CN113298061A - Method for accurately calculating number of transfer persons - Google Patents
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- CN113298061A CN113298061A CN202110849636.3A CN202110849636A CN113298061A CN 113298061 A CN113298061 A CN 113298061A CN 202110849636 A CN202110849636 A CN 202110849636A CN 113298061 A CN113298061 A CN 113298061A
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
Abstract
The invention discloses a method for accurately calculating the number of transfer persons, which comprises the following steps: acquiring the site information of a wire network and combing the transfer relationship in the site information; using video monitoring equipment at a platform door of a transfer station to collect, analyze and identify face information of a transfer user; acquiring the face information collected when a user enters and exits the gate, comparing the face information with the face information collected by transfer, and matching the same face users according to the comparison result; combining two types of data, namely station transfer face information and station entering and exiting gate passing face information, summarizing all face data of each passenger, sequencing according to time sequence to obtain a track sequence of riding of a user and dividing a trip closed loop; and carrying out effective transfer analysis and transfer times statistics on the transfer path of each section of travel. According to the invention, passenger faces are collected through the platform door camera equipment of the transfer station, the faces are recognized, and the transfer point positions and the in-and-out closed loops of passengers are restored by combining the in-and-out data of the face gate, so that accurate transfer people counting can be realized.
Description
Technical Field
The invention relates to the field of rail transit, in particular to a method for accurately calculating the number of transfer persons in a subway station.
Background
With the continuous development of the world economy and science and technology, the urban rail transit around the world enters a new development stage. In the aspect of layout, the single-line construction is changed into the multi-level, three-dimensional and comprehensive networking construction; in function, the intelligent management system with intellectualization, informatization as marks, large passenger flow, large network and large transaction amount is realized.
The developed degree of the urban rail transit intelligent management system not only becomes the representation of the advancement of important transportation means for daily trips of citizens, but also reflects the foundation of urban comprehensive competitiveness, and plays an increasingly important role in the development of national economy and even the construction of a harmonious society. The study on the travel characteristics of the rail transit has great significance for guiding the construction of the rail transit, providing a solution for relieving urban congestion and guiding cities and traffic planning.
After the rail transit network operation, due to the existence of transfer stations, a plurality of transfer paths can be selected by passengers between any two stations in a line network. In order to obtain accurate passenger flow distribution data in the rail transit network and facilitate subsequent passenger flow statistics, ticket service clearing, operation management analysis and decision, the passenger flow clearing is the basis and the core. At present, a multi-path selection probability distribution method is mostly adopted in each city, the travel of passengers is divided into different routes according to a certain rule for estimation, but the estimation and the actual situation have deviation.
For example, patent application No. CN111210624A discloses a method for counting passenger traffic flow, which discloses a method for counting passenger traffic flow, comprising: A) the vehicle-mounted terminal system calculates and matches arrival information of the bus, acquires the travel direction and current stop information of the bus, uploads the current GPS positioning information of the bus to a background through a wireless communication module, and the background performs track analysis; B) when a bus arrives, opening a camera, and recording videos of front and rear doors of the bus; C) when the bus leaves a station, the camera is controlled to be closed, station information and video are uploaded to a background to be stored, the number of people getting on the bus and the number of people getting off the bus are counted, and the flow of people at each station is counted. Although the scheme can collect the passenger flow data of all buses, the trip closed loop of passengers is not restored, whether the passengers have transfer behaviors or not is not judged, and the method is not suitable for passenger flow statistics in subway scenes.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for accurately calculating transfer people.
The purpose of the invention is realized by the following technical scheme:
a method of accurately calculating transfer people, comprising the steps of:
the method comprises the following steps: acquiring the site information of a wire network and combing the transfer relationship in the site information;
step two: using video monitoring equipment at a platform door of a transfer station to collect, analyze and identify face information of a transfer user;
step three: acquiring the face information collected when a user enters and exits the gate, comparing the face information with the face information collected by transfer, and matching the same face users according to the comparison result;
step four: combining the station transfer face information and the effective riding data set in the step two and the four groups of data of the station passing face information and the effective riding data set in the step three, summarizing all face data of each passenger, sequencing according to time sequence to obtain a riding track sequence of the user and dividing a traveling closed loop;
step five: and carrying out effective transfer analysis and transfer times statistics on the transfer path of each section of travel.
Specifically, the first step specifically comprises:
and acquiring the running information of each line network station from the rail transit network, wherein the letter S represents the station, marking the stations in each line by using a combination mode of the letter S and the number, and acquiring and recording the transfer relationship in each station.
Specifically, the second step specifically includes the following substeps:
s21, acquiring the video of each transfer station platform door by using video monitoring equipment, and acquiring the face information of the video stream of each transfer station platform door;
s22, matching the identity of the same face information in the transfer process, marking the user with a letter P, combing a transfer original data set in a transfer station S-transfer, character P and transfer time T format, and marking the transfer original data set as (S-transfer, P, T);
and S23, finally, preliminarily cleaning the data in the transfer original data sets, and combining different original data sets which have the same transfer station S and the same character P and have the transfer time T within 3 minutes into a group of effective transfer data sets.
Specifically, the third step specifically includes the following substeps:
s31, acquiring inbound face information and outbound face information when the user successfully passes through the gate;
s32, marking the collected user inbound face information and outbound face information, and marking the user by using a letter P, combing an original riding data set in a form of an inbound station S, a character P and a riding time T, and marking the original riding data set as (S inbound, P, T) and (S outbound, P, T);
and S33, preliminarily cleaning the data in the original riding data group, and combining different riding original data groups which have the same station S and person P and have the same riding time T within 1 minute into a group of effective riding data groups.
Specifically, the fourth step specifically includes: and combining the two types of data of the station transfer face information in the step two and the station entering and exiting lockage face information in the step three, combining an effective riding data group and an effective transfer data group, summarizing all face data of each passenger, sequencing the effective riding data group and the effective transfer data group of each user according to the time sequence of face information acquisition in the passenger riding process, obtaining the sequence of the transfer station and the station entering and exiting corresponding to each user from the effective riding data group and the effective transfer data group corresponding to each user according to the sequencing result, and taking a group of complete S entering and S exiting as a closed loop split node to obtain the outgoing closed loop related to the figure P.
Specifically, the step five specifically comprises: in each group of trip closed loops of each user, effective transfer station screening is carried out, and the screening is divided into three aspects:
1) excluding the starting station, and when the transfer station of the same user is the same as the in-out station, the transfer station is regarded as invalid transfer to be excluded;
2) judging whether a transfer point omission exists in the outgoing closed loop of the user or not according to whether the continuous transfer stations of the same user are in a direct relation or not, judging that the outgoing closed loop of the user has no transfer point omission if the continuous transfer stations of the same user are in the direct relation, and considering that the transfer points are omitted in the transfer period of the user if the continuous transfer stations of the same user are in the direct relation or adopting a station corresponding to the shortest transfer path in a network to supplement the transfer stations for the outgoing closed loop of the user;
3) judging whether the transfer station has been transferred, respectively connecting the front and rear stations of the transfer station with the transfer station to form two line segments, judging whether the two line segments are on the same line, if so, determining that no transfer has occurred, and excluding the transfer station as an invalid transfer station, otherwise, taking the transfer station as an effective transfer station;
taking the remaining effective transfer stations as the number of transfer persons for the passenger to go out this time; and finally, adding the transfer times of all the travel sections to obtain the line net transfer times.
The invention has the beneficial effects that:
1. in the aspect of data, the passenger face is collected through the platform door camera equipment of the transfer station, the face is recognized, the transfer and path routes of passengers and the closed loop of the station are accurately restored by combining the data of the face gate entering and exiting the station, compared with the traditional sorting mode distributed in proportion, the passenger flow counting and sorting method can realize fine passenger flow counting and sorting, and can provide more accurate decision basis for ticket income sorting and operation management analysis.
2. From the aspect of passengers, the invention realizes accurate depiction of individual behaviors of the passengers by utilizing the faces, and is beneficial to analysis of passenger travel. Studying passenger trip time period distribution, trip stations, trip route selection, trip times, trip frequency statistical analysis and the like under daily conditions; and analyzing the travel behavior change of the passenger under the conditions of new line opening, major activities, emergency operation events, major public health events, extreme weather and the like under special conditions.
3. From the aspect of the station, the invention can obtain the accurate passenger flow of the station by accurately calculating the passenger transfer path, and is favorable for analyzing the station attribute. By analyzing the composition of station passenger flow, the source destination of the station passenger flow, the travel time characteristic of the station and the arrival and destination space-time distribution of the station passenger flow, the station passenger flow attribute, the commercial value and the like can be further clarified and the station planning can be facilitated.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is an exemplary diagram of the net relationships of the present invention.
Detailed Description
In order to clearly understand the technical features, objects and effects of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the present invention, the letter S represents a station, S in represents an inbound station when a passenger (user) takes a car, S exchange represents a transfer station when a passenger (user) takes a car, S out represents an outbound station when a passenger (user) takes a car, and the inbound and outbound stations S represent inbound and outbound stations S.
The first embodiment is as follows:
in this embodiment, as shown in fig. 1, a method for accurately calculating the number of transfer persons includes the following steps:
the method comprises the following steps: acquiring the site information of a wire network and combing the transfer relationship in the site information;
step two: using video monitoring equipment at a platform door of a transfer station to collect, analyze and identify face information of a transfer user;
step three: acquiring the face information collected when a user enters and exits the gate, comparing the face information with the face information collected by transfer, and matching the same face users according to the comparison result;
step four: combining the two types of data of the station transfer face information in the step two and the station passing face information in and out in the step three, summarizing all face data of each passenger, sequencing according to the time sequence to obtain a riding track sequence of the user and dividing a trip closed loop;
step five: and carrying out effective transfer analysis and transfer times statistics on the transfer path of each section of travel.
In this embodiment, the first step specifically includes: and acquiring the running information of each line network station from the rail transit network, wherein the letter S represents the station, marking the stations in each line by using a combination mode of the letter S and the number, and acquiring and recording the transfer relationship in each station. Taking the wire network relationship shown in fig. 2 as an example, stations are labeled with letters and the transfer relationship among the stations is observed, wherein the station of S2, the station of S3 and the station of S5 are three transfer stations.
In this embodiment, the second step specifically includes the following substeps:
s21, acquiring the video of each transfer station platform door by using video monitoring equipment, and acquiring the face information of the video stream of each transfer station platform door;
s22, matching the identity of the same face information in the transfer process, marking the user with a letter P, combing the original transfer data set in the format of a transfer station S, a character P and transfer time T, marking the original transfer data set as (S, P and T) to represent that the character P appears in the transfer station S at the time T;
and S23, finally, preliminarily cleaning the data in the transfer original data sets, and combining different original data sets which have the same transfer station S and the same character P and have the transfer time T within 3 minutes into a group of effective transfer data sets.
If 6 passengers (p 1-p 6) appear at the bus transfer stations within the statistical period, the effective data of the faces appearing at each bus transfer station is finally obtained as shown in the following table 1.
TABLE 1 effective data sheet of human face appearing at transfer station
In the embodiment, passenger faces are collected through the platform door camera equipment of the transfer station, the faces are recognized, the transfer and path routes of passengers are accurately restored by combining the data of the entrance and the exit of the face gate, and the closed loop of the entrance and the exit is realized.
In this embodiment, the step three specifically includes the following substeps:
s31, acquiring inbound face information and outbound face information when the user successfully passes through the gate;
s32, matching the acquired user inbound face information and outbound face information with the face information in the user transfer process, labeling the user successfully matched with the identity by using a letter P, combing the original data group of the bus by the format of the station S, the character P and the bus time T, marking the original data group of the bus as (S inbound, P, T) or (S outbound, P, T), and respectively representing that the character P enters or exits the station S at the time T;
and S33, preliminarily cleaning the data in the original riding data group, and combining different riding original data groups which have the same station S and person P and have the same riding time T within 1 minute into a group of effective riding data groups. If it is assumed that 6 passengers (p 1-p 6) enter and exit the station within the statistical period, all the station entering and exiting effective data sets are finally obtained as shown in the following table 2.
Table 2 effective data group table for station entrance and exit
In this embodiment, the fourth step specifically includes: and combining the two types of data of the station transfer face information in the step two and the station entering and exiting lockage face information in the step three, combining the effective riding data group in the step three and the effective transfer data group in the step two, summarizing all face data of each passenger, sequencing the effective riding data group and the effective transfer data group of each user according to the face information acquisition time sequence mode in the passenger riding process, obtaining the transfer station and station entering and exiting sequence corresponding to each user from the effective riding data group and the effective transfer data group corresponding to each user according to the sequencing result, and taking a group of complete S entering and S exiting as a closed loop split node to obtain a person P-related outgoing closed loop. Taking the experimental data of the second step and the third step as an example, the transfer sequence of all persons is obtained, as shown in the following table 3.
TABLE 3 transfer order Table
In the embodiment, the accurate depiction of the individual behaviors of the passengers is realized by utilizing the human faces, and the travel analysis of the passengers is facilitated. Studying passenger trip time period distribution, trip stations, trip route selection, trip times, trip frequency statistical analysis and the like under daily conditions; and analyzing the travel behavior change of the passenger under the conditions of new line opening, major activities, emergency operation events, major public health events, extreme weather and the like under special conditions.
In this embodiment, the fifth step specifically includes: in each group of trip closed loops of each user, effective transfer station screening is carried out, and the screening is divided into three aspects:
1) excluding the starting station, and when the transfer station of the same user is the same as the in-out station, the transfer station is regarded as invalid transfer to be excluded;
2) judging whether a transfer point omission exists in the outgoing closed loop of the user or not according to whether the continuous transfer stations of the same user are in a direct relation or not, judging that the outgoing closed loop of the user has no transfer point omission if the continuous transfer stations of the same user are in the direct relation, and considering that the transfer points are omitted in the transfer period of the user if the continuous transfer stations of the same user are in the direct relation or adopting a station corresponding to the shortest transfer path in a network to supplement the transfer stations for the outgoing closed loop of the user;
3) judging whether the transfer station has been transferred, respectively connecting the front and rear stations of the transfer station with the transfer station to form two line segments, judging whether the two line segments are on the same line, if so, determining that no transfer has occurred, and excluding the transfer station as an invalid transfer station, otherwise, taking the transfer station as an effective transfer station;
taking the remaining effective transfer stations as the number of transfer persons for the passenger to go out this time; finally, the number of the line net transfer persons is obtained by adding the number of the transfer persons of all the travel sections, and the final result is shown in the following table 4.
In the embodiment, the accurate passenger flow of the station can be obtained by accurately calculating the passenger transfer path, and the analysis of the station attribute is facilitated. By analyzing the composition of station passenger flow, the source destination of the station passenger flow, the travel time characteristic of the station and the arrival and destination space-time distribution of the station passenger flow, the station passenger flow attribute, the commercial value and the like can be further clarified and the station planning can be facilitated.
TABLE 4 efficient transfer datasheet
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (6)
1. A method for accurately calculating transfer times is characterized by comprising the following steps:
the method comprises the following steps: acquiring the site information of a wire network and combing the transfer relationship in the site information;
step two: using video monitoring equipment at a platform door of a transfer station to collect, analyze and identify face information of a transfer user;
step three: acquiring the face information collected when a user enters and exits the gate, comparing the face information with the face information collected by transfer, and matching the same face users according to the comparison result;
step four: combining the station transfer face information and the effective riding data set in the step two and the four groups of data of the station passing face information and the effective riding data set in the step three, summarizing all face data of each passenger, sequencing according to time sequence to obtain a riding track sequence of the user and dividing a traveling closed loop;
step five: and carrying out effective transfer analysis and transfer times statistics on the transfer path of each section of travel.
2. The method for accurately calculating transfer times of claim 1, wherein the first step specifically comprises:
the method comprises the steps of obtaining operation information of each line network station from a rail transit network, marking the stations in each line by utilizing a letter and number combination mode, and collecting and recording transfer relations in each station, wherein a letter S represents a station.
3. The method for accurately calculating transfer times of claim 1, wherein the second step specifically comprises the following sub-steps:
s21, acquiring the video of each transfer station platform door by using video monitoring equipment, and acquiring the face information of the video stream of each transfer station platform door;
s22, matching the identity of the same face information in the transfer process, marking the user with a letter P, combing a transfer original data set in a transfer station S-transfer, character P and transfer time T format, and marking the transfer original data set as (S-transfer, P, T);
and S23, finally, preliminarily cleaning the data in the transfer original data sets, and combining different original data sets which have the same transfer station S and the same character P and have the transfer time T within 3 minutes into a group of effective transfer data sets.
4. The method for accurately calculating transfer times of claim 1, wherein the third step specifically comprises the following sub-steps:
s31, acquiring inbound face information and outbound face information when the user successfully passes through the gate;
s32, marking the collected user inbound face information and outbound face information, and marking the user by using a letter P, combing an original riding data set in a form of an inbound station S, a character P and a riding time T, and marking the original riding data set as (S inbound, P, T) and (S outbound, P, T);
and S33, preliminarily cleaning the data in the original riding data group, and combining different riding original data groups which have the same station S and person P and have the same riding time T within 1 minute into a group of effective riding data groups.
5. The method for accurately calculating the transfer times of the passengers according to the claim 1, characterized in that the step four specifically comprises: and combining the two types of data of the station transfer face information in the step two and the station entering and exiting lockage face information in the step three, combining an effective riding data group and an effective transfer data group, summarizing all face data of each passenger, sequencing the effective riding data group and the effective transfer data group of each user according to the time sequence of face information acquisition in the passenger riding process, obtaining the sequence of the transfer station and the station entering and exiting corresponding to each user from the effective riding data group and the effective transfer data group corresponding to each user according to the sequencing result, and taking a group of complete S entering and S exiting as a closed loop split node to obtain the outgoing closed loop related to the figure P.
6. The method for accurately calculating transfer times of claim 1, wherein the step five specifically comprises: in each group of trip closed loops of each user, effective transfer station screening is carried out, and the screening is divided into three aspects:
1) excluding the starting station, and when the transfer station of the same user is the same as the in-out station, the transfer station is regarded as invalid transfer to be excluded;
2) judging whether a transfer point omission exists in the outgoing closed loop of the user or not according to whether the continuous transfer stations of the same user are in a direct relation or not, judging that the outgoing closed loop of the user has no transfer point omission if the continuous transfer stations of the same user are in the direct relation, and considering that the transfer points are omitted in the transfer period of the user if the continuous transfer stations of the same user are in the direct relation or adopting a station corresponding to the shortest transfer path in a network to supplement the transfer stations for the outgoing closed loop of the user;
3) judging whether the transfer station has been transferred, respectively connecting the front and rear stations of the transfer station with the transfer station to form two line segments, judging whether the two line segments are on the same line, if so, determining that no transfer has occurred, and excluding the transfer station as an invalid transfer station, otherwise, taking the transfer station as an effective transfer station;
taking the remaining effective transfer stations as the number of transfer persons for the passenger to go out this time; and finally, adding the transfer times of all the travel sections to obtain the line net transfer times.
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