Urban rail transit network section passenger flow post estimation method and system

Abstract

The invention discloses an urban rail transit network section passenger flow post-estimation method and system, and the method comprises the steps: building an urban rail transit system network space-time topology model based on the basic information data of stations and lines of an urban rail transit system, and searching for the shortest path between network OD pairs through employing a breadth-first algorithm with constraints; based on the transaction data of the automatic fare collection system and the train operation timetable data, matching the passenger with the corresponding train taken by the passenger, and deducing a passenger trip chain; the method comprises the following steps: positioning boarding and alighting nodes of a passenger trip chain, counting the number of boarding and alighting passengers at a station, estimating the line network train passenger capacity, constructing a line network flow calculation model, and further completing the calculation of the rail transit line network section passenger flow based on a mathematical statistics method. According to the method, the trip chain of the passengers in the urban rail transit network can be accurately estimated, the getting-on and getting-off time of all the passengers in the network is obtained, and therefore the passenger capacity of trains running in the network is estimated.

Description

Technical Field

[0001] The present invention relates to the field of urban rail transit network passenger flow simulation, in particular to an urban rail transit network section passenger flow post-estimation method and system. Background Art

[0002] As the backbone network in the comprehensive urban public transportation network, rail transit has always been an important mode of travel to alleviate urban traffic congestion and is also the focus of urban transportation development. In recent years, rail transit in many cities has entered the stage of network operation. In order to better understand the passenger flow operation status of the road network, optimize the driving organization and accurately clear the ticketing, it is necessary to clarify the passenger flow of the line network section. In order to count the passenger flow of the line network section, it is necessary to reconstruct the travel trajectory of passengers in the urban rail network, so as to locate the trains that passengers take in the road network and the time and space coordinates of passengers getting on and off when the train arrives at the station, and count the number of passengers getting on and off when the train stops at the station. By constructing a road network simulation model, according to the matching of the transaction data of the automatic ticket vending and checking (AFC) system and the train operation timetable, the passenger travel chain is calculated, and then the number of passengers on the trains issued on different lines in the road network is counted according to the passenger getting on and off nodes in the passenger travel chain, and then the line network flow calculation model based on mathematical statistics is used. Regarding the post-estimation of the cross-sectional passenger flow of urban rail transit lines, most existing studies at home and abroad use manual sampling surveys to obtain the time between the two nodes of getting on and off and entering and exiting the station, and then use it to infer the number of people getting on and off to calculate the cross-sectional passenger flow, or directly use sensing equipment or weighing systems to obtain the number of people getting on and off and then calculate the cross-sectional passenger flow. However, of these two methods, the former has the problem of partial sampling and the result is not representative, and the latter is costly and technically difficult, making it difficult to apply on a large scale in rail transit lines. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide a method for post-estimation of passenger flow in the section of urban rail transit rail transit network based on spatiotemporal network construction and multi-source data driving, so as to provide a basis for the daily operation management of urban rail transit, emergency handling of sudden passenger flow and ticket clearing.

[0004] Technical solution: The method for post-estimation of passenger flow in a section of an urban rail transit network described in the present invention comprises the following steps:

[0005] S1, collects basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data;

[0006] S2, using a constrained breadth-first algorithm to search for a set of feasible paths between OD pairs that meet the maximum number of transfer constraints, and select the shortest path between OD pairs; based on loading the train operation schedule information in the road network topology model, construct a road network spatiotemporal topology model;

[0007] S3, divide the passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of travel transfers; match the passengers to the OD shortest path in the road network spatiotemporal topology model according to the travel OD pairs recorded in the passenger AFC transaction data, and obtain the passenger travel chain;

[0008] S4, according to the matching of the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the station train, build a train passenger capacity calculation model, and calculate the passenger flow of the urban rail transit line network section.

[0009] Furthermore, in S3, the passenger travel chain containing k travel sub-chains is expressed as:

[0010]

[0011] In the formula, λ x represents the passenger travel chain, x represents a passenger entering the urban rail transit system, ta represents the transaction time when the passenger passes through the entry gate, and te represents the transaction time when the passenger passes through the exit gate; Denotes passenger x at station v i Board the train k time, Passenger x takes train tr k At site v i +1 drop-off time; It constitutes a travel sub-chain of passengers taking a train in the urban rail transit system;

[0012] Passengers without transfers are assigned to trains through the path time similarity index to obtain a travel chain of passengers without transfers.

[0013] Calculate the station entry and exit time distribution based on the non-transfer passenger travel chain;

[0014] The single-transfer passenger travel chain includes two travel sub-chains. According to the station entry and exit time distribution, the constraints between the passenger travel chain and the train operation chain, and the path time similarity index, the transfer time of the single-transfer passenger is calculated to obtain the two travel sub-chains of the single-transfer passenger;

[0015] The travel chain of multi-transfer passengers includes at least three travel sub-chains. According to the station entry and exit time distribution, the constraints between the passenger travel chain and the train operation chain, and the path time similarity index, the transfer time of each multi-transfer passenger is calculated to obtain each travel sub-chain of the multi-transfer passengers.

[0016] Further, S3 includes the following steps:

[0017] S3.1, according to the obtained train schedule, define the train operation chain of path p:

[0018]

[0019] In the formula, λ p represents the train operation chain of path p, is the jth travel subchain of the train operation chain, and the travel subchain includes the starting point of the train on section j Departure time on and end point Arrival time on The train operation chain of the non-transfer path contains one train operation sub-chain, and the train operation chain of the transfer path contains multiple train operation sub-chains; i n Indicates the station number within the line; l j Indicates the line number to which the station belongs. Indicates line l j The kth vehicle sent out;

[0020] S3.2, define the similarity between the passenger travel time interval and the train operation time interval on the path:

[0021]

[0022] In the formula, represents the time similarity between the travel chain of passenger x and the travel chain of train tr on path p, is the length of the intersection of the passenger travel time interval and the train operation time interval on segment j of path p, represents the travel time interval length of passenger x on segment j of path p, represents the length of the time interval of train tr running on section j of path p, γ is a positive constant, J represents the number of time intervals, P w is the shortest path set of OD pairs;

[0023] S3.3, based on the passenger transaction data recorded by the automatic ticket vending and checking system x , extract the passenger's entry and exit OD information, and then search for the shortest path set P in the road network w , match the passengers to the corresponding shortest path according to the OD pairs, and divide the passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of transfers on the path;

[0024] S3.4, for passengers without transfers, the trains taken by passengers are matched by time similarity; the travel time interval of passengers is determined by the transaction data Trade xThe transaction time of the passenger entering and exiting the station is obtained from the transaction time recorded in the train schedule information. The train operation time interval is obtained from the train schedule information. The similarity between the operation time interval of the train tr on the path p after the passenger enters the station and the travel time interval of the passenger x is calculated, and the passenger is matched to the time interval similarity The highest train goes up;

[0025] S3.5, based on the matching results of passengers without transfer obtained in S3.4, calculate the time from the passenger entering the station through the gate to boarding the train and the time from the passenger getting off the train to exiting the station through the gate, expressed as

[0026]

[0027] In the formula, ACT represents the time from when the passenger enters the station through the gate to when he / she boards the train tr, and x v (tr) is the time when the passenger boards the train tr at station v, ta is the transaction time when the passenger passes through the entrance gate; EGT is the time when the passenger gets off the train and passes through the gate to exit the station, tr(x v ) is the time when the passenger gets off the train tr at station v, te is the transaction time when the passenger passes through the exit gate; let the entry and exit time distribution of passengers without transfer at station v represent the entry and exit time distribution of passengers at station v, and calculate the distribution of passenger entry and exit time;

[0028] S3.6, matching transfer passengers to trains, the following relationship needs to be satisfied between the passenger travel chain and the train operation chain:

[0029]

[0030] Where, t d (l, tr, v) represents the time when train tr on line l leaves station v, t a (l, tr, v) represents the time when train tr running on line l arrives at station v, ACT min (l, v) represents the minimum entry time of a passenger at station v on line l, EGT min (l, v) represents the minimum exit time of passengers at station v on line l, t d (l′, tr′, v) represents the time when the transfer train tr′ running on the transfer line l′ leaves the station v, TFT min (l, l′, v) represents the minimum transfer time for passengers to transfer from line l to line l′ at station v;

[0031] To match transfer passengers to trains, it is necessary to match and analyze single transfer passengers to obtain the transfer time in different transfer directions between transfer station lines; the entry and exit time distribution of station passengers calculated by S3.5 is obtained to obtain ACT min(l, v) and EGT min (l, v);

[0032] By analyzing the passenger's AFC transaction data and train schedule, substituting them into constraint (2) of S3.6, the train that the single-transfer passenger takes in the last segment of the travel sub-chain is found, and the boarding time of the passenger's last segment of the travel sub-chain is obtained;

[0033] Taking the passenger boarding time of the last travel subchain as the estimated end time of the first travel subchain, taking ta as the estimated start time of the first travel subchain, calculate the time similarity between the estimated time interval of the passenger's first travel subchain and the train operation chain of the section where the passenger's first travel subchain is located;

[0034] Match the passenger to the train with the highest time similarity, and obtain the passenger's first travel subchain, thus obtaining the complete travel chain of the single-transfer passenger;

[0035] Then the transfer time of passengers is calculated. The transfer time calculation method is as follows:

[0036] TFT=TRT--ACT--IVT--EGT

[0037] In the formula, TFT represents the passenger transfer time, TRT represents the total travel time of the passenger, ACT represents the passenger entry time, IVT represents the passenger time in the train, and EGT represents the passenger exit time. Assuming that the transfer time distribution of single-transfer passengers at the station represents the transfer time distribution of transfer passengers, the transfer time distribution of transfer passengers at the station is obtained by calculating the transfer time of single-transfer passengers in each transfer direction at the station;

[0038] S3.7, put the multi-transfer passengers on the train, and obtain the passenger's first travel sub-chain according to constraint (1) in S3.6. Then take the passenger's get-off time in the first travel sub-chain as the start time of the next travel sub-chain. When constraint (3) in S3.6 is satisfied, take the time similarity between the travel sub-chain and the train running time interval on the path as the standard to infer the train that the passenger of the next travel sub-chain will board. The passenger's last travel sub-chain satisfies constraint (2) in S3.6, and obtains the complete travel chain of the multi-transfer passengers. At this point, the complete travel chain of all passengers is obtained.

[0039] Furthermore, in S4, a train passenger capacity calculation model is constructed as follows:

[0040]

[0041] In the formula, Indicates time state I j The passenger capacity of the following train tr at station v is, express The passenger volume of the train at the previous state, Indicates that in time state I j Number of passengers boarding the train tr at the next station v, Indicates that in time state I j Number of passengers getting off train tr at next station v, initial passenger capacity Time Status I j Represents the jth prediction time interval, which contains the start and end time of the time state;

[0042] The following steps are involved:

[0043] S4.1, counting the number of passengers boarding the platform: generating time state I according to the passenger travel chain j Next stop v Passengers who have successfully boarded the bus will gather Indicates time state I j Passenger alighting x q Get on the train at station v k+n , Statistical time status I j The number of passengers boarding the train arriving at the next station v is set B v，j :

[0044]

[0045] In the formula, Indicates time state I j Next station v train tr k Number of passengers boarding the vehicle;

[0046] S4.2, count the number of people getting off the platform: generate time state I according to the passenger travel chain j Get-off stop v Get-off passengers gathering Indicates time state I j Passenger alighting x q At station v from train tr k+n Get off the bus, count time status I j The number of passengers who get off the train at the next station v is set E v，j :

[0047]

[0048] In the formula, Indicates time state I j Next station v train tr k Number of passengers getting off the bus;

[0049] S4.3, substitute the number of passengers boarding and getting off the train at the platform obtained in S4.1 and S4.2 into the train passenger capacity calculation model to obtain the time state I j The passenger capacity of the following train tr at station v Thus, the passenger capacity of all trains running in the entire urban rail transit network is obtained:

[0050]

[0051] In the formula, Indicates time state I j The passenger capacity of trains running in the urban rail transit network is as follows: Indicates time state I j Next site v m Train tr k of passenger capacity.

[0052] Further, in S4, the method for calculating the cross-sectional passenger flow of the urban rail transit network is: according to the passenger capacity results of all trains running on the network obtained in S4.3, the cross-sectional passenger flow of the rail transit network line in unit time is calculated;

[0053] According to the train timetable data, time status I j The interval length is less than the minimum departure interval of the train, so for the single time state I of station v i There is at most one train under, so I j At most one train tr k ;

[0054] Define the rail transit network section set and define the station v m and site v m+1 The cross section between m , the cross-section set of the wire network O = {O 1 , O 2 , ..., O m};

[0055] For all time states contained in the unit time I a , I a+1 ,...I a+h , traverse For site v m , find all the For the same train tr appearing continuously Define the first value as Time state I p Lower section O m passenger flow;

[0056] All time states I in unit time p Lower section O m The passenger flow of section O per unit time is summed up and the m The passenger flow Q m :

[0057]

[0058] Thus, the passenger flow of the entire urban rail transit network section is obtained:

[0059] Q={Q 1 , Q 2 , ..., Q m}

[0060] Furthermore, the method for constructing the road network spatiotemporal topology model in S2 includes the following steps:

[0061] S2.1, construct a road network spatial topology model O = {φ(L, V), G(V, A)}, and represent the rail transit network as a directed graph G(V, A) according to the logical relationship between stations and lines in the road network N = {φ(L, V)}, where V is the set of stations in the rail transit network, and A is the set of directed edges in the rail transit network, and the directed edges represent the train track areas between stations;

[0062] S2.2, constructing a network train operation time information model T(L, V, TR); L is the set of lines in the subway network, TR is the set of trains in the subway network;

[0063] S2.3, loading the road network train operation time information model T (L, V, TR) into the road network spatial topology model constructed in S2.1, and obtaining the road network spatiotemporal topology model H is expressed as follows:

[0064] H={O={φ(L,V),G(V,A)},T(L,V,TR)}.

[0065] Furthermore, in S2, a constrained breadth-first algorithm is used to search for a set of feasible paths between OD pairs that meet the maximum number of transfer constraints. Selecting the shortest path between OD pairs includes the following steps:

[0066] A1. Initialization: Load the road network directed graph G(V, A) constructed in S2.1, set the maximum number of transfers for road network passengers X, and input the road network OD pair set R w ;

[0067] A2. Cycle R w OD in w ij (v i , v j ), and perform the following B1-B2 operations to generate the OD feasible path decision tree:

[0068] B1. Create an empty queue Q, with OD as the starting point v i As the root node, put it into Q, define array C to represent the number of path transfers, and set C = 0;

[0069] B2. When the queue Q is not empty, loop through the following operations C1 to C3;

[0070] C1. Take out the nodes in Q in order and determine whether the taken out node is the travel end point v j , if yes, execute C3; otherwise, execute C2;

[0071] C2. Take the node taken from Q as the parent node v p , search for sites connected to the parent node in G(V, A) as its direct child node and put it into queue Q, where n s is the child node number, is the nth child node of the sth parent node; determine whether the child node is a transfer station. If so, the number of transfers for the node is increased by one, otherwise, no operation is performed; the distance from the parent node station to the child node station is Number of transfers The sub-node site number is recorded together Stored in the corresponding child node;

[0072] C3. End the search; determine the number of transfers of the tree subnodes of the feasible path decision tree c r , r=1,2,..., whether x is less than or equal to the maximum number of transfers, x is the number of leaf nodes, if so, keep the branch, otherwise perform pruning;

[0073] A3. Read the feasible path decision tree generated in A2. Each leaf node branch corresponds to a feasible path. Calculate the cost of each feasible path and select the path with the least path cost as the OD pair w. ij The shortest path between Store OD in the shortest path set P w middle.

[0074] The urban rail transit network section passenger flow post-estimation system of the present invention comprises:

[0075] Data collection unit, used to collect basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data;

[0076] The road network spatiotemporal topology model construction unit is used to use a constrained breadth-first algorithm to search for a feasible path set between OD pairs that meets the maximum transfer number constraint, and select the shortest path between OD pairs; and construct the road network spatiotemporal topology model according to the train operation schedule information loaded in the road network topology model;

[0077] The passenger travel chain reconstruction unit is used to classify passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of travel transfers; according to the travel OD pairs recorded in the passenger AFC transaction data, the passengers are matched to the OD shortest path in the road network spatiotemporal topology model to obtain the passenger travel chain;

[0078] The urban rail transit network cross-section passenger flow calculation unit is used to match the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the train at the station, build a train passenger capacity calculation model, and calculate the cross-section passenger flow of the urban rail transit network.

[0079] The electronic device described in the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is loaded into the processor, the method for post-estimation of passenger flow in a cross-section of an urban rail transit network is implemented.

[0080] The computer-readable storage medium of the present invention stores a computer program, and when the computer program is executed by a processor, the method for post-estimation of passenger flow in a cross-section of an urban rail transit network is implemented.

[0081] Beneficial effects: Compared with the prior art, the advantages of the present invention are: the present invention can accurately estimate the travel chain of passengers in the urban rail transit network, obtain the boarding and alighting time of all passengers in the network, and thus estimate the passenger capacity of trains running in the network. The present invention can obtain the post-estimated passenger flow of the urban rail transit network section, and can provide a basis for rail transit network simulation, train operation plan formulation, rail transit network dispatching plan formulation, and emergency response to emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 This is a flow chart of the method for post-estimation of passenger flow in a cross-section of an urban rail transit network according to the present invention.

[0083] Figure 2 This is a directed graph of an urban rail transit network according to an embodiment of the present invention.

[0084] Figure 3 The feasible path set search algorithm between OD pairs in the embodiment of the present invention is OD pair w ij (v i , v j ) between the feasible paths in the decision tree. DETAILED DESCRIPTION

[0085] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0086] like Figure 1 As shown, the method for post-estimation of passenger flow in a section of an urban rail transit network includes the following steps.

[0087] S1, obtains and analyzes the basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data, and obtains the specified data format after data cleaning.

[0088] S1.1, obtain basic data of rail transit network stations and lines;

[0089] The urban rail transit network station data includes four attribute values: station number, station longitude, station latitude and the line to which it belongs, expressed as:

[0090] VS={[v 1 , Lon 1 , Lat 1 ,l 1 ],...,[v i , Lon i , Lat i , l j ]}

[0091] VS represents the basic data of network sites and lines, i represents the site number, and v i Indicates the site number, Lon i Indicates the longitude of the site, Lat i represents the latitude of the station, j represents the line number, l j Indicates the line number to which the station belongs;

[0092] The urban rail transit network is divided into three levels in space, from high to low: road network, line, and station. The network contains different operating lines. N = {φ(L, V)} represents the urban rail transit network spatial model, where N represents the road network, L represents the line set, and V represents the station set. The lines and stations form a network through a nonlinear relationship φ.

[0093] The basic properties of the network are derived from the logical relationship between lines, stations, and network in the network N = {φ(L, V)}:

[0094] At the line level, line l j The site collection is represented as in, Indicates line l j The i-th station in the j The number of sites in

[0095] At the network level, all lines constitute a road network, and the line set is represented by L = {l 1 , l 2 , ..., l j , ..., l m}, where l jrepresents the jth route in the road network, and m is the total number of routes in the road network;

[0096] The road network contains all sites, and the set of all sites in the road network is represented as

[0097]

[0098] Using φ(L, V) to represent the spatial relationship between stations, routes, and road networks, we have the road network spatial model: N = {φ(L, V)}. In the model, route l j Contains two attribute values: line name and line rail transit clearing system (hereinafter referred to as ACC) number; station It contains five attribute values: station name, line number, station ACC number, station line number, and whether it is a transfer station. The station ACC number uniquely encodes all stations in the network. The station line number is encoded according to the order of the uplink and downlink directions of the line. The station code is not unique, and the codes of transfer stations in different lines are different. According to the attributes of the line and station, the query function of station and line information in the network is realized.

[0099] S1.2, obtain AFC transaction data;

[0100] The transaction data recorded by the urban rail transit automatic ticketing system includes the passenger's travel starting and ending points and entry and exit times. The AFC transaction data of a complete trip of passenger x is expressed as: x ={ID x , v o ,ta,v d ,te};

[0101] Where, ID x represents the transaction number of passenger x recorded in the automatic ticket vending and checking system, v o , v d They represent the starting and ending stations of passengers in the urban rail transit system, ta and te represent the time when passengers pass through the entry and exit gates respectively;

[0102] S1.3, obtain train timetable data;

[0103] The train operation schedule data includes the arrival and departure time information of the trains on the line, which is expressed as T(L, TR), where L is the line set in the subway network and TR is the train set in the subway network;

[0104] TR = {tr 1 , tr 2 , ..., tr k , ..., tr K}, tr k is the kth vehicle in the network, K is the total number of vehicles dispatched in the network;

[0105] On each line in the network, different train numbers will be dispatched. j The set of trains dispatched from Indicates line l j The g-th train departs from the line l. j The number of departures on.

[0106] S2, construct a road network spatiotemporal topological model and a constrained breadth-first algorithm to search for the shortest path. According to the characteristics of the urban rail transit network, the road network spatial topological structure is constructed; a constrained breadth-first algorithm is used to search for a set of feasible paths between OD pairs that meet the maximum number of transfer constraints, and the shortest path between OD pairs is selected; then, based on the train operation timetable information loaded in the road network topological model, a rail transit road network spatiotemporal topological model is constructed.

[0107] S2.1, construct a road network spatial topology model to search for the shortest path between OD pairs in the road network;

[0108] According to the logical relationship between stations and lines in the road network N = {φ(L, V)}, the rail transit network is represented as a directed graph G(V, A), as follows: Figure 2 As shown, where V is the set of stations in the rail transit network, A is the set of directed edges in the rail transit network, and the directed edges represent the train track areas between stations; construct the adjacency matrix M of G(V, A) c and the distance matrix M d :

[0109]

[0110] In the formula, the adjacency matrix M c The matrix element c ij =1 indicates that sites i and j are directly connected, otherwise, they are not directly connected, which is represented by 0; the distance matrix M d The matrix element d ij Represents the distance of the directed edge from site i to site j. If two sites are directly connected, the edge distance between adjacent sites is the distance a between the sites. ij , otherwise, it is +∞;

[0111] The logical relationship between stations and routes in the road network and the directed graph of the road network together constitute the road network spatial topology model:

[0112] O={φ(L,V),G(V,A)}

[0113] Among them, O represents the spatial topological model of the road network. In the network directed graph G(V, A), v∈V represents the nodes of the graph, and a∈A represents the edges of the graph. There are edges in the upstream and downstream directions between adjacent stations, and virtual platforms are set up in the transfer station to describe the transfer behavior of passengers in the transfer station.

[0114] Specifically, Line A and Line B are at the transfer station v T connected, then the transfer station v T Describes that there are stations on Line A and Line B and And with the virtual platform v T For a two-way connection, the walking time for passengers to transfer between the two lines is the time it takes for passengers to get off the platform of the previous service train and arrive at the virtual platform v. T The walking time plus the time from the virtual platform v T Walking time to the platform where the subsequent service train arrives.

[0115] S2.2, construct the network train operation time information model T (L, V, TR), which includes the arrival and departure time information of trains running on different lines. The network time dimension information is extracted from the train timetable. The train arrival and departure information in the train operation timetable is expressed as:

[0116]

[0117] In the formula, Respectively represent the arrival time of trains in the up and down directions, Respectively represent the departure time of trains in the up and down directions, Respectively represent line l j The i-th site The kth vehicle The arrival time of up and down trains, Respectively represent line l j The i-th site The kth vehicle The departure time of up and down trains, m, n, q are the number of lines in the network, the number of stations on the lines, and the number of train departures on the lines, respectively.

[0118] S2.3, loading the road network train operation time information model T (L, V, TR) into the road network spatial topology model constructed in S2.1, and obtaining the road network spatiotemporal topology model H is expressed as follows:

[0119] H={O={φ(L,V),G(V,A)},T(L,V,TR)}

[0120] T(L, V, TR) includes the arrival time and departure time of the train on the line, which can be expressed as:

[0121]

[0122]

[0123] In the formula, the constraint condition is equivalent to the logical relationship between stations and lines in the road network N = {φ(L, V)} in S2.1;

[0124] In the spatial directed graph, a constrained breadth-first algorithm is used to search for a set of feasible paths between OD pairs in the road network that meet the maximum number of transfer constraints, and select the shortest path between OD pairs. The specific algorithm is:

[0125] A1. Initialization: Load the road network directed graph G(V, A) constructed in S2.1, set the maximum number of transfers for road network passengers X, and input the road network OD pair set R w ;

[0126] A2. Cycle R w OD in w ij (v i , v j ), and perform the following B1~B2 operations to generate the OD feasible path decision tree, such as Figure 3 As shown:

[0127] B1. Create an empty queue Q, with OD as the starting point v i As the root node, put it into Q, define array C to represent the number of path transfers, and set C = 0;

[0128] B2. When the queue Q is not empty, loop through the following operations C1 to C3;

[0129] C1. Take out the nodes in Q in order and determine whether the taken out node is the travel end point v j , if yes, execute C3; otherwise, execute C2;

[0130] C2. Take the node taken from Q as the parent node v p , search for sites connected to the parent node in G(V, A) as its direct child node and put it into queue Q, where n s is the child node number, is the nth child node of the sth parent node; determine whether the child node is a transfer station. If so, the number of transfers for the node is increased by one, otherwise, no operation is performed; the distance from the parent node station to the child node station is Number of transfers The sub-node site number is recorded together Stored in the corresponding child node;

[0131] C3. End the search; determine the number of transfers of the tree subnodes of the feasible path decision tree c r , r=1,2,..., whether x is less than or equal to the maximum number of transfers, x is the number of leaf nodes, if so, keep the branch, otherwise perform pruning;

[0132] A3. Read the feasible path decision tree generated in A2. Each leaf node branch corresponds to a feasible path. Calculate the cost of each feasible path and select the path with the least path cost as the OD pair w. ij The shortest path between Store OD in the shortest path set P w middle.

[0133] S3, reconstruct the passenger travel chain, match the passengers to the OD shortest path in the road network spatiotemporal topology model according to the travel OD pairs recorded in the passenger AFC transaction data, and divide the passengers into non-transfer, single-transfer, and multiple-transfer passengers according to the number of travel transfers; assign non-transfer passengers to trains through the path time similarity index to obtain the travel chain of non-transfer passengers, and calculate the station entry and exit time distribution based on the travel chain of non-transfer passengers; match the passengers to trains on the travel sub-chain according to the station entry and exit time distribution, passenger travel chain constraints, and time similarity, reconstruct the single-transfer passenger travel chain, and calculate the transfer time distribution of different transfer directions at the transfer station; after obtaining the transfer time distribution, infer the travel chain of multiple transfer passengers.

[0134] The passenger's travel chain is represented as:

[0135]

[0136] In the formula, λ x represents the passenger travel chain, x represents a passenger entering the urban rail transit system, ta represents the transaction time when the passenger passes through the entry gate, and te represents the transaction time when the passenger passes through the exit gate; Denotes passenger x at station v i Board the train k time, Passenger x takes train tr k At site v i+1 The time of getting off the bus;

[0137] A passenger trip chain contains one or more trip subchains. It constitutes the travel sub-chain of a passenger taking a train in the urban rail transit system. The travel chain of passengers without transfers contains only one travel sub-chain, while the travel chain of passengers with transfers contains multiple travel sub-chains. In the above formula, the travel chain of the passenger contains k travel sub-chains.

[0138] According to the obtained train schedule, define the train operation chain of path p:

[0139]

[0140] In the formula, λ p represents the train operation chain of path p, is the jth travel subchain of the train operation chain, and the travel subchain includes the starting point of the train on section j Departure time on and end point Arrival time on The train operation chain without transfer path contains only one train operation sub-chain, and the train operation chain with transfer path contains multiple train operation sub-chains; i n Indicates the station number within the line.

[0141] Define the similarity between the passenger travel time interval and the train operation time interval on the path:

[0142]

[0143] In the formula, represents the time similarity between the travel chain of passenger x and the travel chain of train tr on path p, is the length of the intersection of the passenger travel time interval and the train operation time interval on segment j of path p, represents the travel time interval length of passenger x on segment j of path p, represents the length of the time interval of train tr running on section j of path p, γ is a positive constant, J represents the number of time intervals, P w is the shortest path set of OD pairs.

[0144] Passenger travel type classification:

[0145] According to the passenger transaction data recorded by the automatic ticket vending and checking system x , extract the passenger's entry and exit OD information, and then search for the shortest path set P in the road network w , match the passengers to the corresponding shortest path according to the OD pairs, and divide the passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of transfers on the path.

[0146] Reconstruction of passenger travel chain:

[0147] (1) Reconstruction of the travel chain of passengers without transfers: For passengers without transfers, the trains they take are matched using time similarity; the travel time intervals of passengers are determined by the transaction data Trade xThe transaction time of the passenger entering and exiting the station is obtained from the train timetable information T(L, TR). The similarity between the running time interval of the train tr on path p after the passenger enters the station and the travel time interval of passenger x is calculated, and the passenger is matched to the time interval similarity. The highest train goes up.

[0148] (2) Reconstruction of the travel chain of transfer passengers: Based on the matching results of passengers without transfers, the time from the passenger entering the station through the gate to boarding the train and the time from the passenger getting off the train to exiting the station through the gate are calculated, expressed as

[0149]

[0150] In the formula, ACT represents the time from when the passenger enters the station through the gate to when he / she boards the train tr, and x v (tr) is the time when the passenger boards the train tr at station v, ta is the transaction time when the passenger passes through the entrance gate; EGT is the time when the passenger gets off the train and passes through the gate to exit the station, tr(x v ) is the time when the passenger gets off the train tr at station v, te is the transaction time when the passenger passes through the exit gate; let the entry and exit time distribution of passengers without transfer at station v represent the entry and exit time distribution of passengers at station v, and calculate the distribution of passenger entry and exit time;

[0151] To match transfer passengers to trains, the following relationship needs to be satisfied between the passenger travel chain and the train operation chain:

[0152]

[0153] Where, t d (l, tr, v) represents the time when train tr on line l leaves station v, t a (l, tr, v) represents the time when train tr running on line l arrives at station v, ACT min (l, v) represents the minimum entry time of a passenger at station v on line l, EGT min (l, v) represents the minimum exit time of passengers at station v on line l, t d (l′, tr′, v) represents the time when the transfer train tr′ running on the transfer line l′ leaves the station v, TFT min (l, l′, v) represents the minimum transfer time for passengers to transfer from line l to line l′ at station v.

[0154] (2.1) Reconstruction of single-transfer passenger travel chain:

[0155] To match transfer passengers to trains, it is necessary to match and analyze single transfer passengers to obtain the transfer time in different transfer directions between transfer station lines; the ACT is obtained by the distribution of passenger entry and exit time at the station. min (l, v) and EGT min (l, v); By analyzing the passenger's AFC transaction data and train schedule, substitute them into constraint formula (2) to find the train that the single-transfer passenger takes on the last travel subchain, and obtain the boarding time of the passenger's last travel subchain; take the boarding time of the passenger in the last travel subchain as the estimated end time of the first travel subchain, and take ta as the estimated start time of the first travel subchain, and calculate the time similarity between the estimated time interval of the passenger's first travel subchain and the train operation chain of the section where the passenger's first travel subchain is located; match the passenger to the train with the highest time similarity, and obtain the passenger's first travel subchain, thereby obtaining the complete travel chain of the single-transfer passenger;

[0156] Then the transfer time of passengers is calculated. The transfer time calculation method is as follows:

[0157] TFT=TRT--ACT--IVT--EGT

[0158] In the formula, TFT represents the passenger transfer time, TRT represents the total travel time of the passengers, ACT represents the time when the passengers enter the station, IVT represents the time when the passengers are in the train, and EGT represents the time when the passengers leave the station. Assuming that the transfer time distribution of passengers transferring at a station represents the transfer time distribution of passengers transferring, the transfer time distribution of passengers transferring at the station is obtained by calculating the transfer time of passengers transferring at a station in each transfer direction.

[0159] (2.2) Reconstruction of multi-transfer passenger travel chain:

[0160] The multi-transfer passengers are put on the train, and the first travel sub-chain of the passengers is obtained according to constraint (1). The time when the passengers get off the first travel sub-chain is used as the start time of the next travel sub-chain. When constraint (3) is satisfied, the time similarity between the travel sub-chain and the train running time interval on the path is used as the standard to infer the train that the passengers of the next travel sub-chain will board. The last travel sub-chain of the passengers satisfies constraint (2) and the complete travel chain of the multi-transfer passengers is obtained. Thus, the complete travel chain of all passengers is obtained.

[0161] S4, according to the matching of the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the station train, and then use the train passenger capacity calculation model to obtain the train passenger capacity, thereby obtaining the network operation train passenger capacity.

[0162] The train passenger capacity calculation model is constructed as follows:

[0163]

[0164] In the formula, Indicates time state I j The passenger capacity of the following train tr at station v is, express The passenger volume of the train at the previous state, Indicates that in time state I j Number of passengers boarding the train tr at the next station v, Indicates that in time state I j Number of passengers getting off train tr at next station v, initial passenger capacity Time Status I j Represents the jth prediction time interval, which contains the start and end time of the time state;

[0165] The train passenger capacity calculation model further includes:

[0166] S4.1, counting the number of passengers boarding the platform: generating time state I according to the passenger travel chain j Next stop v Passengers who have successfully boarded the bus will gather Indicates time state I j Passenger alighting x q Get on the train at station v k+n , Statistical time status I j The number of passengers boarding the train arriving at the next station v is set B v，j :

[0167]

[0168] In the formula, Indicates time state I j Next station v train tr k Number of passengers boarding the vehicle;

[0169] S4.2, count the number of people getting off the platform: generate time state I according to the passenger travel chain j Get-off stop v Get-off passengers gathering Indicates time state I j Passenger alighting x q At station v from train tr k+n Get off the bus, count time status I j The number of passengers who get off the train at the next station v is set E v，j :

[0170]

[0171] In the formula, Indicates time state I j Next station v train trk Number of passengers getting off the bus;

[0172] S4.3, substitute the number of passengers boarding and getting off the train at the platform obtained in S4.1 and S4.2 into the train passenger capacity calculation model to obtain the time state I j The passenger capacity of the following train tr at station v Thus, the passenger capacity of all trains running in the entire urban rail transit network is obtained:

[0173]

[0174] In the formula, Indicates time state I j The passenger capacity of trains running in the urban rail transit network is as follows: Indicates time state I j Next site v m Train tr k of passenger capacity.

[0175] S4.4, based on the passenger capacity results of all trains running on the network obtained in S4.3, calculate the passenger flow of the rail transit network line section per unit time.

[0176] According to the train timetable data, time status I j The interval length is less than the minimum departure interval of the train, so for the single time state I of station v j There is at most one train under, so I j At most one train tr k .

[0177] Define rail transit network section set. Define station v m and site v m+1 The cross section between m , the cross-section set of the wire network O = {O 1 , O 2 , ..., O m}.

[0178] For all time states contained in the unit time I a , I a+1 , ..., I a+h , traverse For site v m , find all the For the same train tr appearing continuously Define the first value as Time state I p Lower section O m The passenger flow. All the time states I in the unit timep Lower section O m The passenger flow of section O per unit time can be obtained by summing up the passenger flow of section O per unit time. m The passenger flow Q m :

[0179]

[0180] Thus, the passenger flow of the entire urban rail transit network section is obtained:

[0181] Q={Q 1 , Q 2 , ..., Q m}.

[0182] The urban rail transit network section passenger flow post-estimation system of the present invention comprises:

[0183] Data collection unit, used to collect basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data;

[0184] The road network spatiotemporal topology model construction unit is used to use a constrained breadth-first algorithm to search for a feasible path set between OD pairs that meets the maximum transfer number constraint, and select the shortest path between OD pairs; and construct the road network spatiotemporal topology model according to the train operation schedule information loaded in the road network topology model;

[0185] The passenger travel chain reconstruction unit is used to classify passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of travel transfers; according to the travel OD pairs recorded in the passenger AFC transaction data, the passengers are matched to the OD shortest path in the road network spatiotemporal topology model to obtain the passenger travel chain;

[0186] The urban rail transit network cross-section passenger flow calculation unit is used to match the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the train at the station, build a train passenger capacity calculation model, and calculate the cross-section passenger flow of the urban rail transit network.

[0187] The electronic device described in the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is loaded into the processor, the method for post-estimation of passenger flow in a cross-section of an urban rail transit network is implemented.

[0188] The computer-readable storage medium of the present invention stores a computer program, and when the computer program is executed by a processor, the method for post-estimation of passenger flow in a cross-section of an urban rail transit network is implemented.

[0189] The computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and that can be accessed by a computer.

[0190] The processor is used to execute the computer program stored in the memory to implement each step of the method involved in the above embodiment.

Claims

1. A method for post-estimation of passenger flow in a section of an urban rail transit network, characterized in that: The steps include: S1, collects basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data; S2, using a constrained breadth-first algorithm to search for a set of feasible paths between OD pairs that meet the maximum number of transfer constraints, and select the shortest path between OD pairs; based on loading the train operation schedule information in the road network topology model, construct a road network spatiotemporal topology model; S3, divide the passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of travel transfers; match the passengers to the OD shortest path in the road network spatiotemporal topology model according to the travel OD pairs recorded in the passenger AFC transaction data, and obtain the passenger travel chain; S4, according to the matching of the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the station train, build a train passenger capacity calculation model, and calculate the passenger flow of the urban rail transit line network section.

2. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 1, characterized in that: In S3, the passenger travel chain containing k travel sub-chains is expressed as: In the formula, λ x represents the passenger travel chain, x represents a passenger entering the urban rail transit system, ta represents the transaction time when the passenger passes through the entry gate, and te represents the transaction time when the passenger passes through the exit gate; Denotes passenger x at station v i Board the train k time, Passenger x takes train tr k At site v i+1 The time of getting off the bus; It constitutes a travel sub-chain of passengers taking a train in the urban rail transit system; Passengers without transfers are assigned to trains through the path time similarity index to obtain a travel chain of passengers without transfers. Calculate the station entry and exit time distribution based on the non-transfer passenger travel chain; The single-transfer passenger travel chain includes two travel sub-chains. According to the station entry and exit time distribution, the constraints between the passenger travel chain and the train operation chain, and the path time similarity index, the transfer time of the single-transfer passenger is calculated to obtain the two travel sub-chains of the single-transfer passenger; The travel chain of multi-transfer passengers includes at least three travel sub-chains. According to the station entry and exit time distribution, the constraints between the passenger travel chain and the train operation chain, and the path time similarity index, the transfer time of each multi-transfer passenger is calculated to obtain each travel sub-chain of the multi-transfer passengers.

3. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 1, characterized in that: S3 includes the following steps: S3.1, according to the obtained train schedule, define the train operation chain of path p: In the formula, λ p represents the train operation chain of path p, is the jth travel subchain of the train operation chain, and the travel subchain includes the starting point of the train on section j Departure time on and end point Arrival time on The train operation chain of the non-transfer path contains one train operation sub-chain, and the train operation chain of the transfer path contains multiple train operation sub-chains; i n Indicates the station number within the line; l j Indicates the line number to which the station belongs. Indicates line l j The kth vehicle sent out; S3.2, define the similarity between the passenger travel time interval and the train operation time interval on the path: In the formula, represents the time similarity between the travel chain of passenger x and the travel chain of train tr on path p, is the length of the intersection of the passenger travel time interval and the train operation time interval on segment j of path p, represents the travel time interval length of passenger x on segment j of path p, represents the length of the time interval of train tr running on section j of path p, γ is a positive constant, J represents the number of time intervals, P w is the shortest path set of OD pairs; S3.3, based on the passenger transaction data recorded by the automatic ticket vending and checking system x , extract the passenger's entry and exit OD information, and then search for the shortest path set P in the road network w , match the passengers to the corresponding shortest path according to the OD pairs, and divide the passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of transfers on the path; S3.4, for passengers without transfers, the trains taken by passengers are matched by time similarity; the travel time interval of passengers is determined by the transaction data Trade x The transaction time of the passenger entering and exiting the station is obtained from the transaction time recorded in the train schedule information. The train operation time interval is obtained from the train schedule information. The similarity between the operation time interval of the train tr on the path p after the passenger enters the station and the travel time interval of the passenger x is calculated, and the passenger is matched to the time interval similarity The highest train goes up; S3.5, based on the matching results of passengers without transfer obtained in S3.4, calculate the time from the passenger entering the station through the gate to boarding the train and the time from the passenger getting off the train to exiting the station through the gate, expressed as In the formula, ACT represents the time from when the passenger enters the station through the gate to when he / she boards the train tr, and x v (tr) is the time when the passenger boards the train tr at station v, ta is the transaction time when the passenger passes through the entrance gate; EGT is the time when the passenger gets off the train and passes through the gate to exit the station, tr(x v ) is the time when the passenger gets off the train tr at station v, te is the transaction time when the passenger passes through the exit gate; let the entry and exit time distribution of passengers without transfer at station v represent the entry and exit time distribution of passengers at station v, and calculate the distribution of passenger entry and exit time; S3.6, matching transfer passengers to trains, the following relationship needs to be satisfied between the passenger travel chain and the train operation chain: In the formula, t d (l,tr,v) represents the time when train tr on line l leaves station v, t a (l,tr,v) represents the time when train tr running on line l arrives at station v, ACT min (l,v) represents the minimum entry time of a passenger at station v on line l, EGT min (l,v) represents the minimum exit time of passengers at station v on line l, t d (l',tr',v) represents the time when the transfer train tr' running on the transfer line l' leaves the station v, TFT min (l,l',v) represents the minimum transfer time for passengers to transfer from line l to line l' at station v; To match transfer passengers to trains, it is necessary to match and analyze single transfer passengers to obtain the transfer time in different transfer directions between transfer station lines; the entry and exit time distribution of station passengers calculated by S3.5 is obtained to obtain ACT min (l,v) and EGT min (l,v); By analyzing the passenger's AFC transaction data and train schedule, substituting them into constraint (2) of S3.6, the train that the single-transfer passenger takes in the last segment of the travel sub-chain is found, and the boarding time of the passenger's last segment of the travel sub-chain is obtained; Taking the passenger boarding time of the last travel subchain as the estimated end time of the first travel subchain, taking ta as the estimated start time of the first travel subchain, calculate the time similarity between the estimated time interval of the passenger's first travel subchain and the train operation chain of the section where the passenger's first travel subchain is located; Match the passenger to the train with the highest time similarity, and obtain the passenger's first travel subchain, thus obtaining the complete travel chain of the single-transfer passenger; Then the transfer time of passengers is calculated. The transfer time calculation method is as follows: TFT=TRT-ACT-IVT-EGT In the formula, TFT represents the passenger transfer time, TRT represents the total travel time of the passenger, ACT represents the passenger entry time, IVT represents the passenger time in the train, and EGT represents the passenger exit time. Assuming that the transfer time distribution of single-transfer passengers at the station represents the transfer time distribution of transfer passengers, the transfer time distribution of transfer passengers at the station is obtained by calculating the transfer time of single-transfer passengers in each transfer direction at the station; S3.7, put the multi-transfer passengers on the train, and obtain the first travel subchain of the passengers according to constraint formula (1) in S3.

6. Then take the time when the passengers get off the first travel subchain as the start time of the next travel subchain. When constraint formula (3) in S3.6 is met, take the time similarity between the travel subchain and the train running time interval of the path as the standard to infer the train boarded by the passengers in the next travel subchain. The last travel subchain of the passengers satisfies constraint formula (2) in S3.6, and obtain the complete travel chain of the multi-transfer passengers. So far, the complete travel chain of all passengers is obtained.

4. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 1, characterized in that: In S4, the train passenger capacity calculation model is constructed as follows: In the formula, Indicates time state I j The passenger capacity of the following train tr at station v is, express The passenger volume of the train at the previous state, Indicates that in time state I j Number of passengers boarding the train tr at the next station v, Indicates that in time state I j Number of passengers getting off train tr at next station v, initial passenger capacity Time Status I j Represents the jth prediction time interval, which contains the start and end time of the time state; The following steps are involved: S4.1, counting the number of passengers boarding the platform: generating time state I according to the passenger travel chain j Next stop v Passengers who have successfully boarded the bus will gather Indicates time state I j Passenger alighting x q Get on the train at station v k+n , Statistical time status I j The number of passengers boarding the train arriving at the next station v is set B v,j : In the formula, Indicates time state I j Next station v train tr k Number of passengers boarding the vehicle; S4.2, count the number of people getting off the platform: generate time state I according to the passenger travel chain j Get-off point v Get-off passengers gathering Indicates time state I j Passenger alighting x q At station v from train tr k+n Get off the bus, count time status I j The number of passengers who get off the train at the next station v is set E v,j : In the formula, Indicates time state I j Next station v train tr k Number of passengers getting off the bus; S4.3, substitute the number of passengers boarding and getting off the train at the platform obtained in S4.1 and S4.2 into the train passenger capacity calculation model to obtain the time state I j The passenger capacity of the following train tr at station v Thus, the passenger capacity of all trains running in the entire urban rail transit network is obtained: In the formula, Indicates time state I j The passenger capacity of trains running in the urban rail transit network is as follows: Indicates time state I j Next site v m Train tr k of passenger capacity.

5. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 4, characterized in that: In S4, the method for calculating the cross-sectional passenger flow of the urban rail transit network is as follows: according to the passenger capacity results of all trains running on the network obtained in S4.3, the cross-sectional passenger flow of the rail transit network line in unit time is calculated; According to the train timetable data, time status I j The interval length is less than the minimum departure interval of the train, so for the single time state I of station v j There is at most one train under, so I j At most one train tr k ; Define the rail transit network section set and define the station v m and site v m+1 The cross section between m , the cross-section set of the wire network is O = {O1, O2, ..., O m }; For all time states contained in the unit time I a ,I a+1 ,…,I a+h , traverse For site v m , find all the For the same train tr appearing continuously Define the first value as Time state I p Lower section O m passenger flow; All time states I in unit time p Lower section O m The passenger flow of section O per unit time is summed up and the m The passenger flow Q m : Thus, the passenger flow of the entire urban rail transit network section is obtained: Q={Q1,Q2,...,Q m }。 6. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 1, characterized in that: The method for constructing the road network spatiotemporal topology model in S2 includes the following steps: S2.1, construct a road network spatial topology model O = {φ(L,V), G(V,A)}, and represent the rail transit network as a directed graph G(V,A) according to the logical relationship between stations and lines in the road network N = {φ(L,V)}, where V is the set of stations in the rail transit network, and A is the set of directed edges in the rail transit network, and the directed edges represent the train track areas between stations; S2.2, construct the network train operation time information model T(L,V,TR); L is the line set in the subway network, TR is the train set in the subway network; S2.3, load the road network train operation time information model T (L, V, TR) into the road network spatial topology model constructed in S2.1, and obtain the road network spatiotemporal topology model H as follows: H={O={φ(L,V),G(V,A)},T(L,V,TR)}.

7. The method for post-estimation of passenger flow in a section of an urban rail transit network according to claim 6, characterized in that: In S2, a constrained breadth-first algorithm is used to search for a set of feasible paths between OD pairs that meet the maximum number of transfer constraints. Selecting the shortest path between OD pairs includes the following steps: A1. Initialization: Load the road network directed graph G(V,A) constructed in S2.1, set the maximum number of transfers for road network passengers X, and input the road network OD pair set R w ; A2. Cycle R w OD in w ij (v i ,v j ), and perform the following B1-B2 operations to generate the OD feasible path decision tree: B1. Create an empty queue Q, with OD as the starting point v i As the root node, put it into Q, define array C to represent the number of path transfers, and set C = 0; B2. When the queue Q is not empty, loop through the following operations C1 to C3; C1. Take out the nodes in Q in order and determine whether the taken out node is the travel end point v j , if yes, execute C3; otherwise, execute C2; C2. Take the node taken from Q as the parent node v p , search for sites connected to the parent node in G(V,A) as its direct child node and put it into queue Q, where n s is the child node number, is the nth child node of the sth parent node; determine whether the child node is a transfer station. If so, the number of transfers for the node is increased by one, otherwise, no operation is performed; the distance from the parent node station to the child node station is Number of transfers The sub-node site number is recorded together Stored in the corresponding child node; C3. End the search; Determine the number of transfers c of the tree child nodes of the feasible path decision tree r , r=1,2,…, whether x is less than or equal to the maximum number of transfers, x is the number of leaf nodes, if so, keep the branch, otherwise perform pruning operation; A3. Read the feasible path decision tree generated in A2. Each leaf node branch corresponds to a feasible path. Calculate the cost of each feasible path and select the path with the least path cost as the OD pair w. ij The shortest path between Store OD in the shortest path set P w middle.

8. A post-estimation system for passenger flow in a section of an urban rail transit network, characterized in that: include: Data collection unit, used to collect basic data of urban rail transit network stations and lines, passenger entry and exit transaction data recorded by the AFC system, and train operation timetable data; The road network spatiotemporal topology model construction unit is used to use a constrained breadth-first algorithm to search for a feasible path set between OD pairs that meets the maximum transfer number constraint, and select the shortest path between OD pairs; and construct the road network spatiotemporal topology model according to the train operation schedule information loaded in the road network topology model; The passenger travel chain reconstruction unit is used to classify passengers into non-transfer passengers, single-transfer passengers, and multiple-transfer passengers according to the number of travel transfers; according to the travel OD pairs recorded in the passenger AFC transaction data, the passengers are matched to the OD shortest path in the road network spatiotemporal topology model to obtain the passenger travel chain; The urban rail transit network cross-section passenger flow calculation unit is used to match the nodes where passengers get on and off the train in the passenger travel chain with the train timetable, count the number of passengers getting on and off the train at the station, build a train passenger capacity calculation model, and calculate the cross-section passenger flow of the urban rail transit network.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is loaded into the processor, the method for post-estimation of passenger flow in a section of an urban rail transit network according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for post-estimation of passenger flow in a section of an urban rail transit network according to any one of claims 1 to 7 is implemented.

Images