CN103279669B - A kind of transport capacity of urban rail transit network emulated computation method and system - Google Patents

Abstract

The present invention discloses a kind of transport capacity of urban rail transit network emulated computation method and system, comprises and following arranges simulating scenes, and this simulating scenes comprises road network feature, passenger flow characteristic sum service chart; Initial passenger flow generating capacity is loaded in road network; Start emulation; Calculate and export each circuit and the service level at each station; Judging whether described service level meets and calculate end condition, if meeting, then showing described current total volume of the flow of passengers; If not meeting, then in road network, increasing increment passenger flow, then repeating described beginning and emulating. System comprises scene setting module, initialize module, service level calculate module, end condition and judge module, pressure increasing module, display module and emulation module. The present invention adopts the thought of pressure test, take Computer Simulation as means, it is contemplated that this factor of road network service level, reduce calculated amount, it is to increase calculation result reliability.

Description

A kind of transport capacity of urban rail transit network emulated computation method and system

Technical field

The present invention relates to the emulated computation method of urban track traffic. In particular, it relates to a kind of transport capacity of urban rail transit network emulated computation method and system.

Background technology

At present, the method calculating transport capacity of urban rail transit network both at home and abroad is less, mainly taking circuit capacity calculation as background, it does not have consider from the overall angle of road network.

In existing method of calculation, road network transportcapacity calculates based on graphics and analytical calculation method, and graphics is by computer or hand simulation transport production practical situation drawing route map of train, so that it is determined that the method for road network transportcapacity. The method is relatively directly perceived, but calculated amount is big, and computation process is loaded down with trivial details, and calculation result varies with each individual. Analytical calculation method is carrying out practical situation analyzing on the basis of research, by founding mathematical models, utilizes mathematical formula to calculate the method for road network transportcapacity. Analytical calculation method calculates simple and easy to do, highly versatile, but research object and influence factor have all been carried out certain simplify processes, and its result is bigger to the dependency of model, when model is comparatively complicated, the possibility of result using analytical calculation method to solve differs relatively big with actual result, and accuracy is not high.

And, passenger flow feature is as one of the influence factor of road network transportcapacity, play an important role in road network transportcapacity calculates, but the Time and place characteristic of passenger flow all can not well be portrayed by graphics and analytical calculation method, and computer emulation method can fully simulate the situation that pedestrian goes on a journey in urban mass transit network, with practical situation relatively.

In addition, the service quality that service level and passenger perceive, this service level also affects the transportcapacity of road network. Because only from objective angle, road network system can also increase passenger's quantity of transport again, but from the subjective point of passenger, the degree of crowding has reached the limit of its tolerance, and other passengers can not enter in system again. And existing additive method is when calculating road network transportcapacity, it does not have considering the requirement of service level, therefore calculation result reliability is on the low side.

Summary of the invention

The object of the invention is to provide a kind of transport capacity of urban rail transit network emulated computation method and system, when calculating given road network characteristic sum passenger flow feature, and transport capacity of urban rail transit network when certain service level.

Concrete technical scheme is as follows:

A kind of transport capacity of urban rail transit network emulated computation method, comprises the following steps:

Step 1, arranging simulating scenes, this simulating scenes comprises road network feature, passenger flow characteristic sum service chart;

Step 2, initial passenger flow generating capacity is loaded in road network;

Step 3, starting emulation, every passenger is by the trip of its trip characteristics;

Step 4, calculate and export each circuit and the service level at each station;

Step 5, judge described service level and whether meet to calculate end condition, if meeting, then performing step 7, if not meeting, then performing step 6;

Step 6, in road network, increase increment passenger flow, then perform step 3;

Step 7, showing the described current total volume of the flow of passengers, simulation calculation terminates.

Described passenger flow feature comprises each od to the volume of the flow of passengers distribution in a day and the distribution of each day part volume of the flow of passengers of od pair.

Described end condition comprises lines service level qualification rate more than the first preset ratio and station service level qualification rate more than the 2nd preset ratio;

Described lines service level qualification rate ��_LRepresent, for:

${\mathrm{\γ}}_L=\frac{n_L}{N_L}$

Described station service level qualification rate ��_sRepresent, for:

${\mathrm{\γ}}_s=\frac{n_s}{N_s}$

Wherein, n_LLines service level standard class and the number of lines of following grade thereof is reached, N for lines service level in road network_LFor the total number of the circuit in road network; n_sThe station quantity of the number of lines of station LOS criteria grade and following grade thereof is reached, N for station service level in road network_sFor the station total quantity in road network.

Described step 4 calculates and the service level that exports each circuit and each station comprises further:

The weighted mean L of the load factor of described lines service level circuit in one day_lineWeigh, obtained by following formula successively:

$L_{\mathrm{line}}=\underset{k=1}{\overset{n-1}{\mathrm{\Σ}}}{l}_{\mathrm{fk}}{w}_k$

Wherein, I is used_kRepresenting that the kth on circuit is interval, n is the station number on this circuit, and n-1 is the interval number on this circuit, l_fkFor the load factor weighted mean of kth in interval one day, w_kFor l_fkWeight, 1��k��n-1.

Further, the load factor weighted mean l of described kth in interval one day is obtained by following formula_fk:

$l_{\mathrm{fk}}=\underset{s=1}{\overset{t}{\mathrm{\Σ}}}\frac{P_s}{C_s}\·{\mathrm{\δ}}_s$

Wherein, by interval I_kOperation in one day is divided into t time period, P_sFor interval I_kPassenger's total number of persons of train within the s period, C_sFor interval I_kThe total passenger places number of train within the s period, ��_sIt is the load factor weight of s period, s=1,2 ... t.

Further, described station service level platform carrying capacity utilization ratio and the collecting and distributing Time dynamic coefficient of passenger are weighed, and this platform carrying capacity utilization ratio and passenger's collecting and distributing Time dynamic coefficient are obtained by following formula:

$\mathrm{\α}=\frac{{\mathrm{\ρ}}_{\mathrm{average}}}{{\mathrm{\ρ}}_{\max }},$

And

$\mathrm{\β}=\frac{T_{\mathrm{average}}}{T_{\mathrm{free}}}$

Wherein, �� represents platform carrying capacity utilization ratio, and �� represents the collecting and distributing Time dynamic coefficient of passenger, ��_averageFor station average passenger density, ��_maxFor maximum station passenger's density, T_averageFor the average passenger collecting and distributing time, T_freeFor collecting and distributing time when passenger freely walks row.

Described step 6, in road network, increase increment passenger flow comprise further:

According to described each od, the volume of the flow of passengers in a day is distributed, by described increment bus traveler assignment to each od to upper, obtain the increment passenger flow of each od pair;

According to each day part volume of the flow of passengers of od pair described distribution, by the increment bus traveler assignment of described od pair to, on this each time period of od pair, obtaining this od to the increment passenger flow of each period.

Further, the described current total volume of the flow of passengers be described initial passenger flow generating capacity and all increment passenger flows add and.

The present invention also provides a kind of transport capacity of urban rail transit network simulation computing system, and this system comprises:

Scene setting module, for setting simulating scenes, this simulating scenes comprises road network feature, passenger flow characteristic sum service chart;

Initialize module, for being loaded in road network by initial passenger flow generating capacity;

Emulation module, goes on a journey by its trip characteristics for emulating every passenger;

Service level calculate module, for calculating and export each circuit and the service level at each station;

End condition judges module, calculates end condition for judging whether described service level meets;

Pressure increasing module, for increasing increment passenger flow in road network;

Display module, for showing described current total volume of the flow of passengers.

Described service level calculates module and is further used for according to following formulae discovery lines service level:

$L_{\mathrm{line}}=\underset{k=1}{\overset{n-1}{\mathrm{\Σ}}}{l}_{\mathrm{fk}}{w}_k$

Wherein, I is used_kRepresenting that the kth on circuit is interval, n is the station number on this circuit, and n-1 is the interval number on this circuit, l_fkFor the load factor weighted mean of kth in interval one day, w_kFor l_fkWeight, 1��k��n-1, L_lineFor the weighted mean of the load factor of circuit in one day;

Described service level calculates module and is further used for station service level according to following formulae discovery:

$\mathrm{\α}=\frac{{\mathrm{\ρ}}_{\mathrm{average}}}{{\mathrm{\ρ}}_{\max }},$

And

$\mathrm{\β}=\frac{T_{\mathrm{average}}}{T_{\mathrm{free}}}$

Wherein, �� represents platform carrying capacity utilization ratio, and �� represents the collecting and distributing Time dynamic coefficient of passenger, ��_averageFor station average passenger density, ��_maxFor maximum station passenger's density, T_averageFor the average passenger collecting and distributing time, T_freeFor collecting and distributing time when passenger freely walks row;

And, described end condition judges module, be further used for judging described lines service level qualification rate whether more than the first preset ratio and described station service level qualification rate whether more than the 2nd preset ratio;

Described lines service level qualification rate ��_LRepresent, for:

${\mathrm{\γ}}_L=\frac{n_L}{N_L}$

Described station service level qualification rate ��_sRepresent, for:

${\mathrm{\γ}}_s=\frac{n_s}{N_s}$

Wherein, n_LLines service level standard class and the number of lines of following grade thereof is reached, N for lines service level in road network_LFor the total number of the circuit in road network; n_sThe station quantity of the number of lines of station LOS criteria grade and following grade thereof is reached, N for station service level in road network_sFor the station total quantity in road network.

Further, in described scene setting module, described passenger flow feature comprises each od to the volume of the flow of passengers distribution in a day and the distribution of each day part volume of the flow of passengers of od pair.

Further, described pressure increasing module, is further used for the volume of the flow of passengers in a day being distributed according to described each od, by described increment bus traveler assignment to each od to upper, obtains the increment passenger flow of each od pair; And, it is further used for according to each day part volume of the flow of passengers of od pair described distribution, by the increment bus traveler assignment of described od pair to, on this each time period of od pair, obtaining this od to the increment passenger flow of each period.

Further, in described display module, the described current total volume of the flow of passengers be described initial passenger flow generating capacity and all increment passenger flows add and.

The useful effect of the present invention is:

(1) present invention employs the thought of pressure test, compared with Traditional calculating methods, reduce calculated amount so that operability strengthens.

(2) the present invention is taking Computer Simulation as main technique means, features temporal characteristics and the space characteristics of urban track traffic for passenger flow well.

(3) contemplated by the invention this factor of road network service level, it is to increase calculation result reliability.

Accompanying drawing explanation

Below with reference to accompanying drawings and the present invention is specifically described in conjunction with the embodiments.

Fig. 1 is the method flow diagram of the present invention;

Fig. 2 is passenger flow Annual distribution situation schematic diagram.

Embodiment

With reference to the accompanying drawings and by embodiments of the invention, the technical scheme of the present invention is described in detail.

The transport capacity of urban rail transit network emulated computation method of the present invention and system have employed the thought of pressure test, taking Computer Simulation as main technique means, and when considering service level, calculate transport capacity of urban rail transit network during given road network characteristic sum passenger flow feature.

Described system comprises scene setting module, initialize module, service level calculate module, end condition and judge module, pressure increasing module, display module and emulation module.

As shown in Figure 1, the method for the present invention comprises the steps:

Step 1: the simulating scenes arranged according to customer need by scene setting module, this simulating scenes mainly comprises road network topology structure, road network passenger flow feature (comprising temporal characteristics and space characteristics), and the service chart of road network in one day.

Described road network topology structure mainly shows the way the information such as the station spacing between the number of lines in net, each line length, the station that each bar circuit comprises, each station, and road network topology structure reflects described road network feature.

Described passenger flow feature comprises passenger flow spatial distribution characteristic and passenger flow period distribution characteristics, will be described respectively below.

Passenger flow spatial distribution refers to the space distribution situation of urban track traffic for passenger flow on urban track traffic road network, the i.e. distribution situation between each initial station and Zhongdao station in road network of passenger flow on road network, this distribution situation can represent for each od of road network as shown in table 1 is to distribution table.

The each od of table 1 road network is to distribution table

In this table, o represents initial station, and d represents Zhongdao station, and i, j represent numbering that is initial and Zhongdao station respectively, and n represents the sum at station, o_id_jRepresent the volume of the flow of passengers from initial station i to Zhongdao station j. As i=j, o_i=d_j, namely originating station and terminal station are same station, now have o_id_j=0��

Carrying out in the process emulated, for the ease of in step 6 by the increment bus traveler assignment that is loaded in road network every time to each od to upper, the od distribution table of passenger flow can be deformed into the od distribution proportion matrix of passenger flow, as follows:

The total passenger flow generating capacity assuming this road network is O, namely

$\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{o}_i{d}_j=O$

Then have

${\mathrm{\ω}}_v=\frac{o_i{d}_j}{O}$

Wherein, initial station i is the v od pair, �� to Zhongdao station j_vRepresent this volume of the flow of passengers ratio of the v od pair.

The distribution of passenger flow period refers to the distribution situation of road network passenger flow on the period. O in table 1_id_jWhat represent is the volume of the flow of passengers in a day from station i to station j, is a static numerical value, can not reflect the characteristics of time interval that in a day, the upper volume of the flow of passengers is distributed by this od, and the period distribution characteristics in a day can be represented for as shown in Figure 2 by this v od.

By the period that total operation Time segments division of a day is different, t in figure₁��t₂������t_q��������t_mEach period in representing one day respectively, m is the period sum divided.Represent t_qThe volume of the flow of passengers of period accounts for the v od to volume of the flow of passengers o in a day_id_jRatio, thenRepresent that this v od is at t_qThe volume of the flow of passengers of period. In Fig. 2, the base length of each dash area represents o_id_j, make the base of dash area equal, then the area of each dash areaChanging conditions reflect in road network od to o_id_jThe period distribution characteristics of passenger flow.

Therefore, in the process carrying out simulating scenes setting, described passenger flow feature to be inputted the od distribution proportion matrix of passenger flow respectivelyWith each od to the distribution proportion on day part in a day. Due to different times, such as working days and Holidays, the od distribution characteristics of road network passenger flow is different, and the od distribution proportion matrix therefore inputted is also different with each period distribution proportion of od pair. The od distribution proportion matrix in a certain period can calculate by adding up the historical data of this road network same period, each period distribution proportion of od pair also draws by each passenger flow period distribution characteristics of od pair on statistics road network, and the period distribution proportion of different od pair may be different.

Described service chart mainly comprises the information such as the departure interval of each bar circuit in road network, section operation time-division of each train, dwell time.

Step 2: initial passenger flow generating capacity is loaded in road network by initialize module. This initial passenger flow generating capacity is the passenger flow total amount loaded at the beginning in road network, is the mean value of the history statistic data same period. Each numerical value that this initial passenger flow generating capacity is multiplied by described od distribution proportion matrix by described initialize module OD, the matrix of consequence drawn is exactly the distribution matrix of the initial passenger flow od after loading, and this initial passenger flow od each od of distribution moment matrix representation is to upper initial passenger flow generating capacity.

Step 3: start emulation in emulation module, in this module, use computer simulation technique, the situation of the simulation actual trip of passenger, every passenger goes on a journey in analogue system according to its trip characteristics from o to d, and this trip characteristics refers to starting point o, Zhongdao point d and selected path that this passenger goes on a journey. Further, the trip situation of pedestrian in urban track traffic system be can fully simulate by Computer Simulation, trip requirements, trip od, the travel route choice behavior etc. of pedestrian comprised. Carry out well portraying to the Time and place feature of passenger flow. Working days is different with the passenger flow trip requirements of Holidays, and on the basis that this passenger flow is gone on a journey, the transportcapacity of road network is not identical yet.

Step 4, calculate module by service level and calculate and export each circuit and the service level at each station.

For a given circuit, passenger's different amts of its each interval each period transport in a day, therefore its load factor is not identical in each period in each interval of circuit yet, in order to calculate the average load factor of circuit in one day, the load factor mean value of each period that should first calculate each interval of circuit in one day, then calculate the load factor mean value of this circuit in one day accordingly. For trying to achieve each mean value of load factor, the method for weighted mean can be adopted.

Assume that on certain circuit, station sum is n, then on circuit, interval number is n-1, available I₁��I₂��I₃��I_k��I_n-1(1��k��n-1) represents each interval on circuit. The value of the load factor in each interval in one day each time period be different, the division of time period can not also be fixed, and different intervals can have different time period to divide. Because the load factor changing conditions in each interval is not necessarily identical, such as, the morning peak of interval A is 7 o'clock to 8 o'clock, and the morning peak of interval B is that 7 thirty are to 8 thirty. Such as interval I_k, the operation in its day is divided into t time period, the load factor weight �� of a certain period s can be determined according to the changing conditions of the value of its load factor in one day_s, then interval I_kLoad factor weighted mean in one day is:

$l_{\mathrm{fk}}=\underset{s=1}{\overset{t}{\mathrm{\Σ}}}\frac{P_s}{C_s}\·{\mathrm{\δ}}_s$

In formula, l_fkIt is interval I_kLoad factor weighted mean in one day, P_sFor interval I_kPassenger's total number of persons of train within the s period, C_sInterval I_kThe total passenger places number of train within the s period.

Determine interval I_kAfter load factor weighted mean in one day, then the l according to each interval_fkValue, it is determined that the weight (this weight can be determined by such as expert graded) that the average load factor in each interval is shared in sliver road, it is assumed that interval I_kL_fkThe shared on the line weight of value is w_k, then the load factor weighted mean of circuit in one day is:

$L_{\mathrm{line}}=\underset{k=1}{\overset{n-1}{\mathrm{\Σ}}}{l}_{\mathrm{fk}}\·w_k$

l_lineValue can reflect the mean value of this circuit load factor in a day. l_lineValue more big, namely the average load factor of circuit is more big, then the passenger in compartment is more crowded, and the service level of circuit is also more poor; Otherwise, the service level of circuit is more good.

Described station service level can be weighed with two indices, is respectively platform carrying capacity utilization ratio �� and the collecting and distributing Time dynamic factor beta of passenger, is shown below:

$\mathrm{\α}=\frac{{\mathrm{\ρ}}_{\mathrm{average}}}{{\mathrm{\ρ}}_{\max }}$

$\mathrm{\β}=\frac{T_{\mathrm{average}}}{T_{\mathrm{free}}}$

Wherein, ��_averageFor platform average passenger density, ��_maxFor maximum platform passenger's density, T_averageFor the average passenger collecting and distributing time, T_freeFor collecting and distributing time when passenger freely walks row. This collecting and distributing time refers to that passenger is entered the station to from the gate that enters the station and gets on the bus, and the time spent when setting off from departures gate of getting off.

Step 5, judge module by end condition and judge described service level and whether meet to calculate end condition, if meeting, then performing step 7, if not meeting, then performing step 6.

Step 6, in road network, increase increment passenger flow (representing with �� O) by pressure increasing module, then perform step 3.

Step 7, showing the described current total volume of the flow of passengers by display module, simulation calculation terminates.

Described end condition comprises lines service level qualification rate more than the first preset ratio and station service level qualification rate more than the 2nd preset ratio. Whether qualified and specified by user the LOS criteria grade of described service level be relevant.

The grade scale of lines service level is as shown in table 2, and station service level grade scale is as shown in table 3.

Table 2 lines service level grade scale

Table 3 station service level grade scale

In table 2 and table 3, grade A represents that service level is best, and grade E represents that service level is worst. In different cities, l_a,l_b,l_c,l_d, ��_a,��_b,��_c,��_d, ��_a,��_b,��_c,��_dValue may be different.

In the present invention, such as user specifies lines service level standard class and station LOS criteria grade is all that B level, then qualified lines service level and station service level should reach B level or following.

Described lines service level qualification rate ��_LRepresent, for:

${\mathrm{\γ}}_L=\frac{n_L}{N_L}$

Described station service level qualification rate ��_sRepresent, for:

${\mathrm{\γ}}_s=\frac{n_s}{N_s}$

Wherein, n_LB level and the number of lines of following grade thereof is reached, N for lines service level in road network_LFor the total number of the circuit in road network; n_sFor station service level in road network reaches the station quantity of the number of lines of B level and following grade thereof, N_sFor the station total quantity in road network.

Such as, the first preset ratio and the 2nd preset ratio are all 80%, then described end condition is:

��_L>80%&&��_S>80%

In steps of 5, judging whether lines service level and station service level meet above-mentioned end condition, if met, then performing step 7, showing described current total volume of the flow of passengers, simulation calculation terminates. If not meeting, then perform step 6, in road network, increase increment passenger flow, continue to perform step 3.

Increment passenger flow in step 6 embodies the thought of pressure test. Pressure test is generally used for finance tissue and computer software, this thought principle is in the present invention: track traffic road network is regarded as a pressure test object, using the increment passenger flow of loading as pressure, by constantly increasing pressure to test the maximum load-carrying capacity of this road network, when road network reaches edge (i.e. the end condition) of supporting capacity, can not increase pressure again, then pressure total amount now and current passenger flow total amount are just the transportcapacity of this road network.

Specifically, first according to each numerical value �� in od distribution proportion matrix₁, ��₂, ��₃..., ��_v..., respectively increment Delta O is assigned to each od to upper, namely the increment passenger flow of the v od pair is ��_v����O��

Further, according to each od to the difference of upper flow space-time distribution, it is possible to increment passenger flow is assigned to further each od on the time periods different in one day. Such as, the v od is to representing from Fuchengmen station, station, Xizhimen, then its increment passenger flow is ��_v�� O, can be divided into such as 7 time periods in one day, the volume of the flow of passengers of each time period accounts for this od and to the ratio of total amount isThen the generating capacity of each period is respectively

Time the current total volume of the flow of passengers in step 7 refers to that last algorithm terminates, the total number of persons in road network, namely initial passenger flow generating capacity and all increment passenger flows add and. Method and system below by the present invention calculate the road network transportcapacity in following condition:

First preset ratio ��_LWith the 2nd preset ratio ��_SBeing all 70%, lines service level standard class and station LOS criteria grade are all B level

Step 1 arranges simulating scenes

(1) od distribution space distribution proportion table; Od Annual distribution, it is assumed that the period distribution situation of each od is identical, mt=5, t₁=t₂=t₃=t₄=t₅,

(2) road network feature, namely Beijing Metro 1,2,3,4,5,6,10,13, Batong Line, altogether eight lines;

(3) service chart (i.e. timetable)

The initial passenger flow generating capacity of step 2, is set to 1000000 according to statistic data;

Step 3 starts emulation;

Step 4 exports each lines service level and station service level;

Step 5 judges whether described service level meets and calculates end condition, if meeting, then performing step 7, if not meeting, then performing step 6;

Step 6 increases increment passenger flow in road network, increment passenger flow �� O=50000, then performs step 3

Step 7 terminates, and exporting current total volume of the flow of passengers is 4150000

Within a working days, by Beijing Metro 1,2,4,5,8,10,13, the Batong Line road network that eight lines form altogether, be all B level in given service level grade, ��_LAnd ��_SWhen being all 70%, its transportcapacity is 4150000 people.

It is to be understood that the above detailed explanation technical scheme of the present invention carried out by preferred embodiment is illustrative and not restrictive. Technical scheme described in each embodiment can be modified by the those of ordinary skill of this area on the basis reading specification sheets of the present invention, or wherein part technology feature carries out equivalent replacement; And these amendments or replacement, do not make the spirit and scope of the essence disengaging various embodiments of the present invention technical scheme of appropriate technical solution. Protection scope of the present invention is only limited by following claims.

Claims (8)

1. a transport capacity of urban rail transit network emulated computation method, it is characterised in that, comprise the following steps:

Step 1, arranging simulating scenes, this simulating scenes comprises road network feature, passenger flow characteristic sum service chart;

Step 2, initial passenger flow generating capacity is loaded in road network;

Step 3, starting emulation, every passenger is by the trip of its trip characteristics;

Step 4, calculate and export each circuit and the service level at each station;

Step 5, judge described service level and whether meet to calculate end condition, if meeting, then performing step 7, if not meeting, then performing step 6; In step 5, described end condition comprises lines service level qualification rate more than the first preset ratio and station service level qualification rate more than the 2nd preset ratio;

Described lines service level qualification rate ��_LRepresent, for:

${\mathrm{\γ}}_L=\frac{n_L}{N_L}$

Described station service level qualification rate ��_sRepresent, for:

${\mathrm{\γ}}_s=\frac{n_s}{N_s}$

Wherein, n_LLines service level standard class and the number of lines of following grade thereof is reached, N for lines service level in road network_LFor the total number of the circuit in road network; n_sThe station quantity of the number of lines of station LOS criteria grade and following grade thereof is reached, N for station service level in road network_sFor the station total quantity in road network

Step 6, in road network, increase increment passenger flow, then perform step 3;

Step 7, the current total volume of the flow of passengers of display, simulation calculation terminates.

2. a kind of transport capacity of urban rail transit network emulated computation method according to claim 1, it is characterised in that,

Described passenger flow feature comprises each od to the volume of the flow of passengers distribution in a day and the distribution of each day part volume of the flow of passengers of od pair.

3. a kind of transport capacity of urban rail transit network emulated computation method according to claim 1, it is characterised in that, described step 4 calculates and the service level that exports each circuit and each station comprises further:

The weighted mean L of the load factor of described lines service level circuit in one day_lineWeigh, obtained by following formula successively:

$L_{line}=\underset{k=1}{\overset{n-1}{\Σ}}{l}_{fk}{w}_k$

Wherein, I is used_kRepresenting that the kth on circuit is interval, n is the station number on this circuit, and n-1 is the interval number on this circuit, l_fkFor the load factor weighted mean of kth in interval one day, w_kFor l_fkWeight, 1��k��n-1.

4. a kind of transport capacity of urban rail transit network emulated computation method according to claim 3, it is characterised in that,

The load factor weighted mean l of described kth in interval one day is obtained by following formula_fk:

$l_{fk}=\underset{s=1}{\overset{t}{\Σ}}\frac{P_s}{C_s}\·{\mathrm{\δ}}_s$

Wherein, by interval I_kOperation in one day is divided into t time period, P_sFor interval I_kPassenger's total number of persons of train within the s period, C_sFor interval I_kThe total passenger places number of train within the s period, ��_sIt is the load factor weight of s period, s=1,2 ... t.

5. a kind of transport capacity of urban rail transit network emulated computation method according to claim 1, it is characterised in that,

Described station service level platform carrying capacity utilization ratio and the collecting and distributing Time dynamic coefficient of passenger are weighed, and this platform carrying capacity utilization ratio and passenger's collecting and distributing Time dynamic coefficient are obtained by following formula:

$\mathrm{\α}=\frac{{\mathrm{\ρ}}_{average}}{{\mathrm{\ρ}}_{\max }},$

And

$\mathrm{\β}=\frac{T_{average}}{T_{free}}$

Wherein, �� represents platform carrying capacity utilization ratio, and �� represents the collecting and distributing Time dynamic coefficient of passenger, ��_averageFor station average passenger density, ��_maxFor maximum station passenger's density, T_averageFor the average passenger collecting and distributing time, T_freeFor collecting and distributing time when passenger freely walks row.

6. a kind of transport capacity of urban rail transit network emulated computation method according to claim 2, it is characterised in that, described step 6, in road network, increase increment passenger flow comprise further:

According to described each od, the volume of the flow of passengers in a day is distributed, by described increment bus traveler assignment to each od to upper, obtain the increment passenger flow of each od pair;

According to each day part volume of the flow of passengers of od pair described distribution, by the increment bus traveler assignment of described od pair to, on this each time period of od pair, obtaining this od to the increment passenger flow of each period.

7. a kind of transport capacity of urban rail transit network emulated computation method according to claim 1, it is characterised in that,

The described current total volume of the flow of passengers be described initial passenger flow generating capacity and all increment passenger flows add and.

8. a transport capacity of urban rail transit network simulation computing system, it is characterised in that, this system comprises:

Scene setting module, for setting simulating scenes, this simulating scenes comprises road network feature, passenger flow characteristic sum service chart;

Initialize module, for being loaded in road network by initial passenger flow generating capacity;

Emulation module, goes on a journey by its trip characteristics for emulating every passenger;

Service level calculate module, for calculating and export each circuit and the service level at each station; Described service level calculates module and is further used for according to following formulae discovery lines service level:

$L_{line}=\underset{k=1}{\overset{n-1}{\Σ}}{l}_{fk}{w}_k$

Wherein, I is used_kRepresenting that the kth on circuit is interval, n is the station number on this circuit, and n-1 is the interval number on this circuit, l_fkFor the load factor weighted mean of kth in interval one day, w_kFor l_fkWeight, 1��k��n-1, L_lineFor the weighted mean of the load factor of circuit in one day;

Described service level calculates module and is further used for station service level according to following formulae discovery:

$\mathrm{\α}=\frac{{\mathrm{\ρ}}_{average}}{{\mathrm{\ρ}}_{\max }},$

And

$\mathrm{\β}=\frac{T_{average}}{T_{free}}$

Wherein, �� represents platform carrying capacity utilization ratio, and �� represents the collecting and distributing Time dynamic coefficient of passenger, ��_averageFor station average passenger density, ��_maxFor maximum station passenger's density, T_averageFor the average passenger collecting and distributing time, T_freeFor collecting and distributing time when passenger freely walks row;

And,

End condition judges module, be further used for judging described lines service level qualification rate whether more than the first preset ratio and described station service level qualification rate whether more than the 2nd preset ratio;

Described lines service level qualification rate ��_LRepresent, for:

${\mathrm{\γ}}_L=\frac{n_L}{N_L}$

Described station service level qualification rate ��_sRepresent, for:

${\mathrm{\γ}}_s=\frac{n_s}{N_s}$

Wherein, n_LLines service level standard class and the number of lines of following grade thereof is reached, N for lines service level in road network_LFor the total number of the circuit in road network; n_sThe station quantity of the number of lines of station LOS criteria grade and following grade thereof is reached, N for station service level in road network_sFor the station total quantity in road network;

End condition judges module, calculates end condition for judging whether described service level meets;

Pressure increasing module, for increasing increment passenger flow in road network;

Display module, for showing current total volume of the flow of passengers.