CN106709609B - A kind of method of the PREDICTIVE CONTROL subway station amount of entering the station - Google Patents

A kind of method of the PREDICTIVE CONTROL subway station amount of entering the station Download PDF

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CN106709609B
CN106709609B CN201710020497.7A CN201710020497A CN106709609B CN 106709609 B CN106709609 B CN 106709609B CN 201710020497 A CN201710020497 A CN 201710020497A CN 106709609 B CN106709609 B CN 106709609B
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李得伟
尹浩东
樊佳慧
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Beijing Jiaotong University
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Abstract

A kind of method that the present invention discloses PREDICTIVE CONTROL subway amount of entering the station, should be the following steps are included: construct the linear function formula between the station amount of entering the station and section section flow；Linear fit is carried out based on the historical data values of the station amount of entering the station and section section flow, determines parameter to be estimated；Section flow based on given section calculates the target amount of entering the station at corresponding station；Passenger flow control strategy is determined based on the target amount of entering the station.The present invention applies to urban track traffic for passenger flow organization and administration, and the subway station amount of entering the station is limited by PREDICTIVE CONTROL, controls Subway Tunnel load factor, alleviates passenger flow congestion phenomenon, so that large passenger flow be avoided to cause excessive pressure to route or gauze.Further, it by the classification to the section section volume of the flow of passengers, instructs subway station in actual operation management, grading control measure according to circumstances is taken to the amount of entering the station in different periods, keep the amount of entering the station control more reasonable.

Description

Method for predicting and controlling subway station arrival amount
Technical Field
The invention relates to the technical field of urban rail transit. And more particularly, to a method for predictive controlling the amount of station arrivals at a subway station.
Background
With the rapid development of economic society, a plurality of cities in China have built or plan to build urban rail transit so as to solve the problem of increasingly congested traffic in the process of urbanization. However, with the gradual increase of passenger flow, the passenger flow control of urban rail transit stations is increasingly difficult, the contradiction between the rapidly increasing passenger flow demand of urban rail transit and the transport capacity is increasingly prominent, and a feasible method for relieving the congestion problem is to manage the demand from the perspective of passenger flow control. Passenger flow control, also known as flow limiting, refers to safety measures taken to limit the speed at which passengers can enter a station to meet the need of ensuring the safety of passenger transportation organizations, so as to achieve the purpose of reducing the flow of passengers entering the station in unit time. Station current limiting mainly includes normal current limiting and interim current limiting: the normal current limiting means that the same current limiting measures are adopted in a specific time interval in a certain period, and the normal current limiting method is mainly applied to the early-late peak time interval; the temporary current limiting refers to short-time uncertain current limiting on a station, and is mainly influenced by sudden large passenger flows caused by emergencies, large-scale activities and severe weather.
Currently, in actual operation management, there is no appropriate theoretical basis and calculation method for current limiting station selection, current limiting time period determination, current limiting intensity determination, and the like, and the experience of a manager is mainly relied on. The theoretical studies on the above problems are mainly as follows: in the aspect of control measures, the Liuhua and the like put forward for the first time that passenger flow control is implemented by three control modes of a station level, a line level and a network level, and the application conditions and the disposal measure principles of the control modes of each layer are analyzed; zhao Peng and the like construct a station passenger flow cooperative control model from a line level by using a linear programming method, and model verification is carried out by taking the No. 5 line of the Beijing city rail transit as an example; liu Xiao Hua and the like construct a joint control strategy between stations, and reserve train conveying capacity for the station by reducing the passenger flow station entering speed of an upstream station so as to balance the capacity of the train on a line; the Zhang-Zheng-wait establishes a cooperative current limiting method of passenger flow on station single points and lines according to a flow balance principle; the principle of dealing with sudden large passenger flow events, such as prediction in advance, system association, communication enhancement and grading responsibility, is provided, a driving organization and station passenger flow control mode under the condition of large passenger flow is designed in a key way, and large passenger flow safety control measures of self-organization and other organizations are provided; the method is characterized in that the 6 th line and the 8 th line of the rail transit of the maritime city above Lijialin are taken as backgrounds, the contradiction between the demand and the transport capacity in the early peak period is analyzed, improvement suggestions are provided for current limiting measures, and the operation effects of different current control measures are analyzed.
In the prior patent document, publication number CN103661501A discloses an automatic station current limiting method based on multipoint passenger flow detection information feedback, which includes the steps: detecting and calculating the number of passengers in the station hall and the number of passengers in the station platform in real time, and analyzing the increasing trend of the passenger capacity of the station platform; calculating the passenger remaining capacity in the station hall and the passenger remaining capacity in the platform; adjusting the number of passengers entering and exiting the station hall in real time according to the remaining amount of the passengers in the station hall; adjusting the number of passengers at the platform according to the amount of passengers remaining at the platform; and further adjusting the number of passengers entering and exiting the station hall according to the number increase of the passengers entering and exiting the station hall caused by the adjustment of the number of the passengers entering and exiting the station, so as to achieve the purpose of flow limitation. The technical scheme belongs to post regulation, namely measures are taken when or after passenger flow congestion occurs in stations, the current limiting effect is poor, and the scheme is a local regulation strategy and mainly has the defect that the congestion state of some stations can be relieved, and the aim of comprehensively implementing the overall current limiting measures of a network can not be achieved.
Therefore, it is required to provide a method for predictive controlling the arrival amount of the subway station.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a method for predicting and controlling the arrival rate of a subway station. The method is applied to urban rail transit passenger flow organization management, and mainly aims to limit the station entering amount of subway stations through prediction control, control the full load rate of subway intervals and relieve the passenger flow congestion phenomenon, so that overlarge pressure of large passenger flows on lines or a line network is avoided.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for predicting and controlling the arrival amount of a subway comprises the following steps:
s1: according to the analysis of the relationship between the station arrival passenger flow and the section flow in the subway line network, constructing a linear function formula between the station arrival flow and the section flow in the subway line network:
wherein,
xithe total station entering amount of the ith station is i-1, 2, …, n;
yjthe total flow of the section in the jth interval, j is 1,2, …, m;
αjithe proportion of the passenger flow volume which enters the station from the ith station and passes through the section of the jth interval to the total station entering volume of the ith station is shown;
βijthe proportion of the passenger flow entering from the ith station in the j section passenger flow is the total passenger flow of the j section;
Δtjiconsidering the punctuality of urban rail transit for the time required for the passenger flow to reach the jth section from the ith station, it can be considered that for the determined iAnd j, Δ tjiIs a constant value;
xi(t-Δtji) Is the (t- Δ t)ji) The total station entering amount of the ith station in each time interval;
yj(t) is the total flow of the cross section in the jth interval in the tth time period;
m and n are natural numbers, n is the total number of stations, and m is the total number of intervals.
S2: performing linear fitting based on historical data values of station arrival amount and zone discontinuous flow to determine parameters to be estimated;
s3: calculating the target station-entering amount of the corresponding station based on the section flow of the given interval;
s4: and determining a passenger flow control strategy based on the target arrival amount.
Preferably, step S2 specifically includes the following steps:
s21: determining that the jth interval has the following relation
yj(t)＝αj1x1(t-Δtj1)+αj2x2(t-Δtj2)+αj3x3(t-Δtj3)+...+αjnxn(t-Δtjn)；
S22: selecting total flow y of the upper section of the jth interval in the t time period in one day from historical dataj(t) and the amount of arrival x at n stations1、x2、x3…xnAs a set of input data;
s23: selecting a plurality of sets of input data for different days from the history data as in step S22;
s24: substituting multiple sets of input data into the relational expression in step S21 to determine the parameter alpha to be estimatedj1、αj2、αj3…αjnWherein j is 1,2, …, m in sequence;
s25: determining that the ith station has the following relational expression
xi(t-Δtji)＝βi1y1(t)+βi2y2(t)+βi3y3(t)+...+βinyn(t)；
S26: selecting the total station entering amount y of the ith station in the time period t in one day from the historical dataj(t) and total flow y of cross-section in m intervals1、y2、y3…ynAs a set of input data;
s27: selecting a plurality of sets of input data for different days from the history data as in step S26;
s28: substituting multiple sets of input data into the relational expression in step S25 to determine the parameter beta to be estimatedi1、βi2、βi3…βmjWherein i is 1,2, …, n in sequence.
Preferably, step S3 specifically includes the following steps:
s31: based on the fact that the passenger flow volume of the ith station entering the station and passing through the jth interval is equal to the passenger flow volume of the ith station entering the station in the section passenger flow of the jth interval, the following equation is obtained:
αjixi(t-Δtji)＝βijyj(t)；
s32: determining the maximum section flow y of the jth section based on the section maximum full load ratej(t)；
S33: let i equal to 1, j take the values 1,2, …, m in turn, to obtain the (t- Δ t) thj1) M station-entering amounts x of 1 st station in each time period1(t-Δt11)、x1(t-Δt21)、x1(t-Δt31)、…、x1(t-Δtm1)；
S34: selecting the m inbound traffic x1(t-Δt11)、x1(t-Δt21)、x1(t-Δt31)、…、x1(t-Δtm1) Min x of (1)1(t-Δtj1) As the 1 st station at the (t- Δ t) th stationj1) A control value of the station entering amount in each time interval;
s35: sequentially taking the value of i as 2, …, n, and repeating the steps to obtain the (t-delta t) th stationj1) And the control value of the station entering amount in each time interval is the target station entering amount of the corresponding station.
The accuracy of the parameter values to be estimated increases with the increase of the historical database.
Further preferably, the maximum loading of the section is 140%.
Preferably, in step S4, the regression parameter α is determinedji、βijThe determining of passenger flow control policy based on the target inbound traffic, based on the above calculations, uses a large amount of historical data, thus comprising:
forecasting and estimating the future time period of current limiting of each station every day and the corresponding passenger flow control value, and giving a station current limiting forecasting suggestion; and/or
And determining whether the current station needs to carry out current limiting and implementing measures for controlling the station entering amount by comparing the station entering amount in the current time period with the target station entering amount.
Preferably, the passenger flow control strategy also comprises a hierarchical control of station current limiting measures.
Preferably, different full load rates of different levels are set in different intervals, and the current limiting time period and the passenger flow control value corresponding to the full load rates of different levels are obtained through calculation, so that the hierarchical control of the station current limiting measures is realized.
Further preferably, the different levels of full load comprise three levels, 120%, 130% and 140%, respectively.
The invention has the following beneficial effects:
the method for predicting and controlling the subway station arrival amount is applied to urban rail transit passenger flow organization management, the subway station arrival amount is limited through prediction control, the full load rate of subway sections is controlled, and the passenger flow congestion phenomenon is relieved, so that overlarge pressure of large passenger flow on lines or a line network is avoided. Furthermore, the subway station is guided to adopt a grading control measure for the station-entering amount in different time periods according to conditions in the actual operation management through grading the passenger flow of the section, so that the station-entering amount is more reasonable to control.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 shows a method step diagram for predicting and controlling the subway station entering amount.
Fig. 2 shows a flow chart of a method for predicting and controlling the subway station entering amount.
Fig. 3 is a schematic diagram showing a relationship between a station and an interval in embodiment 1.
Detailed Description
In order to more clearly illustrate the invention, the invention is further described below with reference to preferred embodiments and the accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. It is to be understood by persons skilled in the art that the following detailed description is illustrative and not restrictive, and is not to be taken as limiting the scope of the invention.
As shown in fig. 1, a method for predicting and controlling the arrival amount of a subway comprises the following steps:
s1: constructing a linear function formula between station arrival volume and section cross-section flow in the subway network according to the analysis of the relation between the station arrival passenger flow and the section cross-section flow in the subway network;
s2: performing linear fitting based on historical data values of station arrival amount and zone discontinuous flow to determine parameters to be estimated;
s3: calculating the target station-entering amount of the corresponding station based on the section flow of the given interval;
s4: and determining a passenger flow control strategy based on the target arrival amount.
As shown in fig. 2, the specific method steps are as follows:
step S1: according to the analysis of the relationship between the station arrival passenger flow and the section flow in the subway line network, constructing a linear function formula between the station arrival flow and the section flow in the subway line network:
considering the state transition and the hysteresis of the station arrival passenger flow propagation, adding time information in the analysis process, and constructing a linear function relationship between the two as follows:
wherein x isiThe total station entering amount of the ith station is i-1, 2, …, n; y isjThe total flow of the section in the jth interval, j is 1,2, …, m; alpha is alphajiThe proportion of the passenger flow volume which enters the station from the ith station and passes through the section of the jth interval to the total station entering volume of the ith station is shown; beta is aijThe proportion of the passenger flow entering from the ith station in the j section passenger flow is the total passenger flow of the j section; Δ tjiFor the time required for the passenger flow to reach the jth section from the ith station, Δ t may be considered for certain i and j in consideration of the punctuality of urban rail transitjiIs a constant value; x is the number ofi(t-Δtji) Is the (t- Δ t)ji) The total station entering amount of the ith station in each time interval; y isj(t) is the total flow of the cross section in the jth interval in the tth time period; m and n are natural numbers, n is the total number of stations, and m is the total number of intervals.
Step S2: the method comprises the following steps of performing linear fitting based on historical data values of station entrance amount and zone discontinuous surface flow, and determining parameters to be estimated, wherein the method specifically comprises the following steps:
s21: determining that the jth interval has the following relation
yj(t)＝αj1x1(t-Δtj1)+αj2x2(t-Δtj2)+αj3x3(t-Δtj3)+...+αjnxn(t-Δtjn)；
S22: selecting total flow y of the upper section of the jth interval in the t time period in one day from historical dataj(t) and the amount of arrival x at n stations1、x2、x3…xnAs a set of input data;
s23: selecting a plurality of sets of input data for different days from the history data as in step S22;
s24: substituting multiple sets of input data into the relational expression in step S21 to determine the parameter alpha to be estimatedj1、αj2、αj3…αjnWherein j is 1,2, …, m in sequence;
s25: determining that the ith station has the following relational expression
xi(t-Δtji)＝βi1y1(t)+βi2y2(t)+βi3y3(t)+...+βinyn(t)；
S26: selecting the total station entering amount y of the ith station in the time period t in one day from the historical dataj(t) and total flow y of cross-section in m intervals1、y2、y3…ynAs a set of input data;
s27: selecting a plurality of sets of input data for different days from the history data as in step S26;
s28: substituting multiple sets of input data into the relational expression in step S25 to determine the parameter beta to be estimatedi1、βi2、βi3…βmjWherein i is 1,2, …, n in sequence.
Step S3: and calculating the target station-entering amount of the corresponding station based on the section flow of the given interval.
S31: based on the fact that the passenger flow volume of the ith station entering the station and passing through the jth interval is equal to the passenger flow volume of the ith station entering the station in the section passenger flow of the jth interval, the following equation is obtained:
αjixi(t-Δtji)＝βijyj(t)；
s32: determining the maximum section flow y of the jth section based on the section maximum full load ratej(t)；
S33: let i equal to 1, j take the values 1,2, …, m in turn, to obtain the (t- Δ t) thj1) M station-entering amounts x of 1 st station in each time period1(t-Δt11)、x1(t-Δt21)、x1(t-Δt31)、…、x1(t-Δtm1)；
S34: selecting the m inbound traffic x1(t-Δt11)、x1(t-Δt21)、x1(t-Δt31)、…、x1(t-Δtm1) Min x of (1)1(t-Δtj1) As the 1 st station at the (t- Δ t) th stationj1) A control value of the station entering amount in each time interval;
s35: sequentially taking the value of i as 2, …, n, and repeating the steps to obtain the (t-delta t) th stationj1) And the control value of the station entering amount in each time interval is the target station entering amount of the corresponding station.
It should be noted that the accuracy of the parameter values to be estimated increases with the increase of the historical database.
Step S4: and determining a passenger flow control strategy based on the target arrival amount.
Due to the regression parameter αji、βijThe determining of passenger flow control policy based on the target inbound traffic, based on the above calculations, uses a large amount of historical data, thus comprising: forecasting and estimating the future time period of current limiting of each station every day and the corresponding passenger flow control value, and giving a station current limiting forecasting suggestion; and/or determining whether the current station needs to be limited and implementing measures for controlling the station entering amount by comparing the station entering amount in the current time period with the target station entering amount.
Further, the passenger flow control strategy also comprises the hierarchical control of station current limiting measures: setting full load rates of different levels in different intervals, and calculating to obtain current limiting time periods and passenger flow control values corresponding to the full load rates of the different levels to realize the hierarchical control of the current limiting measures of the station. In the present invention, the different levels of full load include three levels, 120%, 130%, and 140%, respectively.
Example 1
As shown in fig. 3, this embodiment includes (c) three stations and (c) two zones, namely zone 1 and zone 2.
According to the analysis of the relationship between the station arrival passenger flow and the section flow in the subway line network, constructing a linear function formula between the station arrival flow and the section flow in the subway line network:
wherein x isiThe total station entering amount of the ith station is i-1, 2, …, n; y isjThe total flow of the section in the jth interval, j is 1,2, …, m; alpha is alphajiThe proportion of the passenger flow volume which enters the station from the ith station and passes through the section of the jth interval to the total station entering volume of the ith station is shown; beta is aijThe proportion of the passenger flow entering from the ith station in the j section passenger flow is the total passenger flow of the j section; Δ tjiFor the time required for the passenger flow to reach the jth section from the ith station, Δ t may be considered for certain i and j in consideration of the punctuality of urban rail transitjiIs a constant value; x is the number ofi(t-Δtji) Is the (t- Δ t)ji) The total station entering amount of the ith station in each time interval; y isj(t) is the total flow of the cross section in the jth interval in the tth time period; m and n are natural numbers, n is the total number of stations, and m is the total number of intervals.
In this embodiment, assuming that the current time period is the t-th time period, on the premise of considering the state transition and the time lag, the following formula is given for the interval 1 and the interval 2:
for a station (I):
for station two:
for station three:
through collecting and linearly fitting historical data of the station-entering amount of 3 stations and the flow of 2 zone discontinuities, the undetermined parameter alphajiAnd betaijThe specific process is as follows:
step 1: determining that the jth interval has the following relation
yj(t)＝αj1x1(t-Δtj1)+αj2x2(t-Δtj2)+αj3x3(t-Δtj3)+...+αjnxn(t-Δtjn)；
Step 2: selecting total flow y of the upper section of the jth interval in the t time period in one day from historical dataj(t) and the amount of arrival x at n stations1、x2、x3…xnAs a set of input data;
and step 3: selecting a plurality of groups of input data on different days from the historical data as in the step 2;
and 4, step 4: substituting a plurality of groups of input data into the relational expression in the step 1 to determine the parameter alpha to be estimatedj1、αj2、αj3…αjnWherein j takes the values 1 and 2 in sequence;
and 5: determining that the ith station has the following relational expression
xi(t-Δtji)＝βi1y1(t)+βi2y2(t)+βi3y3(t)+...+βinyn(t)；
Step 6: selecting the total station entering amount y of the ith station in the time period t in one day from the historical dataj(t) and total flow y of cross-section in m intervals1、y2、y3…ynAs a set of input data;
and 7: selecting multiple sets of input data on different days from the historical data as in step 6;
and 8: substituting a plurality of groups of input data into the relational expression in the step 5 to determine the parameter beta to be estimatedi1、βi2、βi3…βmjWherein i takes the values 1,2 and 3 in sequence.
And step 9: obtaining a parameter alpha to be determined11、α12、α13、α21、α22、α23、β11、β12、β21、β22、β31And beta32。
According to the analysis of the relationship between the station entering amount and the section flow, the following equation is established for the station (i):
α11x1(t-Δt11)＝β11y1(t) (6)
α21x1(t-Δt21)＝β12y2(t) (7)
at this time, if the total loading of the given section is 140%, y is the same1(t)、y2(t) As known, two different arrival magnitudes of the first station can be calculated according to the equations 6 and 7, and x is respectively1(t-Δt11)、x1(t-Δt21) Taking min [ x ]1(t-Δt11),x1(t-Δt21)]As the control entry amount of station 1, let x1(t-Δt11) At the minimum, station 1 is at (t- Δ t)11) The maximum station-entering amount in each time period must not exceed x1(t-Δt11)。
In future station passenger flow management, the station can be guided to be (t-delta t) in advance according to the result11) Monitoring the station entering amount in each time period, and confirming whether the current station entering amount exceeds the calculated control station entering amount x or not1(t-Δt11) Corresponding current limiting measures are taken in advance, so that the purpose of predicting and controlling the station entering amount is achieved.
Similarly, for station two, the following equation holds:
α12x2(t-Δt12)＝β21y1(t) (8)
α22x2(t-Δt22)＝β22y2(t) (9)
taking min [ x ] also according to the above method2(t-Δt12),x2(t-Δt22)]As the control arrival amount of the station (c).
Similarly, the following equation holds for station c:
α13x3(t-Δt13)＝β31y1(t) (10)
α23x3(t-Δt23)＝β32y2(t) (11)
taking min [ x ] also according to the above method3(t-Δt13),x2(t-Δt23)]The control station entering amount of the station (c) is used.
Example 2
On the basis of example 1, it is assumed that the section full load is given different set values such as: 120%, 130%, 140%, the times to reach the full load of these three levels are obviously different, and are set as t1、t2、t3Then the achievable zone discontinuity flow is: y (t)1)c＝120％、y(t2)c＝130％、y(t3)c＝140％The cross section flow of three levels is used as input data, and the corresponding station entering control value and time period can be output by the method. Here, the description is given by taking the station (i) as an example:
suppose y (t)1)c＝120％In time, the station arrival amount control value of the first station is x1(t1-Δt11)c＝120％Then, it is represented as (t)1-Δt11) In each time period, the interval 1 may be slightly congested, and the station should pay attention to take measures for reducing the station entering amount.
Suppose y (t)2)c＝130％In time, the station arrival amount control value of the first station is x1(t2-Δt11)c＝130％Then, it is represented as (t)2-Δt11) A time period, interval1, medium congestion is possible, and the station is required to further reduce the station entering amount on the basis of the original limit.
Suppose y (t)3)c＝140％In time, the station arrival amount control value of the first station is x1(t3-Δt11)c＝140％Then, it is represented as (t)3-Δt11) In each time period, the interval 1 may be heavily congested, and the station should take more strict measures for limiting the station entering amount on the basis of the original limit.
In the embodiment, the subway station can be guided to take the grading control measures for the station-entering amount in different periods according to conditions in the actual operation management by grading the passenger flow (or the full load rate) of the section, so that the station-entering amount is more reasonable to control.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.

Claims (7)

1. A method for predicting and controlling the subway station entering amount is characterized by comprising the following steps:
s1: constructing a linear function formula between station entering amount and zone discontinuous surface flow in a subway network:
wherein,
xithe total station entering amount of the ith station is i-1, 2, …, n;
yjis the jth zoneTotal flow rate of the cross section at intervals, j is 1,2, …, m;
αjithe proportion of the passenger flow volume which enters the station from the ith station and passes through the section of the jth interval to the total station entering volume of the ith station is shown;
βijthe proportion of the passenger flow entering from the ith station in the j section passenger flow is the total passenger flow of the j section;
△tjithe time required for the passenger flow to reach the jth section from the ith station;
xi(t-△tji) Is the (t- Δ t)ji) The total station entering amount of the ith station in each time interval;
yj(t) is the total flow of the cross section in the jth interval in the tth time period;
n is the total number of stations, and m is the total number of intervals;
s2: performing linear fitting based on historical data values of station arrival amount and zone discontinuous flow to determine parameters to be estimated;
s3: calculating the target station-entering amount of the corresponding station based on the section flow of the given interval;
in step S3, the method specifically includes the following steps:
s31: based on the fact that the passenger flow volume of the ith station entering the station and passing through the jth interval is equal to the passenger flow volume of the ith station entering the station in the section passenger flow of the jth interval, the following equation is obtained:
αjixi(t-△tji)＝βijyj(t)；
s32: determining the maximum section flow y of the jth section based on the section maximum full load ratej(t)；
S33: let i equal to 1, j take the values 1,2, …, m in turn, to obtain the (t-. DELTA.t)j1) M station-entering amounts x of 1 st station in each time period1(t-△t11)、x1(t-△t21)、x1(t-△t31)、…、x1(t-△tm1)；
S34: selecting the m inbound traffic x1(t-△t11)、x1(t-△t21)、x1(t-△t31)、…、x1(t-△tm1) Minimum value minx of (1)1(t-△tj1) The 1 st station is at the (t-Deltat) thj1) A control value of the station entering amount in each time interval;
s35: sequentially taking the value of i as 2, …, n, and repeating the steps S33 and S34 to obtain the (t-delta t) th station of each stationj1) The control value of the station entering amount in each time interval is the target station entering amount of the corresponding station;
s4: and determining a passenger flow control strategy based on the target arrival amount.
2. A method for predicting and controlling a subway approach amount as claimed in claim 1, wherein said step S2 specifically includes the following steps:
s21: determining that the jth interval has the following relation
yj(t)＝αj1x1(t-△tj1)+αj2x2(t-△tj2)+αj3x3(t-△tj3)+...+αjnxn(t-△tjn)；
S22: selecting total flow y of the upper section of the jth interval in the t time period in one day from historical dataj(t) and the amount of arrival x at n stations1、x2、x3…xnAs a set of input data;
s23: selecting sets of input data for different days from the historical data as described in step S22;
s24: substituting the multiple sets of input data selected in S23 into the relational expression in step S21 to determine the parameter alpha to be estimatedj1、αj2、αj3…αjnWherein j is 1,2, …, m in sequence;
s25: determining that the ith station has the following relational expression
xi(t-△tji)＝βi1y1(t)+βi2y2(t)+βi3y3(t)+...+βinyn(t)；
S26: selecting the time period t in one day from the historical dataTotal station entering amount x of ith stationi(t) and total flow y of cross-section in m intervals1、y2、y3…ymAs a set of input data;
s27: selecting sets of input data for different days from the historical data as described in step S26;
s28: substituting the multiple sets of input data selected in S27 into the relational expression in step S25 to determine the parameter beta to be estimatedi1、βi2、βi3…βmjWherein i is 1,2, …, n in sequence.
3. A method for predicting and controlling the arrival amount of a subway according to claim 1, wherein said maximum loading rate of section is 140%.
4. A method for predictively controlling a subway approach traffic as claimed in claim 1, wherein in said step S4, determining a passenger flow control strategy based on a target approach traffic comprises:
forecasting and estimating the future time period of current limiting of each station every day and the corresponding passenger flow control value, and giving a station current limiting forecasting suggestion; and/or
And determining whether the current station needs to carry out current limiting and implementing measures for controlling the station entering amount by comparing the station entering amount in the current time period with the target station entering amount.
5. A method for predictively controlling the arrival volume of a subway as defined in claim 2, wherein said passenger flow control strategy further comprises a hierarchical control of station current limiting measures.
6. The method for predicting and controlling the subway station entering quantity according to claim 1, wherein full load rates of different levels are set for different intervals, and current limiting time periods and passenger flow volume control values corresponding to the full load rates of different levels are calculated to realize hierarchical control of station current limiting measures.
7. A method for predicatively controlling the arrival amount of a subway according to claim 6, wherein said different levels of full load rates comprise three levels of 120%, 130% and 140%, respectively.
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