A subway interruption management method for the coordinated cooperation of bus feeder service and subway short-turn operation

Abstract

The present invention discloses a subway interruption management method for the coordinated cooperation of bus connection and subway short-turn operation. First, obtain the basic information of rail transit and public transportation; then, obtain the information on passengers' boarding demands; next, extract useful subway fault information and emergency measure information; then, establish a coordinated model for bus connection and subway short-turn operation; finally, solve the established coordinated model for bus connection and subway short-turn operation to obtain the optimal solution of the decision variables of the coordinated model. The present invention can not only make full use of the bus connection method to evacuate stranded passengers, but also adopt the subway short-turn operation method to coordinate with the bus connection, and can effectively reduce the delay time of passengers' trips affected by subway interruptions.

Description

Technical Field

[0001] The present invention relates to the technical field of transportation, and particularly to a subway interruption management method for coordinated cooperation between bus connection and subway short turn. Background Art

[0002] As the backbone of urban public transportation, the subway plays an important role in alleviating traffic congestion and maintaining urban operation. During operation, the subway is often affected by various factors (such as equipment failures, bad weather, and emergency medical assistance), and subway interruption events often occur, affecting the normal travel of passengers. Subway interruption events with a large impact range and long duration often cause serious ground traffic congestion and even paralysis of the entire traffic network. In subway stations with a large number of stranded passengers, crowd trampling accidents may also occur. In recent years, various methods have emerged to evacuate stranded passengers as soon as possible and restore normal traffic, such as using taxis to evacuate stranded passengers, using buses to evacuate stranded passengers, and traffic management and control of passenger flow in and out of subway stations.

[0003] However, the existing methods have the following problems:

[0004] Using taxis to evacuate stranded passengers has the problem of a small passenger capacity per taxi. In the case of a large number of stranded passengers, this method cannot effectively evacuate a large number of stranded passengers in a timely manner. Moreover, this method requires a large number of taxis, which is costly and cannot be applied to actual subway fault situations.

[0005] The method of using buses to evacuate stranded passengers can evacuate a large number of stranded passengers, and the required cost is relatively low, which can be applied to actual subway fault situations. However, the method of using a single bus to evacuate stranded passengers has limitations. The single bus connection method can connect the fault site and the subway turnback site near the fault site, and the connecting buses run in a loop between the fault site and the turnback station. This method "bridges" the two normal sections before and after, and needs to transport a large number of passengers from one normal section to another normal section, which may cause a large number of passengers waiting to transfer to the subway at the turnback station, resulting in serious congestion or even paralysis at some stations. Moreover, a large number of passengers are stranded at some stations, which is likely to cause safety accidents.

[0006] The traffic management and control of passenger flow in and out of subway stations is to control the flow of people in and out of some affected subway stations, which takes into account the safety issues in the subway station. However, a large number of passengers affected by the fault still cannot complete their normal travel.

[0007] In summary, due to the huge scale and complex structure of the urban traffic network, it is difficult to effectively solve the problems caused by serious subway disruptions if the above single solution mode is adopted. In order to ensure the safety of the crowds gathering inside and outside the subway stations and enable passengers to resume normal passage as soon as possible, there is an urgent need to establish a subway disruption management method that coordinates bus shuttles and small subway loops. Summary of the Invention

[0008] To solve the technical problem of the difficulty in quickly resuming normal passage when serious subway disruptions occur currently, the present invention provides a subway disruption management method that coordinates bus shuttles and small subway loops, which can ensure the safety of the crowds gathering inside and outside the subway stations and enable passengers to resume normal passage as soon as possible with a diagnostic effect.

[0009] To achieve the above technical objectives, the technical solution of the present invention is as follows:

[0010] A subway disruption management method that coordinates bus shuttles and small subway loops, comprising the following steps:

[0011] Step 1: Obtain the traffic basic information of the subway line with disruptions and the bus lines with stations between all adjacent stations on the subway line.

[0012] Step 2: Obtain the information on passengers' boarding demands.

[0013] Step 3: Obtain the subway fault information and the emergency measure information for bus shuttles.

[0014] Step 4: Construct a coordination model of bus shuttles and small subway loops with the number of passengers boarding at station j on bus shuttle route b in the k-th time window and the number of passengers boarding at station i on small subway loop route m in the k-th time window as decision variables and with the goal of maximizing the number of evacuated passengers by bus shuttle service and small subway loop service during the entire subway disruption process.

[0015] Step 5: For the established coordination model of bus shuttles and small subway loops, use an optimization solver to solve it, obtain the optimal solution of the decision variables of the coordination model, and use the optimal solution as the basis for controlling the number of passengers entering each station during subway disruptions, thereby completing the subway disruption management method that coordinates bus shuttles and small subway loops.

[0016] In the subway disruption management method that coordinates bus shuttles and small subway loops, in the above Step 1, the traffic basic information includes the running time between adjacent stations of the studied subway line, the bus running time between stations along the subway line, the passenger capacity of a subway train and a bus, and the departure frequencies of subway trains and buses.

[0017] The subway interruption management method for the coordinated cooperation of bus connection and subway short turn-back. In step 2 of the method, the passenger boarding demand information is obtained through the following steps:

[0018] 2.1) Clean the abnormal data from the historical card-swipe data recorded by the smart card swipe terminals on the subway line;

[0019] 2.2) For each subway passenger who swipes the smart card for a transaction, obtain the boarding station and alighting station of the passenger, and determine the travel time of the passenger for this trip in combination with the card-swipe in and out times;

[0020] 2.3) Calculate the average number of people entering each subway station during the interruption period based on the historical data;

[0021] 2.4) According to the running time of the subway train passing through adjacent subway stations and the boarding and alighting stations and travel time of each passenger, use the Dijkstra algorithm to calculate the travel path of the passenger for this trip, and thereby calculate the average number of passengers on other subway lines transferring to the studied subway line from each transfer station of the studied subway line during the interruption period;

[0022] 2.5) Count the number of people boarding at each station on the subway line, that is, the boarding demand at the station: the number of people boarding at non-transfer stations is equal to the number of people entering the station; while the number of people boarding at transfer stations is equal to the number of people entering the station and taking the studied subway line plus the number of people transferring from other lines;

[0023] 2.6) Determine the proportion of affected passengers using the bus connection or subway short turn-back route according to the actual scenario and historical data.

[0024] In the subway interruption management method for the coordinated cooperation of bus connection and subway short turn-back, in step 2.1), the abnormal data cleaning includes at least abnormal data such as duplicate data, data with missing values, abnormal date data, and abnormal time data.

[0025] In the subway interruption management method for the coordinated cooperation of bus connection and subway short turn-back, in step 2.4), the process of calculating the travel path of the passenger for this trip includes:

[0026] First, obtain the subway running time between adjacent stations on each line; then, judge the travel time according to the boarding and alighting times of the passenger; finally, use the shortest path algorithm to obtain the travel path according to the boarding and alighting stations of the passenger.

[0027] In the subway interruption management method for the coordinated cooperation between bus feeder service and subway short-turn operation, in step 3, the subway fault information and the emergency measure information of using bus feeder service include the station or section where the subway fault occurs, the section affected by the subway, the section where the subway short-turn operation is carried out, the start time of the bus feeder service and the subway short-turn service, and the estimated time for the subway to resume normal operation.

[0028] In the subway interruption management method for the coordinated cooperation between bus feeder service and subway short-turn operation, step 4 includes:

[0029] 4.1, Establish the objective function:

[0030]

[0031] Among them, Z is the value of the objective function; represents the number of passengers evacuated by bus feeder service; B is the set of bus feeder routes, B = {b1, b2, b3, b4}, b ∈ B; J b is the set of stations on bus feeder route b, j ∈ J b ; K is the set of time windows, k ∈ K; is the number of passengers boarding at station j on bus feeder route b within the k-th time window; represents the number of passengers evacuated by subway short-turn service; M is the set of subway short-turn routes, M = {m1, m2, m3, m4}, m ∈ M; I m is the set of stations on subway short-turn route m, i ∈ I m ; is the number of passengers boarding at station i on subway short-turn route m within the k-th time window.

[0032] 4.2, To calculate the basic parameters of the bus feeder process part in the coordination model, add constraint conditions (1)(2)(3) in sequence:

[0033]

[0034]

[0035]

[0036] Among them, is the passenger boarding demand at station j on bus feeder route b within the k-th time window; is the boarding demand of non-transfer passengers at station j on bus feeder route b within the k-th time window; E j (k) is the number of passengers transferring from the subway short-turn route to the bus feeder route at station j within the k-th time window; is the proportion of passengers transferring from the subway short-turn route to the bus feeder route b at station j; is the number of passengers who fail to board at station j of the bus feeder route b within the k-th time window; S is the set of endpoints of the sections with faults on the subway line, i.e., the return stations, S = s1 ∪ s2; k′ is the time window when the passengers waiting at station j′ b board the bus, and at this time, the value of k takes the integer part of the value; j′ b is the station in front of station j on the bus feeder route b; Δt is the cross time of a time window; is the travel time of the subway train from station i to station j; is the proportion of passengers transferring from the subway short-turn route m to the bus feeder route at station i; is the number of passengers passing through the section of the bus feeder route b within the k-th time window; is the first section behind station j on the bus feeder route b; is at station j′ b board the bus and pass through the section The proportion of passengers, indicating the contribution rate of station j′ b to the section is estimated based on the historical data of smart cards;

[0037] According to constraint condition (1), calculate the passenger boarding demand at each return station or interruption station within each time window. If j = s1, then b ∈ {b2, b4}; if j = s2, then b ∈ {b1, b3}, and estimate according to the historical data of smart cards and According to constraint condition (2), calculate the number of passengers transferring from each subway short-turn route to each bus feeder route. If m = m1, then j = s2; if m = m3, then j = s1, and estimate according to the historical data of smart cards According to constraint condition (3), calculate the number of passengers passing through each section of the ordinary bus feeder route within each time window. If j = s1, then b = b2; if j = s2, then b = b1;

[0038] 4.3 Add restrictions on the bus feeder process, and add constraint conditions (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) in sequence:

[0039]

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050]

[0051] wherein, N B is the number of passengers that a bus can accommodate; N is the set of natural numbers;

[0052] Constraint (4) ensures that the number of passengers getting on the bus at each stop does not exceed the passenger boarding demand at that stop; Constraint (5) ensures that the number of passengers getting on the bus at non-origin stops does not exceed the remaining passenger capacity of the bus on this route when it arrives at that stop; Constraint (6) ensures that the number of passengers getting on the bus at the origin stop does not exceed the passenger capacity provided by the bus on this route. If j = s1, then b = b2; if j = s2, then b = b1; Constraint (7) ensures that the number of passengers passing through each section of the ordinary bus feeder route does not exceed the passenger capacity provided by the bus on that section. If j = s1, then b = b2; if j = s2, then b = b1; Constraint (8) ensures that the number of passengers getting on the bus at the starting station of the BRT feeder route does not exceed the passenger capacity provided by the bus on this route; Constraint (9) ensures that the passenger boarding demand at each stop is non-negative; Constraint (10) ensures that the boarding demand of non-transfer passengers at each stop is non-negative; Constraint (11) ensures that the number of passengers who fail to board the bus at each stop is non-negative; Constraint (12) ensures that the number of passengers at each stop is non-negative when a subway interruption occurs; Constraint (13) ensures that the boarding demand of transfer passengers at each stop is non-negative; Constraint (14) ensures that the number of passengers getting on the bus at each stop is non-negative; Constraint (15) ensures that the number of passengers passing through each section is non-negative;

[0053] 4.4. To calculate the basic parameters of the subway short-turn process part in the coordination model, add Constraints (16), (17), and (18) in sequence:

[0054]

[0055]

[0056]

[0057] Among them, is the boarding demand of passengers at station i on the short-turn subway route m within the k-th time window; is the boarding demand of non-transfer passengers at station i on the short-turn subway route m within the k-th time window; is the number of passengers who fail to board at station i on the short-turn subway route m within the k-th time window; is the number of passengers transferring from the bus feeder route to station i on the short-turn subway route m within the k-th time window; k′ is the time window when the passengers waiting at station i′ m board the subway, and at this time, the value of k takes the integer part of the value; i′ m is the station in front of station i on the short-turn subway route m; is the proportion of passengers transferring from station j of the bus feeder route b to the short-turn subway route; is the number of passengers passing through section of the short-turn subway route m within the k-th time window; is the first section behind station i on the short-turn subway route m; is the proportion of passengers boarding at station i′ m and passing through section , indicating the contribution rate of station i′ m to section , and its value is estimated based on the historical data of smart cards;

[0058] The boarding demand of passengers at each normal station in each time window is calculated according to constraint condition (16). If i = s1, then m = m4; if i = s2, then m = m2, and is estimated based on the historical data of smart cards. The number of passengers transferring from each bus feeder route to each short-turn subway route is calculated according to constraint condition (17). If i = s1, then b ∈ {b1, b3}, m = m4; if i = s2, then b ∈ {b2, b4}, m = m2, and is estimated based on the historical data of smart cards. The number of passengers passing through each section of the short-turn subway route in each time window is calculated according to constraint condition (18). If i = s1, then m = m4; if i = s2, then m = m2;

[0059] 4.5 Add restrictions on the short-turn subway process, and successively add constraint conditions (19)(20)(21)(22)(23)(24)(25)(26)(27)(28):

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070] where N M is the number of passengers that a subway train can accommodate;

[0071] Constraint (19) ensures that the number of passengers getting on at each subway station is not greater than the passenger boarding demand at that station; Constraint (20) ensures that the number of passengers getting on at non-turnaround stations of the subway short-turn route is not greater than the remaining passenger capacity of the subway train on that route when it arrives at that station; Constraint (21) ensures that the number of passengers getting on at the subway turnaround station is not greater than the passenger capacity provided by the subway train on that route. If i = s1, then m = m4; if i = s2, then m = m2; Constraint (22) ensures that the number of passengers passing through each section of the subway short-turn route is not greater than the passenger capacity provided by the subway train on that section. If i = s1, then m = m4; if i = s2, then m = m2; Constraint (23) ensures that the passenger boarding demand at each station is non-negative; Constraint (24) ensures that the boarding demand of non-transfer passengers at each station is non-negative; Constraint (25) ensures that the number of passengers who fail to board at each station is non-negative; Constraint (26) ensures that the number of passengers at each station is non-negative when a subway interruption occurs; Constraint (13) ensures that the boarding demand of transfer passengers at each station is non-negative; Constraint (27) ensures that the number of passengers getting on at each station is non-negative.

[0072] For the subway interruption management method of coordinating the bus connection with the subway short-turn route, the step five includes:

[0073] 5.1 Add Constraints (1) to (15) in the bus connection process and Constraints (16) to (28) in the subway short-turn process to the constraints of the current model;

[0074] 5.2 Solve the model using the Gorubi optimization solver:

[0075] Program the coordinated model of bus feeder service and subway short-turn operation using the Gurobi optimization solver in Python to obtain:

[0076] The objective function value, i.e., the number of passengers evacuated by the bus feeder service and the subway short-turn service: Z;

[0077] Each decision variable is respectively the number of passengers boarding at station j on bus feeder route b in the k-th time window and the number of passengers boarding at station i on subway short-turn route m in the k-th time window:

[0078] The technical effect of the present invention is that it can make full use of the bus feeder mode to evacuate stranded passengers, and can also adopt the subway short-turn operation mode to coordinate with the bus feeder, which can effectively reduce the delay time of passengers' travel affected by subway disruptions. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a schematic flow chart of the present invention.

[0080] Figure 2 It is a schematic diagram of the coordinated model of bus feeder service and subway short-turn operation

[0081] Figure 3 It is a schematic diagram of the passenger flow demand at subway stations. DETAILED DESCRIPTION OF THE INVENTION

[0082] The present invention will be further described in detail below with reference to the drawings and specific embodiments, but it is not limited to the present invention. The method provided in this embodiment mainly includes the following steps:

[0083] Step 1: Obtain the basic information of rail transit and public transportation. These basic information mainly include the subway running time and bus running time between adjacent stations on the subway line, the passenger capacity of a subway train and a bus shuttle, and the departure frequencies of subway trains and buses. In this embodiment, the subway Line 11 in Shenzhen is taken as an example:

[0084] 1.1) There are 18 subway stations in total along the whole line of the subway Line 11 in Shenzhen. The running time of the subway train passing through adjacent subway stations is obtained from the official website of Shenzhen Metro. At the same time, the running time of the bus passing through the subway stations along the line is estimated by using the road distance between the stations and the average running speed of the bus (set to 25 km / h). For example: The subway running time from Bao'an Station to Fuyong Station is 18.1 minutes, and the bus running time from Bao'an Station to Fuyong Station is 36.72 minutes.

[0085] 1.2) The passenger capacity of an urban subway train is 1500 people, and the passenger capacity of a bus shuttle is 90 people.

[0086] 1.3) The train departure interval of Shenzhen Metro Line 11 is 5 minutes, that is, the maximum train departure frequency is 12 times per hour; in 2017, a total of 634 buses were reserved for emergency use in Shenzhen (not for daily operation). According to the reference, the departure frequency of buses was set to 60 times per hour, that is, a maximum of 36 buses were required for one bus connection route, and a total of at most 144 buses were required, far lower than 634 buses. Therefore, the departure frequency setting is reasonable.

[0087] Step 2: Obtain the passenger boarding demand information. Every time a passenger swipes their card when entering and leaving the subway station, the time and station information will be recorded. Therefore, the passenger's itinerary can be extracted from the smart card data. In this example, the smart card data collected from November 1 to December 12, 2017 was used to estimate the passenger boarding demand during the interruption period. The specific steps are as follows:

[0088] 2.1) Clean the smart card swiping data recorded by the smart card swiping terminal, and delete the missing, duplicate, and other abnormal data in the smart card swiping data.

[0089] 2.2) For each subway passenger with a card transaction, obtain their entry station and exit station, and combine the entry and exit times of the smart card swiping to determine the travel time of this passenger's trip.

[0090] 2.3) Calculate the average number of people entering each subway station during the period from 8:00 to 9:05 am on weekdays.

[0091] 2.4) After obtaining the travel time of the subway train passing through adjacent subway stations, according to each passenger's entry and exit stations and travel time, use the Dijkstra algorithm to infer their travel path for this trip, and thus calculate the average number of passengers on other subway lines transferring to Line 11 from each transfer station to Line 11 during the period from 8:00 to 9:05 am on weekdays.

[0092] 2.5) The number of people boarding at non-transfer stations is equal to the number of people entering the station; while the number of people boarding at transfer stations is equal to the number of people entering the station and taking Line 11 plus the number of people transferring from other lines.

[0093] 2.6) When the urban subway is interrupted, passengers are not limited to using bus shuttles and short subway trips to reach their original destinations. Instead, they can also use other transportation modes (such as taxis or walking) to reach their destinations. Therefore, based on different scenarios and historical data, the proportion of affected passengers using bus shuttles or short subway trips is defined here. In this embodiment, this proportion is set to 60%. That is, once the subway is interrupted, affected passengers will make different choices to continue their journey to the destination. In this embodiment, it is assumed that 60% of the people will accept bus shuttle and short subway services and become the passenger demand at the station in subsequent research. The other 40% will give up traveling or choose other modes such as taxis and will not become the passenger demand at the station. This proportion can be obtained from other existing studies.

[0094] Step 3: According to the subway interruption information provided by the subway operation department and the emergency measures information taken by the subway operation department after the subway interruption, extract the useful subway fault information and emergency measures information. In this example, a subway interruption accident on Line 11 of the Shenzhen Subway is selected, and the useful subway fault information and emergency measures information obtained include:

[0095] The interruption started at 8:00 am on a normal weekday and resumed at 9:05 am, lasting for 65 minutes. The three subway stations of Bihaiwan Station, Airport Station, and Airport North Station were the interrupted stations. The two stations of Bao'an Station and Fuyong Station had the conditions for short subway trips and could be used as turning-back stations. There were 4 damaged sections between the two stations. After the interruption, the bus company urgently dispatched several buses from the parking points near Line 11 and some existing lines with relatively small passenger demand for shuttling. The subway operation department began to prepare for the operation of short subway trips. The bus shuttle and short subway services started 20 minutes after the interruption, that is, at 8:20 am.

[0096] Step 4: Construct a coordinated model for bus shuttles and short subway trips with the number of passengers boarding at station j on bus shuttle route b in the k-th time window and the number of passengers boarding at station i on short subway trip route m in the k-th time window as decision variables and with the goal of maximizing the number of evacuated passengers by bus shuttle service and short subway trip service during the entire subway interruption process. The specific steps are as follows:

[0097] 4.1 Establish the objective function:

[0098]

[0099] where Z is the value of the objective function; represents the number of passengers evacuated by bus shuttle service; B is the set of bus shuttle routes, B = {b1, b2, b3, b4}, b ∈ B; J bis the set of stations on bus feeder route b, where j ∈ J b ; K is the set of time windows, where k ∈ K; is the number of passengers boarding at station j on bus feeder route b within the k-th time window; represents the number of passengers evacuated by the subway short-turn service; M is the set of subway short-turn routes, M = {m1, m2, m3, m4}, where m ∈ M; I m is the set of stations on subway short-turn route m, where i ∈ I m ; is the number of passengers boarding at station i on subway short-turn route m within the k-th time window.

[0100] 4.2 Basic parameters for calculating the bus feeder process part in the coordination model, and constraint conditions (1), (2), and (3) are added in sequence:

[0101]

[0102]

[0103]

[0104] Among them, is the passenger boarding demand at station j on bus feeder route b within the k-th time window; is the boarding demand of non-transfer passengers at station j on bus feeder route b within the k-th time window; E j (k) is the number of passengers transferring from the subway short-turn route to bus feeder route at station j within the k-th time window; is the proportion of passengers transferring from the subway short-turn route to bus feeder route b at station j; is the number of passengers who fail to board at station j on bus feeder route b within the k-th time window; S is the set of turnaround stations, S = s1 ∪ s2; k′ is the time window when passengers waiting at station j′ b board the bus, and at this time, the value of k takes the integer part of the value of; j′ b is the station in front of station j on bus feeder line b; Δt is the cross time of a time window; is the travel time of the subway train from station i to station j; is the proportion of passengers transferring from station i on subway short-turn route m to bus feeder route; is the number of passengers passing through section of bus feeder line b within the k-th time window; is the first section behind station j on bus feeder route b; is at station j′ bGet on the vehicle and pass through the section The proportion of passengers, indicating station j′ b To the section The contribution rate, and its value is estimated based on the historical data of smart cards.

[0105] According to constraint condition (1), calculate the boarding demand of passengers at each turn-back station or interruption station within each time window. If j = s1, then b ∈ {b2, b4}; if j = s2, then b ∈ {b1, b3}, and estimate based on the historical data of smart cards And According to constraint condition (2), calculate the number of passengers transferring from each subway short-turn route to each bus feeder route. If m = m1, then j = s2; if m = m3, then j = s1, and estimate based on the historical data of smart cards According to constraint condition (3), calculate the number of passengers passing through each section of the ordinary bus feeder route within each time window. If j = s1, then b = b2; if j = s2, then b = b1.

[0106] 4.3 Add restrictions on the bus feeder process, and successively add constraint conditions (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15):

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119] Among them, N B Is the number of passengers that a bus can accommodate; N is the set of natural numbers.

[0120] Constraint (4) ensures that the number of passengers getting on the bus at each bus stop is not greater than the demand for passengers getting on at that stop; Constraint (5) ensures that the number of passengers getting on the bus at non-origin stops is not greater than the remaining passenger capacity of the bus on that route when it arrives at that stop; Constraint (6) ensures that the number of passengers getting on the bus at the origin stop is not greater than the passenger capacity provided by the bus on that route. If j = s1, then b = b2; if j = s2, then b = b1; Constraint (7) ensures that the number of passengers passing through each section of the ordinary bus feeder route is not greater than the passenger capacity provided by the bus on that section. If j = s1, then b = b2; if j = s2, then b = b1; Constraint (8) ensures that the number of passengers getting on the bus at the starting station of the BRT feeder route is not greater than the passenger capacity provided by the bus on that route; Constraint (9) ensures that the demand for passengers getting on at each stop is non-negative; Constraint (10) ensures that the demand for non-transfer passengers getting on at each stop is non-negative; Constraint (11) ensures that the number of passengers who fail to board the bus at each stop is non-negative; Constraint (12) ensures that the number of passengers at each stop is non-negative when the subway disruption occurs; Constraint (13) ensures that the demand for transfer passengers getting on at each stop is non-negative; Constraint (14) ensures that the number of passengers getting on the bus at each stop is non-negative; Constraint (15) ensures that the number of passengers passing through each section is non-negative.

[0121] 4.4 To calculate the basic parameters of the subway short-turn process part in the coordination model, add Constraints (16), (17), and (18) in sequence:

[0122]

[0123]

[0124]

[0125] Among them, is the demand for passengers getting on at station i of subway short-turn route m in the k-th time window; is the demand for non-transfer passengers getting on at station i of subway short-turn route m in the k-th time window; is the number of passengers who fail to board the bus at station i of subway short-turn route m in the k-th time window; is the number of passengers transferring from the bus feeder route to subway short-turn route m at station i in the k-th time window; k′ is the time window when the passengers waiting at station i′ m board the subway. At this time, the value of k takes the integer part of the value; i′ m is the station in front of station i on subway short-turn route m; is the proportion of passengers transferring from station j of bus feeder route b to the subway short-turn route; is the number of passengers passing through the section of the subway short-turn route m within the k-th time window ; is the first section after station i on the subway short-turn route m; is at station i′ m boarding and passing through the section The proportion of passengers, indicating the contribution rate of station i′ m to the section , and its value is estimated based on the historical data of smart cards.

[0126] Calculate the boarding demand of passengers at each normal station within each time window according to constraint condition (16). If i = s1, then m = m4; if i = s2, then m = m2, and estimate based on the historical data of smart cards Calculate the number of passengers transferring from each bus connection route to each subway short-turn route according to constraint condition (17). If i = s1, then b ∈ {b1, b3}, m = m4; if i = s2, then b ∈ {b2, b4}, m = m2, and estimate based on the historical data of smart cards Calculate the number of passengers passing through each section of the subway short-turn route within each time window according to constraint condition (18). If i = s1, then m = m4; if i = s2, then m = m2.

[0127] 4.5 Add restrictions to the subway short-turn process, and successively add constraint conditions (19)(20)(21)(22)(23)(24)(25)(26)(27)(28):

[0128]

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] where N M is the number of passengers that a subway train can accommodate.

[0139] Constraint (19) ensures that the number of passengers boarding at each subway station does not exceed the passenger boarding demand at that station; Constraint (20) ensures that the number of passengers boarding at non-turnaround stations on the subway short-turn route does not exceed the remaining passenger capacity when the subway train on that route arrives at that station; Constraint (21) ensures that the number of passengers boarding at the subway train turnaround station does not exceed the passenger capacity provided by the subway train on that route. If \(i = s1\), then \(m = m4\); if \(i = s2\), then \(m = m2\); Constraint (22) ensures that the number of passengers passing through each section of the subway short-turn route does not exceed the passenger capacity provided by the subway train on that section. If \(i = s1\), then \(m = m4\); if \(i = s2\), then \(m = m2\); Constraint (23) ensures that the passenger boarding demand at each station is non-negative; Constraint (24) ensures that the boarding demand of non-transfer passengers at each station is non-negative; Constraint (25) ensures that the number of passengers who fail to board at each station is non-negative; Constraint (26) ensures that the number of passengers at each station is non-negative when a subway interruption occurs; Constraint (13) ensures that the boarding demand of transfer passengers at each station is non-negative; Constraint (27) ensures that the number of passengers boarding at each station is non-negative.

[0140] Step 5: For the established coordinated model of bus connection and subway short-turn, use the Gorubi optimization solver in Python to solve it, obtain the optimal solution of the decision variables of the coordinated model, and use the optimal solution as the basis for controlling the number of passengers entering the station at each station during subway interruption, so as to obtain a subway interruption management method for the coordinated cooperation of bus connection and subway short-turn. The specific steps are as follows:

[0141] 5.1 Establish the objective function:

[0142]

[0143] Among them, \(Z\) is the number of passengers evacuated by bus connection service and subway short-turn service during the entire subway interruption process.

[0144] 5.2 Add Constraints (1) to (15) in the bus connection process and Constraints (16) to (28) in the subway short-turn process to the constraint conditions of the current model.

[0145] 5.3 Use the Gorubi optimization solver to solve the model.

[0146] Program and solve the coordinated model of bus connection and subway short-turn using the Gorubi 9.1.2 optimization solver in Python, and it can be directly obtained:

[0147] Objective function value (i.e., the number of passengers evacuated by bus feeder service and subway short-turn service): Z = 77,231 person-times, among which 14,474 person-times are evacuated during the bus feeder process and 62,757 person-times are evacuated during the subway short-turn process. Compared with the non-coordinated model under the same conditions, 361 more person-times are evacuated.

[0148] Each decision variable Thus, the number of passengers boarding at station j on bus feeder route b in the k-th time window and the number of passengers boarding at station i on subway short-turn route m in the k-th time window are obtained respectively, and this can be used as the basis for controlling the number of passengers entering each station, thereby completing the subway interruption management method of coordinating bus feeder and subway short-turn provided in this embodiment.

Claims

1. A subway interruption management method for coordinated cooperation between bus feeder service and subway short-turn operation, characterized in that It includes the following steps: Step 1: Obtain the traffic basic information of the subway line with interruptions and the bus lines with stations between all adjacent stations on the subway line; Step 2: Obtain the passenger boarding demand information; Step 3: Obtain the subway fault information and the emergency measure information of using bus connection; Step 4: Construct the number of passengers boarding at station j on bus connection route b during the k-th time window and the number of passengers boarding at station i on the short-turn subway route m during the k-th time window as decision variables, and establish a coordinated model of bus connection and short-turn subway aiming to maximize the number of evacuated passengers in the entire subway interruption process Step 5: For the established coordination model of bus connection and subway short turn, use an optimization solver to solve it, obtain the optimal solution of the decision variables of the coordination model, and use the optimal solution as the basis for controlling the number of passengers entering each station during subway interruption, so as to complete the subway interruption management method of the coordinated cooperation between bus connection and subway short turn; The said Step 4 includes: 4.1, Establish the objective function: ； Among them, Z is the objective function value; represents the number of passengers evacuated by the bus shuttle service; B is the set of bus shuttle routes, , ; is the set of stations on bus shuttle route b, ; K is the set of time windows, ; is the number of passengers boarding at station j on bus shuttle route b in the k-th time window; represents the number of passengers evacuated by the subway short-turn service; M is the set of subway short-turn routes, , ; is the set of stations on subway short-turn route m, ; is the number of passengers boarding at station i on subway short-turn route m in the k-th time window; 4.2, In order to calculate the basic parameters of the bus connection process in the coordination model, add constraint conditions (1)(2)(3) in sequence: ； , ； , ； Among them, is the boarding demand of passengers at station j of bus transfer route b within the k-th time window; is the boarding demand of non-transfer passengers at station j of bus transfer route b within the k-th time window; is the number of passengers transferring from the subway short-turn route to the bus transfer route at station j within the k-th time window; is the proportion of passengers transferring from the subway short-turn route to bus transfer route b at station j; is the number of passengers who fail to board at station j of bus transfer route b within the k-th time window; S is the set of endpoints of the faulty section on the subway line, i.e., the set of return stations, ; is at the station The time window when the passengers waiting at board the bus, and at this time, the value of k takes the integer part of the value; is the station in front of station j on bus transfer route b; Δt is the cross time of a time window; is the travel time of the subway train from station i to station j; is the proportion of passengers transferring from station i of subway short-turn route m to the bus transfer route; is the number of passengers passing through section of bus transfer route b within the k-th time window; is the first section behind station j on bus transfer route b; is at the station board and pass through section The proportion of passengers, indicating the contribution rate of station to section , which is estimated based on the historical data of smart cards.

2. The subway interruption management method for coordinated cooperation between bus feeder service and small subway service according to claim 1, wherein In the said Step 1, the traffic basic information includes the running time between adjacent stations of the studied subway line, the bus running time between stations along the subway line, the passenger capacity of a subway train and a bus, and the departure frequencies of the subway train and the bus.

3. The subway interruption management method for the coordinated cooperation between bus feeder service and small subway service according to claim 1, wherein In the said Step 2, the passenger boarding demand information is obtained through the following steps: 2.1) Clean the abnormal data in the historical card swiping data recorded by the smart card swiping terminals on the subway line; 2.2) For each subway passenger who swipes the smart card for a transaction, obtain the boarding station and alighting station of the passenger, and combine the card swiping in and out times to determine the travel time of the passenger for this trip; 2.3) Calculate the average number of people entering each subway station during the interruption period according to the historical data; 2.4) According to the running time of the subway train passing through adjacent subway stations and the entry and exit stations and travel time of each passenger, use the Dijkstra algorithm to calculate the travel path of the passenger for this trip, and thus calculate the average number of passengers from other subway lines transferring to the studied subway line at each transfer station during the interruption period; 2.5) Count the number of people boarding at each station on the subway line, that is, the boarding demand of the station: among them, the number of people boarding at non-transfer stations is equal to the number of people entering the station; while the number of people boarding at transfer stations is equal to the number of people entering the station and taking the studied subway line plus the number of people transferring from other lines; 2.6) Determine the proportion of affected passengers using the bus connection or subway short turn route according to the actual scenario and historical data.

4. The subway interruption management method for coordinated cooperation between bus connection and subway short turn according to claim 3, characterized in that, In the said step 2.1), the abnormal data cleaning includes at least abnormal data such as removing duplicate data, data with missing values, abnormal date data, and abnormal time data.

5. The subway interruption management method for coordinated cooperation between bus feeder service and small subway service according to claim 3, wherein In the said step 2.4), the process of calculating the travel path of the passenger for this trip includes: First, obtain the subway running time between adjacent stations of each line; then, according to the entry and exit times of the passenger, judge the travel time; finally, according to the entry and exit stations of the passenger, use the shortest path algorithm to obtain the travel path.

6. The subway interruption management method for coordinated cooperation between bus connection and subway short-turn described in claim 1, characterized in that In the said Step 3, the subway fault information and the emergency measure information of using bus connection include the station or section where the subway fault occurs, the section affected by the subway, the section where the subway short turn operates, the start time of the bus connection and subway short turn services, and the time when the subway is expected to resume normal operation.

7. The subway interruption management method for coordinated cooperation between bus connection and subway short-turn described in claim 1, characterized in that Step 4 further includes: Constraint (1) calculates the passenger boarding demand at each turn-back station or interruption station within each time window. If , then ; if , then , and estimates and based on the historical data of smart cards; Constraint (2) calculates the number of passengers transferring from each subway short-turn route to each bus feeder route. If , then ; if , then , and estimates based on the historical data of smart cards; Constraint (3) calculates the number of passengers passing through each section of the ordinary bus feeder route within each time window. If , then ; if , then ; 4.

3. Add restrictions on the bus transfer process, and sequentially add constraint conditions (4), (5), (6), (7), (8), (9), (10), (11), (12), (13), (14), (15): ； ； ； ； ； ； ； ； ； ； ； ； ； Among them, is the number of passengers that a bus can accommodate; N is the set of natural numbers; Constraint (4) ensures that the number of passengers boarding at each bus stop does not exceed the passenger boarding demand at that stop; Constraint (5) ensures that the number of passengers boarding at non-origin stops of the bus does not exceed the remaining passenger capacity of the bus on this route when it arrives at that stop; Constraint (6) ensures that the number of passengers boarding at the origin stop of the bus does not exceed the passenger capacity provided by the bus on this route. If , then ; If , then ; Constraint (7) ensures that the number of passengers passing through each section of the ordinary bus feeder route does not exceed the passenger capacity provided by the bus on this section. If , then ; If , then ; Constraint (8) ensures that the number of passengers boarding at the origin of the BRT feeder route does not exceed the passenger capacity provided by the bus on this route; Constraint (9) ensures that the passenger boarding demand at each stop is non-negative; Constraint (10) ensures that the boarding demand of non-transfer passengers at each stop is non-negative; Constraint (11) ensures that the number of passengers who fail to board at each stop is non-negative; Constraint (12) ensures that the number of passengers at each stop is non-negative when a subway disruption occurs; Constraint (13) ensures that the boarding demand of transfer passengers at each stop is non-negative; Constraint (14) ensures that the number of passengers boarding at each stop is non-negative; Constraint (15) ensures that the number of passengers passing through each section is non-negative; 4.

4. To calculate the basic parameters of the subway short-turn process in the coordination model, sequentially add constraint conditions (16), (17), (18): ； ； ； ； ； Among them, is the boarding demand of passengers at station i on the subway short-turn route m within the k-th time window; is the boarding demand of non-transfer passengers at station i on the subway short-turn route m within the k-th time window; is the number of passengers who fail to board at station i on the subway short-turn route m within the k-th time window; is the number of passengers transferring from the bus feeder route to station i on the subway short-turn route m within the k-th time window; is the time window when the passengers waiting at station board the subway. At this time, the value of k takes the integer part of the value; is the station in front of station i on the subway short-turn route m; is the proportion of passengers transferring from station j on the bus feeder route b to the subway short-turn route; is the number of passengers passing through section of the subway short-turn route m within the k-th time window; is the first section behind station i on the subway short-turn route m; is the proportion of passengers boarding at station and passing through section , indicating the contribution rate of station to section . Its value is estimated based on the historical data of smart cards. Constraint condition (16) calculates the boarding demand of passengers at each normal station within each time window. If , then ; if , then , and estimates based on the historical data of smart cards; Constraint condition (17) calculates the number of passengers transferring from each bus feeder route to each subway short-turn route. If , then , ; if , then , , and estimates based on the historical data of smart cards; Constraint condition (18) calculates the number of passengers passing through each section of the subway short-turn route within each time window. If , then ; if , then ; 4.

5. Add restrictions on the subway short-turn process, and sequentially add constraint conditions (19), (20), (21), (22), (23), (24), (25), (26), (27), (28): ； ； ； ； ； ； ； ； ； ； ； Among them, is the number of passengers that a subway train can accommodate; Constraint (19) ensures that the number of passengers boarding at each subway station does not exceed the passenger boarding demand at that station; Constraint (20) ensures that the number of passengers boarding at non-turnaround stations on the subway short turn does not exceed the remaining passenger capacity of the subway train on that route when it arrives at that station; Constraint (21) ensures that the number of passengers boarding at the subway train turnaround station does not exceed the passenger capacity provided by the subway train on that route. If , then ; If , then ; Constraint (22) ensures that the number of passengers passing through each section of the subway short turn route does not exceed the passenger capacity provided by the subway train on that section. If , then ; If , then ; Constraint (23) ensures that the passenger boarding demand at each station is non-negative; Constraint (24) ensures that the boarding demand of non-transfer passengers at each station is non-negative; Constraint (25) ensures that the number of passengers who fail to board at each station is non-negative; Constraint (26) ensures that the number of passengers at each station is non-negative when a subway interruption occurs; Constraint (13) ensures that the boarding demand of transfer passengers at each station is non-negative; Constraint (27) ensures that the number of passengers boarding at each station is non-negative.

8. The subway interruption management method for coordinated cooperation between bus connection and subway short-turn described in claim 7, characterized in that, Step 5 includes: 5.1 Add constraint conditions (1) to (15) in the bus transfer process and constraint conditions (16) to (28) in the subway short-turn process to the constraint conditions of the current model; 5.2 Solve the model using the Gorubi optimization solver: Program and solve the bus transfer and subway short-turn coordination model using the Gorubi optimization solver in Python, so as to obtain: The objective function value, i.e., the number of passengers evacuated by the bus transfer service and the subway short-turn service: Z Each decision variable is respectively the number of passengers boarding at station j on bus feeder route b in time window k and the number of passengers boarding at station i on subway short-turn route m in time window k: , .

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