CN113393355B - Rail transit relative passenger flow distribution calculation method, system, electronic equipment and medium - Google Patents
Rail transit relative passenger flow distribution calculation method, system, electronic equipment and medium Download PDFInfo
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Abstract
The invention provides a method, a system, electronic equipment and a medium for calculating relative passenger flow distribution of rail transit, wherein the method comprises the following steps: acquiring passenger flow data; according to the passenger flow data, calculating to obtain a passenger flow distribution function; according to the passenger flow data, calculating to obtain an average passenger flow distribution function; according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function; obtaining a track traffic relative passenger flow distribution calculation conclusion according to the relative passenger flow distribution function; the invention realizes the overall consideration of the passenger flow data in the waiting area and the transportation means by comprehensively considering the passenger flow density of the waiting area and the passenger flow density data of the transportation means, and can accurately reflect the passenger flow congestion condition during transfer.
Description
Technical Field
The present invention relates to the field of rail traffic information technologies, and in particular, to a method, a system, an electronic device, and a medium for calculating relative passenger flow distribution of rail traffic.
Background
Along with the acceleration of urban process and the formation of rail transit networking, rail transit important stations and hub stations often have station waiting and transfer congestion aggravation in usual times and in the morning and evening peaks, thereby affecting station operation organization and train transportation efficiency. With development and application of information technology, the station PIS system and the vehicle-mounted PIS system realize release of train arrival and operation information, and part of cities and lines are also added with dynamic display of train passenger flow density data, but the prior art has the following defects:
In the prior art, the acquisition and analysis are carried out from a single dimension of the passenger flow density of the station platform and the passenger flow density data of the train carriage. On one hand, the platform passenger flow density and the train carriage passenger flow density data can not realize the linkage of train-ground data, and are associated and integrally operated through a driving organization, so that the actual conditions of the on-off links are difficult to reflect; on the other hand, in the aspect of calculating the passenger flow crowdedness index, factors such as the waiting area of a station platform, the carriage area, the change of passenger flow with time and the like cannot be considered, so that the final calculated result has relatively single meaning on guiding the transfer of the upper carriage and the lower carriage.
Therefore, various factors of the congestion of passengers getting on and off the platform are difficult to comprehensively reflect in the prior art, accurate calculation is difficult to be carried out on the congestion degree of the passengers aiming at the conditions of the riding links of the oversized platform and the like, and the efficiency of the transfer organization of getting on and off the platform is not facilitated.
Disclosure of Invention
Aiming at the problems existing in the prior art, the embodiment of the invention provides a method, a system, electronic equipment and a medium for calculating the relative passenger flow distribution of rail transit.
The invention provides a method for calculating the distribution of relative passenger flow of rail transit, which comprises the following steps:
acquiring passenger flow data;
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
According to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a collection of passenger flow for a plurality of regions within the vehicle, and a collection of areas for a plurality of regions within the vehicle.
According to the method for calculating the relative passenger flow distribution of the rail transit, the step of acquiring the passenger flow data comprises the following steps:
acquiring passenger flow data corresponding to a specific vehicle; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
The step of acquiring the specific waiting area data includes:
dividing a specific waiting area into m 'waiting areas, respectively collecting real-time passenger flow densities of m set waiting areas in the m' waiting areas to form a first passenger flow density set which is recorded as { x } i |i∈[1，m]-a }; the areas of m set waiting areas in the m' waiting areas are respectively collected to form a first area set which is marked as { s } i |i∈[1，m]}；
Wherein m' is an integer greater than 1; i is an integer; x is x i For real time in the ith waiting areaPassenger flow density; s is(s) i An area of the ith waiting area; m is a positive integer not greater than m';
the step of acquiring the specific vehicle data includes:
dividing a specific vehicle into n 'vehicle regions, respectively collecting real-time passenger flow densities of n set vehicle regions in the n' vehicle regions to form a second passenger flow density set, and recording as { y } j |j∈[1，n]-a }; the areas of n set vehicle areas in the n' vehicle areas are respectively collected to form a second area set which is marked as { t } j |j∈[1，n]}；
Wherein n' is an integer greater than 1; j is an integer; y is j Real-time passenger flow density in the jth vehicle region; t is t j An area that is the jth vehicle region; n is a positive integer not greater than n';
According to the method for calculating the relative passenger flow distribution of the rail transit, which is provided by the invention, the step of calculating the average passenger flow distribution function according to the passenger flow data comprises the following steps:
calculating to obtain an average passenger flow distribution function according to passenger flow data corresponding to a specific vehicle; the step of calculating the average passenger flow volume distribution function comprises the following steps:
calculating a passenger flow volume distribution function S in an ith waiting area through a first formula 1i The method comprises the steps of carrying out a first treatment on the surface of the The first formula is:
S 1i ＝x i ×s i
calculating a passenger flow volume distribution function S in the jth vehicle region through a second formula 2j The method comprises the steps of carrying out a first treatment on the surface of the The second formula is:
S 2j ＝y j ×t j
calculating an average passenger flow volume distribution function S through a third formula; the third formula is:
according to the method for calculating the relative passenger flow distribution of the rail transit, which is provided by the invention, the step of calculating the passenger flow distribution function according to the passenger flow data comprises the following steps:
according to passenger flow data corresponding to a specific vehicle, calculating to obtain a passenger flow distribution function;
the step of calculating the passenger flow volume distribution function comprises the following steps:
if n is less than or equal to m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a fourth formula i 'A'; the fourth formula is:
Wherein the waiting area corresponding to the jth vehicle area comprises an ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′
if n > m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a sixth formula i 'A'; the sixth formula is:
the set I is a set of sequence numbers j of the vehicle area corresponding to the ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′。
according to the method for calculating the relative passenger flow distribution of the rail transit, which is provided by the invention, the step of calculating the relative passenger flow distribution function according to the average passenger flow distribution function and the passenger flow distribution function comprises the following steps:
calculating the relative passenger flow volume distribution function theta of the ith waiting area by a seventh formula i The method comprises the steps of carrying out a first treatment on the surface of the The seventh formula is:
wherein delta is a set adjustment factor;
the adjustment factor delta is calculated by an eighth formula; the eighth formula is:
wherein f (x) is a set passenger flow volume function with an independent variable of time, and f (x) is the passenger flow volume at the moment x; t is t 1 The time when the vehicle starts to operate; t is t 2 The time when the vehicle stops operating; t is the current moment; t' is the set period end time.
According to the method for calculating the relative passenger flow distribution of the rail transit, the waiting area is an area where a vehicle stops through; the vehicle is the specific vehicle with the shortest arrival time at the waiting area.
The invention also provides a relative passenger flow distribution computing system of the rail transit, which comprises an acquisition module and a passenger flow density analysis module;
the acquisition module comprises an acquisition terminal; the acquisition terminal is arranged in a waiting area and a traffic tool area and can acquire passenger flow data;
the passenger flow density analysis module can:
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a collection of passenger flow for a plurality of regions within the vehicle, and a collection of areas for a plurality of regions within the vehicle.
The invention provides a relative passenger flow distribution computing system of rail transit, which also comprises an ATS analysis module, a data processing module and a display module;
the ATS analysis module can analyze and obtain the information of the upcoming arrival times of the specific traffic tool to be analyzed;
the data processing module can receive the passenger flow data and the information of the upcoming arrival times of the specific vehicles and extract the passenger flow data corresponding to the specific vehicles; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
the passenger flow density analysis module can calculate out relative passenger flow distribution functions corresponding to the specific vehicles and the specific waiting areas according to the specific waiting area data and the specific vehicle data, and obtain display information corresponding to the specific vehicles and the specific waiting areas according to the relative passenger flow distribution functions corresponding to the specific vehicles and the specific waiting areas;
the display module comprises a display terminal; the display terminal is arranged in the waiting area and/or the vehicle area and can display information;
the data processing module can also receive display information and distribute the display information to a display terminal of the display module.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the steps of the rail transit relative passenger flow distribution calculating method according to any one of the above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the rail transit relative passenger flow distribution calculation method as described in any one of the above.
According to the method, the system, the electronic equipment and the medium for calculating the relative passenger flow distribution of the rail transit, the passenger flow data in the waiting area and the transportation means are realized by comprehensively considering the passenger flow density of the waiting area and the passenger flow density data of the transportation means, and the passenger flow congestion condition during transfer can be accurately reflected.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for calculating the relative passenger flow distribution of rail transit;
FIG. 2 is a schematic diagram of a track traffic relative passenger flow distribution computing system provided by the present invention;
FIG. 3 is a schematic diagram of a relative passenger flow distribution computing system of rail transit according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a network structure of a relative passenger flow distribution computing system for rail transit provided by an embodiment of the present invention;
FIG. 5 is a schematic flow chart of a processing method of a rail transit relative passenger flow distribution computing system provided by an embodiment of the invention;
FIG. 6 is a diagram showing the effect of the congestion index of a platform and a train according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device provided by the present invention.
Reference numerals:
11: an acquisition module; 12: an ATS parsing module;
13: a data processing module; 14: a passenger flow density analysis module;
15: a display module; 21: a station server;
22: a platform PIS broadcasting controller; 23: station exchanges;
24: a station; 25: an edge intelligent terminal;
26: a carriage; 27: a vehicle-mounted display screen;
28: station AP 29: vehicle-mounted camera.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The method for calculating the relative passenger flow distribution of the rail transit is described below with reference to the accompanying drawings.
As shown in fig. 1, the present embodiment provides a method for calculating relative passenger flow distribution of rail transit, including:
step 1, acquiring passenger flow data;
step 2, calculating to obtain a passenger flow distribution function according to the passenger flow data;
step 3, calculating to obtain an average passenger flow distribution function according to the passenger flow data;
step 4, calculating a relative passenger flow distribution function according to the average passenger flow distribution function and the passenger flow distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a collection of passenger flow for a plurality of regions within the vehicle, and a collection of areas for a plurality of regions within the vehicle.
The beneficial effects of this embodiment lie in:
by comprehensively considering the passenger flow density of the waiting area and the passenger flow density data of the vehicles, the passenger flow data in the waiting area and the vehicles can be realized, and the passenger flow congestion condition during transfer can be accurately reflected.
According to the above embodiment, in the present embodiment:
the step of obtaining the passenger flow data comprises the following steps:
acquiring passenger flow data corresponding to a specific vehicle; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
the step of acquiring the specific waiting area data includes:
dividing a specific waiting area into m 'waiting areas, respectively collecting real-time passenger flow densities of m set waiting areas in the m' waiting areas to form a first passenger flow density set which is recorded as { x } i |i∈[1，m]-a }; the areas of m set waiting areas in the m' waiting areas are respectively collected to form a first area set which is marked as { s } i |i∈[1，m]}；
Wherein m' is an integer greater than 1; i is an integer; x is x i The real-time passenger flow density in the ith waiting area; s is(s) i An area of the ith waiting area; m is a positive integer not greater than m';
the step of acquiring the specific vehicle data includes:
the particular vehicle is divided into n' vehicle regions, Respectively collecting the real-time passenger flow densities of n set vehicle areas in the n' vehicle areas to form a second passenger flow density set which is recorded as { y } j |j∈[1，n]-a }; the areas of n set vehicle areas in the n' vehicle areas are respectively collected to form a second area set which is marked as { t } j |j∈[1，n]}；
Wherein n' is an integer greater than 1; j is an integer; y is j Real-time passenger flow density in the jth vehicle region; t is t j An area that is the jth vehicle region; n is a positive integer not greater than n';
the beneficial effects of this embodiment lie in:
the factors such as the waiting area of the station platform, the carriage area, the change of the passenger flow with time and the like are fully considered, the calculation result is accurate, and the method has very strong guiding significance on the condition of the up-down passenger flow crowding and the passenger flow evacuation of the train at the calculation time point.
According to the above embodiment, in the present embodiment:
the step of calculating the average passenger flow distribution function according to the passenger flow data comprises the following steps:
calculating to obtain an average passenger flow distribution function according to passenger flow data corresponding to a specific vehicle; the step of calculating the average passenger flow volume distribution function comprises the following steps:
calculating a passenger flow volume distribution function S in an ith waiting area through a first formula 1i The method comprises the steps of carrying out a first treatment on the surface of the The first formula is:
S 1i ＝x i ×s i
calculating a passenger flow volume distribution function S in the jth vehicle region through a second formula 2j The method comprises the steps of carrying out a first treatment on the surface of the The second formula is:
S 2j ＝y j ×t j
calculating an average passenger flow volume distribution function S through a third formula; the third formula is:
the beneficial effects of this embodiment lie in:
the factors such as the waiting area of the station platform, the carriage area, the change of the passenger flow with time and the like are fully considered, the calculation result is accurate, and the method has very strong guiding significance on the condition of the up-down passenger flow crowding and the passenger flow evacuation of the train at the calculation time point.
According to any of the embodiments described above, in the present embodiment:
the step of calculating the passenger flow distribution function according to the passenger flow data comprises the following steps:
according to passenger flow data corresponding to a specific vehicle, calculating to obtain a passenger flow distribution function;
the step of calculating the passenger flow volume distribution function comprises the following steps:
if n is less than or equal to m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a fourth formula i 'A'; the fourth formula is:
wherein the waiting area corresponding to the jth vehicle area comprises an ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′
if n > m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a sixth formula i 'A'; the sixth formula is:
the set I is a set of sequence numbers j of the vehicle area corresponding to the ith waiting area;
by a fifth formulaCalculating a passenger flow volume distribution function Z of the ith waiting area i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′。
the beneficial effects of this embodiment lie in:
by subdividing the waiting area, the method for calculating the passenger flow distribution function of the congestion index under different corresponding relations between the waiting area and the vehicle area is discussed, so that the application range of the method is widened, and a hardware system can be matched more flexibly.
According to any of the embodiments described above, in the present embodiment:
the step of calculating the relative passenger flow distribution function according to the average passenger flow distribution function and the passenger flow distribution function comprises the following steps:
calculating the relative passenger flow volume distribution function theta of the ith waiting area by a seventh formula i The method comprises the steps of carrying out a first treatment on the surface of the The seventh formula is:
wherein delta is a set adjustment factor;
the adjustment factor delta is calculated by an eighth formula; the eighth formula is:
wherein f (x) is a set passenger flow volume function with an independent variable of time, and f (x) is the passenger flow volume at the moment x; t is t 1 The time when the vehicle starts to operate; t is t 2 The time when the vehicle stops operating; t is the current moment; t' is the set period end time.
The beneficial effects of this embodiment lie in:
by adding the adjustment factors, the influence of the passenger flow change in the peak/low peak period on the congestion index is further considered, and the accuracy of the conclusion is improved.
According to any of the embodiments described above, in the present embodiment:
the step of obtaining the track traffic relative passenger flow distribution calculation conclusion according to the relative passenger flow distribution function comprises single critical value analysis or multi-critical value analysis;
the single threshold analysis includes:
setting a critical value and a relative passenger flow volume distribution function theta for the ith waiting area i And (3) judging: if theta is i If the traffic is not greater than the critical value, the calculation conclusion of the relative passenger flow distribution of the track traffic in the ith waiting area is comfortable; if theta is i If the traffic is larger than the critical value, the calculation conclusion of the relative passenger flow distribution of the track traffic in the ith waiting area is crowded;
the multi-threshold analysis includes:
setting a critical values, wherein the a critical values are theta i The whole value range of (2) is divided into a+1 intervals; the a+1 intervals are marked as a first interval to an a+1 interval from small to large according to the numerical range;
Judging the relative passenger flow volume distribution function theta of the ith waiting area i The interval is according to theta i The section corresponds to the ith waiting area to obtain a calculation conclusion of the relative passenger flow distribution of the rail transit in the ith waiting area;
the first interval to the a+1th interval correspond to the set first conclusion to the a+1th conclusion; and the comfort level of the first conclusion to the a+1 conclusion is gradually decreased, and the crowding level is gradually increased.
The beneficial effects of this embodiment lie in:
by adopting the technical means of single/multiple critical value judgment, the method is compatible with different hardware calculation forces and different judgment precision requirements, and the applicability of the method is enhanced.
According to any of the embodiments described above, in the present embodiment:
the waiting area is an area where vehicles pass through and stop; the vehicle is the specific vehicle with the shortest arrival time at the waiting area.
The beneficial effects of this embodiment lie in:
by preferentially calculating the specific vehicles with the shortest arrival time at the waiting area, the method for calculating the relative passenger flow distribution of the rail transit in the embodiment can timely and comprehensively calculate the congestion degree of each vehicle and the corresponding waiting area.
The track traffic relative passenger flow distribution computing system provided by the invention is described below, and the track traffic relative passenger flow distribution computing system described below and the track traffic relative passenger flow distribution computing method described above can be correspondingly referred to each other.
As shown in fig. 2, the track traffic relative passenger flow distribution computing system provided in this embodiment includes an acquisition module 11 and a passenger flow density analysis module 14;
the acquisition module 11 comprises an acquisition terminal; the acquisition terminal is arranged in a waiting area and a traffic tool area and can acquire passenger flow data;
the passenger flow density analysis module 14 is capable of:
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a collection of passenger flow for a plurality of regions within the vehicle, and a collection of areas for a plurality of regions within the vehicle.
The beneficial effects of this embodiment lie in:
by adopting the technical means of finely dividing and collecting data, the problem that passenger flow in a waiting area and a traffic tool area are unevenly distributed when rail transit is transferred is solved, but the traditional congestion measuring and calculating method only considers the whole congestion degree is solved.
According to the above embodiment, in the present embodiment:
the embodiment also comprises an ATS analysis module 12, a data processing module 13 and a display module 15;
the ATS analyzing module 12 can analyze and obtain the information of the upcoming train number of the specific vehicle to be analyzed;
the data processing module 13 can receive the passenger flow data and the information of the upcoming train number of the specific vehicle, and extract the passenger flow data corresponding to the specific vehicle; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
the passenger flow density analysis module 14 can calculate a relative passenger flow distribution function corresponding to the specific vehicle and the specific waiting area according to the specific waiting area data and the specific vehicle data, and obtain display information corresponding to the specific vehicle and the specific waiting area according to the relative passenger flow distribution function corresponding to the specific vehicle and the specific waiting area;
The display module 15 includes a display terminal; the display terminal is arranged in the waiting area and/or the vehicle area and can display information;
the data processing module 13 is also capable of receiving display information and distributing it to the display terminals of the display module 15.
The beneficial effects of this embodiment lie in:
by adopting the technical means of finely dividing and collecting data, the problem that passenger flow in a waiting area and a traffic tool area are unevenly distributed when rail transit is transferred is solved, but the traditional congestion measuring and calculating method only considers the whole congestion degree is solved.
Embodiments of a method and a system for analyzing and processing the passenger flow density of rail transit station vehicles in a public rail transit scene are provided below, specifically as follows.
Fig. 3 shows an urban rail transit relative passenger flow distribution computing system in the present embodiment, including: the system comprises a passenger flow density acquisition module 11, a data processing module 13, a station vehicle passenger flow density analysis module 14, an ATS analysis module 12 and a station vehicle passenger flow congestion index display module 15.
The passenger flow density acquisition module 11 acquires images acquired by intelligent terminals at each edge of a platform and a plurality of video cameras in a train carriage, and acquires passenger flow data in real time through a video image analysis method;
The ATS analysis module 12 acquires train arrival data from an ATS system and analyzes train number of trains to be arrived at a platform;
the data processing module 13 is responsible for collecting and forwarding passenger flow data of each area of a platform and a train carriage, acquiring the number of trains coming to the station from the ATS analysis module 12, pairing and binding the number of trains coming to the station and the panoramic passenger flow congestion index of the station, and distributing the panoramic passenger flow congestion index to each intelligent terminal of the platform and the train;
the station passenger flow density analysis module 14 invokes a passenger flow density analysis algorithm to calculate the transfer congestion index of each carriage, and feeds back the calculation result to the data processing module 13.
The passenger flow congestion index display module 15 realizes subscription, release and display of panoramic passenger flow congestion index information through a platform and a train intelligent display terminal.
Furthermore, the data processing module 13 realizes interactive transmission of train data through a train-ground wireless transmission channel, carries out association binding on the train number of the train to be arrived at the present and the train passenger flow density data, and carries out data receiving and transmitting by adopting a release-subscription model taking the train number as a theme, thereby realizing association and reliable transmission of the train data. Because of the characteristic of high-speed mobile transmission between the train and the ground, the traditional TCP/IP message communication mode is adopted to have the possibility of incomplete data or serial packets, the embodiment adopts a release-subscription model mode to carry out message transmission and reception, a train vehicle-mounted end server or an application program is not directly connected with the data processing module 13, and message proxy transmission is carried out through a third party message middleware, so that the train running process can be ensured to accurately upload the passenger flow density data of the carriage, and meanwhile, the station-train panoramic passenger flow congestion index issued by a station to a train can be received.
In the data processing process, in order to ensure the relevance between the train data and the platform data processed by the data processing module 13 and ensure the accuracy of the display data of the coming station train and the coming station, the embodiment processes the data in a mode of taking the train number as a key and a theme, and when the passenger flow density data of the carriage is uploaded, the data is transmitted to the data processing module 13 in a mode of { key, value = { train number, passenger flow density object data }; when issuing the panoramic congestion index of the train, pushing the data of the train number to the subscription subject number= "train number". And (3) associating the platform and the train data through the train number, so that the consistency of the data displayed in the train carriage to be arrived and the data displayed by the platform intelligent terminal is realized.
Fig. 4 shows a network structure diagram of a relative passenger flow distribution computing system of urban rail transit in the embodiment, and the system realizes the processing of images of platform and train passengers, completes the operations of collecting the passenger flow density data of the platform, forwarding the data, analyzing the passenger flow density, displaying the passenger flow congestion index and the like, and realizes the automatic analysis and processing of the panoramic passenger flow congestion index of the platform and the train. The system is composed of three parts: hardware system, software platform, passenger flow density analysis algorithm. The hardware system comprises a platform edge intelligent terminal 25, a vehicle-mounted display screen 27, a carriage camera 29, a station server 21, a platform PIS broadcasting controller 22, a station switch 23, a station AP28 and the like, and all hardware devices are connected with a vehicle-ground wireless network through a station transmission network. The passenger flow images of the platform 24 area and the train carriage 26 are respectively acquired through the edge intelligent terminal 25 and the carriage camera 29, and the passenger flow is analyzed by applying an image identification and analysis method; the platform edge intelligent terminal 25 and the vehicle-mounted display screen 27 are used for displaying the platform transfer panorama passenger flow congestion index in real time, so that the edge intelligent terminal 25 is a display terminal of information and an acquisition terminal of passenger images. The software platform is used for processing, analyzing and calculating the acquired passenger flow density data, taking the passenger flow density data acquired by the platform and the carriage as input parameters, and calculating by using an intelligent density analysis algorithm, so as to calculate the panoramic passenger flow congestion index of the station train of the train to be arrived at the current time point.
Fig. 5 shows an algorithm flow chart of a method for calculating urban rail transit relative passenger flow distribution in the present embodiment, which includes the following steps:
step S1: collecting passenger flow density data of a station car: and acquiring passenger flow data of passengers in each region of the platform and each carriage of the train in real time by using a video image analysis method through the intelligent terminal equipment at the edges of the platform and the carriage of the train.
Step S2: station vehicle data receiving and transmitting and processing: the passenger flow data of passengers in each area of the platform and each carriage of the train are collected, and the data are forwarded to the passenger flow density analysis module 14 for analysis and calculation; the real-time station vehicle panoramic traffic congestion index calculated by the station vehicle traffic density analysis module 14 is acquired, the upcoming train number is acquired from the ATS analysis module 12 and is paired and bound with the station vehicle panoramic traffic congestion index, and finally, the station vehicle panoramic traffic congestion index is issued.
Step S3: calculating a station passenger flow distribution average value: and calculating the average value of passenger flow distribution of the platform and the train carriage at the current moment of the station.
Step S4: calculating passenger flow distribution values of corresponding stations of each carriage: and calculating passenger flow distribution values of the corresponding platforms of the carriages and the carriages of the train.
Step S5: calculating a station vehicle panoramic passenger flow crowdedness index: and comparing the corresponding station passenger flow distribution value of each carriage with the average value of station passenger flow distribution, and calculating a station transfer panoramic passenger flow crowding index distributed according to the position of each carriage.
Step S3, calculating a mean value of the passenger flow distribution of the station vehicle:
let the passenger flow volume of the coverage area of the intelligent terminal acquisition range be x i The platform area of the coverage area of the acquisition range is s i Collecting passenger flow y of carriage where train is j The area of the carriage where the collection train is positioned is t j . Wherein i=1, n represents collecting n train carriages, j=1, m represents collecting m edge intelligent terminals of passenger flow volume of the platform, in the scheme, a single carriage corresponds to at least more than 1Edge intelligent terminal (n.gtoreq.m. calculate the sum of the product of the area of the collecting range of the station platform and the corresponding passenger flow volume and the product of the area of each carriage to be listed through the station platform and the corresponding passenger flow volume, then the single carriage mean value expression S of the passenger flow volume area of the waiting station to be analyzed is the formula (1):
the congestion condition of the train transfer process depends on passenger flow on one hand and on the space area of the transfer area on the other hand, so that the embodiment obtains the products of the passenger flow and the area of the transfer area of the station and the train by taking two variables of the passenger flow and the area of the area as product factors, and finally averages each carriage of the train, thereby obtaining the single carriage mean value of the passenger flow area of the station side, and further taking the single carriage mean value as a reference of the congestion degree of each carriage.
S4, calculating a mean value of the passenger flow distribution of the station vehicle:
and calculating the average value of passenger flow distribution of each carriage and the corresponding platform, so as to carry out arithmetic representation on the transfer congestion degree condition of each carriage. Thus, the passenger flow area and expression Z representing a single car and corresponding platform i Is formula (2):
taking the periodicity of the passenger flow of the station passengers into consideration, setting the function of the passenger flow and the time as y=f (x), and setting the operation starting time as t 1 Ending time t 2 Calculating the passenger flow volume of the t moment point in the (t, t+1) period range asPassenger flow is +.>In progress, the formula for calculating the adjustment factor δ(3)：
Furthermore, because the passenger flow of the rail transit presents typical wave crest-wave trough distribution characteristics, the passenger flow of the early peak and the late peak is large, and the passenger flow of other time special changes are smaller in the working period. Therefore, in order to objectively reflect the congestion index condition of station transfer, an adjusting factor delta is specially introduced, and the ratio of the passenger flow of the current time point of approximately one hour to the passenger flow of the current operation time period is calculated, so that the average value of the passenger flow distribution of each carriage station at the current time point is adjusted, and the calculated average value of the passenger flow distribution of each carriage station can reflect the actual relative passenger flow congestion condition of the station at the calculating moment.
S5, calculating a mean value of the passenger flow distribution of the station vehicle:
and finally, calculating the ratio of the passenger flow volume of the single carriage and the corresponding platform to the average daily passenger flow volume, thereby finally calculating the current time point passenger flow congestion condition. The calculation formula is as follows Analyzing and judging the corresponding calculation result:
θ is less than or equal to 0.8, so that the comfort is improved; θ is more than or equal to 0.8 and less than or equal to 1.2, so that the device is more crowded; θ is not less than 1.2, and severe congestion occurs.
Fig. 6 shows a real effect diagram of a station panoramic passenger flow congestion index displayed on a station display screen or a vehicle-mounted display screen by applying the system and the method of the embodiment.
In summary, according to the urban rail transit relative passenger flow distribution calculation method and system provided by the embodiment of the invention, passenger flow density in each area of a platform and a carriage is acquired through the intelligent terminal at the edge of the platform and the vehicle-mounted camera, and accurate calculation of the transfer panoramic passenger flow crowding index of each carriage is realized by using a passenger flow density analysis algorithm. On one hand, the platform passenger flow density and the train carriage passenger flow density data are comprehensively considered, the overall consideration of the platform passenger flow data and the train passenger flow data is realized, and the passenger flow congestion condition during transfer can be accurately reflected; on the other hand, in the passenger flow crowding degree index calculation algorithm, factors such as the waiting area of a station platform, the carriage area, the change of passenger flow with time and the like are fully considered, the calculation result is accurate, and the method has very strong guiding significance on the up-down passenger flow crowding condition and the passenger flow evacuation of the train at the calculation time point.
Fig. 7 illustrates a physical schematic diagram of an electronic device, as shown in fig. 7, which may include: processor 810, communication interface (Communications Interface) 820, memory 830, and communication bus 840, wherein processor 810, communication interface 820, memory 830 accomplish communication with each other through communication bus 840. The processor 810 may invoke logic instructions in the memory 830 to perform a method of urban rail transit relative passenger flow distribution calculation, the method comprising:
acquiring passenger flow data;
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
and obtaining a calculation conclusion of the urban rail transit relative passenger flow distribution according to the relative passenger flow distribution function.
Further, the logic instructions in the memory 830 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, are capable of performing the method for calculating the relative passenger flow distribution of urban rail transit provided by the above methods, the method comprising:
acquiring passenger flow data;
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
and obtaining a calculation conclusion of the urban rail transit relative passenger flow distribution according to the relative passenger flow distribution function.
In yet another aspect, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the above-provided urban rail transit relative passenger flow distribution calculating method, the method comprising:
acquiring passenger flow data;
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
According to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
and obtaining a calculation conclusion of the urban rail transit relative passenger flow distribution according to the relative passenger flow distribution function.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. The method for calculating the relative passenger flow distribution of the rail transit is characterized by comprising the following steps of:
acquiring passenger flow data;
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a passenger flow set of a plurality of regions within the vehicle, and an area set of a plurality of regions within the vehicle;
The step of obtaining the passenger flow data comprises the following steps:
acquiring passenger flow data corresponding to a specific vehicle; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
the step of acquiring the specific waiting area data includes:
dividing a specific waiting area into m ′ A plurality of waiting areas for respectively collecting the m ′ The real-time passenger flow densities of m set waiting areas in the plurality of waiting areas form a first passenger flow density set which is marked as { x } i |i∈[1，m]-a }; respectively collect the m ′ The areas of m set waiting areas in the plurality of waiting areas form a first area set, which is marked as { s } i |i∈[1，m]}；
Wherein m is ′ Is an integer greater than 1; i is an integer; x is x i The real-time passenger flow density in the ith waiting area; s is(s) i An area of the ith waiting area; m is not greater than m ′ Is a positive integer of (2);
the step of acquiring the specific vehicle data includes:
dividing a particular vehicle into n ′ A plurality of vehicle regions for respectively collecting the n ′ Real-time passenger flow for n set vehicle zones of the n vehicle zonesDensity, forming a second set of passenger flow densities, denoted as { y } j |j∈[1，n]-a }; respectively collecting the n ′ The areas of n set vehicle regions in the vehicle regions form a second set of areas, denoted as { t } j |j∈[1，n]}；
Wherein n is ′ Is an integer greater than 1; j is an integer; y is j Real-time passenger flow density in the jth vehicle region; t is t j An area that is the jth vehicle region; n is not greater than n ′ Is a positive integer of (2);
the step of calculating the average passenger flow distribution function according to the passenger flow data comprises the following steps:
calculating to obtain an average passenger flow distribution function according to passenger flow data corresponding to a specific vehicle; the step of calculating the average passenger flow volume distribution function comprises the following steps:
calculating a passenger flow volume distribution function S in an ith waiting area through a first formula 1i The method comprises the steps of carrying out a first treatment on the surface of the The first formula is:
S 1i ＝x i ×s i ；
calculating a passenger flow volume distribution function S in the jth vehicle region through a second formula 2j The method comprises the steps of carrying out a first treatment on the surface of the The second formula is:
S 2j ＝y j ×t j ；
calculating an average passenger flow volume distribution function S through a third formula; the third formula is:
the step of calculating the passenger flow distribution function according to the passenger flow data comprises the following steps:
according to passenger flow data corresponding to a specific vehicle, calculating to obtain a passenger flow distribution function;
the step of calculating the passenger flow volume distribution function comprises the following steps:
if n is less than or equal to m, then:
calculating the corresponding ith waiting area through a fourth formulaPassenger flow volume function Z of a vehicle region i ′ The method comprises the steps of carrying out a first treatment on the surface of the The fourth formula is:
wherein the waiting area corresponding to the jth vehicle area comprises an ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′ ；
if n > m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a sixth formula i ′ The method comprises the steps of carrying out a first treatment on the surface of the The sixth formula is:
Z i ′ ＝∑ j∈I y j ×t j ；
the set I is a set of sequence numbers j of the vehicle area corresponding to the ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′ 。
2. the method for calculating relative passenger flow distribution of rail transit according to claim 1, wherein the step of calculating the relative passenger flow distribution function from the average passenger flow distribution function and the passenger flow distribution function comprises:
calculating the relative passenger flow volume distribution function theta of the ith waiting area by a seventh formula i The method comprises the steps of carrying out a first treatment on the surface of the The seventh formula is:
wherein delta is a set adjustment factor;
the adjustment factor delta is calculated by an eighth formula; the eighth formula is:
wherein f (x) is a set passenger flow volume function with an independent variable of time, and f (x) is the passenger flow volume at the moment x; t is t 1 The time when the vehicle starts to operate; t is t 2 The time when the vehicle stops operating; t is the current moment; t is t ′ The set period end time is set.
3. The method for calculating the relative passenger flow distribution of the rail transit according to claim 1 or 2, wherein the waiting area is an area where vehicles pass by and stop; the vehicle is the specific vehicle with the shortest arrival time at the waiting area.
4. The track traffic relative passenger flow distribution computing system is characterized by comprising an acquisition module and a passenger flow density analysis module;
the acquisition module comprises an acquisition terminal; the acquisition terminal is arranged in a waiting area and a traffic tool area and can acquire passenger flow data;
the passenger flow density analysis module can:
according to the passenger flow data, calculating to obtain a passenger flow distribution function;
according to the passenger flow data, calculating to obtain an average passenger flow distribution function;
according to the average passenger flow volume distribution function and the passenger flow volume distribution function, calculating to obtain a relative passenger flow volume distribution function;
wherein the relative passenger flow volume distribution function is a function of a ratio of a real-time passenger flow volume distribution to an average passenger flow volume distribution; the passenger flow volume data comprise waiting area passenger flow volume data and/or vehicle passenger flow volume data; the waiting area passenger flow volume data comprises any one or any combination of a waiting area total passenger flow volume, a waiting area total area, a passenger flow volume set of a plurality of areas in the waiting area and an area set of a plurality of areas in the waiting area; the vehicle passenger flow data includes any one or a combination of any one or more of a vehicle total passenger flow, a vehicle total area, a passenger flow set of a plurality of regions within the vehicle, and an area set of a plurality of regions within the vehicle;
The step of obtaining the passenger flow data comprises the following steps:
acquiring passenger flow data corresponding to a specific vehicle; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
the step of acquiring the specific waiting area data includes:
dividing a specific waiting area into m ′ A plurality of waiting areas for respectively collecting the m ′ The real-time passenger flow densities of m set waiting areas in the plurality of waiting areas form a first passenger flow density set which is marked as { x } i |i∈[1，m]-a }; respectively collect the m ′ The areas of m set waiting areas in the plurality of waiting areas form a first area set, which is marked as { s } i |i∈[1，m]}；
Wherein m is ′ Is an integer greater than 1; i is an integer; x is x i The real-time passenger flow density in the ith waiting area; s is(s) i An area of the ith waiting area; m is not greater than m ′ Is a positive integer of (2);
the step of acquiring the specific vehicle data includes:
dividing a particular vehicle into n ′ A plurality of vehicle regions for respectively collecting the n ′ The real-time passenger flow densities of n set vehicle regions in the n vehicle regions form a second passenger flow density set, denoted as { y } j |j∈[1，n]-a }; respectively collecting the n ′ The areas of n set vehicle regions in the vehicle regions form a second set of areas, denoted as { t } j |j∈[1，n]}；
Wherein n is ′ Is an integer greater than 1; j is an integer; y is j For real-time passenger flow density in the jth vehicle zone；t j An area that is the jth vehicle region; n is not greater than n ′ Is a positive integer of (2);
the step of calculating the average passenger flow distribution function according to the passenger flow data comprises the following steps:
calculating to obtain an average passenger flow distribution function according to passenger flow data corresponding to a specific vehicle; the step of calculating the average passenger flow volume distribution function comprises the following steps:
calculating a passenger flow volume distribution function S in an ith waiting area through a first formula 1i The method comprises the steps of carrying out a first treatment on the surface of the The first formula is:
S 1i ＝x i ×s i ；
calculating a passenger flow volume distribution function S in the jth vehicle region through a second formula 2j The method comprises the steps of carrying out a first treatment on the surface of the The second formula is:
S 2j ＝y j ×t j ；
calculating an average passenger flow volume distribution function S through a third formula; the third formula is:
the step of calculating the passenger flow distribution function according to the passenger flow data comprises the following steps:
according to passenger flow data corresponding to a specific vehicle, calculating to obtain a passenger flow distribution function;
the step of calculating the passenger flow volume distribution function comprises the following steps:
if n is less than or equal to m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a fourth formula i ′ The method comprises the steps of carrying out a first treatment on the surface of the The fourth formula is:
wherein the waiting area corresponding to the jth vehicle area comprises an ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′ ；
if n > m, then:
calculating a passenger flow function Z of a vehicle region corresponding to the ith waiting region through a sixth formula i ′ The method comprises the steps of carrying out a first treatment on the surface of the The sixth formula is:
Z i ′ ＝∑ j∈I y j ×t j ；
the set I is a set of sequence numbers j of the vehicle area corresponding to the ith waiting area;
calculating passenger flow volume distribution function Z of ith waiting area through fifth formula i The method comprises the steps of carrying out a first treatment on the surface of the The fifth formula is:
Z i ＝S 1i +Z i ′ 。
5. the track traffic relative passenger flow distribution computing system according to claim 4, further comprising an ATS parsing module, a data processing module, and a display module;
the ATS analysis module can analyze and obtain the information of the upcoming arrival times of the specific traffic tool to be analyzed;
the data processing module can receive the passenger flow data and the information of the upcoming arrival times of the specific vehicles and extract the passenger flow data corresponding to the specific vehicles; the passenger flow volume data corresponding to the specific vehicles comprises specific waiting area data and specific vehicle data;
The passenger flow density analysis module can calculate out relative passenger flow distribution functions corresponding to the specific vehicles and the specific waiting areas according to the specific waiting area data and the specific vehicle data, and obtain display information corresponding to the specific vehicles and the specific waiting areas according to the relative passenger flow distribution functions corresponding to the specific vehicles and the specific waiting areas;
the display module comprises a display terminal; the display terminal is arranged in the waiting area and/or the vehicle area and can display information;
the data processing module can also receive display information and distribute the display information to a display terminal of the display module.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the rail transit relative passenger flow distribution calculation method according to any one of claims 1 to 3 when the program is executed.
7. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of the rail transit relative passenger flow distribution calculation method according to any one of claims 1 to 3.
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