CN111367900B - Method for calculating normal current limiting intensity of urban rail transit network based on AFC data - Google Patents
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Abstract
The invention provides a calculation method of urban rail transit network normal current limiting strength based on AFC data. The method comprises the following steps: collecting urban rail transit AFC data to obtain the number of passengers entering and the number of passengers exiting from each station in each period; according to the urban rail transit AFC data, train operation schedule information and the urban rail transit network topology structure, the number of transfer passengers of each transfer station in each period is obtained through simulation calculation; according to the number of passengers entering, the number of passengers exiting and the number of passengers transferring in each time period of each station, the indexes of the minimum number of passengers, the maximum number of passengers and the total number of passengers in each time period of each station are calculated, and the current limiting intensity and the current limiting rate of each time period of each station are calculated. The invention can provide a set of urban rail transit network normal current limiting strategy based on AFC data for urban rail transit managers, and provides technical support and decision basis for urban rail transit management departments to deal with large passenger flow and obtain normal current limiting measures.
Description
Technical Field
The invention relates to the technical field of urban rail transit current limiting optimization, in particular to a calculation method of urban rail transit network normal current limiting intensity based on AFC data.
Background
With the continuous expansion of urban scale and the continuous increase of traffic demand, a plurality of cities form a 'large urban disease' with traffic jam as a core. The urban rail transit with the name of green traffic is gradually becoming a main traffic mode of people, particularly office workers in commuter travel due to the characteristics of large capacity, high speed, low energy consumption and the like. Urban rail transit gradually becomes the backbone of urban public transit, and urban rail transit networked operation is further expanded. However, the development of urban rail transit is facing tremendous passenger pressures, especially in the early and late peak periods, due to the imbalance between oversized demand and limited passenger capacity and the irregularity in the spatial and temporal distribution of travel demand. In fact, the oversaturated passenger flow demand of urban rail transit necessarily gives rise to serious effects for passenger and train operation. On the one hand, a train with an excessively large occupancy is difficult to meet the boarding requirements of all waiting passengers on a platform, so that a large number of passengers stay on the platform for a long time to wait, and the number of waiting passengers accumulated on the platform increases. It has been found that overcrowding at a platform presents a significant security threat to passenger safety and train operation. On the other hand, the oversized boarding and alighting time is required, which directly leads to the increase of the stopping time of the train and causes delay of the train. In addition, under the condition of severe travel pressure, the delay of the partially waiting train is difficult to eliminate, and the delay can be extended continuously so as to influence the normal operation of the subsequent train. In order to reduce the pressure of large passenger flows on lines and stations, a safer and more effective passenger flow organization management method is urgently needed.
At present, a widely adopted and effective method for relieving the large passenger flow pressure of urban rail transit in China is to carry out passenger flow control, also called 'current limiting', and mainly comprises control measures of reducing the passenger arrival rate, surrounding and blocking outside the station, shunting, intercepting and the like. With the increase of urban rail transit network passenger flows, current limiting control measures have become normal in the early and late peak hours, especially in extra large cities such as Beijing, shanghai and the like. The current limiting measure comprises three elements: current limiting station, current limiting time and current limiting intensity. However, in actual passenger flow organizations, the manager usually determines the current limiting strength according to subjective experience, and lacks powerful theory and data support. At present, although some scholars have studied the current limiting strategy under the condition of large passenger flow, they usually take one line or one or several stations as study objects, and lack a passenger flow organization method for taking transfer behaviors into consideration and cooperatively limiting current for a plurality of lines and stations. Moreover, there is a lack of a current limiting method for mining urban rail transit networks based on large amounts of passenger travel data.
One urban rail transit current limiting scheme in the prior art is as follows: based on the network passenger flow demand and distribution characteristics, a multi-objective mathematical planning model with maximized passenger flow demand and conveying capacity matching degree and minimized delayed passenger flow is established from a network layer, and a Beijing urban rail transit network is taken as an object to carry out demonstration analysis. The disadvantage of this solution is: the input passenger flow volume required by each line is not acquired through actual data.
Another urban rail transit current limiting scheme in the prior art is as follows: by means of definition of equal time intervals, the urban rail transit passenger flow control optimization model based on one line is provided for urban rail transit commute lines by considering the limit of station arrival gate, namely the capacity of a train. The key current limiting stations and the current limiting time periods are identified by constructing state evaluation indexes (full load rate distribution entropy, high full load rate interval proportion, station platform crowding degree and average full load rate of arriving trains) of urban rail transit access networks and stations, and a road network cooperative current limiting model is established on the basis to determine specific current limiting stations and current limiting strength. The disadvantage of this solution is: the calculation process for obtaining the current limiting strength is complicated.
Disclosure of Invention
The embodiment of the invention provides a calculation method of urban rail transit network normal current limiting strength based on AFC data, which aims to overcome the problems in the prior art.
The method for calculating the normal current limiting strength of the urban rail transit network based on the AFC data preferably comprises the following steps:
collecting urban rail transit AFC data, and processing and counting the AFC data to obtain the number of inbound passengers and the number of outbound passengers in each period of each station;
according to the urban rail transit AFC data, train operation schedule information and the urban rail transit network topology structure, the number of transfer passengers of each transfer station in each period is obtained through simulation calculation;
according to the number of passengers entering and exiting each time interval of each station and the number of passengers transferring each time interval of each transfer station, the indexes of the minimum number of passengers, the maximum number of passengers and the total number of passengers of each station in each time interval are calculated, and then the current limiting intensity and the current limiting rate of each time interval of each station are calculated.
Preferably, the collecting the urban rail transit AFC data, and processing and counting the AFC data to obtain the number of passengers entering and passengers exiting from each station in each period, including:
the urban rail transit system is provided with intelligent card charging equipment at the entrance and exit of each station, when passengers pass through the intelligent card charging equipment, the intelligent card charging equipment records the AFC data of the passengers, the AFC data comprises information such as a passenger ID number, passenger entering stations, passenger entering time, passenger exiting stations, passenger exiting time and the like, and the AFC data of all the passengers of each station are summarized to obtain the number of entering passengers and the number of exiting passengers of each station in each period.
Preferably, the simulation calculation obtains the number of transfer passengers of each transfer station in each period according to the urban rail transit AFC data, the train operation schedule information and the urban rail transit network topology structure, and the simulation calculation comprises the following steps:
the number of passengers arriving at the station and the number of passengers arriving at the station in each time interval are obtained according to the AFC data of all passengers, and the number of passengers arriving at the station in each time interval is obtained through simulation calculation according to the number of passengers arriving at the station and the number of passengers arriving at the station in each time interval, the OD data of the passengers going out, the train running schedule information and the urban rail transit network topology structure.
Preferably, the calculating the index of the minimum number of passengers, the maximum number of passengers and the total number of passengers in each time zone according to the number of passengers in each time zone and the number of passengers out of each station and the number of passengers in each time zone of each transfer station, and further calculating the restriction intensity and restriction rate of each time zone of each station includes:
calculating the indexes of the minimum number of passengers, the maximum number of passengers and the total number of passengers of each station in each period by using a minimum-maximum equation, and carrying out normalization processing on the indexes of the minimum number of passengers, the maximum number of passengers and the total number of passengers, wherein specific parameters and symbols are defined as follows:
·x lst indicating the number of passengers entering station s on line l during period t;
·representing the minimum number of passengers entering a certain station of the urban rail transit in the period t;
·representing the maximum number of passengers entering a certain station of the urban rail transit in the period t;
·x t，sum representing the total number of passengers entering the urban rail transit station at time t;
·representing a minimum total number of passengers entering the urban rail transit network in a time period dimension;
·representing the maximum total number of passengers entering the urban rail transit network in a time period dimension;
·a weight index representing the number of passengers entering the bus at the time t;
·y lst indicating the number of passengers leaving station s on line l during period t;
·representing a minimum number of passengers leaving a station of the urban rail transit at time t;
·representing the maximum number of passengers leaving a station of urban rail transit in period t;
·y t，sum representing the total number of passengers leaving the urban rail transit station during period t;
·representing a minimum total number of passengers leaving the urban rail transit network in a time period dimension;
·representing a maximum total number of passengers leaving the urban rail transit network in a time period dimension;
·a weight index representing the number of outbound passengers in the t period;
·z lst representing the number of transfer passengers at station s on line l in period t;
·representing the minimum transfer passenger number of a certain station of urban rail transit in the period t;
·representing the maximum transfer passenger number of a certain station of urban rail transit in a period t;
·z t，sum representing the total transfer passenger number of the urban rail transit station in the period t;
·representing the minimum total transfer passenger number of the urban rail transit network in the time period dimension;
·representing the maximum total transfer passenger number of the urban rail transit network in the time period dimension;
·a weight index representing the number of passengers transferred in the t period;
·θ st a current limiting intensity value of the station s in a t period is represented;
ρ is a preset current limiting intensity threshold value, which represents the minimum current limiting intensity value of the urban rail transit when current limiting measures are implemented, and the value is 0.02;
·ρ st the flow limit rate of station s in the period t is indicated.
Calculating a time period weight index of each station by using a minimum-maximum value equation:
the three indexes of the number of passengers in the station and the number of passengers out of the station and the number of passengers in the transfer are normalized by using a minimum-maximum value equation:
according toAnd->And calculating the current limiting intensity of each station in each period by weighted summation of the normalized indexes:
wherein w is 1 ,w 2 ,w 3 Is the weighting coefficient of three indexes;
calculating the flow limiting rate of each station in each period according to the flow limiting intensity:
ρ is a preset current limiting intensity threshold.
According to the technical scheme provided by the embodiment of the invention, after cleaning, preprocessing and counting the AFC data, the influence factors of the current limiting strength are determined, the current limiting measures are represented by selecting proper indexes from the influence factors, and finally, the corresponding current limiting strength and current limiting rate calculation method is designed. The method can be used for daily passenger flow management and control of the urban rail transit network.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an implementation principle of a method for calculating a normal current limiting strength of an urban rail transit network based on AFC data according to an embodiment of the present invention.
Detailed Description
For the purpose of facilitating an understanding of the embodiments of the invention, reference will now be made to the drawings of several specific embodiments illustrated in the drawings and in no way should be taken to limit the embodiments of the invention.
Example 1
Based on the background technology, the embodiment of the invention discloses an urban rail transit network normal state current limiting intensity calculation method based on AFC data by collecting the passenger taking urban rail transit travel in-and-out data through a AFC (Automatic Fare Collection) system, and provides urban rail transit network normal state current limiting measures from the aspects of the number of in-and-out passengers, the number of transfer passengers, the number of out-and-out passengers and the like. The number of the transfer passengers is calculated by referring to a multi-agent-based simulation method adopted by Yang et al (2019). The method provides technical support and decision basis for the urban rail transit management department to deal with large passenger flow and obtain normal current limiting measures.
The implementation principle schematic diagram of the calculation method of the urban rail transit network normal current limiting strength based on the AFC data provided by the embodiment of the invention is shown in fig. 1, and the method comprises the following processing steps:
step 1, collecting urban rail transit AFC (Automatic Fare Collection System, referring to an automatic fare collection system) data, and processing and counting the data to obtain the number of passengers entering and passengers exiting from each station in each period.
The urban rail transit system is provided with intelligent card charging equipment at the entrance and exit of each station, passengers can record AFC data of the passengers when passing through the equipment, the AFC data comprises information such as passenger ID numbers, passenger entering stations, passenger entering time, passenger exiting stations, passenger exiting time and the like, the AFC data of all the passengers of each station are summarized, and the number of passengers entering each station and the number of passengers exiting each time period are obtained.
And step 2, according to the urban rail transit AFC data, train operation schedule information and the urban rail transit network topology structure, the number of transfer passengers of each transfer station in each period is obtained through simulation calculation.
Since the smart card data only contains the position and time information of the passenger getting on/off the bus station, the number of the passengers getting in and out of the bus station and the number of passengers getting out of the bus station in each bus station and each time period can be simply obtained. However, considering the uncertainty of the passenger transfer process, it is difficult to directly obtain the number of transfer passengers per transfer station from the data. The invention refers to a simulation process based on multiple intelligent agents, and combines the passenger travel OD (Origin to Destination, starting point to end point) data, train operation schedule information and urban rail transit network topology structure, so that the number of transfer passengers of each transfer station in each period is obtained through simulation calculation.
Because each line in the urban rail transit network has directionality, N is defined to represent a finite set of sites, (O, D) to represent an OD pair from O site to D site, where O, D e N. Further, p defines a passenger. It is thus known that passengers have seven different states: just entering the urban rail transit network, going from an entrance to a station waiting area, arriving at the station waiting area, taking trains on, getting off at a transfer station for preparation for transfer, getting off at a station of a destination station and checking out tickets. Passengers may not have a transfer in the urban rail transit network or more than one transfer may occur, so not all passengers contain these seven states. The state of the passenger is discretized into simulation step length delta T and T by using the simulation clock T b And t e Respectively represent the starting and ending time of simulation, K represents the number of simulation cycles, T c Represents the length of each simulation cycle time, where k= (t e -t b )/T c . By collected AFC data, baseAnd matching the motion states of the passengers in the urban rail transit according to the OD data of the passengers to obtain paths of all the passengers, and counting the inbound quantity, outbound quantity and transfer quantity of the stations in each simulation period.
The simulation calculation can approximate the selection behavior of passengers in the urban rail transit network, and the proposed simulation parameters are verified through actual measurement data and a large amount of historical data.
And step 3, carrying out normalization processing on three indexes of each station in each period, and determining a reasonable and effective current limiting intensity calculation method.
The division of time periods may be peak periods, off-peak periods, or a fixed period of time, such as 1-2 hours, etc. The three indexes comprise the minimum passenger number, the maximum passenger number and the total passenger number, and because the influence degrees of the three indexes are different, the three indexes of each station in each period are normalized by referring to a minimum-maximum value equation, and specific parameters and signs are defined as follows:
·x lst indicating the number of passengers entering station s on line l during period t;
·representing the minimum number of passengers entering a certain station of the urban rail transit in the period t;
·representing the maximum number of passengers entering a certain station of the urban rail transit in the period t;
·x t，sum representing the total number of passengers entering the urban rail transit station at time t;
·representing a minimum total number of passengers entering the urban rail transit network in a time period dimension;
·representing the maximum total number of passengers entering the urban rail transit network in a time period dimension;
·a weight index representing the number of passengers entering the bus at the time t;
·y lst indicating the number of passengers leaving station s on line l during period t;
·representing a minimum number of passengers leaving a station of the urban rail transit at time t;
·representing the maximum number of passengers leaving a station of urban rail transit in period t;
·y t，sum representing the total number of passengers leaving the urban rail transit station during period t;
·representing a minimum total number of passengers leaving the urban rail transit network in a time period dimension;
·representing a maximum total number of passengers leaving the urban rail transit network in a time period dimension;
·a weight index representing the number of outbound passengers in the t period;
·z lst representing the number of transfer passengers at station s on line l in period t;
·representing the minimum transfer passenger number of a certain station of urban rail transit in the period t;
·representing the maximum transfer passenger number of a certain station of urban rail transit in a period t;
·z t，sum representing the total transfer passenger number of the urban rail transit station in the period t;
·representing the minimum total transfer passenger number of the urban rail transit network in the time period dimension;
·representing the maximum total transfer passenger number of the urban rail transit network in the time period dimension;
·a weight index representing the number of passengers transferred in the t period;
·θ st a current limiting intensity value of the station s in a t period is represented;
delta represents the minimum current limiting intensity value of the urban rail transit when current limiting measures are implemented, and the value is 0.02;
·ρ st the flow limit rate of station s in the period t is indicated.
Calculating a time period weight index of each station by using a minimum-maximum value equation:
the three indexes of the number of passengers in the station and the number of passengers out of the station and the number of passengers in the transfer are normalized by using a minimum-maximum value equation:
and 4, calculating the current limiting intensity of each station in each period.
According toAnd->And calculating the current limiting intensity of each station in each period by weighted summation of the normalized indexes:
wherein w is 1 ,w 2 ,w 3 Is the weighting coefficient of the three indexes.
And 5, calculating the flow limiting rate of each station in each period.
Urban railThe traffic flow limiting intensity refers to the force of implementing the flow limiting measure. The current limiting intensity of each station of the urban rail transit network is calculated based on the AFC data, and the current limiting intensity value theta is calculated according to the current limiting intensity value theta st It can be intuitively found whether a current limiting measure needs to be taken in the s station t period: when theta is as st When delta is less than or equal to 0, no current limiting measure is needed, and the current limiting rate is 0; when theta is as st When delta is larger than delta, a current limiting measure is needed, and the current limiting rate is theta st - δ. Delta is a preset current limiting intensity threshold.
Example two
Based on the intelligent card data collected by the Beijing urban rail transit network AFC system, the current limiting condition of 238 stations in the Beijing urban rail transit network in the working days is analyzed and calculated. The Beijing urban rail transit network topology and the passenger traffic data used by the invention are for 20 days (Saturday) 2 in 2014. The present invention is described by calculating the current limiting intensity per time period (hour) per station by the calculation method proposed by the present invention, but is not limited thereto.
Step 1, cleaning and preprocessing the collected AFC data of passengers to obtain the number of passengers entering each station and each time period and the number of passengers exiting each station;
the time dimension is divided by taking the hour as the time step, so that the number of passengers entering each station per hour and the number of passengers exiting each station can be obtained. Table 1 below lists the number of inbound passengers and the number of outbound passengers for 5 stops of urban rail transit in beijing city.
Table 1 number of passengers entering and number of passengers exiting are exemplified
Step 2, obtaining the number of transfer passengers per station and per hour;
the number of transfer passengers per hour at each station is calculated based on the multi-agent simulation process, and table 2 below lists the number of transfer passengers at 10 stations of the urban rail transit in beijing city.
TABLE 2 transfer passenger flows per station per hour
Step 3, carrying out normalization processing on three indexes of the minimum passenger number, the maximum passenger number and the total passenger number of each station in each period, and determining a reasonable and effective current limiting intensity calculation method;
wherein,,
and 4, calculating the current limiting intensity of each station in each period.
Wherein w is 1 ,w 2 ,w 3 Is the weighting coefficient of three indexes, and is set as w 1 ＝0.7,w 2 ＝0.1,w 3 ＝0.2。
And 5, calculating the flow limiting rate of each station in each period.
Table 3 early peak period, current limiting strength, current limiting rate and ranking of 20 stops in beijing city
Table 4 peak evening period, current limiting strength, current limiting rate and ranking of 20 stops in beijing city
The calculation result shows that the station current limiting intensity distribution in the early peak period is different from that in the late peak period, and the current limiting intensity is the largest between 7:00-9:00 and 17:00-19:00.
In the early peak period, 61 stations need to implement current limiting measures between 7:00 and 8:00, 57 stations need to implement current limiting measures before 8:00 and 9:00, and stations with high current limiting strength are mainly concentrated in suburban areas (such as Tiantong yuan, north, apple orchards and the like). Moreover, stations with high current limiting strength gradually shift to the city center over time. By observation, stations that first began to perform the flow restriction were Tiantong yuan north station and Tiantong yuan station, which also ended the flow restriction at the latest. Stations with high current limiting strength during 7:00-8:00 are more than 8:00-9:00.
In the late peak period, 59 stations need to implement current limiting measures between 17:00 and 18:00, 33 stations need to implement current limiting measures before 18:00 and 19:00, and stations with high current limiting strength are mainly concentrated in CBD (such as national trade, national gate building and the like), throat areas (Western two flag, great hope road and the like) for connecting urban centers and suburban large-scale residences. Further, stations with high current limiting strength gradually shift from the urban center to suburban areas over time. Notably, the current limiting intensity values of the western-flag station are relatively large in the morning and evening peak hours, because the station is not only a transfer station (located in urban and rural junctions), but also is close to a mid-guan software garden, and has a large number of commuters.
Overall, the current limiting intensity of the rail transit system is greater during the early peak than during the late peak, which is closely related to the commuter being on duty in the morning (typically 9:00 commuter).
The calculation method based on the AFC data provided by the invention is used for carrying out example verification on the Beijing urban rail transit network to calculate and analyze the urban rail transit network current limiting intensity. The result shows that the current limiting intensity and the distribution rule accord with the tide travel rule of urban commuters. In the early peak period, stations with high current limiting strength are mainly concentrated in suburbs (such as Tiantong yuan, tiantong yuan north, apple orchards and the like); in the late peak period, stations with high current limiting strength are mainly concentrated in CBDs (such as national trade) and throat areas (such as Western two flag, great hope road and the like) connecting the urban center and suburban large residences. The above conclusions are in line with the actual situation, which means that the proposed method is feasible and reasonable.
Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.
Those of ordinary skill in the art will appreciate that: the modules in the apparatus in the embodiments may be distributed in the apparatus in the embodiments according to the description of the embodiments, or may be located in one or more apparatuses different from the present embodiments with corresponding changes. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.
In summary, the embodiment of the invention determines the influencing factor of the current limiting strength by cleaning, preprocessing and counting the AFC data, selects a proper index from the influencing factor to represent the current limiting measure, and finally designs a corresponding current limiting strength calculation method. The method can be used for daily passenger flow management and control of the urban rail transit network.
The method of the embodiment of the invention can be used for cooperatively optimizing the schedule and the current limiting measure of the urban rail transit train, reasonably setting the passenger flow management measure and the schedule running scheme, improving the operation safety and the passenger safety in the urban rail transit system, reducing the long-time retention of partial station passengers and improving the fairness of each station.
By applying the method provided by the embodiment of the invention, reasonable and effective peak current limiting measures can be obtained, the safety of the interior of passenger rail traffic (mainly on a platform and a train) can be improved, and the potential risk caused by a passenger flow supersaturation state is reduced; the train schedule and the current limiting measures can be considered at the same time, and the coordination of train operation and passenger flow management can be improved.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (3)
1. A calculation method of urban rail transit network normal current limiting strength based on AFC data is characterized by comprising the following steps:
collecting urban rail transit AFC data, and processing and counting the AFC data to obtain the number of inbound passengers and the number of outbound passengers in each period of each station;
according to the urban rail transit AFC data, train operation schedule information and the urban rail transit network topology structure, the number of transfer passengers of each transfer station in each period is obtained through simulation calculation;
according to the number of passengers entering and exiting each time period of each station and the number of passengers transferring each time period of each transfer station, the minimum number of passengers, the maximum number of passengers and the total number of passengers of each station in each time period are calculated, and then the current limiting intensity and the current limiting rate of each time period of each station are calculated; comprising the following steps:
the minimum number of passengers, the maximum number of passengers and the total number of passengers in each station in each period are calculated by using a minimum-maximum equation, the minimum number of passengers, the maximum number of passengers and the total number of passengers are normalized, and specific parameters and signs are defined as follows:
·x lst indicating the number of passengers entering station s on line l during period t;
·representing the minimum number of passengers entering a certain station of the urban rail transit in the period t;
·representing the maximum number of passengers entering a certain station of the urban rail transit in the period t;
·x t，sum representing the total number of passengers entering the urban rail transit station at time t;
·representing a minimum total number of passengers entering the urban rail transit network in a time period dimension;
·representing the maximum total number of passengers entering the urban rail transit network in a time period dimension;
·a weight representing the number of passengers entering the bus during period t;
·y lst indicating the number of passengers leaving station s on line l during period t;
·representing a minimum number of passengers leaving a station of the urban rail transit at time t;
·representing the maximum number of passengers leaving a station of urban rail transit in period t;
·y t，sum representing the total number of passengers leaving the urban rail transit station during period t;
·representing a minimum total number of passengers leaving the urban rail transit network in a time period dimension;
·representing a maximum total number of passengers leaving the urban rail transit network in a time period dimension;
·a weight representing the number of outbound passengers in period t;
·z lst representing the number of transfer passengers at station s on line l in period t;
·representing the minimum transfer passenger number of a certain station of urban rail transit in the period t;
·representing the maximum transfer passenger number of a certain station of urban rail transit in a period t;
·z t，sum representing the total transfer passenger number of the urban rail transit station in the period t;
·representing a time period dimensionThe minimum total transfer passenger number of the urban rail transit network;
·representing the maximum total transfer passenger number of the urban rail transit network in the time period dimension;
·a weight indicating the number of transfer passengers in the t period;
·θ st a current limiting intensity value of the station s in a t period is represented;
delta is a preset current limiting intensity threshold value, and represents the minimum current limiting intensity value of the urban rail transit when current limiting measures are implemented, and the value is 0.02;
·ρ st representing the flow limit rate of station s in period t;
calculating the time period weight of each station by using a minimum-maximum value equation:
normalization of the number of passengers in-coming and passengers out-coming and passengers in transit is performed using a min-max equation:
according toAnd->And calculating the restriction intensity per station per period by a weighted sum of the normalized number of inbound passengers, the normalized number of outbound passengers, and the normalized number of transfer passengers:
wherein w is 1 ,w 2 ,w 3 Is a weighting coefficient for the number of inbound passengers, the number of outbound passengers, and the number of transfer passengers;
calculating the flow limiting rate of each station in each period according to the flow limiting intensity:
delta is a preset current limiting intensity threshold.
2. The method of claim 1, wherein collecting the urban rail transit AFC data and processing and counting the AFC data to obtain the number of inbound passengers and the number of outbound passengers per station per period, comprises:
the urban rail transit system is provided with intelligent card charging equipment at the entrance and exit of each station, when passengers pass through the intelligent card charging equipment, the intelligent card charging equipment records the AFC data of the passengers, the AFC data comprises the ID numbers of the passengers, the arrival time of the passengers at the station and the arrival time information of the passengers at the station, and the AFC data of all the passengers at each station are summarized to obtain the number of the passengers at each time interval of each station and the number of the passengers at each station.
3. The method according to claim 1, wherein the step of calculating the number of transfer passengers per transfer station per time period based on the urban rail transit AFC data, the train operation schedule information, and the urban rail transit network topology by simulation comprises:
the number of passengers arriving at the station and the number of passengers arriving at the station in each time interval are obtained according to the AFC data of all passengers, and the number of passengers arriving at the station in each time interval is obtained through simulation calculation according to the number of passengers arriving at the station and the number of passengers arriving at the station in each time interval, the OD data of the passengers going out, the train running schedule information and the urban rail transit network topology structure.
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| CN108876064A (en) * | 2018-08-23 | 2018-11-23 | 北京交通大学 | Urban mass transit network key station recognition methods based on the volume of the flow of passengers |
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| CN108550098A (en) * | 2018-04-24 | 2018-09-18 | 西南交通大学 | A kind of urban rail transit network passenger flow current-limiting method |
| CN108876064A (en) * | 2018-08-23 | 2018-11-23 | 北京交通大学 | Urban mass transit network key station recognition methods based on the volume of the flow of passengers |
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