CN109634998A - A kind of traffic journey characteristic analysis platform based on mobile phone signaling big data - Google Patents
A kind of traffic journey characteristic analysis platform based on mobile phone signaling big data Download PDFInfo
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Abstract
The invention discloses a kind of traffic journey characteristic analysis platforms based on mobile phone signaling big data, including data preprocessing module, data mart modeling module, data distribution module, data acquisition module, data statistic analysis module and data to visualize module.Mobile phone signaling data is pre-processed by the big data analysis platform of operator, the relevant available fields of extraction platform, rejects noise；Pretreated signaling data is processed, carries out traffic model calculating using spark big data technology；The Trip chain result data that big data calculates is distributed in redis cluster；It is acquired by result of the http mode to data mart modeling by the security gateway of major operator, result data is stored on the server of user according to rule after acquisition；The population duty for collecting local result data and carrying out traffic service is lived and the analyses such as trip characteristics；Data visualization is carried out to traffic service analysis result, the component exhibiting of various configurations can be used.
Description
Technical field
The present invention relates to Urban Traffic Plannings and big data processing technology field, especially a kind of to be based on the big number of mobile phone signaling
According to traffic journey characteristic analysis platform.
Background technique
With the rapid development of social economy with the continuous improvement of the national level of urbanization, urban construction constantly improve,
To Urban Traffic Planning, construction and management, more stringent requirements are proposed.For Urban Planner, with information technology, lead to
Letter technology and mobile phone terminal it is universal, be gradually taken seriously using the new technologies acquisition traffic information such as mobile phone positioning, huge hand
Machine user group provides a large amount of data source for the acquisition of traffic data, for the analysis of resident's traffic journey characteristic provide it is abundant can
The data leaned on are supported.
Mobile phone signaling data be mobile phone user make a phone call, send short messages, change in location and while periodically updating generate
Mobile position data, recently as the development of wireless location technology, mobile phone signaling data constantly improve and increases, so that utilizing
Mobile phone positioning come calculate urban population duty live, trip characteristics, trip distance, Commuting Distance on and off duty become a kind of possibility.This phase
For conventional survey mode, it is available more comprehensively, more acurrate, more real-time data, provided for traffic journey characteristic analysis
Good data basis.For example, big mobile communication carrier, Beijing three (China Mobile, China Unicom and China Telecom) is daily
Signaling data about 6000G of 2G, 3G and 4G of generation or so, data set huge in this way, need big data technology come into
Row storage and processing.
Summary of the invention
It can be gone out by the progress traffic of the mobile phone signaling big data of mobile operator the purpose of the present invention is to provide a kind of
Row signature analysis provides Data safeguard for the traffic programme in city.
To achieve the above object, the invention adopts the following technical scheme: a kind of traffic based on mobile phone signaling big data
Trip characteristics analysis platform, including data preprocessing module, data mart modeling module, data distribution module, data acquisition module, number
Analysis module and data visualize module according to statistics.Data acquisition module, data statistic analysis module and data visualization
Display module is sequentially connected with, and data preprocessing module, data mart modeling module and data distribution module are sequentially connected with, data distribution mould
It is connected between block and data acquisition module by security gateway, this six functions module is combined closely, pre- from the data of data source
The data of processing to the end are visualized, this data preprocessing module, data mart modeling module, data distribution module, number
According to acquisition module, the traffic journey characteristic of data statistic analysis module five functional module composition based on mobile phone signaling big data
The nucleus module of analysis platform enables to the platform can flexible expansion, stabilization, efficient operation.
A kind of traffic journey characteristic analysis platform based on mobile phone signaling big data, each functional module for including is specifically such as
Under:
Data preprocessing module pre-processes the mobile phone signaling data of operator, extracts useful field, composition with
User imei code (DecryptDecryption) is the position coordinate data of critical field, and carries out abnormal judgement according to speed and angle, will be different
Normal point is removed.
Data mart modeling module is clustered to pretreated signaling data had been carried out using the clustering algorithm of optimization
Analysis forms accumulation point, uses the space length algorithm after optimization simultaneously in clustering algorithm, picks out each mobile phone user
The daily all dwell points to sort according to chronological order and stop beginning and ending time, form the traffic trip of the mobile phone user
Chain, and be stored in operator's big data platform HDFS file system.
Data distribution module, to traffic trip chain result data, data volume is big, by spark big data computing engines into
Result data is distributed in the redis cluster of operator by row data distribution, while the total amount of data size of this distribution being sent out
Cloth is into redis cluster, so that data volume of the data acquisition module to acquisition is effectively verified.
Data acquisition module, operator external user send get or post request by https mode and penetrate operator
Security gateway obtains trip link by the key value being previously set in http request parameter from the redis cluster of operator
Collected result data is uniformly stored in use according to the value after rear two hash of the imei code of mobile phone user by fruit data
In 256 data files in the presence server of family, subsequent traffic service is facilitated to statistically analyze.
Data statistic analysis module, the intermediate result Trip chain data arrived using data collecting module collected, according to design
Unified traffic model analysis interface, these traffic service models contain urban population duty live, population OD, trip distance,
Analysis models, these analysis models such as commuter distance, trip number are configured in platform with plug-in mode, are provided for user
Flexibly, easily business diagnosis, analysis result are stored in relational database, and graphical data is facilitated to show.
Data visualization module, according to data statistic analysis as a result, Service Component pair can be selected flexibly from platform
Data are visualized, these Service Component contain GIS map, thermodynamic chart, line chart, histogram, instrument board etc., Neng Gouzhi
Xml configuration mode was connected, it is convenient and practical.
Detailed description of the invention
Fig. 1 is the structural block diagram of this system.
Fig. 2 is the mobile original mobile phone signaling sample data of operator in Beijing.
Fig. 3 is the original mobile phone signaling sample data of operator of Beijing connection.
Fig. 4 is the original mobile phone signaling sample data of operator of Beijing Telecom.
Fig. 5 is Trip chain result data sample.
Specific embodiment
A kind of traffic journey characteristic analysis platform based on mobile phone signaling big data, including data prediction, data mart modeling,
Data distribution, data acquisition, data statistic analysis and data visualization etc..
As shown in Figure 1, the mobile phone signaling data amount of operator is huge, day regular data increment it is swift and violent, be stored in major fortune
It seeks in the hdfs file system of the big data platform of quotient, signaling data must be processed by existing big data analysis technology
Processing, the platform that the present invention designs use spark technology, and spark is to aim at large-scale data processing and design quick logical
Memory computing engines.
Its described data preprocessing module, due to operator provide the original not all data of mobile phone signaling data all
Be it is qualified, than if any lack longitude and latitude data, some lacks user's unique identification IMSI code, and some latitude and longitude coordinates are got over
Boundary, then Data duplication etc., pretreated result are then that one day data of a user are weeded out hashed field to some, are merged into
Together, and according to time-sequencing.The original mobile phone signaling sample data of movement in the big operator in Beijing three is as shown in Figure 2:
Explanation of field is as follows:
.The original mobile phone signaling sample data of connection in the big operator in Beijing three is as shown in Figure 3:
Explanation of field is as follows:
The original mobile phone signaling sample data of movement in the big operator in Beijing three is as shown in Figure 4:
Explanation of field is as follows:
Data mart modeling module described in it improves arithmetic speed in order to utmostly reduce operand, uses excellent
Clustering algorithm after change.When being clustered to the data of each user, all points of the user are put together space clustering, it can
Multiple clusters can be clustered into, when generating final Trip chain data, will also actually be used according to time continuity sub-clustering again
User data is clustered in two dimensions of room and time.
In the case where this dual-dimension cluster, there is very efficient optimal way in clustering algorithm.Due to number of users
According to being sorted in advance according to the time, the method discontinuously clustered can be taken, while carrying out room and time cluster.It is specific to calculate
Method is as follows:
First point is put into cluster, subsequent point singly judges whether in cluster, if be added in cluster
Cluster, if it was not then all the points room and time cluster of front is is completed, this point is placed in a new cluster, after continuation
Continuous cluster, and so on.When actually using the clustering algorithm after this optimization, calculating speed is substantially increased, is saved
Computing resource.When clustering algorithm carries out space clustering calculating, using the method for calculating two o'clock longitude and latitude difference, according to estimating
It calculates, if dimension is identical, the difference of the longitude of two coordinate points is greater than 0.0036, then more than 300 meters of cluster radius；If longitude phase
Together, the difference of longitude is greater than 0.0027, then more than 300 meters of cluster radius, need to only calculate the difference of the longitude and latitude of two o'clock in this way, so that it may
Judge space length, provides computational efficiency significantly.And traditional normed space distance algorithm contain addition subtraction multiplication and division, sine more than
The various operations such as string, algorithm comparison is complicated, in data cleansing and clustering algorithm, will calculate two o'clock space length, is counting greatly
In the case where amount, efficiency is extremely low.
Trip chain result data sample is as shown in Figure 5.
Explanation of field:
IMSI: time started, end time, longitude, latitude, cluster points；Time started, end time, longitude, latitude
Degree, cluster points ...
Data distribution module described in it, due to that need to pass the Trip chain result of calculating from the big data platform of operator back
On the server of data consumer, it will calculate in the Trip chain data distribution to the redis cluster of operator completed, user can
It is directly acquired with passing through the security gateway of operator from redis cluster.
Data acquisition module described in it, data consumer are sent get/post request, are passed through by http request mode
The security gateway acquisition Trip chain data of operator are simultaneously saved on the server of user local.Since Trip chain data are larger
(about 20G daily), data acquisition module use multi-process multithreading, collected Trip chain data are stored in service
In 256 files on device.To improve treatment effeciency, this acquisition module realizes that multi-process acquires using Python, at acquisition
Reason process is as follows:
1. newly-built 0-f totally 16 files create 0-f totally 16 files under each file；
2. each row of data obtained by http request, carries out md5 encryption for IMSI, according to encrypted field last two
Position, is written in corresponding 0-f, 0-f file, such as is d1ff16c637c9c859c545e66ccdb5acc8 after encryption, then will
8 files under c catalogue are written in this row data.
Data statistic analysis module described in it is realized by the Callable multithreading of Java, is patrolled previously according to server
It collects CPU number and generates thread pool, then analyze processing respectively according to traffic service model algorithm by the thread in thread pool by counting
According to collected 256 data files of acquisition module, the analyses such as residence, employment ground, commuting OD are obtained as a result, and protecting result
It is stored in relevant database.
Data visualization module described in it, to the analysis generated by statistical analysis module as a result, passing through visualization component
Flexibly shown.These components contain GIS map, thermodynamic chart, line chart, histogram, instrument board etc., can be matched by xml
Parameter is set, browser directly parses.
Claims (7)
1. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data, it is characterised in that: including data prediction
Module, data mart modeling module, data distribution module, data acquisition module, data statistic analysis module and data visualize
Module；Data acquisition module, data statistic analysis module and data visualize module and are sequentially connected with, data prediction mould
Block, data mart modeling module and data distribution module are sequentially connected with, and pass through safety between data distribution module and data acquisition module
Gateway connection, this six functions module combines closely, and carries out visualization exhibition from the data of the data prediction of data source to the end
Show, this data preprocessing module, data mart modeling module, data distribution module, data acquisition module, data statistic analysis module five
Big functional module constitutes the nucleus module of the traffic journey characteristic analysis platform based on mobile phone signaling big data.
2. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
It is:
Data preprocessing module pre-processes the mobile phone signaling data of operator, extracts useful field, forms with user
Imei code (DecryptDecryption) is the position coordinate data of critical field, and carries out abnormal judgement according to speed and angle, by abnormal point
Remove position.
3. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
Be: data mart modeling module carried out clustering using the clustering algorithm of optimization to pretreated signaling data has been carried out
Accumulation point is formed, the space length algorithm after optimization is used simultaneously in clustering algorithm, it is daily to pick out each mobile phone user
According to chronological order sequence all dwell points and stop the beginning and ending time, form the traffic trip chain of the mobile phone user,
And it is stored in operator's big data platform HDFS file system.
4. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
Be: data distribution module, to traffic trip chain result data, data volume is big, is counted by spark big data computing engines
According to distribution, result data is distributed in the redis cluster of operator, while this total amount of data size distributed being published to
In redis cluster, so that data volume of the data acquisition module to acquisition is effectively verified.
5. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
Be: data acquisition module, operator external user send the peace that get or post request penetrates operator by https mode
Full gateway obtains Trip chain result by the key value being previously set in http request parameter from the redis cluster of operator
Collected result data is uniformly stored in user according to the value after rear two hash of the imei code of mobile phone user by data
In 256 data files in presence server, subsequent traffic service is facilitated to statistically analyze.
6. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
It is: data statistic analysis module, the intermediate result Trip chain data arrived using data collecting module collected, according to the system of design
One traffic model analysis interface, these traffic service models contain urban population duty live, population OD, trip distance, commuting
Analysis models, these analysis models such as trip distance, trip number are configured in platform with plug-in mode, provide spirit for user
Living, convenient and fast business diagnosis, analysis result are stored in relational database, and graphical data is facilitated to show.
7. a kind of traffic journey characteristic analysis platform based on mobile phone signaling big data according to claim 1, feature
It is: data visualization module, according to data statistic analysis as a result, selecting Service Component to carry out visually data from platform
Change, these Service Component contain GIS map, thermodynamic chart, line chart, histogram, instrument board etc., can directly be matched by xml
Set mode.
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| CN116206452A (en) * | 2023-05-04 | 2023-06-02 | 北京城建交通设计研究院有限公司 | Sparse data characteristic analysis method and system for urban traffic travel |
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