CN111401614A - Dynamic passenger flow distribution method and system for urban rail transit - Google Patents

Dynamic passenger flow distribution method and system for urban rail transit Download PDF

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CN111401614A
CN111401614A CN202010157754.3A CN202010157754A CN111401614A CN 111401614 A CN111401614 A CN 111401614A CN 202010157754 A CN202010157754 A CN 202010157754A CN 111401614 A CN111401614 A CN 111401614A
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吕红霞
文迪
胡煜堃
潘金山
倪少权
李雪婷
张�杰
陈钉均
吕苗苗
陈韬
廖常宇
郭秀云
谢春
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Abstract

The invention relates to the technical field of urban rail transit, in particular to a dynamic passenger flow distribution method and system for urban rail transit. The method comprises the following steps: establishing an urban rail transit space-time service network; dividing a passenger travel path into a plurality of arc sections according to the behavior of passengers, and respectively constructing a generalized travel expense calculation model of the passengers in each arc section and a total generalized travel expense calculation model according to the state of the urban rail transit network in each time section; and judging the current state of the network according to the transport capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result. The method can be used for the dynamic passenger flow distribution problem of urban rail transit, the modeling process is convenient and simple, the modeling standard is unified, the method has high calculation efficiency, the method is real and reliable, and the method has good operability, universality and reusability.

Description

Dynamic passenger flow distribution method and system for urban rail transit
Technical Field
The invention relates to the technical field of urban rail transit, in particular to a dynamic passenger flow distribution method and system for urban rail transit.
Background
The urban rail transit dynamic passenger flow distribution is a passenger flow distribution method for dynamically distributing the road network passenger flow to the trains of each train number by combining the urban rail transit train schedule information and the dynamic road network passenger flow information, provides effective decision support and reference for road network passenger flow organization and urban rail transit operation, and is an important basis for realizing urban rail transit passenger guidance information distribution and passenger dynamic management. The dynamic passenger flow distribution of urban rail transit mainly needs to be solved: (1) analyzing the influence of the road network conveying capacity and the dynamic passenger flow density on the decision of the passenger travel path selection in the distribution process; (2) and (3) building a dynamic passenger flow distribution model of the urban rail transit in a smooth state and a congested state.
At present, dynamic passenger flow distribution of urban rail transit in China is mainly concentrated on dynamic passenger flow distribution under the condition of a normal operation road network, a space-time expansion network is established on a basis, the processing of passenger trip generalized cost calculation on perception cost is simple, and the constraint consideration on the road network conveying capacity in the flow distribution model establishment process is less.
The method comprises the steps that a space-time expansion service network is constructed by combining a graph theory method with an urban rail transit train schedule, the calculation description of sensing expenses in the calculation process of generalized expenses of passengers in traveling is insufficient, the crowdedness and the traveling time period cause the generation of the sensing expenses by influencing the psychological states of passengers, the sensing expenses under different road network service states have differences, and the prior art scheme is lack of the research on the difference of the sensing expenses;
in the process of constructing the dynamic passenger flow distribution model, the research on the influence of the transportation capacity constraint of the road network and the dynamic passenger flow density on the dynamic passenger flow distribution of the road network is less, the deviation exists between the dynamic passenger flow distribution model and the actual road network distribution rule, and a larger obstacle is formed for the application of the dynamic passenger flow distribution model in the actual production management.
Disclosure of Invention
The invention aims to provide a dynamic passenger flow distribution method and a dynamic passenger flow distribution system for urban rail transit, so as to solve the problems. In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in one aspect, the application provides a dynamic passenger flow distribution method for urban rail transit, which includes:
adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network, and establishing an urban rail transit time-space service network;
dividing a passenger travel path into a plurality of arc sections according to the behavior of passengers, and respectively constructing a generalized travel expense calculation model of the passengers in each arc section and a total generalized travel expense calculation model according to the state of the urban rail transit network in each time section;
and judging the current state of the network according to the transport capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
Optionally, the adding the time information of the urban rail transit train, the spatial information of the passenger travel path, and the time information of the passenger travel path into a physical network to establish an urban rail transit spatiotemporal service network includes:
according to the train timetable, adding the arrival time and departure time of each train at each station to the nodes of the abstract physical network to form a space-time network;
connecting the departure time of a preorder node of each shift of train and the arrival time of a posterior node under each urban rail transit line in a space-time network by using an arc section to form a running arc section of each shift of train;
the arrival time and the departure time of the same-class train on the same line on the same node in the network are connected by an arc section to form a stop arc section of the same-class train at the node, so that the space-time service network of the urban rail transit is constructed.
Optionally, the method further comprises:
and constructing a travel path of the passengers in the urban rail transit network.
Optionally, the constructing a travel path of the passenger in the urban rail transit network includes:
marking the station and time when the passenger enters the urban rail transit system on the time axis of the corresponding station;
connecting the station entering information marking point of the passenger with the departure time of the train on which the passenger takes to form an active arc section of the passenger at the departure station;
and sequentially connecting the space-time nodes representing all stations according to the stations and lines actually passed by the passengers until the passengers are out of the station.
The station and time when the passenger enters the urban rail transit system and the station and time when the passenger leaves the station can be obtained from AFC data.
Optionally, the method further comprises:
and distinguishing states of the urban rail transit network according to the transport capacity and the number of passenger flows, wherein the states comprise a smooth state, a congestion state and an interruption state.
Optionally, the dividing the passenger travel route into a plurality of arc segments according to the behavior of the passenger, and respectively constructing a generalized travel cost calculation model of the passenger in each arc segment and a total generalized travel cost calculation model according to the state of the urban rail transit network in each time period, includes:
constructing a generalized travel expense calculation model of a passenger inbound walking arc and a generalized travel expense calculation model of a passenger outbound walking arc;
constructing a generalized travel expense calculation model of a passenger in a vehicle travel arc;
constructing a generalized travel cost calculation model of a passenger platform waiting arc, wherein the generalized travel cost calculation model of the passenger platform waiting arc comprises a generalized travel cost calculation model of a smooth-state passenger platform waiting arc and a generalized travel cost calculation model of a blocked-state passenger platform waiting arc;
constructing a generalized travel expense calculation model of a passenger transfer walking arc;
and constructing a passenger total generalized travel expense calculation model which comprises a general generalized travel expense calculation model in a smooth state and a general generalized travel expense calculation model in a congestion state.
Optionally, the generalized travel cost calculation model for the inbound walking arc and the generalized travel cost calculation model for the outbound walking arc respectively include a formula (1) and a formula (2):
Figure BDA0002404687980000041
Figure BDA0002404687980000042
in the formula (1) and the formula (2),
Figure BDA0002404687980000043
when the travel time period is g, the generalized travel cost of the passengers for entering the station and traveling the arc at the station i; t isi-inThe station-entering time of passengers at station i;
Figure BDA0002404687980000044
the station congestion degree of the station i in the g time period can be obtained from passenger flow density observation data in the station;
Figure BDA0002404687980000045
when the trip time period is g, the generalized trip cost of the trip arc of the passenger at the station j is reached; t isj-outThe outbound time of the passenger at the j station;
the generalized travel expense calculation model of the vehicle travel arc comprises a formula (3), a formula (4), a formula (5), a formula (6) and a formula (7);
Figure BDA0002404687980000046
Figure BDA0002404687980000047
Figure BDA0002404687980000048
Figure BDA0002404687980000049
Figure BDA00024046879800000410
in formula (3), formula (4), formula (5), formula (6) and formula (7), Tij-lkThe time from the station i to the station j of the kth train on the passenger riding line l;
Figure BDA00024046879800000411
the arrival time of the kth train at the j station of the rail transit line l;
Figure BDA00024046879800000412
the arrival time of the kth train at the station i of the rail transit line l;
Figure BDA00024046879800000413
the congestion degree of the carriage of the kth train on the line l between the station i and the station (i +1) at the time t;
Figure BDA0002404687980000051
at the time t, the load capacity of the kth train on the line l between the station i and the station (i +1) is obtained; y islThe passenger capacity of the train seat of the urban rail transit line l can be served; zlThe maximum load of the train of the line l, α and β are correction coefficients of a calculation formula of the degree of congestion of the train, and YlkThe passenger capacity which can be served by the kth train seat of the urban rail transit line l;
Figure BDA0002404687980000052
at the time t, the passengers take the generalized fare of the on-train travel arc of the kth train of the urban rail transit line l from the station i to the next station ((i +1) station) adjacent to the station i;
Figure BDA0002404687980000053
the departure time of the kth train on the station i of the rail transit line l;
the generalized cost of the train traveling arc of the k-th train of the passenger on the urban rail transit line l from the station i to the station (i +1) next to the station is that the k-th train of the passenger on the urban rail transit line l from the station i to the station (i +1) next to the stationTravel time T of passenger in vehiclei(i+1)-lkAdding extra sensing cost of the train caused by the congestion degree of the train on the line l in the current time period, wherein the sensing cost calculation formula is the travel time of the passenger on the train multiplied by the time of the passenger getting on the train
Figure BDA0002404687980000054
Coefficient of congestion of passenger train
Figure BDA0002404687980000055
The correction coefficient set for reducing the system error can be determined by actual road network data investigation or simulation.
In the Chongqing rail transit network passenger flow distribution in the embodiment, the people can use the method
Figure BDA0002404687980000056
When the correction coefficient α is 0.11, when
Figure BDA0002404687980000057
When the correction coefficient α is 0.12, β is 0.13.
The generalized trip expense calculation model of the unblocked state passenger platform waiting arc and the generalized trip expense calculation model of the blocked state passenger platform waiting arc respectively comprise a formula (8) and a formula (9):
Figure BDA0002404687980000058
Figure BDA0002404687980000059
Figure BDA0002404687980000061
the generalized trip cost of the smooth-state passenger waiting for the arc at the platform of the station i when the trip time period g is reached;
Figure BDA0002404687980000062
for a trip periodg, the general trip cost of the passengers waiting for the arc at the station platform of the station i in the congestion state is calculated;
Figure BDA0002404687980000063
the departure interval of the line l; g is the number of trains which are required by passengers going out in the period g on average;
the generalized travel expense calculation model of the passenger transfer walking arc comprises a formula (12):
Figure BDA0002404687980000064
in the formula (12), the first and second groups,
Figure BDA0002404687980000065
when the travel time is g, the passengers change the generalized cost of the traveling arc at the h station; t ish-transferThe travel time of passengers for transfer at the h station of the transfer station; h is a certain transfer station of the urban rail transit;
the general generalized travel cost calculation model for the unblocked state and the general generalized travel cost calculation model for the congested state respectively include a formula (13) and a formula (14):
Figure BDA0002404687980000066
Figure BDA0002404687980000067
in the formulas (13) and (14), CclearRepresenting the total generalized travel cost of passengers from station i to station j; cjamRepresenting the total generalized travel fare of passengers from station i to station j.
Optionally, the clear status may be determined by equation (10):
Abilityg≥Numg(10)
the congestion state can be determined by equation (11):
Abilityg<Numg(11)
equation (10) and equation(11) In (1), AbilitygThe transport capacity of the rail transit network is a time period g; numgThe time period is the passenger flow of the rail transit network.
Optionally, the determining a current state of the network according to the transportation capacity of the network, calculating a generalized travel cost of the passenger according to the generalized travel cost calculation model, and allocating the passenger flow according to the network state and the generalized travel cost includes:
inputting physical network data and passenger flow data at the current moment;
judging whether the space-time service network is interrupted at the current moment or not through effective path search;
if the interruption exists, updating the time-space service network data, and after updating, continuously judging whether the time-space service network is interrupted;
if the interruption does not exist, judging the state of the current road network according to whether the transport capacity meets the passenger flow requirement or not;
if the road network transport capacity meets the passenger flow demand, calculating the generalized travel cost of the passengers in the unblocked network in the current time period, and performing passenger flow distribution by using a logit model;
if the transportation capacity of the road network is not enough to meet the passenger flow demand, the passenger flow is averagely decomposed into 3 sub-tables, the generalized travel cost of the passengers in the time period is calculated, the passenger flow of the first sub-table is distributed, the travel cost is recalculated on the basis of the distribution of the first sub-table until the distribution of all the passenger flows is completed, and the passenger flow distribution amount of each time is accumulated to obtain the passenger flow distribution amount of each road section at the current time;
and updating the road network information and the passenger flow data at the next moment, repeating the steps, and accumulating the obtained results after the passenger flow distribution at all the moments is completed to obtain the passenger flow distribution result of the road network.
In another aspect, the present invention provides a dynamic passenger flow distribution system for urban rail transit, the system comprising:
the network construction module is used for adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network and establishing an urban rail transit space-time service network;
the modeling module is used for dividing a passenger travel path into a plurality of arc sections according to the behavior of the passenger, and respectively constructing a generalized travel cost calculation model of the passenger in each arc section and a total generalized travel cost calculation model according to the state of the urban rail transit network in each time period;
and the passenger flow distribution module is used for judging the current state of the network according to the transportation capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
The invention has the beneficial effects that:
the invention combines the urban rail transit network and the train schedule information, establishes a space-time expansion service network, and distinguishes the calculation method of the generalized travel cost of passengers under the unblocked state and the congested state; capacity limitation is set through road network conveying capacity constraint, a logic passenger flow distribution model is built in a batch loading mode, travel expenses are dynamically corrected, and a solution algorithm is designed to achieve dynamic passenger flow distribution. The method can be used for the dynamic passenger flow distribution problem of urban rail transit, the modeling process is convenient and simple, the modeling standard is unified, the method has high calculation efficiency, the method is real and reliable, and the method has good operability, universality and reusability.
The method fully considers the influence of congestion degree and travel time period on the calculation of the generalized travel cost of passengers, constructs different dynamic passenger flow distribution models based on the state of the urban rail transit service network, constructs L g-grid models and algorithms based on capacity limitation and batch loading, fully embodies the constraint effect of capacity limitation conditions in an actual road network on the dynamic passenger flow distribution process, has better universality, and meets the dynamic passenger flow distribution requirements of urban rail transit road networks with different characteristics.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flow chart of a dynamic passenger flow distribution method for urban rail transit according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a spatiotemporal service network of urban rail transit according to an embodiment of the present invention;
FIG. 3 is a detailed flowchart of step S30 according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating an upstream passenger flow distribution scenario in an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating an upstream passenger flow distribution scenario in an embodiment of the present invention;
fig. 6 is a block diagram of a dynamic passenger flow distribution system for urban rail transit according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
The terms referred to in the examples of the present invention:
OD passenger flow: the passenger quantity between the initial station and the final station in the urban rail transit network can be obtained through data in an automatic fare collection system (AFC) of urban rail transit, and can be used for the research of problems such as passenger travel behavior analysis, passenger flow prediction, passenger flow distribution and the like.
Road network transmission capacity: under certain operation conditions (without unreasonable delay, danger or limitation), the maximum number of passengers capable of being borne by the urban rail transit network in one direction in unit time depends on the number of operation trains, the length of the trains, the load standard of the trains, the difference of the requirements of the passengers between the trains and between different carriages of the same train and the like.
A train timetable: the method is a table for expressing the arrival, departure or passing time of a train at an urban rail transit station and the stopping time at a stop, the compilation of the table is based on a train operation diagram, and the table is a tabulation of the operation diagram and has various forms according to different use objects and use occasions, such as use by passengers or use by railway staff; for reading at hand or for posting announcements, etc., and some timetables also show the mileage between stations.
Space-time expansion service network: the graph theory is a branch of operations and research with wide application, and is widely applied in various fields such as physics, chemistry, cybernetics, transportation and the like. The method comprises the steps of describing an urban rail transit road network by using a network topological structure model, adding time information of an urban rail transit train and spatial information and time information of a passenger travel path into an abstract network topological structure, enabling nodes and arc sections in the network to have time attributes, and reflecting spatial positions and time states of passengers in the road network in the network.
The generalized trip cost of passengers: the generalized expenses of passengers traveling on urban rail transit mainly include the expenses of travel time, the expenditure of money expenses and the perception expenses brought by crowding degree, travel time and the like. Because the fare of urban rail transit is relatively low and the difference is not large, the influence of the fare on the travel of passengers is not considered. The cost of travel time is mainly generated from each arc section on the travel path of the passengers. The degree of congestion and the travel time interval are mainly used for additionally increasing the travel burden of the passengers by influencing the psychological states of the passengers, and the burden is called as the perception cost.
The passenger flow distribution model is characterized by comprising L g-bit models, wherein the g-bit models are one of discrete selection method models, the L g-bit models are the earliest discrete selection models and are the most widely applied models at present, and the g-bit models are common methods for statistical empirical analysis of sociology, biometry, clinic, quantity psychology, metrology, marketing and the like.
In one aspect, as shown in fig. 1, the present embodiment provides a dynamic passenger flow distribution method for urban rail transit, where the method includes step S10, step S20, and step S30.
S10, adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network, and establishing an urban rail transit space-time service network;
s20, dividing a passenger travel path into a plurality of arc sections according to the behavior of the passenger, and respectively constructing a generalized travel cost calculation model of the passenger in each arc section and a total generalized travel cost calculation model according to the state of the urban rail transit network in each time section;
and S30, judging the current state of the network according to the transportation capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
Optionally, step S10 may further include step S101, step S102, and step S103.
S101, adding the arrival time and departure time of each train at each station to nodes of an abstract physical network according to a train schedule to form a space-time network;
s102, connecting the departure time of a preamble node of each train in each shift under each urban rail transit line in the space-time network with the arrival time of a subsequent node by using an arc section to form a running arc section of each train in each shift;
and S103, connecting the arrival time and the departure time of the same-class train on the same line on the same node in the network by using an arc section to form a stop arc section of the same-class train on the node, so that the space-time service network of the urban rail transit is constructed.
Optionally, a step S11 may be further included between the step S10 and the step S20.
And S11, constructing a travel path of the passenger in the urban rail transit network.
Optionally, step S11 may further include step S111, step S112, and step S113.
S111, marking the station and time when the passenger enters the urban rail transit system on the time axis of the corresponding station;
s112, connecting the station entering information marking point of the passenger with the departure time of the train on which the passenger takes to form an active arc section of the passenger at the departure station;
and S113, sequentially connecting the space-time nodes representing all stations according to the stations and lines actually passed by the passengers until the passengers are out of the station.
The station and time when the passenger enters the urban rail transit system and the station and time when the passenger leaves the station can be obtained from AFC data.
The expanded urban rail transit space-time service network is represented by a graph G (N, L, E, D, T), wherein N represents a set of urban rail transit station space-time nodes, L represents a set of urban rail transit lines, E represents a set of travel arcs of passengers in the urban rail transit network, D represents a set of urban rail transit line sections (physical connection between adjacent stations), and T represents a set of moments.
In the schematic diagram of the urban rail transit space-time service network shown in fig. 2, a passenger goes from station a to station E, and his travel route in the urban rail transit network is described as follows: passengers enter the station A from the station-entering gate of the station A at 8:42 minutes, then walk to the platform, ride the train with the urban rail transit number X and the train number 1 at 8:57 minutes, and arrive at the station C to transfer to the urban rail transit number Y. Assuming that the time required for the passenger to transfer from the line X to the line Y at the station C is 6 minutes, the passenger cannot take the line Y of the urban rail transit with the number 1. Therefore, passengers have to wait for 9:04 minutes to ride the train with the train number 2 on the line with the line number Y at the platform of the station C to reach the station E at 9:14 minutes. Finally, the station E is connected with the station E through a connecting device at a ratio of 9:18, and the station E is separated from the station E by an outbound gate.
Optionally, before the step S10, a step S12 may be further included.
And step S12, distinguishing the states of the urban rail transit network according to the transport capacity and the passenger flow quantity, wherein the states comprise a smooth state, a congestion state and an interruption state.
Optionally, step S20 may further include step S201, step S202, step S203, step S204, and step S205.
S201, constructing a generalized travel expense calculation model of a passenger inbound walking arc and a generalized travel expense calculation model of a passenger outbound walking arc;
the method comprises the following steps that passengers can generate in-and-out generalized travel expenses on an in-station travel arc and an out-station travel arc, the in-station expenses and the out-station expenses are composed of passenger travel time and perception expenses caused by crowdedness of the current time period of a station, the in-station, out-station and station crowding coefficients are integrated, the crowding coefficients are included in calculation of the in-station travel expense and the out-station travel expense, and a generalized travel expense calculation model of the in-station travel arc and a generalized travel expense calculation model of the out-station travel arc respectively comprise a formula (1) and a formula (2):
Figure BDA0002404687980000131
Figure BDA0002404687980000132
in the formula (1) and the formula (2),
Figure BDA0002404687980000133
when the travel time period is g, the generalized travel cost of the passengers for entering the station and traveling the arc at the station i; t isi-inThe station-entering time of passengers at station i;
Figure BDA0002404687980000134
the station congestion degree of the station i in the g time period can be obtained from passenger flow density observation data in the station;
Figure BDA0002404687980000135
when the trip time period is g, the generalized trip cost of the trip arc of the passenger at the station j is reached; t isj-outThe time of departure of the passenger at station j.
S202, constructing a generalized travel expense calculation model of a passenger in-vehicle travel arc;
the generalized travel expense calculation model of the vehicle travel arc comprises a formula (3), a formula (4), a formula (5), a formula (6) and a formula (7);
the generalized travel cost of the passenger in the vehicle travel arc is mainly determined by a starting station and an end station of the passenger, the arrival time and departure time of the train at the stations can be directly obtained from the timetable, and the travel time of the passenger in the vehicle can be calculated.
Figure BDA0002404687980000141
And calculating the extra sensing cost of the passengers on the train caused by the congestion degree of the train on the line l in the current time period in different travel time periods by using the carriage congestion coefficient.
When the number of passengers is less than the number of seats, calculating the congestion coefficient of the train carriages of two adjacent stations of the urban rail transit:
Figure BDA0002404687980000142
when the number of passengers is larger than the number of seats and is smaller than the maximum load, calculating the congestion coefficient of the carriages of two adjacent trains of the urban rail transit:
Figure BDA0002404687980000143
when the number of passengers is larger than the maximum load, calculating the congestion degree coefficient of the train carriages of two adjacent stations of the urban rail transit:
Figure BDA0002404687980000144
since the traffic congestion coefficient of the train where the passenger is located changes along with the travel, the generalized cost of each section needs to be calculated one by one. And calculating the generalized travel expense of the on-train travel arc of the k-th train of the passenger on the urban rail transit line l from the station i to the station ((i +1) station) next to the station i at the time t.
Figure BDA0002404687980000145
In formula (3), formula (4), formula (5), formula (6) and formula (7), Tij-lkThe time from the station i to the station j of the kth train on the passenger riding line l;
Figure BDA0002404687980000146
the arrival time of the kth train at the j station of the rail transit line l;
Figure BDA0002404687980000151
the arrival time of the kth train at the station i of the rail transit line l;
Figure BDA0002404687980000152
the congestion degree of the carriage of the kth train on the line l between the station i and the station (i +1) at the time t;
Figure BDA0002404687980000153
at the time t, the load capacity of the kth train on the line l between the station i and the station (i +1) is obtained; y islThe passenger capacity of the train seat of the urban rail transit line l can be served; zlThe maximum load of the train of the line l, α and β are correction coefficients of a calculation formula of the degree of congestion of the train, and YlkThe passenger capacity which can be served by the kth train seat of the urban rail transit line l;
Figure BDA0002404687980000154
at the time t, the passengers take the generalized fare of the on-train travel arc of the kth train of the urban rail transit line l from the station i to the next station ((i +1) station) adjacent to the station i;
Figure BDA0002404687980000155
the departure time of the kth train on the station i of the rail transit line l;
the generalized fare of the travel arc of the passenger on the train from the station i to the station (i +1) next to the station when the passenger takes the kth train of the urban rail transit line l is the travel time T of the passenger on the train when the passenger takes the kth train from the station i to the station (i +1) next to the station when the passenger takes the urban rail transit line li(i+1)-lkAdding extra sensing cost of the train caused by the congestion degree of the train on the line l in the current time period, wherein the sensing cost calculation formula is the travel time of the passenger on the train multiplied by the time of the passenger getting on the train
Figure BDA0002404687980000156
Coefficient of congestion of passenger train
Figure BDA0002404687980000157
The correction coefficient set for reducing the system error can be determined by actual road network data investigation or simulation.
Chongqing track in this embodimentIn traffic network passenger flow distribution
Figure BDA0002404687980000158
When the correction coefficient α is 0.11, when
Figure BDA0002404687980000159
When the correction coefficient α is 0.12, β is 0.13.
S203, constructing a generalized travel cost calculation model of the passenger platform waiting arc, wherein the generalized travel cost calculation model of the passenger platform waiting arc comprises a generalized travel cost calculation model of the smooth-state passenger platform waiting arc and a generalized travel cost calculation model of the blocked-state passenger platform waiting arc;
the waiting arc at the platform of the passenger can generate the trip cost of the passenger waiting for the train at the platform, and is determined by the waiting time of the passenger at the platform and the number of the passengers waiting for the train. Therefore, it is necessary to distinguish the state of the network from each other according to the time period.
The generalized trip expense calculation model of the unblocked state passenger platform waiting arc and the generalized trip expense calculation model of the blocked state passenger platform waiting arc respectively comprise a formula (8) and a formula (9):
Figure BDA0002404687980000161
Figure BDA0002404687980000162
Figure BDA0002404687980000163
the generalized trip cost of the smooth-state passenger waiting for the arc at the platform of the station i when the trip time period g is reached;
Figure BDA0002404687980000164
when the time period is a trip time period g, the general trip cost of the passengers waiting for the arc at the station platform of the station i in the congestion state is provided;
Figure BDA0002404687980000165
the departure interval of the line l; g is the number of trains which are required by passengers going out in the period g on average.
S204, constructing a generalized travel expense calculation model of the passenger transfer walking arc;
the generalized travel cost of passengers in the transfer walking process can be generated on the passenger transfer walking arc, and the transfer cost is composed of the passenger transfer walking time and the perception cost caused by the crowdedness of the current time of the station. Passengers can also be influenced by the congestion degree of the current time period of the station when the passengers change the station;
the generalized travel expense calculation model of the passenger transfer walking arc comprises a formula (12):
Figure BDA0002404687980000166
in the formula (12), the first and second groups,
Figure BDA0002404687980000167
when the travel time is g, the passengers change the generalized cost of the traveling arc at the h station; t ish-transferThe travel time of passengers for transfer at the h station of the transfer station; h is a certain transfer station of the urban rail transit.
And S205, constructing a total generalized travel expense calculation model of the passenger, wherein the total generalized travel expense calculation model of the passenger comprises a total generalized travel expense calculation model in a smooth state and a total generalized travel expense calculation model in a congestion state.
The general generalized travel cost calculation model for the unblocked state and the general generalized travel cost calculation model for the congested state respectively include a formula (13) and a formula (14):
Figure BDA0002404687980000172
Figure BDA0002404687980000171
in the formulas (13) and (14), CclearRepresenting passengers from station i to station jTotal generalized trip cost of the station; cjamRepresenting the total generalized travel fare of passengers from station i to station j.
Optionally, the clear status may be determined by equation (10):
Abilityg≥Numg(10)
the congestion state can be determined by equation (11):
Abilityg<Numg(11)
in the formula (10) and the formula (11), AbilitygThe transport capacity of the rail transit network is a time period g; numgThe time period is the passenger flow of the rail transit network.
Optionally, as shown in fig. 3, step S30 may further include step S301, step S302, step S303, step S304, step S305, step S306, and step S307.
S301, inputting physical network data and passenger flow data at the current moment;
s302, judging whether the space-time service network is interrupted at the current moment through effective path search;
step S303, if the interruption exists, updating the spatio-temporal service network data, and after updating, continuously repeating the step S302 to judge whether the spatio-temporal service network is interrupted;
s304, if the interruption does not exist, judging the state of the current road network according to whether the transport capacity meets the passenger flow requirement or not;
s305, if the road network conveying capacity meets the passenger flow requirement, calculating the generalized travel cost of the passengers in the smooth network in the current time period, and performing passenger flow distribution by using a logic model;
s306, if the transportation capacity of the road network is not enough to meet the passenger flow demand, the passenger flow is averagely decomposed into 3 sub-tables, the generalized travel cost of the passengers in the time period is calculated, the passenger flow of the first sub-table is distributed, the travel cost is recalculated on the basis of the distribution of the first sub-table until the distribution of all the passenger flows is completed, and the passenger flow distribution amount of each time is accumulated to obtain the passenger flow distribution amount of each road section at the current time;
and S307, updating road network information and passenger flow data at the next moment, repeating the steps, and accumulating the obtained results after the passenger flow distribution at all the moments is completed to obtain the passenger flow distribution result of the road network.
In the urban rail transit network, not all communication paths have passenger flow distribution, and some paths have no passenger selection due to too large impedance and low utility value, so that only paths reaching a certain utility value are effective paths. The effective path search is carried out in the passenger flow distribution process of urban rail transit, the path which is not considered by the passenger to be selected can be eliminated, and the effective path which can be selected by the passenger in the traveling process can be screened out.
The urban rail transit network is a dynamically changing system, and the states of the road network and passengers can change along with the change of the network structure, the traveling situation of the passengers or some emergencies. The state of the urban rail transit space-time service network is divided into a smooth state, a congestion state and an interruption state.
(1) Unblocked state
The unblocked state of the urban rail transit network means that the rail transit network can completely meet the requirements of passengers entering the urban rail transit network, and means that the passengers can get on the first arriving train when entering the station from any station and arriving at the station.
(2) Congestion status
When the urban rail transit network is in a congestion state, the phenomenon that passengers stay on the platform occurs, namely the passengers need to wait for two or more trains on the platform to get on the train. This situation often occurs during holidays or during periods of high traffic, such as early and late peaks.
(3) Interrupt state
The interruption state of the urban rail transit network refers to section interruption or line interruption caused by physical layer factors such as lines, stations, sections, facility equipment and the like, so that passengers cannot select the lines for traveling.
From the operation condition of rail transit, because the first and last buses of different subway lines have different time, the departure and the receiving stages can occur every day, and some lines and intervals on the urban rail transit network have no train operation, so that the structure of a road network is changed, and the trip selection of passengers is influenced.
In addition, emergencies, major events and holidays can significantly increase passengers at some stations. Often, these stations will take restriction or guidance measures to control the passenger flow in the station within a certain range, and at the same time, the trains are switched on or the running time of the trains is prolonged, so that the passengers staying at the station are reduced.
The urban rail transit dynamic passenger flow distribution method of the technology provided by the embodiment of the invention is illustrated by taking an urban rail transit network formed by a Chongqing rail transit line 1, a Chongqing rail transit line 3 and a Chongqing rail transit line 10 as an example. According to the actual operation situation and historical research of the track traffic of the Chongqing, the following parameters are regulated: each trip time period g is set as 1h (60 min); passenger quantity Y capable of being served by number 1 linear train seat1240, maximum load Z11880; passenger quantity Y capable of being served by No. 3 line 6 marshalling train seats3170, maximum load Z31340, 8 passenger numbers Y that a consist can serve3240, maximum load Z31800; passenger quantity Y capable of being served by number 10 line train seat10280, maximum load Z102322; when in use
Figure BDA0002404687980000191
When the correction coefficient α is 0.11, when
Figure BDA0002404687980000192
The correction coefficient α is 0.12, β is 0.13, and the departure intervals of different lines are convenient for calculation
Figure BDA0002404687980000201
The method is characterized in that the time is 5min in the smooth state (peak-off period) of the network, the time is 3min in the congestion state (peak-off period), and the departure frequency is
Figure BDA0002404687980000202
Is the reciprocal thereof; congestion degree coefficient of station
Figure BDA0002404687980000203
Taking 1.2 in the unblocked state of the network and taking 2.5 in the congested state; the parameter θ in the logit model is taken to be 3.3.
In the embodiment, passenger flow data of 8: 00-9: 00 at a certain day of 2018 in 9 months of Chongqing rail transit are used for passenger flow distribution, in the travel time period, the transport capacity of a rail transit network is smaller than the number of passengers, the network is in a congestion state, the number of passengers needs to be more than 1.7 on average, the passenger flow can be distributed in 3 batches, after the distribution is finished each time, the generalized travel cost of the passengers in each interval is recalculated according to the existing distribution amount of each interval in the network, next distribution is carried out, and the distribution results of three times are accumulated, so that the distribution conditions of the passenger flow in each interval in the uplink and downlink directions of three rail transit lines in the time period of the images 4 and 5 are obtained. According to the regulations of national standards of the people's republic of China (GB50157-2013) subway design specifications on the ascending and descending of subways, a south-north line is operated from south to north as an ascending direction and from north to south as a descending direction. The east-west line runs upward from west to east and downward from east to west. The ascending direction in this study is "steeply pitched-small assorted letter", "fish hole-lifting dam" and "carp pool-king house", and the opposite train running direction is the descending direction.
In the process of distributing passenger flows in batches, because the generalized travel expenses of passengers are recalculated after each distribution, the number of passengers distributed to stations with passenger flows exceeding the capacity and the corresponding sections of the stations is reduced along with the increase of the distribution times, such as sections of 'magnet mouths-gun tombs', 'gun tombs-poplar highway bridges', 'poplar highway bridges-sand terrace dams' of No. 1 line of rail transit and sections of 'two mouths-cattle horns tuo', 'cattle horns tuo-kwan bridges' and 'kwan-yin bridges-red flag ditches' of No. 3 line. The number of passengers distributed for the first time in the section of the "roaster tomb-Yangguan bridge" is 4570, 3884 and 2971, and it can be seen that due to insufficient network capacity, the travel cost in the congested section is increased, the number of the distributed passengers is gradually reduced, meanwhile, the number of the passengers distributed in the relatively smooth section is increased along with the increase of the distribution times, and the passengers select to get on the train from other stations to go to the destination, which accords with the selection of the travel scheme made by the passengers on the dynamic change of the rail transit network in the congested state. If it is necessary to assign the passenger flows for a plurality of consecutive time periods, the step in step S30 is simply repeated.
On the other hand, as shown in fig. 6, the present embodiment provides a dynamic passenger flow distribution system for urban rail transit, the system includes:
the network construction module 41 is used for adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network, and establishing an urban rail transit space-time service network;
the modeling module 42 is used for dividing the travel path of the passenger into a plurality of arc sections according to the behavior of the passenger, and respectively constructing a generalized travel cost calculation model of the passenger in each arc section and a total generalized travel cost calculation model according to the state of the urban rail transit network in each time period;
and the passenger flow distribution module 43 is configured to judge a current state of the network according to the transportation capacity of the network, calculate a generalized travel cost of the passenger according to the generalized travel cost calculation model, and distribute the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
Optionally, the system may further include a path construction module 44.
And the path construction module 44 is used for constructing the traveling path of the passengers in the urban rail transit network.
Optionally, the system may further include a status determination module 45.
And the state judgment module 45 is used for distinguishing states of the urban rail transit network according to the transport capacity and the passenger flow number, wherein the states comprise a smooth state, a congestion state and an interruption state.
Optionally, the network building module 41 may be further configured to:
according to the train timetable, adding the arrival time and departure time of each train at each station to the nodes of the abstract physical network to form a space-time network;
connecting the departure time of a preorder node of each shift of train and the arrival time of a posterior node under each urban rail transit line in a space-time network by using an arc section to form a running arc section of each shift of train;
the arrival time and departure time of the same train on the same line on the same node in the network are connected by an arc section to form a stop arc section of the train on the node.
Optionally, the path building module 44 may be further configured to:
marking the station and time when the passenger enters the urban rail transit system on the time axis of the corresponding station;
connecting the station entering information marking point of the passenger with the departure time of the train on which the passenger takes to form an active arc section of the passenger at the departure station;
and sequentially connecting the space-time nodes representing all stations according to the stations and lines actually passed by the passengers until the passengers are out of the station.
Optionally, the modeling module 42 may be further configured to:
constructing a generalized travel expense calculation model of a passenger inbound walking arc and a generalized travel expense calculation model of a passenger outbound walking arc;
constructing a generalized travel expense calculation model of a passenger in a vehicle travel arc;
constructing a generalized travel cost calculation model of a passenger platform waiting arc, wherein the generalized travel cost calculation model of the passenger platform waiting arc comprises a generalized travel cost calculation model of a smooth-state passenger platform waiting arc and a generalized travel cost calculation model of a blocked-state passenger platform waiting arc;
constructing a generalized travel expense calculation model of a passenger transfer walking arc;
and constructing a passenger total generalized travel expense calculation model which comprises a general generalized travel expense calculation model in a smooth state and a general generalized travel expense calculation model in a congestion state.
Optionally, the passenger flow distribution module 43 may be further configured to:
inputting physical network data and passenger flow data at the current moment;
judging whether the space-time service network is interrupted at the current moment;
if the interruption exists, updating the time-space service network data, and after updating, continuously judging whether the time-space service network is interrupted;
if the interruption does not exist, judging the state of the current road network according to whether the transport capacity meets the passenger flow requirement or not;
if the road network transport capacity meets the passenger flow demand, calculating the generalized travel cost of the passengers in the unblocked network in the current time period, and performing passenger flow distribution by using a logit model;
if the transportation capacity of the road network is not enough to meet the passenger flow demand, the passenger flow is averagely decomposed into 3 sub-tables, the generalized travel cost of the passengers in the time period is calculated, the passenger flow of the first sub-table is distributed, the travel cost is recalculated on the basis of the distribution of the first sub-table until the distribution of all the passenger flows is completed, and the passenger flow distribution amount of each time is accumulated to obtain the passenger flow distribution amount of each road section at the current time;
and updating the road network information and the passenger flow data at the next moment, repeating the steps, and accumulating the obtained results after the passenger flow distribution at all the moments is completed to obtain the passenger flow distribution result of the road network.
The implementation principle and the generated technical effect of the dynamic passenger flow distribution system for urban rail transit provided by the embodiment of the invention are the same as those of the embodiment of the dynamic passenger flow distribution method for urban rail transit, and for the sake of brief description, corresponding contents in the embodiment of the dynamic passenger flow distribution method for urban rail transit can be referred to where the embodiment of the dynamic passenger flow distribution system for urban rail transit is not mentioned.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, for example, in which flow charts and block diagrams illustrate systems and methods according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (10)

1. A dynamic passenger flow distribution method for urban rail transit is characterized by comprising the following steps:
adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network, and establishing an urban rail transit time-space service network;
dividing a passenger travel path into a plurality of arc sections according to the behavior of passengers, and respectively constructing a generalized travel expense calculation model of the passengers in each arc section and a total generalized travel expense calculation model according to the state of the urban rail transit network in each time section;
and judging the current state of the network according to the transport capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
2. The method according to claim 1, wherein the step of adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network to establish an urban rail transit spatiotemporal service network comprises:
according to the train timetable, adding the arrival time and departure time of each train at each station to the nodes of the abstract physical network to form a space-time network;
connecting the departure time of a preorder node of each shift of train and the arrival time of a posterior node under each urban rail transit line in a space-time network by using an arc section to form a running arc section of each shift of train;
the arrival time and departure time of the same train on the same line on the same node in the network are connected by an arc section to form a stop arc section of the train on the node.
3. The method for dynamic urban rail transit passenger flow distribution according to claim 1, wherein the method further comprises:
and constructing a travel path of the passengers in the urban rail transit network.
4. The urban rail transit dynamic passenger flow distribution method according to claim 3, wherein the constructing of the travel path of the passengers in the urban rail transit network comprises:
marking the station and time when the passenger enters the urban rail transit system on the time axis of the corresponding station;
connecting the station entering information marking point of the passenger with the departure time of the train on which the passenger takes to form an active arc section of the passenger at the departure station;
and sequentially connecting the space-time nodes representing all stations according to the stations and lines actually passed by the passengers until the passengers are out of the station.
5. The method for dynamic urban rail transit passenger flow distribution according to claim 1, wherein the method further comprises:
and distinguishing states of the urban rail transit network according to the transport capacity and the number of passenger flows, wherein the states comprise a smooth state, a congestion state and an interruption state.
6. The method according to claim 1, wherein the method for allocating dynamic passenger flow in urban rail transit divides a passenger travel route into a plurality of arc sections according to the behavior of the passenger, and respectively constructs a generalized travel cost calculation model and a total generalized travel cost calculation model of the passenger in each arc section according to the state of the urban rail transit network in each time period, and comprises the following steps:
constructing a generalized travel expense calculation model of a passenger inbound walking arc and a generalized travel expense calculation model of a passenger outbound walking arc;
constructing a generalized travel expense calculation model of a passenger in a vehicle travel arc;
constructing a generalized travel cost calculation model of a passenger platform waiting arc, wherein the generalized travel cost calculation model of the passenger platform waiting arc comprises a generalized travel cost calculation model of a smooth-state passenger platform waiting arc and a generalized travel cost calculation model of a blocked-state passenger platform waiting arc;
constructing a generalized travel expense calculation model of a passenger transfer walking arc;
and constructing a passenger total generalized travel expense calculation model which comprises a general generalized travel expense calculation model in a smooth state and a general generalized travel expense calculation model in a congestion state.
7. The urban rail transit dynamic passenger flow distribution method according to claim 6, characterized in that:
the generalized travel expense calculation model of the inbound walking arc and the generalized travel expense calculation model of the outbound walking arc respectively comprise a formula (1) and a formula (2):
Figure FDA0002404687970000031
Figure FDA0002404687970000032
in the formula (1) and the formula (2),
Figure FDA0002404687970000033
when the travel time period is g, the generalized travel cost of the passengers for entering the station and traveling the arc at the station i; t isi-inThe station-entering time of passengers at station i;
Figure FDA0002404687970000034
the station congestion degree of the station i in the g period;
Figure FDA0002404687970000035
when the trip time period is g, the generalized trip cost of the trip arc of the passenger at the station j is reached; t isj-outThe outbound time of the passenger at the j station;
the generalized travel expense calculation model of the vehicle travel arc comprises a formula (3), a formula (4), a formula (5), a formula (6) and a formula (7);
Figure FDA0002404687970000036
Figure FDA0002404687970000037
Figure FDA0002404687970000038
Figure FDA0002404687970000039
Figure FDA00024046879700000310
in formula (3), formula (4), formula (5), formula (6) and formula (7), Tij-lkThe time from the station i to the station j of the kth train on the passenger riding line l;
Figure FDA0002404687970000041
the arrival time of the kth train at the j station of the rail transit line l;
Figure FDA0002404687970000042
the arrival time of the kth train at the station i of the rail transit line l;
Figure FDA0002404687970000043
the congestion degree of the carriage of the kth train on the line l between the station i and the station (i +1) at the time t;
Figure FDA0002404687970000044
at the time t, the load capacity of the kth train on the line l between the station i and the station (i +1) is obtained; y islThe passenger capacity of the train seat of the urban rail transit line l can be served; zlThe maximum load of the train of the line l, α and β are correction coefficients of a calculation formula of the degree of congestion of the train, and YlkThe passenger capacity which can be served by the kth train seat of the urban rail transit line l;
Figure FDA0002404687970000045
at the time t, the passengers take the generalized fare of the on-train travel arc of the kth train of the urban rail transit line l from the station i to the next station ((i +1) station) adjacent to the station i;
Figure FDA0002404687970000046
the departure time of the kth train on the station i of the rail transit line l;
the generalized trip expense calculation model of the unblocked state passenger platform waiting arc and the generalized trip expense calculation model of the blocked state passenger platform waiting arc respectively comprise a formula (8) and a formula (9):
Figure FDA0002404687970000047
Figure FDA0002404687970000048
Figure FDA0002404687970000049
the generalized trip cost of the smooth-state passenger waiting for the arc at the platform of the station i when the trip time period g is reached;
Figure FDA00024046879700000410
when the time period is a trip time period g, the general trip cost of the passengers waiting for the arc at the station platform of the station i in the congestion state is provided;
Figure FDA00024046879700000413
the departure interval of the line l; v. ofgThe number of trains is more than the average requirement of passengers going out in the time period g;
the generalized travel expense calculation model of the passenger transfer walking arc comprises a formula (12):
Figure FDA00024046879700000412
in the formula (12), the first and second groups,
Figure FDA0002404687970000051
when the travel time is g, the passengers change the generalized cost of the traveling arc at the h station; t ish-transferThe travel time of passengers for transfer at the h station of the transfer station; h is a certain transfer station of the urban rail transit;
the general generalized travel cost calculation model for the unblocked state and the general generalized travel cost calculation model for the congested state respectively include a formula (13) and a formula (14):
Figure FDA0002404687970000052
Figure FDA0002404687970000053
in the formulas (13) and (14), CclearRepresenting the total generalized travel cost of passengers from station i to station j; cjamRepresenting the total generalized travel fare of passengers from station i to station j.
8. The dynamic urban rail transit passenger flow distribution method according to claim 7, wherein the clear status is determined by formula (10):
Abilityg≥Numg(10)
the congestion state can be determined by equation (11):
Abilityg<Numg(11)
in the formula (10) and the formula (11), AbilitygThe transport capacity of the rail transit network is a time period g; numgThe time period is the passenger flow of the rail transit network.
9. The method for allocating dynamic passenger flow in urban rail transit according to claim 1, wherein the current state of the network is judged according to the transportation capacity of the network, the generalized travel cost of the passenger is calculated according to the generalized travel cost calculation model, and allocating the passenger flow according to the network state and the generalized travel cost comprises:
inputting physical network data and passenger flow data at the current moment;
judging whether the space-time service network is interrupted at the current moment;
if the interruption exists, updating the time-space service network data, and after updating, continuously judging whether the time-space service network is interrupted;
if the interruption does not exist, judging the state of the current road network according to whether the transport capacity meets the passenger flow requirement or not;
if the road network transport capacity meets the passenger flow demand, calculating the generalized travel cost of the passengers in the unblocked network in the current time period, and performing passenger flow distribution by using a logit model;
if the transportation capacity of the road network is not enough to meet the passenger flow demand, the passenger flow is averagely decomposed into 3 sub-tables, the generalized travel cost of the passengers in the time period is calculated, the passenger flow of the first sub-table is distributed, the travel cost is recalculated on the basis of the distribution of the first sub-table until the distribution of all the passenger flows is completed, and the passenger flow distribution amount of each time is accumulated to obtain the passenger flow distribution amount of each road section at the current time;
and updating the road network information and the passenger flow data at the next moment, repeating the steps, and accumulating the obtained results after the passenger flow distribution at all the moments is completed to obtain the passenger flow distribution result of the road network.
10. An urban rail transit dynamic passenger flow distribution system, characterized in that the system comprises:
the network construction module is used for adding the time information of the urban rail transit train, the spatial information of the passenger travel path and the time information of the passenger travel path into a physical network and establishing an urban rail transit space-time service network;
the modeling module is used for dividing a passenger travel path into a plurality of arc sections according to the behavior of the passenger, and respectively constructing a generalized travel cost calculation model of the passenger in each arc section and a total generalized travel cost calculation model according to the state of the urban rail transit network in each time period;
and the passenger flow distribution module is used for judging the current state of the network according to the transportation capacity of the network, calculating the generalized travel cost of the passenger according to the generalized travel cost calculation model, and distributing the passenger flow according to the network state and the generalized travel cost to obtain a passenger flow distribution result.
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