A transportation organization design method and equipment applicable to tourist rail transit

Abstract

The present invention discloses a transport organization design method and device applicable to tourist rail transit, including: obtaining the total historical passenger flow and its passenger flow distribution information of a target area, predicting the total future passenger flow by using a flow prediction algorithm, calculating the peak coefficient of passenger flow in the peak season and the flat peak coefficient of passenger flow in the off-season; calculating the passenger flow sharing ratio of tourist rail transit by using the logit model, and predicting the benchmark passenger flow range of tourist rail transit in the target area based on the total future passenger flow, the passenger flow sharing ratio, the peak coefficient of passenger flow in the peak season and the flat peak coefficient of passenger flow in the off-season; taking the benchmark passenger flow range as the target, generating multiple target transport organization plans based on the existing transport organization plan in the target area according to the transport organization design criteria; evaluating the plans based on a pre-constructed evaluation function to obtain an optimal transport organization adjustment plan that meets the evaluation threshold. The present invention designs a corresponding prediction and evaluation plan according to the characteristics of tourist rail transit to assist in the transport organization design of tourist rail transit.

Description

Technical Field

[0001] The present invention relates to the technical field of tourism rail transit design, and relates to a transport organization design method and device applicable to tourism rail transit. Background Art

[0002] The transport organization design of rail transit is mainly based on passenger flow prediction and line function positioning, to verify the transport capacity scale, determine the train operation plan, and provide a basis for the civil engineering and equipment allocation of engineering projects. As a supplement and extension of trunk lines and inter-regional railways, tourism rail transit plays an important marginal benefit in the field of rail transit, and can solve the connection travel problems in most areas with low transport volume demand, complex environments but rich resources at the same time.

[0003] The traditional rail transit transport organization design has the following remarkable characteristics: ① The investment entities are mainly the state and local governments, and social public welfare is emphasized; ② It mainly serves the commuting passenger flow, and punctuality and high efficiency of travel are mainly considered. Therefore, usually, the transport capacity design is directly based on the maximum predicted passenger flow in the peak hour; ③ Usually, the passenger flow prediction is only carried out for weekdays, and the daily average passenger flow does not change much throughout the year. The passenger flow in the morning and evening peak hours accounts for about 12-18% of the full-day passenger flow. Therefore, the way of reducing the operation frequency is adopted to adapt to the passenger flow in the off-peak period, to improve the load factor, save the operation cost, and the adjustment method is relatively single; ④ The evaluation of the transport organization plan pays more attention to aspects such as the passenger ride evaluation, energy consumption evaluation, safety evaluation of delays or accidents, and service evaluation of passenger complaints.

[0004] Compared with traditional rail transit, tourism rail transit has the following characteristics: ① Most of the investment entities are enterprises, and more attention is paid to transport efficiency and investment economy; ② The main service object is the tourism passenger flow, the requirements for train punctuality and high-density frequency are reduced, and more attention is paid to the riding comfort and riding environment; ③ The daily average passenger flow changes greatly throughout the year. After the tourism passenger flow is superimposed with the peak and off-peak seasons, the fluctuation is obvious. The difference between the peak season peak and the off-season off-peak passenger flow can reach dozens of times.

[0005] Due to the completely different investment entities, line functions and passenger flow characteristics of tourism rail transit from traditional rail transit, there will also be obvious differences and emphases in the transport organization design method and evaluation system. If the conventional transport organization design method is adopted, first, the transport capacity is verified based on the maximum predicted passenger flow in the peak hour of the peak season, and the civil engineering and equipment allocation are carried out according to the maximum train formation and the minimum headway, which will inevitably result in large investment and poor benefits of tourism rail transit. Second, for the flat season and off-season, if only the way of adjusting the operation frequency is adopted to meet the low transport volume passenger flow demand, it will lead to too few operation frequencies in the off-season off-peak period, too much reduction in service level, or too low load factor of the train and serious empty running, resulting in serious waste of the system transport capacity. Summary of the Invention

[0006] The object of the present invention is to overcome the problem that when the prior art is applied to tourist rail transit that focuses on investment benefits and service quality, the reasonable economic matching between the actual line transportation capacity and the passenger flow at different times is not effectively considered, which will cause a large project investment scale and overcapacity in transportation capacity, and provide a transportation organization design method and equipment applicable to tourist rail transit.

[0007] In order to achieve the above object of the invention, the present invention provides the following technical solutions:

[0008] A transportation organization design method applicable to tourist rail transit, comprising:

[0009] a. Obtain the total historical passenger flow and its passenger flow distribution information in the target area, predict the total future passenger flow according to the total historical passenger flow by using a flow prediction algorithm, and perform statistical analysis on the passenger flow distribution information to obtain the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season;

[0010] b. Calculate the passenger flow sharing ratio of tourist rail transit by using the logit model, and predict the benchmark passenger flow interval of tourist rail transit in the target area based on the total future passenger flow, the passenger flow sharing ratio, the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season;

[0011] c. Taking the benchmark passenger flow interval as the target, generate multiple target transportation organization plans based on the existing transportation organization plan in the target area according to the transportation organization design criteria;

[0012] d. Pre-construct an evaluation function, evaluate multiple target transportation organization plans based on the evaluation function, and obtain the optimal transportation organization adjustment plan through evaluation; judge whether the evaluation result corresponding to the optimal transportation organization adjustment plan reaches the threshold; if so, output the current optimal transportation organization adjustment plan; if not, return to step a, and recalculate the total future passenger flow, the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season; until an optimal transportation organization adjustment plan with an evaluation result reaching the threshold is generated.

[0013] According to a specific implementation manner, in the above transportation organization design method applicable to tourist rail transit, the flow prediction algorithm is one of the growth rate method, the elasticity coefficient method, the function model method, and the exponential regression method.

[0014] According to a specific implementation manner, in the above transportation organization design method applicable to tourist rail transit, the calculation of the passenger flow sharing ratio of tourist rail transit by using the logit model includes:

[0015] Count the traffic modes corresponding to the total historical passenger flow in the target area, and quantitatively calculate the passenger flow sharing ratios corresponding to different traffic modes by using the logit model.

[0016] According to a specific embodiment, the transport organization design criteria include: increasing or decreasing the train formation number, increasing or decreasing the seating capacity of a single vehicle, adjusting the operating range of train routes, increasing or decreasing the number of train trips, and increasing or decreasing the train travel speed;

[0017] Generating multiple target transport organization plans based on the existing transport organization plan in the target area according to the transport organization design criteria, including:

[0018] Taking the benchmark passenger flow interval as the transport target, arranging and combining the transport organization design criteria to generate multiple adjustment strategies for transport organization plans, and adjusting the existing transport organization plan according to the multiple adjustment strategies for transport organization plans to generate multiple target transport organization plans.

[0019] According to a specific embodiment, in the above transport organization design method applicable to tourist rail transit, the pre-constructed evaluation function includes:

[0020] Taking the passenger flow service level and transport efficiency as the primary evaluation indicators, and determining the secondary evaluation indicators corresponding to the passenger flow service level and transport efficiency;

[0021] And respectively assigning weight values w1 to w to each of the evaluation indicators; n Based on the evaluation indicators and their weight values, establishing the evaluation function.

[0022] According to a specific embodiment, in the above transport organization design method applicable to tourist rail transit, the secondary indicators corresponding to the passenger flow service level are: passenger waiting time, load factor, and average passenger running time;

[0023] Among them, the passenger waiting time E(w) = 1 / 2E(I)×(1 + Var(I) / E(I) 2 ), where E(w) is the passenger waiting time, E(I) is the expected value of the train headway, and Var(I) is the variance of the train headway;

[0024] Load factor = passenger turnover ÷ seating-kilometers × 100%;

[0025] Average passenger running time = line operating mileage ÷ average running speed.

[0026] According to a specific embodiment, in the above transport organization design method applicable to tourist rail transit, the secondary indicators corresponding to the transport efficiency include: vehicle utilization rate and transport capacity utilization rate;

[0027] Among them, the vehicle utilization rate = the number of operating vehicles in off-peak hours ÷ the number of operating vehicles in peak hours;

[0028] Transport capacity utilization rate = Full-day predicted passenger flow ÷ (Full-day train operation pairs × Train seating capacity).

[0029] According to a specific embodiment, in the above transport organization design method applicable to tourist rail transit, the step of pre-constructing the evaluation function further includes: adding a benefit balance degree to the first-level evaluation indicators, and determining the corresponding second-level evaluation indicators for the benefit balance degree;

[0030] Reassigning the corresponding weight values w1 to w to the current multiple evaluation indicators; n Based on the evaluation indicators and their weight values, establishing the evaluation function;

[0031] The second-level indicators corresponding to the benefit balance degree are: operating cost, fare revenue, static investment payback period;

[0032] Among them, operating cost = Unit index of vehicle-kilometer operating cost × Total vehicle-kilometer operation;

[0033] Fare revenue = Total number of passengers × Fare;

[0034] Static investment payback period = Initial investment amount ÷ Annual net cash flow.

[0035] On the other hand, the present invention provides an electronic device, including a processor, a network interface, and a memory, which are interconnected. Among them, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the above transport organization design method applicable to tourist rail transit.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] The method provided by the embodiments of the present invention aims at the characteristics of obvious uneven distribution of passenger flow in the off-season, normal season, and peak season of tourist rail transit, and proposes the "benchmark passenger flow" processed by the weighted average method as the calculation basis for the transport capacity of tourist rail transit, solving the problem of excessive infrastructure project investment scale and poor benefits caused by directly using the maximum predicted passenger flow in the peak hour of the peak season as the design basis; aiming at the differences between the peak flow in the peak season and the off-peak flow in the off-season and the normal season, considering various dynamic adjustment means, a variety of combination methods such as train formation detachment and attachment, seat disassembly, standing density adjustment, and headway adjustment are proposed to adapt to the change of passenger flow, effectively avoiding the waste of train capacity, increasing the flexibility of the transport organization design of tourist rail transit, realizing the mutual matching and adaptation between the transport organization plan and the actual passenger flow in different seasons and train services, and meeting the comprehensive requirements of transport efficiency and investment economy. Description of the Drawings

[0038] Figure 1Flowchart of the transport organization design method applicable to tourist rail transit in an embodiment of the present invention;

[0039] Figure 2 Flowchart of the transport organization design method applicable to tourist rail transit in an embodiment of the present invention;

[0040] Figure 3 Flow model in an embodiment of the present invention;

[0041] Figure 4 Block diagram of the electronic device structure in an embodiment of the present invention. Specific embodiments

[0042] The present invention will be further described in detail below in conjunction with embodiments and specific implementation manners. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments. Any technology implemented based on the content of the present invention belongs to the scope of the present invention.

[0043] Embodiment 1

[0044] Figure 1 A transport organization design method applicable to tourist rail transit according to an exemplary embodiment of the present invention is shown, including:

[0045] a. Obtain the total historical passenger flow and its passenger flow distribution information in the target area, predict the total future passenger flow according to the total historical passenger flow using a flow prediction algorithm, and perform statistical analysis on the passenger flow distribution information to obtain the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season;

[0046] b. Calculate the passenger flow sharing ratio of tourist rail transit using the logit model, and predict the benchmark passenger flow interval of tourist rail transit in the target area based on the total future passenger flow, the passenger flow sharing ratio, the peak passenger flow coefficient in the peak season, and the flat passenger flow coefficient in the off-season;

[0047] c. Take the benchmark passenger flow interval as the target, and generate multiple target transport organization plans based on the existing transport organization plan in the target area according to the transport organization design criteria;

[0048] d. Pre-construct an evaluation function, evaluate multiple target transport organization plans based on the evaluation function, and obtain the optimal transport organization adjustment plan through evaluation; judge whether the evaluation result corresponding to the optimal transport organization adjustment plan reaches the threshold; if so, output the current optimal transport organization adjustment plan; if not, return to step a, and recalculate the total future passenger flow, the peak passenger flow coefficient in the peak season, and the flat passenger flow coefficient in the off-season; until an optimal transport organization adjustment plan with an evaluation result reaching the threshold is generated.

[0049] In this embodiment, considering the characteristics of significantly uneven passenger flow distribution in off-peak, regular, and peak seasons for tourist rail transit, "benchmark passenger flow" processed by the weighted average method is proposed as the calculation basis for the transport capacity of tourist rail transit, solving the problem of excessive infrastructure project investment scale and poor efficiency caused by directly using the maximum predicted passenger flow during peak hours in the peak season as the design basis; for the differences between peak passenger flow in the peak season and off-peak passenger flow in the off-peak season and the regular season, considering various dynamic adjustment measures, a variety of combined methods such as train formation detachment and attachment, seat disassembly, standing density adjustment, and headway adjustment are proposed to adapt to the changes in passenger flow, effectively avoiding the waste of train capacity, increasing the flexibility of the transport organization design for tourist rail transit, achieving the mutual matching and adaptation between the transport organization plan and the actual passenger flow in different seasons and train services, and meeting the comprehensive requirements of transport efficiency and investment economy.

[0050] Embodiment 2

[0051] Furthermore, as Figure 2 shown, the above transport organization design method applicable to tourist rail transit specifically includes:

[0052] a. According to the passenger flow distribution characteristics under peak, regular, and off-peak season conditions, process the predicted passenger flow data by the weighted average method to obtain the "benchmark passenger flow", and determine the peak passenger flow coefficient in the peak season and the off-peak passenger flow coefficient in the off-peak season.

[0053] b. Based on the "benchmark transport capacity" and the line engineering design plan, adjust the transport organization plan according to the peak passenger flow in the peak season and the off-peak passenger flow in the off-peak season to meet the seasonal passenger flow demand. Among them, if there is an existing line project in the target area, adjust the existing transport organization plan; if there is no existing line project in the target area, based on the "benchmark passenger flow", conduct system capacity design according to the traditional rail transit method, verify the "benchmark transport capacity" of the line, and determine the line engineering design plan accordingly, and then dynamically adjust the transport organization plan according to the passenger flow changes.

[0054] c. Comprehensively consider factors such as project investment, passenger waiting time during peak hours in the peak season, minimum headway in the off-peak season, and empty car rate, assign different weights respectively, calculate the optimal system design capacity in the peak season and the off-peak season, and select the optimal transport organization adjustment plan with the best comprehensive evaluation by analyzing the impact of different system design capacities on the passenger flow in the peak season and the off-peak season.

[0055] d. Evaluate whether the transport organization adjustment plan in step c meets the requirements of the balance between transport efficiency and benefit. If not, revise the "benchmark passenger flow", the peak passenger flow coefficient in the peak season, and the off-peak passenger flow coefficient in the off-peak season, and repeat steps a to c.

[0056] Specifically, step a is used to determine the passenger flow data and includes the following steps:

[0057] a1. According to the passenger flow distribution in the peak season, the normal season and the off-season, the predicted passenger flow data is processed by weighted average method to obtain a more reasonable "benchmark passenger flow" as the design basis for the tourist rail transportation capacity;

[0058] a2. Determine the peak passenger flow coefficient in the peak season and the average passenger flow coefficient in the off-season based on the “benchmark passenger flow”, peak passenger flow in the peak season and average passenger flow in the off-season.

[0059] For example, let’s take the tourist rail transit in a certain scenic spot as an example.

[0060] According to the passenger flow of a scenic spot in the peak season, off-season and off-season from 2014 to 2019, the passenger volume after weighted average processing was 5.09 million, 5.62 million, 5.99 million, 6.85 million, 8.58 million and 9.03 million respectively. The power function regression prediction study is more in line with the overall trend of passenger flow changes, and the prediction model is Y=342.13X 0.4736 (R 2 =0.9007), see Figure 2 Among them, Y is the annual number of tourists in the scenic area, X is the interval year with the base year, and R is the correlation coefficient.

[0061] The predicted annual passenger volume and average daily passenger volume in the near future (2028) are 12.34 million / year and 33,800 / day respectively. According to the distribution of passenger flow in the peak season and off-season, the peak passenger flow coefficient in the peak season and the off-season peak passenger flow coefficient are preliminarily determined to be 1.4 and 0.4 respectively, so the predicted average daily passenger volume in the peak season and off-season is 47,300 / day and 13,500 / day respectively.

[0062] The proportion of passenger flow carried by different modes of transportation such as buses, taxis, private cars, rail transit, and tourist special lines can be quantitatively calculated using the logit model to predict the passenger flow share of tourist rail transit, and further calculate the "benchmark passenger flow" of tourist rail transit. The recent full-day passenger volume, full-day maximum one-way cross-sectional passenger flow, and peak hour maximum one-way cross-sectional passenger flow borne by tourist rail transit are 7,937 passengers / day, 4,365 passengers / day, and 909 passengers / hour, respectively.

[0063] Step b is used to determine the engineering design solution, which includes the following steps:

[0064] b1. Based on the "benchmark passenger flow", the system capacity is designed according to the traditional rail transit method, and the "benchmark transportation capacity" of the line such as vehicle formation and capacity, number of pairs of trains running during peak hours, minimum train running interval, number of vehicles in use, etc. is determined;

[0065] b2. According to the "benchmark transport capacity" of the line, determine the line engineering design plan that meets the passenger flow demand, including the road and bridge tunnel plan, station yard layout plan, signal plan, traction power supply plan, etc.

[0066] Based on the predicted "benchmark passenger flow", conduct system capacity design according to the traditional rail transit method. It is verified that the train formation is 4-car formation, the train seating capacity is 240 people (144 seats + 96 standing seats), the peak-hour train operation frequency is 4 pairs / h, and the minimum headway is 15 minutes.

[0067] According to the train formation and vehicle length, determine the platform length of the station; according to factors such as the maximum passenger flow, train formation length, departure frequency, and minimum platform width requirements, determine the platform width of the station. According to the axle load of the train, verify the design plan of the subgrade infrastructure structure. According to the train operation speed, operation density, etc., determine the signal system plan.

[0068] Step b is also used to adjust the transport organization plan, and the following different measures are taken according to the actual passenger flow in the peak season and off-season:

[0069] Based on the principle of "large formation, more seating capacity, increase travel speed, and increase transport volume", adapt to the peak-season peak passenger flow demand by increasing the seating capacity of a single vehicle, increasing the number of vehicle formations, adjusting the train operation range of the train formation, increasing the train operation frequency, and increasing the train travel speed. When there is a large difference between the "benchmark transport capacity" of the line and the peak-season passenger flow, and the adjusted peak-hour transport capacity may still not be able to fully meet the demand of the predicted peak-season peak passenger flow, measures such as passengers queuing up and staggered travel at scenic spots can be taken.

[0070] Among them, increasing the seating capacity of a single vehicle is achieved by removing the seats in the carriage, increasing the standing density of people per unit area in the carriage, or considering the way of transporting passengers with all standing seats.

[0071] Based on the principle of "small formation, less seating capacity, slow travel, and reduce density", adapt to the off-season off-peak passenger flow demand by reducing the seating capacity of a single vehicle, reducing the number of vehicle formations, adjusting the train operation range of the train formation, reducing the train operation frequency, and reducing the train travel speed.

[0072] Among them, reducing the seating capacity of a single vehicle is achieved by reducing the density of people per unit area in the carriage, or considering full-seat passenger carrying.

[0073] Arrange and combine the strategies of increasing the number of vehicle formations, increasing the seating capacity of vehicles, and shortening the headway, generate multiple adjustment strategies for the transport organization plan, and adjust the existing transport organization plan according to multiple adjustment strategies for the transport organization plan to generate multiple target transport organization plans.

[0074] For example, based on the "benchmark passenger flow", the peak passenger flow coefficient in the peak season, and the flat peak coefficient of passenger flow in the off-season, the passenger flow in the peak and off-seasons of the tourist rail transit is obtained as 1,273 person-times per hour and 364 person-times per hour respectively. Taking the maximum one-way cross-sectional passenger flow in a peak hour recently as an example, the passenger flow in the peak tourist season increases by 364 person-times per hour compared with the normal passenger flow. The following measures can be taken to meet the passenger flow demand in the peak season:

[0075] (1) Without changing the headway, increase the train formation, such as increasing from 4-car formation to 6-car formation, then at least 480 more person-times can be carried per hour;

[0076] (2) Appropriately increase the standing density of passengers in the carriages to increase the passenger capacity of the vehicle. For example, if 25 more people are added to each single car, 100 more people can be added in a 4-car formation, then at least 400 more person-times can be carried per hour;

[0077] (3) Without changing the 4-car formation, shorten the headway to 10 minutes, then at least 480 more person-times can be carried per hour;

[0078] (4) Increase the train formation and shorten the headway at the same time. For example, shorten from 4-car formation to 5-car formation and increase the headway to 12 minutes, then at least 540 more person-times can be carried per hour.

[0079] Accordingly, the target transportation plans of serial numbers (1) to (4) are obtained, and then the target transportation plans of serial numbers (1) to (4) are evaluated based on the evaluation function.

[0080] Step c uses the evaluation function to evaluate the generated transportation organization adjustment plan. Among them, the evaluation function comprehensively considers aspects such as passenger flow service level and transportation efficiency, and includes the following steps:

[0081] c1. Consider two situations of removing the seats in the carriages and not removing the seats in the carriages, and calculate the waiting time of passengers in the peak hour of the peak season under different transport capacity design plans;

[0082] c2. Consider the impact of different transportation organization modes (multiple train formation plans, in-car seat adjustment plans) on the service capacity in the off-season, and calculate the minimum headway and empty car rate;

[0083] c3. According to basic data such as the line operation length, benchmark passenger flow, vehicle acceleration and deceleration performance, transportation organization data such as vehicle formation plan, train operation route, operation plan, minimum headway, and number of serviceable vehicles, and economic data such as the operation cost per kilometer, investment per kilometer, and fare, comprehensively consider factors such as project investment, waiting time of passengers in the peak hour of the peak season, minimum headway in the off-season, and empty car rate, assign different weights respectively, and calculate the optimal system design capacity in the peak and off-seasons;

[0084] c4. By analyzing the adaptability of different system design capabilities to the passenger flow during peak and off-peak seasons, select the best transportation organization adjustment plan through comprehensive evaluation.

[0085] Specifically, according to the different transportation organization adjustment plans adopted in step c to meet the passenger flow demand during peak or off-peak seasons, indicators such as the passenger waiting time, full load rate, average passenger running time, vehicle utilization rate, transport capacity utilization rate, operation cost, and fare revenue corresponding to each plan can be calculated. For example: when the train formation increases from 4-car formation to 6-car formation, the full load rate is approximately 0.82 and the transport capacity utilization rate is approximately 0.76; when the headway is shortened to 10 minutes, the passenger waiting time is approximately 0.43, the vehicle utilization rate is approximately 0.85, and the transport capacity utilization rate is approximately 0.79. Among them, the passenger waiting time, full load rate, and average passenger running time are used as evaluation indicators reflecting passenger convenience and comfort, that is, the operation indicators of the passenger flow service level.

[0086] (a) Passenger waiting time E(w) = 1 / 2E(I)×(1 + Var(I) / E(I) 2 ), where E(w) is the passenger waiting time, E(I) is the expected value of the train headway, and Var(I) is the variance of the train headway;

[0087] (b) Full load rate = passenger turnover ÷ capacity kilometers × 100%;

[0088] (c) Average passenger running time = line operation mileage ÷ average running speed.

[0089] Among them, the vehicle utilization rate and transport capacity utilization rate are used as indicators reflecting the utilization efficiency of the line transport capacity, that is, the operation indicators of the transport efficiency.

[0090] (a) Vehicle utilization rate = number of operating vehicles during off-peak hours ÷ number of operating vehicles during peak hours;

[0091] (b) Transport capacity utilization rate = predicted full-day passenger flow ÷ (number of full-day train trips × train capacity).

[0092] In a possible implementation, on the basis of the passenger flow service level and transport efficiency, the evaluation function adds the benefit balance degree as a first-level indicator and determines the corresponding second-level evaluation indicators for the benefit balance degree;

[0093] At the same time, on the basis of the current three first-level indicators and their second-level indicators, reassign the corresponding weight values w1~w n ; establish the evaluation function based on the evaluation indicators and their weight values;

[0094] The second-level indicators corresponding to the benefit balance degree are: operation cost, fare revenue, static investment payback period;

[0095] (a) Operating cost = Unit index of operating cost per vehicle-kilometer × Total number of vehicle-kilometers in operation;

[0096] (b) Fare revenue = Total number of passengers × Fare;

[0097] (c) Static investment payback period = Initial investment amount ÷ Annual net cash flow.

[0098] Among them, calculate the evaluation indicators of passenger flow service level, transportation efficiency, and investment and operation economy, and conduct a weighted comprehensive evaluation of the tourism rail transit transportation organization plan. Based on the actual values of each secondary evaluation indicator, obtain the scores of each secondary evaluation indicator; based on the scores and weights of each secondary evaluation indicator, calculate the scores of the primary indicators corresponding to each secondary indicator; based on the scores and weights of each primary evaluation indicator, calculate the score of the current design plan. The secondary evaluation indicators are passenger waiting time, load factor, average running time of passengers, vehicle utilization rate, transport capacity utilization rate, operating cost, operating revenue, and investment payback period; the primary evaluation indicators are passenger flow service level indicators, transportation efficiency evaluation, and investment and operation economy indicators.

[0099] Specifically, judge the range of the interval in which the actual value of each secondary evaluation indicator is located, and determine the score of this secondary evaluation indicator. For example: when the actual value of the load factor is in the interval range of (0, 0.3], the score of this indicator is 0 - 30; when the actual value of the vehicle utilization rate is in the interval range of (0.3, 0.6], the score of this indicator is 31 - 60; when the actual value of the transport capacity utilization rate is in the interval range of (0.6, 1], the score of this indicator is 61 - 100.

[0100] Specifically, sum the products of the scores of each secondary evaluation indicator and their corresponding weights to obtain the scores of the primary indicators corresponding to each secondary indicator. For example: the score of passenger waiting time is 60, the weight is 0.3, the score of the load factor is 80, the weight is 0.4, and the score of the average running time of passengers is 70, and the weight is 0.3. Then the score of the primary evaluation indicator of passenger flow service level corresponding to the secondary evaluation indicators of passenger waiting time, load factor, and passenger running time is: 60×0.3 + 80×0.4 + 70×0.3 = 71.

[0101] Specifically, the sum of the products of the scores of each first-level evaluation index and their corresponding weights is calculated to obtain the score corresponding to the design scheme. For example: the score of the passenger flow service level evaluation index is 71, and the weight is 0.3; the score of the transportation efficiency evaluation index is 87, and the weight is 0.3; the score of the benefit balance degree evaluation index is 95, and the weight is 0.4; then the comprehensive score of the current design scheme is: 71×0.3 + 87×0.3 + 95×0.4 = 85.4. Further, taking the scheme with a score of 85.4 as the optimal scheme as an example, based on the threshold (in this embodiment, according to the actual application evaluation results, the threshold is set to 85 points), it is evaluated whether the current design scheme meets the requirements of transportation efficiency and benefit balance. If the current scheme reaches the threshold, the current scheme is output as the optimal scheme without returning for recalculation.

[0102] In practical applications, the corresponding relationship between the range of the actual values of each second-level evaluation index and their scores, as well as the weights of each first-level evaluation index and second-level evaluation index and the corresponding scoring thresholds, can be set by those skilled in the art according to the actual application situation, and the embodiments of the present invention do not make specific limitations thereto.

[0103] Embodiment 3

[0104] In another aspect of the present invention, as Figure 4 shown, an electronic device is further provided, including a processor, a network interface, and a memory. The processor, the network interface, and the memory are interconnected. Among them, the memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions to execute the above-mentioned transportation organization design method applicable to tourist rail transit.

[0105] In the embodiments of the present invention, the processor may be an integrated circuit chip with signal processing capabilities. The processor may be a general-purpose processor, a digital signal processor (DSP for short), an application-specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0106] The various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor, or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or can be executed and completed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, register, etc. The processor reads the information in the storage medium and combines its hardware to complete the steps of the above method.

[0107] On the other hand, the present invention also provides a computer storage medium, in which program instructions are stored. When the program instructions are executed by at least one processor, they are used to implement the above-mentioned transport organization design method applicable to tourism rail transit.

[0108] In a possible implementation manner, the above storage medium can be a memory, for example, it can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0109] Among them, the non-volatile memory can be a read-only memory (ROM for short), a programmable read-only memory (PROM for short), an erasable programmable read-only memory (EPROM for short), an electrically erasable programmable read-only memory (EEPROM for short), or a flash memory.

[0110] The volatile memory can be a random access memory (RAM for short), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM for short), dynamic random access memory (DRAM for short), synchronous dynamic random access memory (SDRAM for short), double data rate synchronous dynamic random access memory (DDR SDRAM for short), enhanced synchronous dynamic random access memory (ESDRAM for short), synchronous link dynamic random access memory (SLDRAM for short), and direct rambus random access memory (DRRAM for short).

[0111] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memories.

[0112] It should be understood that the system disclosed in the present invention can be implemented in other ways. For example, the division of the said modules is only a logical function division. In actual implementation, there can be other division methods. 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 communication connections between the modules can be through some interfaces. The indirect coupling or communication connection of the server or unit can be in an electrical or other form.

[0113] In addition, in each embodiment of the present invention, the functional modules can be integrated in a processing unit, or each module can exist physically alone, or two or more modules can be integrated in a processing unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0114] If the above-mentioned 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 such an understanding, the technical solution of the present invention, in essence, 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. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. And the aforementioned storage medium includes: USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs, etc., which can store program codes.

[0115] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A transportation organization design method applicable to tourist rail transit, characterized in that, Including: a. Obtain the total historical passenger flow in the target area and its passenger flow distribution information, use a flow prediction algorithm to predict the total future passenger flow based on the total historical passenger flow, and perform statistical analysis on the passenger flow distribution information to obtain the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season; b. Use the logit model to calculate the passenger flow sharing ratio of the tourist rail transit, and predict the benchmark passenger flow range of the tourist rail transit in the target area based on the total future passenger flow, the passenger flow sharing ratio, the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season; c. Taking the benchmark passenger flow range as the goal, generate multiple target transportation organization plans based on the existing transportation organization plan in the target area according to the transportation organization design criteria, and the transportation organization design criteria include: increasing or decreasing the train formation number, increasing or decreasing the number of passengers per single vehicle, adjusting the train operation range of the train routes, increasing or decreasing the number of train trips, increasing or decreasing the train travel speed; The generating of multiple target transportation organization plans based on the existing transportation organization plan in the target area according to the transportation organization design criteria includes: Taking the benchmark passenger flow range as the transportation goal, perform permutation and combination on the transportation organization design criteria to generate multiple transportation organization plan adjustment strategies, and adjust the existing transportation organization plan according to the multiple transportation organization plan adjustment strategies to generate multiple target transportation organization plans; d. Pre-construct an evaluation function, evaluate multiple target transportation organization plans based on the evaluation function, and obtain the optimal transportation organization adjustment plan through evaluation; judge whether the evaluation result corresponding to the optimal transportation organization adjustment plan reaches the threshold; if so, output the current optimal transportation organization adjustment plan; if not, return to step a to recalculate the total future passenger flow, the peak passenger flow coefficient in the peak season and the flat passenger flow coefficient in the off-season; until an optimal transportation organization adjustment plan with an evaluation result reaching the threshold is generated; the method for constructing the evaluation function includes: Taking the passenger flow service level and transportation efficiency as the primary evaluation indicators, and determining the secondary evaluation indicators corresponding to the passenger flow service level and transportation efficiency; And assign weight values w1 to wn to each evaluation indicator respectively; establish the evaluation function based on the evaluation indicators and their weight values.

2. The transportation organization design method applicable to tourist rail transit according to claim 1, characterized in that, The flow prediction algorithm is one of the following: growth rate method, elasticity coefficient method, function model method, exponential regression method.

3. The transportation organization design method applicable to tourist rail transit according to claim 1, characterized in that, The calculation of the passenger flow sharing ratio of the tourist rail transit using the logit model includes: Statistical traffic modes corresponding to the total historical passenger flow in the target area, and quantitatively calculate the passenger flow sharing ratio corresponding to different traffic modes using the logit model.

4. The transportation organization design method applicable to tourist rail transit according to claim 1, characterized in that, The secondary indicators corresponding to the passenger flow service level are: passenger waiting time, load factor, and average passenger running time; Among them, the passenger waiting time E(w)=1 / 2E(I)×(1 + Var(I) / E(I)²), where E(w) is the passenger waiting time, E(I) is the expected value of the train headway, and Var(I) is the variance of the train headway; Load factor = passenger turnover volume ÷ passenger-kilometers of seating capacity × 100%; Average passenger running time = line operation mileage ÷ average running speed.

5. The transportation organization design method applicable to tourist rail transit according to claim 4, characterized in that, The secondary indicators corresponding to the transportation efficiency include: vehicle utilization rate and transport capacity utilization rate; Among them, the vehicle utilization rate = the number of operating vehicles in the off-peak period ÷ the number of operating vehicles in the peak period; The transport capacity utilization rate = the predicted passenger flow for the whole day ÷ (the number of train trips for the whole day × the train seating capacity).

6. The transportation organization design method applicable to tourist rail transit according to claim 5, characterized in that, Pre-building the evaluation function further includes: adding the benefit balance degree to the primary evaluation indicators and determining the secondary evaluation indicators corresponding to the benefit balance degree; Reassigning the corresponding weight values w1 to wn to the current multiple evaluation indicators; establishing the evaluation function based on the evaluation indicators and their weight values; The secondary indicators corresponding to the benefit balance degree are: operating cost, fare revenue, and static investment payback period; Among them, the operating cost = the unit index of vehicle-kilometer operating cost × the total number of vehicle-kilometers in operation; The fare revenue = the total number of passengers × the fare; The static investment payback period = the original investment amount ÷ the annual net cash flow.

7. An electronic device, characterized in that, It includes a processor, a network interface, and a memory. The processor, the network interface, and the memory are interconnected. Among them, the memory is used to store a computer program. The computer program includes program instructions. The processor is configured to call the program instructions to execute the transport organization design method for tourism rail transit according to any one of claims 1-6.

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