different periods, and the average occupancy rate and the standard deviation rate of different lines in the same period.

[0013] Optionally, the evaluation indicators of the interval layer include: the average occupancy rate of the interval; the evaluation module is specifically used to calculate the average occupancy rate of the trains running in each interval of the line based on the target indicator data, so as to obtain the average occupancy rate of the interval; the average occupancy rate of the interval is calculated based on the ratio of the actual passenger turnover completed by the train in each interval to the sum of the passenger seat-kilometers provided by the train; the evaluation module is specifically used to determine the maximum and minimum values ​​of the average occupancy rate of the trains running in each interval based on the average occupancy rate of the interval, and based on the maximum and minimum values ​​of the average occupancy rate of the trains running in each interval, group the average occupancy rate of each interval according to a first preset group distance to generate an average occupancy rate distribution map for all intervals of the line; the evaluation module is also specifically used to obtain the supply and demand matching evaluation result corresponding to the interval layer based on the average occupancy rate distribution map.

[0014] Optionally, the evaluation indicators of the station layer include: a first data sequence and a second data sequence; the evaluation module is specifically used to obtain the first data sequence and the second data sequence based on the target indicator data; the first data sequence is used to indicate: the number of stops at the station in different time periods; the second data sequence is used to indicate: the number of passengers getting on and off the station in different time periods; the evaluation module is also specifically used to calculate the target similarity of the first data sequence and the second data sequence in trend and morphological fluctuations using the Euclidean distance method, and obtain the supply and demand matching evaluation result corresponding to the station layer based on the target similarity; wherein the supply and demand matching corresponding to the station layer is positively correlated with the target similarity.

[0015] Optionally, the train layer evaluation indicators include: average occupancy rate of the route and proportion of cross-line train passenger flow; the evaluation module is specifically used to calculate the average occupancy rate of the route and the proportion of cross-line train passenger flow based on the target indicator data; the average occupancy rate of the route is obtained by the ratio of the sum of the actual passenger turnover of each train in the route to the sum of the provided passenger seat kilometers; the proportion of cross-line train passenger flow is calculated based on the cross-line passenger flow of cross-line trains, the passenger flow of the cross-line train's own line and the passenger flow of the cross-line train's external line; the evaluation module is specifically used to calculate the average occupancy rate of the route based on the average occupancy rate of the route and the passenger flow proportion of cross-line trains, determine the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route; the evaluation module is specifically used to group the average passenger occupancy rate within the route and the passenger flow proportion of cross-line trains within the route according to the second preset group distance based on the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route, to generate a cross-line train and passenger flow distribution map; the evaluation module is specifically used to obtain the supply and demand matching evaluation result corresponding to the train layer based on the cross-line trains and passenger flow distribution map.

[0016] The present application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of any of the above-mentioned methods for evaluating the multi-level supply and demand matching of a train operation diagram based on actual passenger flow data.

[0017] The present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data as described in any one of the above-mentioned methods are implemented.

[0018] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data as described in any of the above are implemented.

[0019] The present application provides a method and device for evaluating the multi-level supply and demand matching of a train operation diagram based on actual passenger flow data. First, the target indicator data required for the supply and demand matching evaluation index of each level in the multiple levels is obtained; the multiple levels include: line level, section level, station level and train level; then, based on the target indicator data, the evaluation method corresponding to each level in the multiple levels is used to calculate the evaluation index of each level to obtain the supply and demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method. In this way, a multi-level supply and demand matching evaluation can be performed on the train operation diagram based on the actual passenger flow data, providing a scientific basis for the adjustment of the train operation diagram. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 This is one of the schematic diagrams of the evaluation index system of the multi-level supply-demand matching evaluation system of the train operation diagram based on actual passenger flow data provided by this application; Figure 2 It is a flow chart of a multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data provided by this application; Figure 3 This is the second schematic diagram of the evaluation method of the multi-level supply-demand matching evaluation system of the train operation diagram based on actual passenger flow data provided by this application; Figure 4 It is a schematic diagram of the definitions of different types of passenger flows provided by this application; Figure 5 It is a structural schematic diagram of a multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data provided by the present application; Figure 6 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0023] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0024] In view of the technical problem that, after the operation diagram is compiled, the supply-demand matching evaluation of the new diagram based on actual passenger flow data still relies on manual experience and lacks the systematicness and scientificity of the evaluation method, which not only consumes a lot of manpower and time costs, but also has low efficiency, the embodiment of the present application provides a multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data, such as Figure 1 As shown, the embodiment of the present application aims to reveal the contradiction between supply and demand in the train operation diagram, realize closed-loop management of operation diagram compilation, and improve the matching degree of supply and demand in the passenger transportation market. Aiming at the problem of supply and demand matching evaluation of high-speed railway train operation diagram, the hierarchical analysis method is used to construct a multi-level high-speed railway train operation diagram supply and demand matching evaluation index system based on line layer, section layer, station layer, and train layer, and the qualitative description of each indicator is converted into a mathematical expression. According to the principles of color scale map and heat map, a visual display method of supply and demand matching is designed. The embodiment of the present application designs different evaluation methods based on the characteristics of different evaluation indicators, objectively reveals the contradiction between supply and demand in the operation diagram, and provides a basis for the optimization and adjustment of the operation diagram.

[0025] In conjunction with the accompanying drawings, the multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data provided by the embodiment of the present application is described in detail below through specific embodiments and their application scenarios.

[0026] like Figure 2 As shown, an embodiment of the present application provides a method for evaluating the multi-level supply-demand matching degree of a train operation diagram based on actual passenger flow data. The method may include the following steps 201 and 202: Step 201: Obtain target indicator data required for supply-demand matching evaluation indicators at each level in multiple levels.

[0027] The multiple levels include: line level, section level, station level and train level. Figure 1 As shown, it is first necessary to build a multi-level high-speed railway train operation diagram supply and demand matching evaluation index system based on the line layer, section layer, station layer and train layer.

[0028] For example, in combination Figure 1 ,like Figure 3 As shown in the figure, the supply and demand matching evaluation indicators at the line level include: the average passenger load factor of the line, which is used to reflect the overall situation of the line load level, and the line standard deviation rate, which is used to reflect the imbalance of the line load level; the supply and demand matching evaluation indicators at the interval level include: the average passenger load factor of the interval, which is used to reflect the rationality of the number of interval trains. The supply and demand matching evaluation indicators at the station level include: the number of station stops and the number of passengers getting on and off, which are used to evaluate the degree of matching between the number of station stops and the number of passengers getting on and off. The supply and demand matching evaluation indicators at the train level include: the average passenger load factor of the intersection, which is used to evaluate the rationality of train operation, and the passenger flow proportion of cross-line trains, which is used to evaluate the rationality of cross-line train operation.

[0029] Step 202: Based on the target indicator data, the evaluation indicator of each level is calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level.

[0030] Among them, the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method.

[0031] Optionally, in the embodiment of the present application, the line-level supply-demand matching refers to the degree of coordination between the line's transport capacity and the actual passenger flow, which is used to comprehensively measure the average degree of matching of transport capacity supply with passenger flow, and reflects the balance of the distribution of supply-demand matching within the line. The line-level supply-demand matching evaluation indicators mainly include: the average passenger load factor of the line and the standard deviation rate of the line.

[0032] Specifically, the supply-demand matching evaluation for the line layer in the above step 202 may further include the following steps 202a1 and 202a2: Step 202a1, based on the target indicator data, calculate the average passenger load factor of the line and the standard deviation rate of the line.

[0033] Among them, the average passenger occupancy rate of the line is calculated based on the ratio of the actual passenger turnover completed by the train to the sum of the passenger seat-kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of the passenger occupancy rate in each section of the line.

[0034] Exemplarily, the average passenger load factor of a line in the embodiments of the present application refers to the average passenger load factor of all trains running on the line during the study period, that is, the ratio of the sum of the actual passenger turnover completed by the train to the sum of the passenger seat kilometers provided. This indicator is used to indicate the extent to which the capacity provided by the operating department along this line is utilized by passengers. This indicator is a global mean indicator, which can reflect the overall situation of the line load level to a certain extent, but cannot reflect the deviation of the internal distribution of the line. Taking the train as the basic unit of the average passenger load factor of the line, the passenger load factor of each train in each section is taken as a sample point, which can be calculated by the following formulas 1 and 2: (Formula 1)

[0035] (Formula 2)

[0036] in, For the line f Direction s The interval k The passenger load factor of each train; f For line up and down; For trains f Direction s The number of trains running in each section, ; s is the number of line sections, ; For the k Trains in f Direction s The number of passengers in each section, For the k The capacity of the train; For the s The interval length of the interval; For the k The running distance of a train.

[0037] For example, the line standard deviation rate in the embodiment of the present application is used to describe the degree of uneven distribution of passenger load factors in each section of the line. The larger the standard deviation rate, the greater the difference in passenger capacity utilization of trains in each section, and the more uneven the capacity utilization of the system; the smaller the value, the smaller the difference, and the more balanced the capacity utilization. The standard deviation rate can be calculated by the following formula three and formula four: (Formula 3)

[0038] (Formula 4)

[0039] in, is the standard deviation rate, is the standard deviation, E is the mathematical expectation.

[0040] Step 202a2: Generate target comparison result data based on the average passenger load factor of the line and the standard deviation rate of the line, and use a comparative analysis method to compare and analyze the changes in the supply and demand matching degree of the line layer to obtain the supply and demand matching degree evaluation result corresponding to the line layer.

[0041] The target comparison result data includes any of the following items: the average occupancy rate and the line standard deviation rate of the same line in different periods, and the average occupancy rate and the line standard deviation rate of different lines in the same period.

[0042] Optionally, in the embodiment of the present application, the evaluation index of supply and demand matching at the interval level mainly includes: the average passenger load factor of each interval during the study period. The higher the interval passenger load factor, the higher the transport capacity utilization rate. If the passenger load factor of a certain interval on a certain line is continuously high, it means that the number of trains in the interval is relatively small, or the vehicle capacity is limited, resulting in a service bottleneck in the section, and capacity expansion should be considered; the lower the interval passenger load factor, the more trains there are in the interval, and the greater the ability to adapt to the growth of passenger demand, but the lower the matching of transport capacity utilization rate, and there is a phenomenon of idle or wasted interval transport resources.

[0043] Specifically, the supply-demand matching evaluation at the interval layer in the above step 202 may further include the following steps 202b1 to 202b3: Step 202b1: Based on the target indicator data, calculate the average passenger occupancy rate of trains running in each section of the line to obtain the average passenger occupancy rate of the section.

[0044] The average passenger occupancy rate of the interval is calculated based on the ratio of the actual passenger turnover completed by the train in each interval to the sum of the passenger seat-kilometers provided by the train.

[0045] For example, the above-mentioned average passenger load factor of the interval refers to the average passenger load factor of all trains running on the interval during the study period, that is, the ratio of the sum of the actual passenger turnover completed by the trains in the interval to the sum of the passenger seat kilometers provided. The average passenger load factor of the interval can be calculated by the following formula 5: (Formula 5)

[0046] in, For the line f Direction s The average occupancy rate for each zone.

[0047] Step 202b2: Based on the average occupancy rate of the interval, determine the maximum and minimum values ​​of the average occupancy rate of trains running in each interval, and based on the maximum and minimum values ​​of the average occupancy rate of trains running in each interval, group the average occupancy rate of each interval according to a first preset group distance to generate an average occupancy rate distribution map for all intervals of the line.

[0048] Step 202b3: obtaining a supply-demand matching evaluation result corresponding to the interval layer based on the average passenger load factor distribution map.

[0049] Exemplarily, in the embodiment of the present application, a group analysis method is used to evaluate the distribution of the average occupancy rate of each interval, that is, the average occupancy rate of each interval is first calculated, and then the maximum and minimum occupancy rates of the intervals are determined, and then the intervals are divided into several levels according to a certain group interval. According to the size of the group interval, the calculation results are grouped and sorted, and assigned to the corresponding groups to obtain the results of internal comparison between the indicators.

[0050] Optionally, in the embodiment of the present application, the station-level supply-demand matching refers to the matching degree between the number of station parking lots and the number of passengers getting on and off the train during the study period. The station-level supply-demand matching evaluation index mainly includes: station parking lot supply-demand matching index.

[0051] Exemplarily, the evaluation index of the station layer includes: a first data sequence and a second data sequence.

[0052] Specifically, the supply-demand matching evaluation at the station level in the above step 202 may further include the following steps 202c1 and 202c2: Step 202c1: Based on the target indicator data, obtain the first data sequence and the second data sequence.

[0053] The first data sequence is used to indicate the number of stops at the station in different time periods; the second data sequence is used to indicate the number of passengers getting on and off the station in different time periods. Based on the first data sequence and the second data sequence, the similarity between the time series of the number of stops at the station and the time series of the number of passengers getting on and off the station in terms of time trend and morphological fluctuations during the study period can be obtained. The greater the similarity, the higher the matching degree.

[0054] Step 202c2: use the Euclidean distance method to calculate the target similarity between the first data sequence and the second data sequence in terms of trend and morphological fluctuations, and obtain the supply-demand matching evaluation result corresponding to the station layer based on the target similarity.

[0055] Among them, the supply and demand matching degree corresponding to the station layer is positively correlated with the target similarity.

[0056] For example, the matching degree of supply and demand of station parking quantity is manifested in that the number of station parking quantities changes with the number of passengers getting on and off the train in terms of form; from the perspective of mathematical relationship, it is manifested in that the time series of station parking quantity and the time series of passengers getting on and off the train are consistent in time trend and morphological fluctuation, which belongs to the problem of measuring the similarity of equal-time series.

[0057] Specifically, the above step 202c2 may further include the following steps 202c21 to 202c23: Step 202c21, record Q is the time series of the number of stops at the station, C is the time series of the number of passengers getting on and off the bus, and the length of the time series is m : (Formula 6)

[0058] (Formula 7)

[0059] Step 202c22: Perform Z-score normalization on the time series Q and C respectively. The normalization calculation formulas are shown in the following formulas 8 and 9: (Formula 8)

[0060] (Formula 9)

[0061] in, S is the value after sample standardization, For time series x No. i data, For time series x The mean of m is the number of data; For time series y No. i data, For time series y The mean of .

[0062] Step 202c23: Calculate the Euclidean distance between the first data sequence and the second data sequence based on the following formula 10: d ( x , y ): (Formula 10)

[0063] Optionally, in an embodiment of the present application, the train-level supply-demand matching evaluation indicators mainly include: average occupancy rate of routes and proportion of cross-line train passenger flow.

[0064] Specifically, the supply-demand matching evaluation for the train layer in the above step 202 may also include the following steps 202d1 to 202d4: Step 202d1: Based on the target indicator data, calculate the average passenger occupancy rate of the route and the passenger flow proportion of the cross-line trains.

[0065] Among them, the average occupancy rate of the route is obtained by the ratio of the sum of the actual passenger turnover of each train in the route to the sum of the passenger seat-kilometers provided; the passenger flow proportion of cross-line trains is calculated based on the cross-line passenger flow of cross-line trains, the passenger flow of the cross-line train's own line and the passenger flow of the external line of cross-line trains.

[0066] For example, the average passenger load factor of a route refers to the average passenger load factor of trains running on the route during the study period, that is, the ratio of the sum of the actual passenger turnover of each train in the route to the sum of the passenger seat kilometers provided by each train in the route. This indicator belongs to the local mean indicator, which can reflect to a certain extent the degree to which the overall capacity of the route provided by the operating department is utilized by passengers. When the average passenger load factor of a route is low, it is recommended that the train be rerouted or changed to a low-season suspension or weekend line.

[0067] For example, m The first N The average passenger load factor of a train can be calculated using the following formula: (Formula 11)

[0068] in, For the n Passenger turnover of each train, For the n The number of kilometers travelled by trains, For the n The capacity of a train.

[0069] It is understandable that although cross-line trains can meet the direct needs of passengers, because cross-line trains cross two or more lines, the cross-line points have stricter time windows for getting on and off the line than the trains on the main line. Cross-line trains not only have a greater impact on the line's capacity, but also seriously restrict the preparation of the train operation diagram for the main line. If a cross-line train is delayed, its adjustment difficulty and impact range will be greater than that of the train on the main line. This phenomenon is particularly prominent on channel-type high-speed railway lines. Therefore, the passenger flow ratio of cross-line trains is used to analyze and calculate the rationality of the operation of cross-line trains. When cross-line trains occupy stations or sections with tight capacity and the proportion of cross-line passenger flow is low, it is recommended that cross-line trains be changed to release the capacity of the tight channel.

[0070] For example, Figure 4 As shown in Figure 1, it is a schematic diagram of the definition of different types of passenger flows. Figure 4 It can be seen that the passenger flow of this line refers to the OD passenger flow of the cross-line trains whose starting and ending points are both on the line; the cross-line passenger flow refers to the OD passenger flow of the cross-line trains whose starting and ending points are one end on the line and the other end outside the line, that is, "passenger flow with one end inside the line and the other end outside the line" or the OD flow with both starting and ending points outside the line, but the section passed through is on the line of this line; the off-line passenger flow refers to the OD passenger flow of the cross-line trains whose starting and ending points are both on the external line, and the section passed through is not on the line of this line. The passenger flow proportion of cross-line trains can be calculated by the following formula 12: (Formula 12)

[0071] in, is the passenger flow ratio of cross-line trains, is the passenger flow of the main line in the cross-line car, is the cross-line passenger flow in the cross-line vehicle, It refers to the external passenger flow in the cross-line vehicle.

[0072] Step 202d2: Based on the average passenger occupancy rate of the route and the passenger flow proportion of cross-line trains, determine the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route.

[0073] Step 202d3: Based on the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route, the average passenger occupancy rate within the route and the passenger flow proportion of cross-line trains within the route are grouped according to a second preset group distance to generate a cross-line train and passenger flow distribution map.

[0074] Step 202d4: obtaining a supply-demand matching evaluation result corresponding to the train layer based on the cross-line train and passenger flow distribution map.

[0075] The embodiment of the present application provides a multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data. First, the target indicator data required for the supply-demand matching evaluation index of each level in the multiple levels is obtained; the multiple levels include: line level, interval level, station level and train level; then, based on the target indicator data, the evaluation index of each level is calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the interval layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method. In this way, a multi-level supply-demand matching evaluation can be performed on the train operation diagram based on the actual passenger flow data, providing a scientific basis for the adjustment of the train operation diagram.

[0076] It should be noted that the execution subject of the multi-level supply-demand matching evaluation method for a train timetable based on actual passenger flow data provided in the embodiment of the present application may be a multi-level supply-demand matching evaluation device for a train timetable based on actual passenger flow data, or a control module in the multi-level supply-demand matching evaluation device for a train timetable based on actual passenger flow data for executing the multi-level supply-demand matching evaluation method for a train timetable based on actual passenger flow data. In the embodiment of the present application, the execution of the multi-level supply-demand matching evaluation method for a train timetable based on actual passenger flow data by a multi-level supply-demand matching evaluation device for a train timetable based on actual passenger flow data is taken as an example to illustrate the multi-level supply-demand matching evaluation method for a train timetable based on actual passenger flow data provided in the embodiment of the present application.

[0077] It should be noted that in the embodiments of the present application, the above-mentioned methods are shown in the drawings. The multi-level supply-demand matching evaluation method of the train operation diagram based on actual passenger flow data is illustrated by combining an accompanying drawing in the embodiments of the present application as an example. In specific implementation, the multi-level supply-demand matching evaluation method of the train operation diagram based on actual passenger flow data shown in the accompanying drawings of the above-mentioned methods can also be implemented in combination with any other accompanying drawings that can be combined as shown in the above-mentioned embodiments, which will not be repeated here.

[0078] The following describes a multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data provided in the present application. The multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data described below can be referenced to each other.

[0079] Figure 5 A schematic diagram of the structure of a multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data provided in an embodiment of the present application, such as Figure 5 As shown, specifically including: An acquisition module 501 is used to acquire target indicator data required for supply-demand matching evaluation indicators at each level in a plurality of levels; the plurality of levels include: line level, section level, station level and train level; an evaluation module 502 is used to calculate the evaluation indicators at each level based on the target indicator data using the evaluation method corresponding to each level in the plurality of levels to obtain a supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line level is the comparative analysis method, the evaluation methods corresponding to the section level and the train level are the grouping analysis method, and the evaluation method corresponding to the station level is the Euclidean distance method.

[0080] Optionally, the evaluation indicators of the line layer include: the average occupancy rate of the line and the standard deviation rate of the line; the evaluation module 502 is specifically used to calculate the average occupancy rate of the line and the standard deviation rate of the line based on the target indicator data; the average occupancy rate of the line is calculated based on the ratio of the actual passenger turnover completed by the train and the sum of the passenger seat kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of the occupancy rate in each section of the line; the evaluation module 502 is also specifically used to generate target comparison result data based on the average occupancy rate of the line and the standard deviation rate of the line, and use a comparative analysis method to compare and analyze the changes in the supply and demand matching degree of the line layer to obtain the supply and demand matching evaluation result corresponding to the line layer; wherein, the target comparison result data includes any one of the following items: the average occupancy rate and the standard deviation rate of the same line in different periods, and the average occupancy rate and the standard deviation rate of different lines in the same period.

[0081] Optionally, the evaluation indicators of the interval layer include: the average passenger occupancy rate of the interval; the evaluation module 502 is specifically used to calculate the average passenger occupancy rate of the trains running in each interval of the line based on the target indicator data, to obtain the average passenger occupancy rate of the interval; the average passenger occupancy rate of the interval is calculated based on the ratio of the actual passenger turnover completed by the train in each interval to the sum of the passenger seat-kilometers provided by the train; the evaluation module 502 is also specifically used to determine the maximum and minimum values ​​of the average passenger occupancy rate of the trains running in each interval based on the average passenger occupancy rate of the interval, and based on the maximum and minimum values ​​of the average passenger occupancy rate of the trains running in each interval, group the average passenger occupancy rate of each interval according to the first preset group distance to generate an average passenger occupancy rate distribution map for all intervals of the line; the evaluation module 502 is also specifically used to obtain the supply and demand matching evaluation result corresponding to the interval layer based on the average passenger occupancy rate distribution map.

[0082] Optionally, the evaluation index of the station layer includes: a first data sequence and a second data sequence; the evaluation module 502 is specifically used to obtain the first data sequence and the second data sequence based on the target index data; the first data sequence is used to indicate: the number of stops at the station in different time periods; the second data sequence is used to indicate: the number of passengers getting on and off the station in different time periods; the evaluation module 502 is also specifically used to calculate the target similarity of the first data sequence and the second data sequence in trend and morphological fluctuations using the Euclidean distance method, and obtain the supply and demand matching evaluation result corresponding to the station layer based on the target similarity; wherein, the supply and demand matching corresponding to the station layer is positively correlated with the target similarity.

[0083] Optionally, the evaluation indicators of the train layer include: the average passenger occupancy rate of the route and the proportion of cross-line train passenger flow; the evaluation module 502 is specifically used to calculate the average passenger occupancy rate of the route and the proportion of cross-line train passenger flow based on the target indicator data; the average passenger occupancy rate of the route is obtained by the ratio of the sum of the passenger turnover actually completed by each train in the route to the sum of the passenger seat-kilometers provided by each train in the route; the proportion of cross-line train passenger flow is calculated based on the cross-line passenger flow of cross-line trains, the passenger flow of the cross-line train's own line and the passenger flow of the cross-line train's external line; the evaluation module 502 is also specifically used to calculate the average passenger occupancy rate of the route based on the average passenger occupancy rate of the route The maximum and minimum values ​​of the average occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route are determined from the average occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route; the evaluation module 502 is further specifically used to group the average occupancy rate within the route and the passenger flow proportion of cross-line trains within the route according to the second preset group distance based on the maximum and minimum values ​​of the average occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route, to generate a cross-line train and passenger flow distribution map; the evaluation module 502 is further specifically used to obtain the supply and demand matching evaluation result corresponding to the train layer based on the cross-line train and passenger flow distribution map.

[0084] The multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data provided in the present application first obtains the target indicator data required for the supply-demand matching evaluation index of each level in the multiple levels; the multiple levels include: line level, section level, station level and train level; then, based on the target indicator data, the evaluation index of each level is calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method. In this way, a multi-level supply-demand matching evaluation can be performed on the train operation diagram based on the actual passenger flow data, providing a scientific basis for the adjustment of the train operation diagram.

[0085] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute a multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data, the method comprising: obtaining target indicator data required for supply-demand matching evaluation indicators of each level in multiple levels; the multiple levels include: line level, section level, station level and train level; based on the target indicator data, using the evaluation method corresponding to each level in the multiple levels to calculate the evaluation indicators of each level, and obtain the supply-demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line level is the comparative analysis method, the evaluation methods corresponding to the section level and the train level are the grouping analysis method, and the evaluation method corresponding to the station level is the Euclidean distance method.

[0086] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable 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 application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0087] On the other hand, the present application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the multi-level supply and demand matching evaluation method for a train operation diagram based on actual passenger flow data provided by the above-mentioned methods, the method including: obtaining target indicator data required for the supply and demand matching evaluation index of each level in the multiple levels; the multiple levels include: line layer, section layer, station layer and train layer; based on the target indicator data, using the evaluation method corresponding to each level in the multiple levels to calculate the evaluation index of each level, and obtain the supply and demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method.

[0088] On the other hand, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the above-mentioned multi-level supply and demand matching evaluation method for a train operation diagram based on actual passenger flow data, the method comprising: obtaining target indicator data required for the supply and demand matching evaluation index of each level in the multiple levels; the multiple levels comprising: line level, section level, station level and train level; based on the target indicator data, using the evaluation method corresponding to each level in the multiple levels to calculate the evaluation index of each level, to obtain the supply and demand matching evaluation result corresponding to each level; wherein the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method.

[0089] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0090] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data, characterized in that: include: Obtain target indicator data required for supply-demand matching evaluation indicators at each level in multiple levels; The multiple levels include: line level, section level, station level and train level; Based on the target indicator data, the evaluation indicator of each level is calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level; Among them, the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method.

2. The method according to claim 1, characterized in that: The evaluation indicators of the line layer include: average passenger load factor of the line and standard deviation rate of the line; Based on the target indicator data, the evaluation method corresponding to each level in the multiple levels is used to calculate the evaluation indicators of each level to obtain the supply and demand matching evaluation results corresponding to each level, including: Based on the target indicator data, the average passenger load factor of the line and the standard deviation rate of the line are calculated; the average passenger load factor of the line is calculated based on the ratio of the passenger turnover actually completed by the train to the sum of the passenger seat kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of passenger load factors in various sections of the line; Based on the average passenger load factor of the line and the standard deviation rate of the line, target comparison result data is generated, and the supply-demand matching degree changes of the line layer are compared and analyzed by using a comparative analysis method to obtain the supply-demand matching degree evaluation result corresponding to the line layer; The target comparison result data includes any of the following items: the average occupancy rate and the line standard deviation rate of the same line in different periods, and the average occupancy rate and the line standard deviation rate of different lines in the same period.

3. The method according to claim 1, characterized in that The evaluation indicators of the interval layer include: average passenger load factor of the interval; Based on the target indicator data, the evaluation indicators of each level are calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation results corresponding to each level, including: Based on the target indicator data, the average passenger load factor of the trains in each section of the line is calculated to obtain the average passenger load factor of the section; the average passenger load factor of the section is calculated based on the ratio of the actual passenger turnover completed by the train in each section to the sum of the passenger seat kilometers provided by the train; Based on the average passenger occupancy rate of the interval, determine the maximum and minimum values ​​of the average passenger occupancy rate of trains running in each interval, and based on the maximum and minimum values ​​of the average passenger occupancy rate of trains running in each interval, group the average passenger occupancy rate of each interval according to a first preset group distance to generate an average passenger occupancy rate distribution map of all intervals of the line; Based on the average occupancy rate distribution diagram, a supply-demand matching evaluation result corresponding to the interval layer is obtained.

4. The method according to claim 1, characterized in that The evaluation index of the station layer includes: a first data sequence and a second data sequence; Based on the target indicator data, the evaluation method corresponding to each level in the multiple levels is used to calculate the evaluation indicators of each level to obtain the supply and demand matching evaluation results corresponding to each level, including: Based on the target indicator data, the first data sequence and the second data sequence are obtained; the first data sequence is used to represent: the number of stops at the station in different time periods; the second data sequence is used to represent: the number of passengers getting on and off the station in different time periods; The target similarity between the first data sequence and the second data sequence in terms of trend and morphological fluctuation is calculated by using the Euclidean distance method, and the supply-demand matching evaluation result corresponding to the station layer is obtained based on the target similarity; Among them, the supply and demand matching degree corresponding to the station layer is positively correlated with the target similarity.

5. The method according to claim 1, characterized in that The evaluation indicators of the train layer include: average passenger occupancy rate of the route and passenger flow ratio of cross-line trains; Based on the target indicator data, the evaluation indicators of each level are calculated using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation results corresponding to each level, including: Based on the target indicator data, the average passenger load factor of the route and the passenger flow proportion of the cross-line train are calculated; the average passenger load factor of the route is obtained based on the ratio of the sum of the passenger turnover actually completed by each train in the route to the sum of the passenger seat kilometers provided by each train in the route; the passenger flow proportion of the cross-line train is calculated based on the cross-line passenger flow of the cross-line train, the passenger flow of the cross-line train on its own line, and the passenger flow of the cross-line train on its external line; Based on the average passenger occupancy rate of the route and the passenger flow proportion of the cross-line trains, determine the maximum and minimum values ​​of the average passenger occupancy rate within the route, and the maximum and minimum values ​​of the passenger flow proportion of the cross-line trains within the route; Based on the maximum and minimum values ​​of the average passenger occupancy rate within the route and the maximum and minimum values ​​of the passenger flow proportion of cross-line trains within the route, the average passenger occupancy rate within the route and the passenger flow proportion of cross-line trains within the route are grouped according to a second preset group distance to generate a cross-line train and passenger flow distribution map; Based on the cross-line trains and passenger flow distribution map, a supply-demand matching evaluation result corresponding to the train layer is obtained.

6. A multi-level supply-demand matching evaluation device for a train operation diagram based on actual passenger flow data, characterized in that: The device comprises: An acquisition module, used to acquire target indicator data required for supply-demand matching evaluation indicators at each level in multiple levels; the multiple levels include: line level, section level, station level and train level; An evaluation module, used to calculate the evaluation index of each level based on the target indicator data using the evaluation method corresponding to each level in the multiple levels to obtain the supply-demand matching evaluation result corresponding to each level; Among them, the evaluation method corresponding to the line layer is the comparative analysis method, the evaluation methods corresponding to the section layer and the train layer are the grouping analysis method, and the evaluation method corresponding to the station layer is the Euclidean distance method.

7. The device according to claim 6, characterized in that The evaluation indicators of the line layer include: average passenger load factor of the line and standard deviation rate of the line; The evaluation module is specifically used to calculate the average passenger load factor of the line and the standard deviation rate of the line based on the target indicator data; the average passenger load factor of the line is calculated based on the ratio of the passenger turnover actually completed by the train to the sum of the passenger seat kilometers provided by the train; the standard deviation rate of the line is used to indicate the degree of uneven distribution of passenger load factors in various sections of the line; The evaluation module is further specifically used to generate target comparison result data based on the average passenger load factor of the line and the standard deviation rate of the line, and to compare and analyze the changes in the supply and demand matching degree of the line layer by using a comparative analysis method to obtain the supply and demand matching degree evaluation result corresponding to the line layer; The target comparison result data includes any of the following items: the average occupancy rate and the line standard deviation rate of the same line in different periods, and the average occupancy rate and the line standard deviation rate of different lines in the same period.

8. The device according to claim 6, characterized in that The evaluation indicators of the interval layer include: average passenger load factor of the interval; The evaluation module is specifically used to calculate the average passenger load factor of the trains in each section of the line based on the target indicator data to obtain the average passenger load factor of the section; the average passenger load factor of the section is calculated based on the ratio of the passenger turnover actually completed by the train in each section to the sum of the passenger seat kilometers provided by the train; The evaluation module is further configured to determine the maximum and minimum values ​​of the average passenger occupancy rate of trains in each section based on the average passenger occupancy rate of the section, and to group the average passenger occupancy rate of each section according to a first preset group distance based on the maximum and minimum values ​​of the average passenger occupancy rate of trains in each section, so as to generate a distribution diagram of the average passenger occupancy rate of all sections of the line; The evaluation module is specifically used to obtain a supply-demand matching evaluation result corresponding to the interval layer based on the average occupancy rate distribution map.

9. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps of the multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data as described in any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the multi-level supply-demand matching evaluation method for a train operation diagram based on actual passenger flow data as described in any one of claims 1 to 5 are implemented.

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