CN112767685A - Public transport passenger flow analysis system based on positioning and card swiping information - Google Patents
Public transport passenger flow analysis system based on positioning and card swiping information Download PDFInfo
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Abstract
The invention provides a public transport passenger flow analysis system based on positioning and card swiping information, and aims to build an innovative public transport passenger flow analysis working platform, construct an application system on the platform, wherein the application system can respectively carry out statistical analysis and query on card swiping data of a whole group, each operation branch company, each line and each single vehicle according to different dimensions and different time periods, realize online transmission and sharing of information by means of a public transport information sharing basic network, and achieve the purpose of carrying out query analysis and application on data on different terminals. The invention designs the system according to the demand of the user, the method for analyzing the bus passenger flow statistics is simple to apply, the result is accurate, scientific basis is provided for optimizing and adjusting the urban bus, and the popularization and the use of the system are beneficial to a traffic management department and a bus enterprise to know the distribution characteristics of the passenger flow and optimize and adjust the bus network in time, thereby more effectively improving the operation efficiency of the bus network.
Description
Technical Field
The invention relates to a bus passenger flow analysis system, in particular to a bus passenger flow analysis system based on positioning and card swiping information, and belongs to the technical field of bus passenger flow analysis.
Background
Along with the continuous expansion of city scale, city quantity is constantly increasing, and the urbanization process is also constantly accelerating, and urban traffic trip structure is showing and is changing, and urban residents' trip demand constantly rises, and the trip total amount also presents the trend of increasing by a wide margin. With the development of economic society, the proportion of motor-driven travel modes adopted by residents is continuously increased, so that urban traffic jam is aggravated, and the pressure on energy consumption and environmental pollution is continuously increased. The scientific and reasonable traffic system has very important significance for the development of cities, the higher the requirements of residents on travel modes and travel quality are, and the new requirements are brought to the development of urban traffic.
Urban traffic is an important infrastructure closely related to daily life of people, and the phenomenon of urban traffic jam is very serious at present. The importance of urban public transport in solving urban traffic congestion is generally recognized by countries in the world, a public transport priority development strategy is implemented, the public transport trip sharing rate and the public transport trip utilization rate are improved, and the method is an important means for improving the utilization efficiency of urban traffic resources and relieving traffic congestion. The priority development strategy of public transport is generally accepted by management and planning departments at all levels of the current city, the importance of public transport is increasingly strengthened and valued in urban transport planning, the public transport network is actively optimized and adjusted, the public transport land is reasonably distributed, the status of public transport in urban planning is continuously improved, a series of safeguard measures about priority development of urban public transport are made, the priority development public transport strategy is comprehensively implemented, and popularization and application of information technology are increased.
Generally, the competitiveness of many urban public transport is obviously insufficient, the development is relatively lagged, and the problems of insufficient service capability and low quality of urban public transport are also prominent. Even the problem that the proportion of the public transportation trip sharing rate in the city resident trip is continuously reduced is solved, and the following two reasons are summarized: firstly, due to the reasons of unreasonable arrangement of the bus station, more travel transfer times, longer waiting time, congestion in the bus and the like, the satisfaction degree of passengers on public transport is low, and the willingness of taking the bus for traveling is gradually reduced; secondly, the management and service system of the public transport enterprise needs to be improved, the operation efficiency is not high, and the travel demand of the passengers cannot be guaranteed to the maximum extent. The current public transit service level and service quality aspect in the promotion possess corresponding potentiality, consequently should further study the preferential development policy of public transit, let more and more residents with the help of the bus trip, further improve the bus trip sharing rate, alleviate urban traffic pressure. Therefore, in order to better provide service for the travel of residents and improve the satisfaction degree of the residents, the public transportation enterprises need to make a more scientific operation plan to improve the punctuality and comfort degree of the public transportation service.
The passenger flow is an important basis for bus planning and production scheduling operation, the passenger flow reflects the number of public transport means required by travel of urban residents on the whole, the bus passenger flow is uneven in time and space distribution, characteristics and change conditions of the passenger flow have great influence on the operation scheduling plan of the bus, and have great reference functions on bus route planning and bus station setting, so that the passenger flow change analysis and the passenger flow rule mastering are very necessary.
The passenger flow data of the public transport is mainly applied to three aspects, namely public transport scheduling operation, public transport internal management and public transport planning layout:
the method is applied to bus dispatching operation: the passenger flow data is analyzed to research and master the change rule of the passenger volume cycle in each season, each month, each week and day and night on the line, master the passenger flow change rule, contribute to improving the operation management level, improve the scheduling measure, modify, supplement and perfect the driving operation plan, relieve the conflict of traffic congestion in the peak time period, avoid the waste caused by the empty driving of the vehicle, use the vehicle economically and reasonably, and ensure the service quality and the service efficiency of public traffic. At present, most public transport enterprises operate and schedule buses according to past experiences of dispatchers, and due to the fact that accurate change conditions of passenger flow cannot be mastered, departure intervals and number of distributed buses cannot adapt to passenger flow changes in time. By timely mastering the passenger flow and the change condition thereof, the dispatching frequency and the number of the dispatched vehicles of the lines in different peak time and peak time can be timely adjusted, the driving operation plan can be scientifically and reasonably formulated, the vehicles can be used at the maximum efficiency, better riding conditions are provided for passengers, and the traveling satisfaction of the passengers is improved.
Be applied to public transit internal management: after the passenger flow data is mastered, the passenger flow data and other related data are comprehensively and systematically analyzed and researched, so that regular related factors are found out, the line network management condition is scientifically evaluated, the operation indexes and the operation plan are reasonably formulated, and the internal management efficiency of the public transport enterprise is improved.
Be applied to public transit planning overall arrangement: the bus line network planning and the bus station setting need to master the bus passenger flow conditions, various indexes related to the passenger flow, such as average full load rate, OD distribution, transfer rate, line network benefits and the like, are important bases for bus line network evaluation and planning, the passenger flow is predicted according to the passenger flow change conditions, and data support is provided for bus planning, such as bus line trend, bus station layout and the like by calculating the medium-long term change trend of the passenger flow.
The following methods are mainly used for acquiring the bus passenger flow data:
the method mainly comprises four surveys, namely, a bus inquiry survey, a resident trip survey, a bus station passenger flow survey and a bus-mounted passenger flow survey. However, the manual survey method is mainly completed by people, consumes a lot of manpower and financial resources, is very difficult to form a mechanism for regularly and manually surveying passenger flow, and the obtained data also has no real-time property, so that the organization and training of related personnel are required in a preparation stage, the data sorting and analyzing work after the survey is completed is also very heavy, and the data quality is difficult to ensure by all manual processing modes, so that the collected and analyzed data is inaccurate.
And the second image discrimination method is to analyze passenger information and getting-on and getting-off behaviors after video images in the buses are obtained and the videos are analyzed by using professional image discrimination software, and finally, the number of passengers getting on and off the buses is analyzed to form final passenger flow data of each bus. However, the cost of image discrimination for passenger flow analysis is high.
Thirdly, a card swiping data analysis method, when a passenger swipes a card, a card swiping system finishes the bus charge, also stores information such as card swiping time and the serial number of a card swiping machine, the information can be used for analyzing the traveling condition of the passenger, collecting passenger flow data in real time, predicting future passenger flow according to historical data, and carrying out passenger flow analysis by using the card swiping data automatically by using a computer program, so that compared with a manual investigation method, a link of manually collecting data is omitted, and when the passenger gets on the bus and swipes the card, the data can be synchronously collected; compared with a data acquisition method based on image discrimination, the card swiping data acquisition is not influenced by light, vibration and temperature, and the data accuracy is higher. However, the card swiping information only comprises the information of the card swiping time and the card swiping vehicle of the passenger, and the card swiping bus station of the passenger cannot be found according to the card swiping record, so that the passenger flow analysis method based on the card swiping data is usually used for calculating by using a mathematical model when the passenger boarding bus station is analyzed, and the boarding bus station of the passenger cannot be found accurately. Along with the popularization and application of the bus positioning system, the running track of the vehicle can be known by utilizing the positioning position information generated by the vehicle, the card swiping time is matched with the time of the vehicle in the positioning data when the vehicle stops at the bus station, the card swiping and getting-on bus station of the passenger can be obtained, and therefore accurate card swiping passenger flow analysis information is obtained.
In summary, the prior art has some obvious disadvantages, which are shown in the following aspects:
firstly, the problem that the service ability of many city buses is not enough, the quality is not high still more outstanding at present, the problem that the proportion of public transport trip sharing rate in city resident's trip has appeared continuously descend has even, the leading cause: firstly, due to the reasons of unreasonable arrangement of bus stations, more travel transfer times, longer waiting time, congestion in buses and the like, the satisfaction degree of passengers on public transport is low, and the willingness of taking buses to travel is gradually reduced; secondly, the management and service system of the public transport enterprise is poor, the operation efficiency is not high, and the travel demand of the passengers cannot be guaranteed to the maximum extent. At present, the public transport service system has considerable potential in the aspects of improving the public transport service level and service quality, and in order to better provide service for the travel of residents and improve the satisfaction degree of the residents, a public transport enterprise needs to make a more scientific operation plan to improve the accuracy and comfort degree of the public transport service, so that a comprehensive and accurate public transport passenger flow analysis system is urgently needed;
secondly, the manual investigation method for acquiring the bus passenger flow data in the prior art is mainly completed by people, consumes a large amount of manpower and financial resources, is very difficult to form a mechanism for regularly and manually investigating the passenger flow, and the acquired data does not have real-time performance, so that the data arrangement and analysis work after the investigation is completed is very heavy except that the preparation stage needs to organize and train related personnel, and the data quality is difficult to ensure by all manual processing modes, so that the acquired and analyzed data is inaccurate;
thirdly, in the image discrimination method in the prior art, after the video image in the bus is obtained, professional image discrimination software is used for analyzing and processing the video, passenger information and getting-on and getting-off behaviors are analyzed, and finally the number of passengers getting on and off the bus is analyzed to form final passenger flow data of each bus, but the image discrimination method is high in cost for passenger flow analysis, consumes a large amount of material and financial resources, is poor in stability and is not recommended to use;
fourthly, the prior art has small analysis scale of the public transport passenger flow, single function and poor accuracy, and can not be applied to the public transport dispatching operation: the reason why the passenger flow data cannot be analyzed is to study and master the change rule of the passenger volume cycle in each season, each month, each week and day and night on the line, and the change rule of the passenger flow cannot be mastered, so that the departure interval and the number of the vehicles cannot be adapted to the change of the passenger flow in time; the method can not be applied to internal management of the public transport, and can not scientifically evaluate the line network operation condition and reasonably make operation indexes and operation plans; the method cannot be applied to bus planning layout, cannot master the conditions of bus passenger flow, cannot master important data of various indexes related to the passenger flow, such as average full load rate, OD distribution, transfer rate, net benefit and the like, cannot predict the passenger flow, and cannot provide data support for bus planning such as bus route trend, bus station layout and the like by calculating the medium-long term change trend of the passenger flow. Meanwhile, the prior art is only suitable for small-scale passenger flow statistics, has low precision and poor portability, is generally only applied to a specific small area, and has the defects of weak interaction performance, low intelligent degree, low expandability, fewer functions and the like.
The invention aims to build an innovative public transport passenger flow analysis working platform, an application system which can respectively carry out statistical analysis and query on card swiping data of a whole group, each operation branch company, each line and each single vehicle according to different dimensions and different time periods is built on the platform, and the on-line transmission and sharing of information are realized by means of a public transport information sharing basic network, so that the aims of carrying out query analysis and application on data on different terminals are fulfilled.
Disclosure of Invention
The invention aims to build an innovative public transport passenger flow analysis working platform, an application system which can respectively carry out statistical analysis and query on card swiping data of a whole group, each operation branch company, each line and each single vehicle according to different dimensions and different time periods is built on the platform, and the on-line transmission and sharing of information are realized by means of a public transport information sharing basic network, so that the aims of carrying out query analysis and application on data on different terminals are fulfilled.
In order to achieve the technical effects, the technical scheme adopted by the invention is as follows:
the public transport passenger flow analysis system based on positioning and card swiping information is characterized in that real-time positioning data and departure data generated in the urban public transport operation process are transmitted to a public transport data center in real time through a mobile network of an operator, after the real-time data are subjected to preliminary processing, the positioning data of a public transport vehicle are stored in a positioning database, a data forwarding server continuously forwards the processed data outwards while the positioning data enter the database, one part of data is forwarded to a passenger flow system, and the positioning data is received and processed by a positioning data acquisition subsystem to serve as a positioning data source of the passenger flow analysis system;
the card swiping detail data is transmitted to a machine room server through the FTP at regular time every day, and after the card swiping detail file is uploaded, the file is decompressed and put in a storage by a card swiping data acquisition subsystem and stored as a card swiping data source;
after the card swiping data acquisition subsystem finishes the acquisition of the card swiping data file, the data generation subsystem automatically operates, matches the card swiping data of the day with the positioning data, and generates various passenger flow data required by production and operation for users to use;
the bus passenger flow analysis system framework based on the positioning and card swiping information is divided into three layers, namely a data acquisition layer, a data analysis layer and a data display layer, wherein the data acquisition layer acquires and converges data acquired in various ways, including line data, bus station data, card swiping data, positioning data and vehicle basic data, and performs pre-processing on all basic data, including analysis of abnormal data in the card swiping data and processing of error data, and completion and correction of lost data to and from a station in the vehicle positioning position information, and the processed data are stored in different data tables respectively; the data analysis layer builds a data analysis target, builds a proper analysis model, analyzes and processes various data by using a predefined data analysis method, is a core part of the whole system, judges a passenger getting-on bus station based on bus card swiping data and positioning data, calculates the passenger getting-off bus station, and analyzes passenger flow conditions of vehicles, lines, bus stations and areas in different time periods; the data display layer displays the analysis result into a browser according to a form required by a user;
passenger card swiping site clustering analysis and calculation: after the bus arrives at a bus stop, passengers sequentially swipe cards to get on the bus, the card swiping time of the passengers taking the same bus is relatively close and has strong time cluster characteristics, the card swiping and getting-on time of the passengers is recorded in the bus card swiping data, the card swiping time can be equal to the card swiping time of the passengers and also has strong time cluster characteristics, the card swiping time is subjected to cluster analysis, and data with short time intervals of two card swiping times of the same bus is used as one group or one class;
the method for carrying out cluster analysis on the bus card swiping data by adopting a system clustering method comprises the following steps:
the method comprises the steps that firstly, all card swiping records of a certain bus are extracted and sorted according to the time sequence, if a total number of Y records exists, each record is taken as one type, namely the initial classification number is Y;
second, comparing the interval h between two adjacent recordsnmCombining two or more types with minimum card swiping interval time into one type;
third, repeat the second step until min [ h ]nm]>WminStopping clustering, WminAnd the shortest card swiping time interval between two adjacent buses of the line is shown.
Bus passenger based on positioning and card swiping informationFlow analysis system, further, passenger card swiping site clustering analysis and calculation, WminThe choice of value is key to cluster analysis of the time of getting on the bus, WminToo large or too small a value setting may lead to erroneous judgment of the passenger getting on the bus stop, if W is too large or too smallminThe value setting is too small, when congestion occurs or more passengers get on the bus at the same bus station, the earliest and latest card swiping time intervals of the passengers getting on the bus at the same bus station are longer, and the wrong card swiping records of the same bus station are classified into different types possibly, namely the passengers get on the bus at different bus stations; if W isminIf the running time of the bus between two bus stations is less than the value, the card-swiping records of the two bus stations are wrongly classified into the same class, namely, the bus is considered to be on the same station, and therefore the value is set according to the distance between the stations and the running speed factor of the bus.
Public transit passenger flow analytic system based on location and information of punching the card, further, location data analysis and processing: the bus positioning data is sent to a bus data center by a vehicle-mounted positioning terminal device through an operator network at the frequency of one data packet every 15 seconds, and the positioning data is mainly divided into real-time data and positioning to-off-station data;
the positioning real-time data mainly comprises the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: longitude and latitude of the vehicle in real time; 4) speed information: the current real-time speed of the vehicle; 5) direction information: the orientation and direction of travel of the vehicle; 6) operation state: whether the vehicle is in operation or not;
the positioning and departure data mainly comprise the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: the serial number of the bus station where the vehicle currently arrives and departs from the station; 4) direction information: the orientation and direction of travel of the vehicle;
the passenger flow of the bus station is analyzed and calculated by a method of matching the card swiping time with the data of the arrival and departure of the vehicle, namely the data of the card swiping time in the time period after the arrival and the departure of the vehicle at a certain bus station are all considered as that passengers swipe the card at the bus station to get on the bus.
The bus passenger flow analysis system based on positioning and card swiping information further comprises the following steps of:
first, vehicle arrival and departure data loss: receive wireless network transmission's influence, vehicle-mounted terminal equipment is at the in-process of uploading the locating data, and the condition that data loss can appear, if the vehicle loses to the data of leaving the station, can cause the influence to correctly calculating the bus station of punching the card, consequently, at first to the vehicle to the data of leaving the station check, correct the benefit to the data that lose, concrete method is:
first, vehicle-to-station packet loss: supplementing the station-to-station data packet by using the station-to-station data of the vehicle and the station-to-station data of the vehicle, and if the station-to-station data of the first station is lost, supplementing the data by referring to the departure time of the vehicle in the scheduling system;
second, vehicle off-station data packet loss: supplementing the station leaving data packet by using the vehicle arrival data and the arrival data of the next station, and if the last station leaving data is lost, supplementing the data by referring to the vehicle final arrival time in the scheduling system;
thirdly, vehicle-to-station data packets are all lost: calculating a data packet of the station by using the data of the previous station of the vehicle and the data of the next station;
secondly, when the passenger punches the card and gets on the bus, the vehicle has not sent the data package that arrives at the station yet: due to the fact that the bus station is unreasonably arranged or the bus is jammed near the platform, the situation that passengers get on or off the bus occurs when the bus does not arrive at the passenger getting-on or getting-off area of the platform, partial card swiping time is not within the arrival and departure time range of the bus, and the card swiping time cannot be correctly matched with the parked bus station, therefore, when the boarding place of the passengers is calculated, the card swiping records of the same bus cannot be completely processed within the arrival and departure time range according to whether the card swiping time is within the arrival and departure time range, and then the card swiping records of the same bus are subjected to clustering analysis and are matched with the most reasonable vehicle departure time, and therefore the correct boarding bus station is calculated.
The bus passenger flow analysis system based on positioning and card swiping information is further composed of a positioning data acquisition subsystem, a card swiping data acquisition subsystem, a data generation subsystem and a passenger flow analysis and query subsystem:
the positioning data acquisition subsystem receives the real-time positioning data forwarded by the scheduling system according to an agreed data format, divides the real-time positioning data and the arrival and departure data into real-time positioning data and stores the real-time positioning data and the arrival and departure data into a database respectively;
the card swiping data acquisition subsystem is used for receiving the card swiping detail data every day and then importing the card swiping detail data into the database in real time to form card swiping detail data;
the data generation subsystem is used for carrying out cluster analysis on the card swiping data, carrying out matching processing on the card swiping data and the positioned departure data, matching the card swiping detail data into the positioned departure data to form arrival time, departure time and card swiping amount of each vehicle at each bus station, and generating the card swiping number of each vehicle at different time intervals according to a predefined time interval;
and the passenger flow analysis and query subsystem is used for querying the passenger flow of different latitudes of the display line and the bus station according to the query conditions of the user.
Public transit passenger flow analytic system based on location and information of punching the card, further, the location data gathers the subsystem: the positioning equipment sends the information of vehicle number, line number, current position and current speed to a positioning data receiving server through an operator network according to a specified time interval, the positioning data receiving server stores the data into a database as a data source of an intelligent dispatching system after receiving the data, and simultaneously forwards the data in real time as a positioning data source of a passenger flow analysis system, and a positioning data acquisition subsystem is used for receiving positioning data transmitted in real time and storing the positioning data into a passenger flow analysis system database;
1) transmission engagement
The data transmission adopts TCP/IP transmission; each data segment is data-separated by using "|", such as: longitude | latitude; the data transmission format of both sides communication is: start character | packet | end character;
2) data packet format: positioning information
Command word: positioning
Data packet format: < vehicle number > < line > < current date > < current time > < longitude (in units of division) > < latitude (in units of division) > < speed (km/h) > < orientation direction (in units of degrees) > < direction of travel (0 go/1 return) > < state of operation (0 in operation/1 not in operation) >;
3) data packet format: arrival and departure information
Command word: STN
Data packet format: < car number > < line > < current date > < current time > < bus stop number > < travel direction (0 go/1 return) > < departure identification (0 go/1 depart) > < departure from station >
The positioning data not only contains the real-time positioning data of each vehicle, but also describes the operation information of each vehicle arriving at each station, namely the arrival and departure information, and the parking time period of the vehicle at each bus station is calculated according to the arrival and departure information of each vehicle at each bus station.
The bus passenger flow analysis system based on the positioning and card swiping information further comprises a positioning data acquisition subsystem, a positioning data forwarding server and a communication interface, wherein the positioning data acquisition subsystem acquires positioning data in real time from the positioning data forwarding server in a Socket mode, the Socket is a group of well-defined interfaces and is software abstraction for TCP/IP protocol communication of an application layer, for a user, a complex TCP/IP protocol is hidden behind the interfaces, and the whole communication process can be completed only by directly calling the interfaces;
when the positioning data acquisition subsystem acquires positioning data, firstly creating a Socket, connecting the Socket to the positioning data acquisition subsystem at a data forwarding server after the Socket is built, sending data to a server, receiving data returned by the server, binding and monitoring a port by the server, completing connection when receiving a connection request of a client, ensuring data quality by adopting TCP (transmission control protocol), and transmitting data by adopting a connection-oriented mode;
the SOCKET receiving data processing steps in the system of the invention are as follows:
step one, an EndPoint object is constructed by using an appointed server IP and a port number;
step two, constructing a Socket object;
binding EndPoint by using a Bind () method of the Socket object and calling a Listen () method to start monitoring;
step four, after receiving a connection request of the client, creating a new object by using an Accept () method of a Socket object for communicating with the requested client;
and step five, closing the socket after the communication is finished.
The bus passenger flow analysis system based on the positioning and card swiping information further comprises a data generation subsystem, wherein the data generation subsystem carries out pre-processing on the acquired card swiping data and the positioning data to form complete vehicle positioning arrival time, departure time and effective card swiping data, then carries out time matching on the two parts of data to find the card swiping and getting-on stations of passengers, carries out various statistics according to the information and finally forms passenger flow statistical data of branch lines and stations.
Public transit passenger flow analytic system based on location and information of punching the card, further, location data preprocess: the public transport vehicle positioning equipment continuously sends the current vehicle number, line number, speed, progress and latitude information to a public transport data center every 15 seconds, the generation of positioning data records in a public transport system is greatly influenced by technical equipment and transmission conditions, error data is easy to generate, and the types of the public transport positioning error data mainly comprise two types of data abnormity and data loss;
data exception is that data records of some fields are far from reality, data loss is that data packet loss occurs in the process of transmitting positioning data through an operator network, partial data loss occurs as a result, especially positioning arrival data and departure data loss can bring great influence on matching card swiping time and calculating card swiping station, therefore, before card swiping information is matched with positioning information, positioning data is preprocessed, and abnormal data and lost data are processed firstly;
vehicle arrival and departure data loss condition processing:
comparing the data of the located station and the data of the located station, which are generated in one operation pass of the vehicle, with the number and the sequence of all the bus stations of the line on which the vehicle runs on the current day, indicating that the data are normal, and not performing additional processing;
if the line on which the vehicle runs has N bus stations, the arrival data of the Q-th bus station is missing, namely 1< ═ Q < ═ N, if Q ═ 1, the departure time of the first bus station minus 2 minutes is taken as the arrival time of the bus station, if Q >1, the departure time of the Q-1-th bus station plus 1 second is taken as the arrival time of the bus station, and other data recorded in the arrival station are written into the database after being supplemented;
if the line on which the vehicle runs has N bus stations, the Q-th bus station departure data is missing, namely 1< ═ Q < ═ N, if Q ═ N, the arrival time of the last bus station plus 2 minutes is taken as the departure time of the bus station, if Q < N, the arrival time of the Q + 1-th bus station minus 1 second is taken as the departure time of the bus station, and other data recorded in the departure station are written into the database after being supplemented;
if the line on which the vehicle runs has N bus stations, the arrival data and the departure data of the Q-th bus station are missing, namely 1< ═ Q < ═ N, if Q < ═ 1, Q +1, namely the arrival time of the second bus station minus 1 second is taken as the departure time of the first bus station, and meanwhile, the departure time minus 2 minutes is taken as the arrival time of the first bus station; if Q is equal to N, the departure time of the Q-1 station plus 1 second is taken as the arrival time of the Nth station, whether the vehicle has continuous operation data after the operation of the current time is finished is judged, if the vehicle has the continuous operation data, the arrival time of the first station of the next time of the vehicle minus 5 seconds is taken as the departure time of the Nth station, if the data is the operation data of the last time of the day, the calculated arrival time plus 60 minutes is taken as the departure time of the Nth station, and other data recorded in the departure are filled in a database and then written in the database.
The bus passenger flow analysis system based on positioning and card swiping information further comprises the following steps of card swiping data preprocessing: the card swiping data collected and stored in the card swiping data collection subsystem comprises card swiping date and card swiping time, in the actual operation process, sometimes due to the conditions of terminal data collection or transmission delay and the like, the card swiping data transmitted on the same day not only comprises the card swiping data on the same day, but also can have the conditions of card swiping data on other dates, so that the data on the different day needs to be cleaned, and the cleaning method comprises the following steps:
firstly, if data on a non-current day is more and the data on the same line in the data accounts for a larger amount, inserting the data into a card swiping data table on a corresponding date, inserting the data into a data regeneration task on the corresponding date, regenerating passenger flow volume data on the corresponding date when the data is idle, and deleting the data from the card swiping data table on the current day;
secondly, if the data on the non-current day is less, the data is directly deleted from the data table of the current day card swiping.
Compared with the prior art, the invention has the following contributions and innovation points:
firstly, the bus passenger flow analysis system based on positioning and card swiping information establishes a time matching getting-on station judgment method based on card swiping data and positioning departure information, and after fault-tolerant processing is carried out on the card swiping data and the positioning data, the card swiping data is matched with the positioning vehicle getting-on and departure data, and a passenger getting-on station is determined. The system is designed according to the requirements of users, the public transport passenger flow statistical analysis method is simple to apply, accurate in result and capable of providing scientific basis for optimizing and adjusting urban public transport, and popularization and application of the system are beneficial to a traffic management department and a public transport enterprise to know the distribution characteristics of passenger flow and optimize and adjust a public transport network in time, so that the operation efficiency of the public transport network is improved more effectively;
secondly, the public transport passenger flow analysis system based on positioning and card swiping information provided by the invention is mainly completed by people aiming at the manual investigation method for acquiring the public transport passenger flow data in the prior art, consumes a large amount of manpower and financial resources, is very difficult to form a mechanism for regularly and manually investigating the passenger flow, and the acquired data also has no real-time property, except that the preparation stage needs to organize and train related personnel, the data arrangement and analysis work after investigation is heavy, and the data quality is difficult to ensure by all manual processing modes, so that the acquired and analyzed data is inaccurate; the image discrimination method in the prior art has the problems of high cost, high material and financial consumption and poor stability when used for passenger flow analysis; matching the card swiping time with the vehicle parking bus station time in the positioning data by using the positioning position information generated by the vehicle, so that the card swiping and boarding bus station of the passenger can be obtained, and accurate card swiping passenger flow analysis information is obtained; the management and service system of the public transport enterprise is improved, the operation efficiency is improved, and the travel requirements of passengers are guaranteed to the greatest extent;
thirdly, the public transport passenger flow analysis system based on the positioning and card swiping information provided by the invention is applied to public transport scheduling operation: the passenger flow data is analyzed to research and master the change rule of the passenger volume cycle in each season, each month, each week and day and night on the line, master the passenger flow change rule, contribute to improving the operation management level, improve the scheduling measure, modify, supplement and perfect the driving operation plan, relieve the conflict of traffic congestion in the peak time period, avoid the waste caused by the empty driving of the vehicle, use the vehicle economically and reasonably, and ensure the service quality and the service efficiency of public traffic. By timely mastering the passenger flow and the change condition thereof, the dispatching frequency and the number of the dispatched vehicles of the line at the peak time and the flat peak time can be timely adjusted, a driving operation plan is scientifically and reasonably formulated, the vehicles are used at the maximum efficiency, better riding conditions are provided for passengers, and the traveling satisfaction of the passengers is improved;
fourthly, the bus passenger flow analysis system based on the positioning and card swiping information provided by the invention is applied to the internal management of the bus: after the passenger flow data is mastered, the passenger flow data and other related data are comprehensively and systematically analyzed and researched, so that regular related factors are found out, the line network management condition is scientifically evaluated, operation indexes and operation plans are reasonably formulated, and the internal management efficiency of the public transport enterprise is improved;
fifth, the system for analyzing the bus passenger flow based on the positioning and card swiping information provided by the invention is applied to the bus planning layout: the public traffic line network planning and the public traffic station setting need to master the conditions of public traffic passenger flow, various indexes related to the passenger flow such as average full load rate, OD distribution, transfer rate, line network benefit and the like are important bases for public traffic line network evaluation and planning, the passenger flow is predicted according to the change conditions of the passenger flow, and data support is provided for public traffic planning such as public traffic line trend, public traffic station layout and the like by calculating the medium-long term change trend of the passenger flow, so that the public traffic line planning and the public traffic station layout have great utilization value and market application space.
Drawings
FIG. 1 is a block diagram of a bus passenger flow analysis system based on location and card swipe information.
FIG. 2 is a block diagram of a functional framework of a bus passenger flow analysis system based on location and card swiping information.
Fig. 3 is a passenger card swiping station matching flow chart of the invention.
Detailed Description
The technical scheme of the bus passenger flow analysis system based on positioning and card swiping information provided by the invention is further described below with reference to the accompanying drawings, so that the technical scheme can be better understood and implemented by those skilled in the art.
System architecture framework
Real-time positioning data and the data of leaving the station that produce among the urban public transit operation process transmit public transit data center through the mobile network of operator in real time, after the preliminary treatment to real-time data, public transit vehicle positioning data is deposited in the positioning database, when the positioning data got into the database, the data forwarding server is continuous outwards forwardding the data after handling, one of them data are forwarded in the passenger flow system, receive through positioning data collection subsystem and handle the back, as passenger flow analytic system's positioning data source.
And regularly transmitting the card swiping detail data to a computer room server through FTP every day, and decompressing and warehousing the file by a card swiping data acquisition subsystem after the card swiping detail file is uploaded to serve as a card swiping data source for storage.
After the card swiping data acquisition subsystem finishes the acquisition of the card swiping data file, the data generation subsystem automatically operates, card swiping data of the day is matched with positioning data, and various passenger flow data required by production and operation are generated for users to use.
A frame diagram of a bus passenger flow analysis system based on positioning and card swiping information is shown in fig. 1 and is divided into three layers, namely a data acquisition layer, a data analysis layer and a data display layer, wherein the data acquisition layer acquires and converges data acquired in various ways, including line data, bus station data, card swiping data, positioning data and vehicle basic data, and performs pre-processing on all basic data, including analysis of abnormal data in the card swiping data and processing of error data, and completion and correction of lost data to and from a station in the vehicle positioning position information, and the processed data are respectively stored in different data tables; the data analysis layer builds a data analysis target, builds a proper analysis model, analyzes and processes various data by using a predefined data analysis method, is a core part of the whole system, judges a passenger getting-on bus station based on bus card swiping data and positioning data, calculates the passenger getting-off bus station, and analyzes passenger flow conditions of vehicles, lines, bus stations and areas in different time periods; and the data display layer displays the analysis result to the browser in a form required by the user.
Secondly, data analysis and processing
Card swiping data analysis and processing
Acquiring the following types of bus card swiping data information: firstly, card swiping time: the date and detailed time of each card swipe; second, vehicle information: the number of the card swiping machine, the vehicle number and the line number corresponding to each card swiping; thirdly, passenger information; and fourthly, deducting money.
(II) analysis and processing of positioning data
The bus positioning data is sent to a bus data center by vehicle-mounted positioning terminal equipment through an operator network at the frequency of one data packet per 15 seconds, and the positioning data is mainly divided into real-time data and positioning to off-station data.
The positioning real-time data mainly comprises the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: longitude and latitude of the vehicle in real time; 4) speed information: the current real-time speed of the vehicle; 5) direction information: the orientation and direction of travel of the vehicle; 6) operation state: whether the vehicle is in operation or not.
The positioning and departure data mainly comprise the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: the serial number of the bus station where the vehicle currently arrives and departs from the station; 4) direction information: the orientation direction and the direction of travel of the vehicle.
The passenger flow of the bus station is analyzed and calculated by a method of matching the card swiping time with the data of the arrival and departure of the vehicle, namely the data of the card swiping time in the time period after the arrival and the departure of the vehicle at a certain bus station are all considered as that passengers swipe the card at the bus station to get on the bus.
Processing positioning abnormal data:
1. vehicle-to-station data loss: receive wireless network transmission's influence, vehicle-mounted terminal equipment is at the in-process of uploading the locating data, and the condition that data loss can appear, if the vehicle loses to the data of leaving the station, can cause the influence to correctly calculating the bus station of punching the card, consequently, at first to the vehicle to the data of leaving the station check, correct the benefit to the data that lose, concrete method is:
first, vehicle-to-station packet loss: supplementing the station-to-station data packet by using the station-to-station data of the vehicle and the station-to-station data of the vehicle, and if the station-to-station data of the first station is lost, supplementing the data by referring to the departure time of the vehicle in the scheduling system;
second, vehicle off-station data packet loss: supplementing the station leaving data packet by using the vehicle arrival data and the arrival data of the next station, and if the last station leaving data is lost, supplementing the data by referring to the vehicle final arrival time in the scheduling system;
thirdly, vehicle-to-station data packets are all lost: and calculating the data packet of the station by using the data of the previous station of the vehicle and the data of the next station.
2. When the passenger punches the card and gets on the bus, the vehicle has not sent the data package that arrives at the station yet: due to the fact that the bus station is unreasonably arranged or the bus is jammed near the platform, the situation that passengers get on or off the bus occurs when the bus does not arrive at the passenger getting-on or getting-off area of the platform, partial card swiping time is not within the arrival and departure time range of the bus, and the card swiping time cannot be correctly matched with the parked bus station, therefore, when the boarding place of the passengers is calculated, the card swiping records of the same bus cannot be completely processed within the arrival and departure time range according to whether the card swiping time is within the arrival and departure time range, and then the card swiping records of the same bus are subjected to clustering analysis and are matched with the most reasonable vehicle departure time, and therefore the correct boarding bus station is calculated.
Thirdly, clustering analysis and calculation of passenger card swiping sites
After the bus arrives at a bus stop, passengers swipe cards in sequence to get on the bus, the card swiping time of the passengers taking the same bus is relatively close, and the bus swiping time is very strong in time clustering characteristic, and the card swiping and getting on time of the passengers is recorded in bus card swiping data, so that the card swiping time can be equal to the getting on time of the passengers, and the bus swiping time also has very strong time clustering characteristic. And performing cluster analysis on the card swiping time, and taking the data with short time interval between two card swiping times of the same vehicle as a group or a class.
The method for carrying out cluster analysis on the bus card swiping data by adopting a system clustering method comprises the following steps:
the method comprises the steps that firstly, all card swiping records of a certain bus are extracted and sorted according to the time sequence, if a total number of Y records exists, each record is taken as one type, namely the initial classification number is Y;
second, comparing the interval h between two adjacent recordsnmCombining two or more types with minimum card swiping interval time into one type;
third, repeat the second step until min [ h ]nm]>WminStopping clustering, WminAnd the shortest card swiping time interval between two adjacent buses of the line is shown.
WminThe choice of value is key to cluster analysis of the time of getting on the bus, WminToo large or too small a value setting may lead to erroneous judgment of the passenger getting on the bus stop, if W is too large or too smallminThe value is set to be too small and is outputWhen the passengers are congested or the number of passengers getting on the same bus station is large, the earliest and latest card swiping time intervals of the passengers getting on the same bus station are long, and the card swiping records of the same bus station are possibly classified into different types, namely the passengers getting on the different bus stations are considered; if W isminIf the setting is too large, when the running time of the bus between two bus stations is less than the value, the card-swiping records of the two bus stations are classified into the same class, namely, the bus is considered to be on the same station. Therefore, the value is set with reference to the distance between stops and the traveling speed factor of the bus.
Fourth, system function frame module
The passenger flow analysis system is composed of a positioning data acquisition subsystem, a card swiping data acquisition subsystem, a data generation subsystem and a passenger flow analysis query subsystem. The functional framework diagram of the system is shown in FIG. 2:
1. the positioning data acquisition subsystem receives the real-time positioning data forwarded by the scheduling system according to an agreed data format, divides the real-time positioning data and the arrival and departure data into real-time positioning data and stores the real-time positioning data and the arrival and departure data into a database respectively;
2. and the card swiping data acquisition subsystem is used for importing the card swiping detail data into the database in real time after receiving the card swiping detail data every day to form card swiping detail data.
3. The data generation subsystem is used for carrying out cluster analysis on the card swiping data, carrying out matching processing on the card swiping data and the positioned departure data, matching the card swiping detail data into the positioned departure data to form arrival time, departure time and card swiping amount of each vehicle at each bus station, and generating the card swiping number of each vehicle at different time intervals according to a predefined time interval;
4. and the passenger flow analysis and query subsystem is used for querying the passenger flow of different latitudes of the display line and the bus station according to the query conditions of the user.
Fifth, positioning data acquisition subsystem
The positioning equipment sends a vehicle number, a line number, a current position and current speed information to the positioning data receiving server through an operator network according to a specified time interval, the positioning data receiving server stores the data in a database as a data source of an intelligent dispatching system after receiving the data, the data are forwarded out in real time at the same time and serve as a positioning data source of a passenger flow analysis system, and the positioning data acquisition subsystem is used for receiving positioning data transmitted in real time and storing the positioning data in the passenger flow analysis system database.
1. Transmission engagement
The data transmission adopts TCP/IP transmission; each data segment is data-separated by using "|", such as: longitude | latitude; the data transmission format of both sides communication is: start character | packet | end character.
2. Data packet format: positioning information
Command word: positioning
Data packet format: < vehicle number > | < line > | < current date > | < current time > | < longitude (in units of division) > | < latitude (in units of division) > | < speed (km/h) > | < orientation direction (in units of degrees) > | < direction of travel (0 go/1 return) > | < state of operation (0 in operation/1 out of operation) > |
3. Data packet format: arrival and departure information
Command word: STN
Data packet format: < car number > < line > < current date > < current time > < bus stop number > < travel direction (0 go/1 return) > < departure identification (0 go/1 depart) > < departure from station >
The positioning data not only contains the real-time positioning data of each vehicle, but also describes the operation information of each vehicle arriving at each station, namely the arrival and departure information, and the parking time period of the vehicle at each bus station is calculated according to the arrival and departure information of each vehicle at each bus station.
The positioning data acquisition subsystem acquires positioning data in real time from the positioning data forwarding server in a Socket mode, the Socket is a set of well-defined interfaces and is software abstraction for TCP/IP protocol communication of an application layer, for a user, a complex TCP/IP protocol is hidden behind the interfaces, and the whole communication process can be completed only by directly calling the interfaces.
When the positioning data acquisition subsystem acquires positioning data, a Socket is firstly created, the Socket is connected to the positioning data acquisition subsystem at a data forwarding server after being constructed, data are sent to a server, data returned by the server are received, the server only needs to bind and monitor a port, connection is completed when a connection request of a client is received, TCP is adopted to guarantee data quality, and a connection-oriented mode is adopted to transmit data.
The SOCKET receiving data processing steps in the system of the invention are as follows:
step one, an EndPoint object is constructed by using an appointed server IP and a port number;
step two, constructing a Socket object;
binding EndPoint by using a Bind () method of the Socket object and calling a Listen () method to start monitoring;
step four, after receiving a connection request of the client, creating a new object by using an Accept () method of a Socket object for communicating with the requested client;
and step five, closing the socket after the communication is finished.
Sixth, data generation subsystem
The data generation subsystem carries out pre-processing on the collected card swiping data and the positioning data to form complete vehicle positioning arrival time, departure time and effective card swiping data, then carries out time matching on the two parts of data to find the card swiping boarding stations of passengers, carries out various statistics according to the information, and finally forms passenger flow statistical data of branch lines and stations. The flow chart is shown in fig. 3.
1. Positioning data pre-processing
The public transport vehicle positioning equipment sends current vehicle number, line number, speed, progress and latitude information to a public transport data center uninterruptedly every 15 seconds, and the generation of positioning data records in a public transport system is greatly influenced by technical equipment and transmission conditions, so that error data are easily generated. The bus positioning error data types mainly comprise data abnormity and data loss.
Data anomalies are data records of some fields which are far from the actual situation, for example, positioning drift problems in the positioning process can cause the received longitude and latitude or real-time speed to be out of the normal range. Data loss is a phenomenon that data packets are lost when positioning data are transmitted through an operator network, and partial data loss occurs as a result, especially positioning arriving data and leaving data loss can bring great influence on matching card swiping time and calculating card swiping stations. Therefore, before matching the card swiping information with the positioning information, the positioning data is preprocessed, and abnormal data and lost data are processed firstly.
Vehicle arrival and departure data loss condition processing:
comparing the data of the located station and the data of the located station, which are generated in one operation pass of the vehicle, with the number and the sequence of all the bus stations of the line on which the vehicle runs on the current day, indicating that the data are normal, and not performing additional processing;
if the line on which the vehicle runs has N bus stations, the arrival data of the Q-th bus station is missing, namely 1< ═ Q < ═ N, if Q < >1, the departure time of the first bus station minus 2 minutes is taken as the arrival time of the bus station, if Q >1, the departure time of the Q-1-th bus station plus 1 second is taken as the arrival time of the bus station, and other data recorded in the arrival station are written into the database after being supplemented.
If the line on which the vehicle runs has N bus stations, the Q-th bus station departure data is missing, namely 1< ═ Q < ═ N, if Q ═ N, the arrival time of the last bus station plus 2 minutes is taken as the departure time of the bus station, if Q < N, the arrival time of the Q + 1-th bus station minus 1 second is taken as the departure time of the bus station, and other data recorded in the departure station are written into the database after being supplemented.
If the line on which the vehicle runs has N bus stations, the arrival data and the departure data of the Q-th bus station are missing, namely 1< ═ Q < ═ N, if Q < ═ 1, Q +1, namely the arrival time of the second bus station minus 1 second is taken as the departure time of the first bus station, and meanwhile, the departure time minus 2 minutes is taken as the arrival time of the first bus station; and if Q is equal to N, the departure time of the Q-1 station plus 1 second is taken as the arrival time of the Nth station, and whether the vehicle has continuous operation data after the operation of the current time is finished is judged. If the continuous operation data exists, subtracting 5 seconds from the arrival time of the first station of the next time of the vehicle to be used as the departure time of the Nth station, and if the data is the operation data of the last time of the current day, adding 60 minutes to the calculated arrival data to be used as the departure time of the Nth station, and writing the data into a database after completing other data recorded in the departure.
2. Card swiping data pre-processing
The card swiping data collected and stored in the card swiping data collection subsystem comprises card swiping date and card swiping time, in the actual operation process, sometimes due to the conditions of terminal data collection or transmission delay and the like, the card swiping data transmitted on the same day not only comprises the card swiping data on the same day, but also can have the conditions of card swiping data on other dates, so that the data on the different day needs to be cleaned, and the cleaning method comprises the following steps:
firstly, if data on a non-current day is more and the data on the same line in the data accounts for a larger amount, inserting the data into a card swiping data table on a corresponding date, inserting the data into a data regeneration task on the corresponding date, regenerating passenger flow volume data on the corresponding date when the data is idle, and deleting the data from the card swiping data table on the current day;
secondly, if the data on the non-current day is less, the data is directly deleted from the data table of the current day card swiping.
3. Card swiping data matching to bus station
The card swiping data is matched with the bus station, each card swiping record corresponds to the bus station, and if the time of the vehicle-mounted positioning device is completely consistent with that of the card swiping machine, the bus time of a passenger is within the range of the time of the arrival and departure of the vehicle, so that the passenger can be finally determined to be the bus on which bus station the vehicle generates the data of the departure as long as the bus card swiping time is matched within the range of the time interval between the arrival and departure of the vehicle. But considering the actual situation of urban public transport at present: some bus stations have many parking routes, vehicles are often arranged into long queues to enter the station during the peak of commuting, the vehicles arranged behind cannot open the doors by the station to allow passengers to get on the station, and the vehicles do not approach the triggering position of the arrival data packet to cause the arrival data packet not to be triggered, so that the card swiping time of the part of passengers is out of the arrival time, and finally the mistake of matching the arrival bus station occurs. Therefore, when the card swiping data is matched with the boarding bus station in the system, the arrival time is ignored, and the departure time is adopted to measure whether the boarding bus station is the boarding bus station, and the specific steps are as follows:
step 1, grouping card swiping records according to lines and vehicles, and sequencing according to a card swiping time sequence;
step 2, arranging the departure time of each trolley of the line in sequence according to the vehicles and the departure time;
and 3, carrying out cluster analysis on the card swiping records of the same trolley to obtain card swiping time, and from the 1 st station, if the card swiping time is less than the corresponding station leaving time of the station, judging that the card swiping records are generated at the station, namely matching the card swiping records with the station.
4. Generating passenger flow analysis results
And according to the result of matching the card swiping with the bus station, carrying out the convergence calculation of the matching data, respectively storing the analysis information into a bus station card swiping analysis table and a line bus station card swiping analysis table to form analysis passenger flow data in any time period, and automatically generating weekly report analysis data and monthly report analysis data after each week and each month are finished.
Seventh, passenger flow analysis query subsystem
The passenger flow analysis and query subsystem performs convergence analysis by using line bus station card swiping detail data generated by matching of the data generation subsystem, and generates different passenger flow information according to various dimensions. The passenger flow analysis query subsystem realizes query analysis of a plurality of functions according to different requirements and is divided into three layers of architectures, namely a data access layer, a service logic layer and a display layer, wherein the data access layer is responsible for data processing and performs various operations on data according to the requirements of the service logic layer, the service logic layer defines various methods according to function division, and the data acquired by the data access layer is returned to the display layer to be displayed to a user.
The main functional modules of the passenger flow analysis and query subsystem comprise:
module 1, daily passenger flow analysis, bus group daily time period card swiping amount analysis: the method mainly aims at counting all card swiping conditions of all vehicles in one day in different time periods, and a user can select a date and a time interval and can look up all card swiping aggregation numbers in all time periods in a certain day, card swiping curves and bar graphs in all time periods.
Module 2, daily passenger flow volume analysis, and company-divided daily time period passenger flow volume comparison: the card swiping total number of each time period in a certain day of each operation branch company, the card swiping curve and the bar graph of each time period of each branch company can be seen through inquiry by mainly carrying out aggregation comparison on the card swiping times of each time period in one day of each operation branch company through the user, and the comparison curve and the bar graph can be seen through any one company or a plurality of companies through the user.
Module 3, daily passenger flow analysis, line daily time period passenger flow comparison: the card swiping times of each time period in each day of each line are gathered and compared, a user can select one or more lines, dates and time intervals, the total card swiping amount of each time period in each day of each line, the card swiping curve and the bar graph of each time period of each line can be seen through inquiry, and the user can select any one or more lines to view the comparison curve and the bar graph.
Module 4, daily passenger flow volume analysis, line bus station period card swiping amount analysis: the method mainly aims at the card swiping times of each time period in one day of each bus station of a single line to conduct aggregation analysis, a user can select the line name, the date, the time interval and the going-back direction, the total card swiping number and the curve graph of each time period in one day of each bus station of the currently selected line can be seen through query, and the user can select any one or more bus stations under the current line to view and compare the curve graphs.
Module 5, daily passenger flow volume analysis, line bus station period card swiping amount analysis: the method mainly aims at the card swiping times of each time period in one day of each bus station of a single line and the train number passing through each bus station in each time period to conduct aggregation analysis, a user can select the line name, the date, the time interval and the going-back direction, an aggregation list of the card swiping total number and the train number of each time period in one day of each station of the currently selected line and a curve graph drawn by the list data can be inquired, and the user can select any one or more bus stations under the current line to check and compare the curve graphs.
Module 6, daily passenger flow volume analysis, bus station daily time period passenger flow volume comparison: the method mainly aims at carrying out convergence analysis on the card swiping amount of each time period in one day of all the bus stations. The user can select the date and the time interval, the total number of the card swiping in each time period in a certain day of each bus station, the curve graph and the histogram can be seen through inquiry, the user can select any one or more bus stations to view the comparison curve graph and the histogram, and the data are sorted from large to small according to the card swiping amount of each bus station.
Module 7, weekly passenger flow analysis, and weekly passenger flow comparison of branch companies: the system mainly aims at analyzing card swiping data of all branch companies of the public transportation group in the same time period every week in the appointed date range, so that a user can conveniently see the passenger transportation condition of each branch company in the same time period in the same week, the user can select the date range and the time interval for inquiry, and meanwhile, a curve graph and a bar graph drawn by the data can also be viewed.
Module 8, weekly passenger flow analysis, line weekly passenger flow comparison: the method mainly aims at analyzing card swiping data of lines in the same time period every week in the appointed date range, so that a user can conveniently see passenger traffic conditions of all lines selected by the user in the same week in the same time period, the user selects line names, date ranges and time intervals for inquiry, and meanwhile, a curve graph and a bar graph drawn by the data can be viewed.
Module 9, weekly passenger flow analysis, weekly passenger flow comparison of bus stations: the method mainly aims at analyzing the card swiping data of the bus stations in the same time period every week in the appointed date range, so that the user can conveniently see the passenger traffic condition of the bus stations selected by the user in the same week in the same time period, and the user selects the bus stations, the date range and the time interval to inquire. The graphs and histograms plotted from these data can also be viewed.
Module 10, weekly passenger flow analysis, weekly passenger flow comparison of branch companies: the card swiping amount of each week is subjected to aggregation analysis from monday to sunday in a time period selected by a user for a certain branch company, the user can select the branch company and the query date, and the total card swiping amount of the currently selected branch company in each week in the selected time period, the comparison curve chart and the histogram can be seen by clicking the query.
Module 11, weekly passenger flow analysis, line weekly passenger flow comparison: the method mainly aims at that the card swiping amount of a certain line in a time period selected by a user is subjected to convergence analysis from Monday to Sunday, the user can select the line and the query date, and the total card swiping amount of the currently selected line in the selected time period per day can be seen by clicking the query, and a comparison curve graph and a histogram are obtained.
Module 12, weekly passenger flow analysis, weekly passenger flow comparison of bus stations: the card swiping amount of each week is subjected to convergence analysis from Monday to Sunday in a time period selected by a user mainly aiming at a certain bus station. The user can input the name and the query date of the bus station, and click the query to see the total number of card swipes per day per week of the currently selected bus station in the selected time period and compare the curve chart with the histogram.
Module 13, weekly passenger flow analysis, line single week passenger volume analysis: the method mainly aims at analyzing the total number of people per day in a week of a specified line, and utilizes the function of comparing the total number of people per day with the average number of people per week. The user selects the line and the date, and all data of the week of the date selected by the user can be seen by clicking the query.
Module 14, monthly passenger flow analysis, and company-divided monthly passenger traffic volume comparison: the data of all branch companies of the public transportation group in a certain two months are gathered and analyzed, the function of data comparison is provided according to different time periods, and a user can select any two months and time intervals and can obtain comparison results through query.
Module 15, monthly passenger flow analysis: comparing the line monthly passenger traffic volume: the method mainly aims at carrying out aggregation analysis on data of one or more lines in a certain two months, and provides a data comparison function according to different time periods. The user can select any one or more lines in the authority range, select any two months and time interval, and the comparison result can be obtained through query. Graphs and histograms plotted from these comparison data can also be viewed.
Module 16, monthly passenger flow analysis, comparison of monthly passenger traffic of a bus station: the system mainly performs convergence analysis on data of a certain bus station in two months, provides a data comparison function according to different time periods, and can be used for inquiring to obtain a comparison result and viewing a curve graph and a histogram drawn by comparison data by selecting any bus station in an authority range and selecting any two months and time intervals.
Module 17, time slot passenger flow analysis, and branch company passenger flow analysis: the card swiping data analysis of each branch company in any time period is provided, the card swiping conditions of each card in any time period can be inquired through the function, a user selects the time period to be inquired, the analysis data can be inquired by clicking the inquiry, and a curve graph and a histogram drawn by the analysis data can also be checked through the function.
Module 18, time quantum passenger flow analysis, operation branch company passenger flow volume analysis: the card swiping data analysis of each branch company in any time period is provided, the card swiping conditions of each card in any time period are inquired through the function, a user selects the time period and the company name which are required to be inquired, the analysis data can be inquired by clicking the inquiry, and a curve graph and a histogram drawn by the analysis data can also be checked through the function.
Module 19, time slot passenger flow analysis, line passenger flow analysis: the card swiping data analysis of each line in any time period is provided, the card swiping conditions of each card in any line in any time period in the user authority range are inquired through the function, a user selects a time period and one or more lines which the user wants to inquire, the analysis data can be inquired by clicking the inquiry, and a curve graph and a histogram drawn by the analysis data can also be checked through the function.
Module 20, time slot passenger flow analysis, line bus station passenger flow analysis: card swiping data analysis of each bus station of a certain line in any time period is provided, card swiping conditions of each bus station of a specified line in any time period and each card type in a user authority range are inquired through the function, a user selects the time period, the line name and the going-back direction which the user wants to check, the analysis result can be inquired through clicking inquiry, and a curve graph and a column graph drawn by the inquiry results can also be checked through the function.
Module 21, time slot passenger flow analysis, line bus station passenger flow analysis: the bus seat number and passenger flow volume analysis of a line bus station provides card swiping data analysis of each bus station of a certain line in any time period, the number of the bus times estimated by each bus station is automatically calculated according to the average bus seat number filled by a user, the user inquires the card swiping conditions of each bus station of a specified line in the authority range of the user and the card types in any time period and the number of the bus times automatically calculated according to the number of the bus seats, the user selects the time period, the line name and the going-back direction to be checked, the analysis result can be inquired by clicking the inquiry, and a curve graph and a column graph drawn by the inquiry results can also be checked through the function.
Claims (10)
1. The public transport passenger flow analysis system based on positioning and card swiping information is characterized in that real-time positioning data and departure data generated in the urban public transport operation process are transmitted to a public transport data center in real time through a mobile network of an operator, after the real-time data are subjected to primary processing, the public transport positioning data are stored in a positioning database, when the positioning data enter the database, a data forwarding server continuously forwards the processed data outwards, one part of data is forwarded to a passenger flow system, and the data are received and processed by a positioning data acquisition subsystem to serve as a positioning data source of the passenger flow analysis system;
the card swiping detail data is transmitted to a machine room server through the FTP at regular time every day, and after the card swiping detail file is uploaded, the file is decompressed and put in a storage by a card swiping data acquisition subsystem and stored as a card swiping data source;
after the card swiping data acquisition subsystem finishes the acquisition of the card swiping data file, the data generation subsystem automatically operates, matches the card swiping data of the day with the positioning data, and generates various passenger flow data required by production and operation for users to use;
the bus passenger flow analysis system framework based on the positioning and card swiping information is divided into three layers, namely a data acquisition layer, a data analysis layer and a data display layer, wherein the data acquisition layer acquires and converges data acquired in various ways, including line data, bus station data, card swiping data, positioning data and vehicle basic data, and performs pre-processing on all basic data, including analysis of abnormal data in the card swiping data and processing of error data, and completion and correction of lost data to and from a station in the vehicle positioning position information, and the processed data are stored in different data tables respectively; the data analysis layer builds a data analysis target, builds a proper analysis model, analyzes and processes various data by using a predefined data analysis method, is a core part of the whole system, judges a passenger getting-on bus station based on bus card swiping data and positioning data, calculates the passenger getting-off bus station, and analyzes passenger flow conditions of vehicles, lines, bus stations and areas in different time periods; the data display layer displays the analysis result into a browser according to a form required by a user;
passenger card swiping site clustering analysis and calculation: after the bus arrives at a bus stop, passengers sequentially swipe cards to get on the bus, the card swiping time of the passengers taking the same bus is relatively close and has strong time cluster characteristics, the card swiping and getting-on time of the passengers is recorded in the bus card swiping data, the card swiping time can be equal to the card swiping time of the passengers and also has strong time cluster characteristics, the card swiping time is subjected to cluster analysis, and data with short time intervals of two card swiping times of the same bus is used as one group or one class;
the method for carrying out cluster analysis on the bus card swiping data by adopting a system clustering method comprises the following steps:
the method comprises the steps that firstly, all card swiping records of a certain bus are extracted and sorted according to the time sequence, if a total number of Y records exists, each record is taken as one type, namely the initial classification number is Y;
second, comparing the interval h between two adjacent recordsnmCombining two or more types with minimum card swiping interval time into one type;
third, repeat the second step until min [ h ]nm]>WminStopping clustering, WminAnd the shortest card swiping time interval between two adjacent buses of the line is shown.
2. The system of claim 1, wherein W is a group of words in the analysis and calculation of passenger card swiping stationsminThe choice of value is key to cluster analysis of the time of getting on the bus, WminToo large or too small a value setting may lead to erroneous judgment of the passenger getting on the bus stop, if W is too large or too smallminThe value setting is too small, when congestion occurs or more passengers get on the bus at the same bus station, the earliest and latest card swiping time intervals of the passengers getting on the bus at the same bus station are longer, and the wrong card swiping records of the same bus station are classified into different types possibly, namely the passengers get on the bus at different bus stations; if W isminIf the running time of the bus between two bus stations is less than the value, the card-swiping records of the two bus stations are wrongly classified into the same class, namely, the bus is considered to be on the same station, and therefore the value is set according to the distance between the stations and the running speed factor of the bus.
3. The bus passenger flow analysis system based on location and card swiping information according to claim 1, wherein location data analysis and processing: the bus positioning data is sent to a bus data center by a vehicle-mounted positioning terminal device through an operator network at the frequency of one data packet every 15 seconds, and the positioning data is mainly divided into real-time data and positioning to-off-station data;
the positioning real-time data mainly comprises the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: longitude and latitude of the vehicle in real time; 4) speed information: the current real-time speed of the vehicle; 5) direction information: the orientation and direction of travel of the vehicle; 6) operation state: whether the vehicle is in operation or not;
the positioning and departure data mainly comprise the following information: 1) vehicle information: the vehicle number and the line number of the vehicle; 2) time information: date and time of sending the data; 3) position information: the serial number of the bus station where the vehicle currently arrives and departs from the station; 4) direction information: the orientation and direction of travel of the vehicle;
the passenger flow of the bus station is analyzed and calculated by a method of matching the card swiping time with the data of the arrival and departure of the vehicle, namely the data of the card swiping time in the time period after the arrival and the departure of the vehicle at a certain bus station are all considered as that passengers swipe the card at the bus station to get on the bus.
4. The bus passenger flow analysis system based on location and card swiping information according to claim 3, wherein location anomaly data processing:
first, vehicle arrival and departure data loss: receive wireless network transmission's influence, vehicle-mounted terminal equipment is at the in-process of uploading the locating data, and the condition that data loss can appear, if the vehicle loses to the data of leaving the station, can cause the influence to correctly calculating the bus station of punching the card, consequently, at first to the vehicle to the data of leaving the station check, correct the benefit to the data that lose, concrete method is:
first, vehicle-to-station packet loss: supplementing the station-to-station data packet by using the station-to-station data of the vehicle and the station-to-station data of the vehicle, and if the station-to-station data of the first station is lost, supplementing the data by referring to the departure time of the vehicle in the scheduling system;
second, vehicle off-station data packet loss: supplementing the station leaving data packet by using the vehicle arrival data and the arrival data of the next station, and if the last station leaving data is lost, supplementing the data by referring to the vehicle final arrival time in the scheduling system;
thirdly, vehicle-to-station data packets are all lost: calculating a data packet of the station by using the data of the previous station of the vehicle and the data of the next station;
secondly, when the passenger punches the card and gets on the bus, the vehicle has not sent the data package that arrives at the station yet: due to the fact that the bus station is unreasonably arranged or the bus is jammed near the platform, the situation that passengers get on or off the bus occurs when the bus does not arrive at the passenger getting-on or getting-off area of the platform, partial card swiping time is not within the arrival and departure time range of the bus, and the card swiping time cannot be correctly matched with the parked bus station, therefore, when the boarding place of the passengers is calculated, the card swiping records of the same bus cannot be completely processed within the arrival and departure time range according to whether the card swiping time is within the arrival and departure time range, and then the card swiping records of the same bus are subjected to clustering analysis and are matched with the most reasonable vehicle departure time, and therefore the correct boarding bus station is calculated.
5. The bus passenger flow analysis system based on positioning and card swiping information as claimed in claim 1, wherein the passenger flow analysis system is composed of four parts of a positioning data acquisition subsystem, a card swiping data acquisition subsystem, a data generation subsystem and a passenger flow analysis query subsystem:
the positioning data acquisition subsystem receives the real-time positioning data forwarded by the scheduling system according to an agreed data format, divides the real-time positioning data and the arrival and departure data into real-time positioning data and stores the real-time positioning data and the arrival and departure data into a database respectively;
the card swiping data acquisition subsystem is used for receiving the card swiping detail data every day and then importing the card swiping detail data into the database in real time to form card swiping detail data;
the data generation subsystem is used for carrying out cluster analysis on the card swiping data, carrying out matching processing on the card swiping data and the positioned departure data, matching the card swiping detail data into the positioned departure data to form arrival time, departure time and card swiping amount of each vehicle at each bus station, and generating the card swiping number of each vehicle at different time intervals according to a predefined time interval;
and the passenger flow analysis and query subsystem is used for querying the passenger flow of different latitudes of the display line and the bus station according to the query conditions of the user.
6. The bus passenger flow analysis system based on location and card swiping information according to claim 1, wherein the location data collection subsystem: the positioning equipment sends the information of vehicle number, line number, current position and current speed to a positioning data receiving server through an operator network according to a specified time interval, the positioning data receiving server stores the data into a database as a data source of an intelligent dispatching system after receiving the data, and simultaneously forwards the data in real time as a positioning data source of a passenger flow analysis system, and a positioning data acquisition subsystem is used for receiving positioning data transmitted in real time and storing the positioning data into a passenger flow analysis system database;
1) transmission engagement
The data transmission adopts TCP/IP transmission; each data segment is data-separated by using "|", such as: longitude | latitude; the data transmission format of both sides communication is: start character | packet | end character;
2) data packet format: positioning information
Command word: positioning
Data packet format: < vehicle number > < line > < current date > < current time > < longitude (in units of division) > < latitude (in units of division) > < speed (km/h) > < orientation direction (in units of degrees) > < direction of travel (0 go/1 return) > < state of operation (0 in operation/1 not in operation) >;
3) data packet format: arrival and departure information
Command word: STN
Data packet format: < car number > < line > < current date > < current time > < bus stop number > < travel direction (0 go/1 return) > < departure identification (0 go/1 depart) > < departure from station >
The positioning data not only contains the real-time positioning data of each vehicle, but also describes the operation information of each vehicle arriving at each station, namely the arrival and departure information, and the parking time period of the vehicle at each bus station is calculated according to the arrival and departure information of each vehicle at each bus station.
7. The bus passenger flow analysis system based on positioning and card swiping information as claimed in claim 6, wherein the positioning data acquisition subsystem acquires the positioning data from the positioning data forwarding server in real time in a Socket manner, the Socket is a group of well defined interfaces, and is a software abstraction for TCP/IP protocol communication of an application layer, for a user, the complex TCP/IP protocol is hidden behind the interface, and the whole communication process can be completed only by directly calling the interface;
when the positioning data acquisition subsystem acquires positioning data, firstly creating a Socket, connecting the Socket to the positioning data acquisition subsystem at a data forwarding server after the Socket is built, sending data to a server, receiving data returned by the server, binding and monitoring a port by the server, completing connection when receiving a connection request of a client, ensuring data quality by adopting TCP (transmission control protocol), and transmitting data by adopting a connection-oriented mode;
the SOCKET receiving data processing steps in the system of the invention are as follows:
step one, an EndPoint object is constructed by using an appointed server IP and a port number;
step two, constructing a Socket object;
binding EndPoint by using a Bind () method of the Socket object and calling a Listen () method to start monitoring;
step four, after receiving a connection request of the client, creating a new object by using an Accept () method of a Socket object for communicating with the requested client;
and step five, closing the socket after the communication is finished.
8. The system for analyzing the passenger flow in the public transport based on the positioning and card swiping information as claimed in claim 1, wherein the data generating subsystem performs pre-processing on the acquired card swiping data and the positioning data to form complete time for positioning the vehicle to the station, time for leaving the station and effective card swiping data, then performs time matching on the two parts of data to find the station where the passenger gets on the card by swiping the card, and performs various statistics according to the information to finally form the passenger flow statistical data of the branch road and the station.
9. The bus passenger flow analysis system based on location and card swiping information according to claim 8, wherein the location data preprocessing: the public transport vehicle positioning equipment continuously sends the current vehicle number, line number, speed, progress and latitude information to a public transport data center every 15 seconds, the generation of positioning data records in a public transport system is greatly influenced by technical equipment and transmission conditions, error data is easy to generate, and the types of the public transport positioning error data mainly comprise two types of data abnormity and data loss;
data exception is that data records of some fields are far from reality, data loss is that data packet loss occurs in the process of transmitting positioning data through an operator network, partial data loss occurs as a result, especially positioning arrival data and departure data loss can bring great influence on matching card swiping time and calculating card swiping station, therefore, before card swiping information is matched with positioning information, positioning data is preprocessed, and abnormal data and lost data are processed firstly;
vehicle arrival and departure data loss condition processing:
comparing the data of the located station and the data of the located station, which are generated in one operation pass of the vehicle, with the number and the sequence of all the bus stations of the line on which the vehicle runs on the current day, indicating that the data are normal, and not performing additional processing;
if the line on which the vehicle runs has N bus stations, the arrival data of the Q-th bus station is missing, namely 1< ═ Q < ═ N, if Q ═ 1, the departure time of the first bus station minus 2 minutes is taken as the arrival time of the bus station, if Q >1, the departure time of the Q-1-th bus station plus 1 second is taken as the arrival time of the bus station, and other data recorded in the arrival station are written into the database after being supplemented;
if the line on which the vehicle runs has N bus stations, the Q-th bus station departure data is missing, namely 1< ═ Q < ═ N, if Q ═ N, the arrival time of the last bus station plus 2 minutes is taken as the departure time of the bus station, if Q < N, the arrival time of the Q + 1-th bus station minus 1 second is taken as the departure time of the bus station, and other data recorded in the departure station are written into the database after being supplemented;
if the line on which the vehicle runs has N bus stations, the arrival data and the departure data of the Q-th bus station are missing, namely 1< ═ Q < ═ N, if Q < ═ 1, Q +1, namely the arrival time of the second bus station minus 1 second is taken as the departure time of the first bus station, and meanwhile, the departure time minus 2 minutes is taken as the arrival time of the first bus station; if Q is equal to N, the departure time of the Q-1 station plus 1 second is taken as the arrival time of the Nth station, whether the vehicle has continuous operation data after the operation of the current time is finished is judged, if the vehicle has the continuous operation data, the arrival time of the first station of the next time of the vehicle minus 5 seconds is taken as the departure time of the Nth station, if the data is the operation data of the last time of the day, the calculated arrival time plus 60 minutes is taken as the departure time of the Nth station, and other data recorded in the departure are filled in a database and then written in the database.
10. The bus passenger flow analysis system based on location and card swiping information according to claim 9, wherein the card swiping data preprocessing comprises: the card swiping data collected and stored in the card swiping data collection subsystem comprises card swiping date and card swiping time, in the actual operation process, sometimes due to the conditions of terminal data collection or transmission delay and the like, the card swiping data transmitted on the same day not only comprises the card swiping data on the same day, but also can have the conditions of card swiping data on other dates, so that the data on the different day needs to be cleaned, and the cleaning method comprises the following steps:
firstly, if data on a non-current day is more and the data on the same line in the data accounts for a larger amount, inserting the data into a card swiping data table on a corresponding date, inserting the data into a data regeneration task on the corresponding date, regenerating passenger flow volume data on the corresponding date when the data is idle, and deleting the data from the card swiping data table on the current day;
secondly, if the data on the non-current day is less, the data is directly deleted from the data table of the current day card swiping.
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