CN104269060B - A kind of public transport crowding harvester based on intelligent video and method - Google Patents
A kind of public transport crowding harvester based on intelligent video and method Download PDFInfo
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Abstract
The present invention relates to a kind of public transport crowding harvester based on intelligent video and method, when which solving existing public transport crowding data acquisition, measurement error is big, accuracy is low, do not possess real-time and technical problem targetedly, it includes board information terminal, video camera, gate controlled switch and central server, in board information terminal is provided with car, crowding analyzes module, video monitoring module, GPS module, control module and mobile communication module, in car, crowding analysis module is connected with control module, GPS module is connected with control module, mobile communication module is connected with control module, video monitoring module is analyzed module with crowding in car and is connected；Gate controlled switch is analyzed module with crowding in car and is connected, and video camera is connected with video monitoring module, and central server is connected with mobile communication module；The present invention is widely used in management and the scheduling of urban public traffic vehicles.
Description
Technical field
The present invention relates to a kind of detection device and detection method, particularly relate to one and regard based on intelligence
The public transport crowding harvester of frequency and method.
Background technology
Along with the growth of urban population, urban public transport congested problem has become very important society
Can problem.By management and scheduling to public transit vehicle fast and accurately, alleviate the public friendship in city
It is open to traffic and the congested problem of circuit increasingly becomes the emphasis that decision-making level pays close attention to.The crowded number of degrees of public transport
According to being that scheduling public transport operation provides objective basis, facilitate adjustment and the vehicle resources of public bus network
Reasonable disposition, and ratio passenger flow number is more scientific and intuitive, refers to be worth higher.
The at present collection to crowding mainly has a following several ways: range sensor detection technique,
The crowded prompting of manual type presses key technology, based on public transport GPS and IC-card real time data technology, base
Congestion degree estimation technology in the three-dimensional video-frequency of video camera.
Range sensor detection technique is to sense space length below by range sensor and incite somebody to action
Output signal by wireless or wired by the way of be transferred to microcomputer, microcomputer is to public affairs
The sensing result value handing over car each range sensor interior is weighted read group total, obtains congestion quotiety,
Public transport congested conditions is embodied with this.But, although in this detection car, the mode of crowding is not deposited
In cumulative error, but the accuracy of detection of range sensor is easily by background, weather, shelter, the moon
The impact of shadow situation etc., thus cause measurement error.
The prompting of manual type is by real-time for vehicle crowding by the way of artificial button by key technology
Information uploads to public transport data service center, and public transport data service center is according to public transport travelling data sequence
The congestion information touch potential information that in row, different time is corresponding, it is judged that this public transport is in different time institute
Whether each position at place exists crowded, obtains real-time public transport congestion state information collection, and combines each reality
Time the public transport numbering corresponding to subset of public transport congestion state information collection, public transport present position obtain correspondence
Each Bus information sequence.But, although to press key technology easy and simple to handle, easily in the prompting of manual type
Strong by property, but crowding situation depends on artificial assumption, and collection result accuracy is low, scientific
All remain to be discussed with objectivity.
It is public by GPS and IC-card Real time data acquisition based on GPS and IC-card real time data technology
Hand over line alignment, site location, the public traffic network data of public transport Terminal Area Facilities, and passenger is upper and lower
Station point, the bus passenger flow data of passenger getting on/off time, and according to public traffic network data and public transport
Passenger flow data sets up go-outside for civilian by bus real time information table, based on this table, according to traffic model, meter
Real-time public bus network passenger flow OD distribution；It is finally based on the distribution of public bus network passenger flow OD, respectively
Crowding analysis is made for bus station and public bus network.But, count in real time based on GPS and IC-card
Although propose website and the concept of circuit crowding according to technology, but by public bus network passenger flow OD
Distribution calculates, and calculating is the mean crowding situation in a certain period, does not possess real-time
And specific aim.
Above-mentioned public transport crowding data collection and analysis technology is to carry out statistical for the crowding in car
Analysis, although have data as foundation, but for public traffic management is dispatched, the crowded feelings of certain car
Condition has sporadic, if vehicle of sending blindly can cause the waste of resource.
So for bus station and circuit crowding collection analysis for public traffic management is dispatched more
Tool science, intuitive and universality.
Summary of the invention
When the present invention is to solve existing public transport crowding data acquisition, measurement error is big, accuracy is low,
Do not possess real-time and technical problem targetedly, it is provided that a kind of accuracy is high, possess real-time and
The public transport crowding based on intelligent video gathered for bus station and circuit crowding targetedly
Harvester and method.
The technical scheme is that, it is provided that a kind of public transport crowding collection based on intelligent video fills
Putting, including board information terminal, video camera, gate controlled switch and central server, on-vehicle information is eventually
In end is provided with car, crowding analyzes module, video monitoring module, GPS module, control module and movement
Communication module, in car, crowding analysis module is connected with control module, and GPS module is with control module even
Connecing, mobile communication module is connected with control module, and video monitoring module analyzes mould with crowding in car
Block connects；Gate controlled switch is analyzed module with crowding in car and is connected, video camera and video monitoring module
Connecting, central server is connected with mobile communication module.
The present invention also provides for a kind of public transport acquisition method of congestion degree based on intelligent video, including following step
Rapid:
(1) public transport crowding harvester is utilized, with a predetermined period in bus driving process
Crowding c, public transport road location I, the number of system time d in taken at regular intervals numbering n, bus
It is believed that breath, obtain public transport travelling data sequence X, more each by collect by mobile communication module
Data message is sent on central server, and in bus, crowding c is public transport crowding collection dress
Put what the video image uploaded with a predetermined period had gathered；
(2) public transport travelling data sequence central server obtained and public transport data service center
Vehicle Attendance Sheet contrasts, and the data that underproof for work attendance vehicle is submitted to is weeded out；
(3) data finally given are stored in the data base of central server；
(4) crowding threshold value c in definition bust, it is defined as more than the public transport driving states of this threshold value
Crowded, according to public transport travelling data sequence X, crowding c in traversal retrieval bus >=ctAnd meet
Analytic statistics date range (the d of user's requesta,db) data, obtain being in the numbering of congestion state
nc, crowding c in bus0, public transport road location I, the public transport travelling data sequence of system time d
Row Xc；
(5) a certain website I is determinediPosition range (Iia,Iib), and according to public transport travelling data sequence
In Xc public transport road location I judge this data set whether in this site-bound, and according to judgement
Result obtains website IiIt is in numbering n of congestion stateL, crowding c in bus0, public transport driving
Position Ii, the public transport travelling data sequence X of system time dL；
(6) by website IiIt is in the public transport travelling data sequence X of congestion stateLDuring according to difference every day
Quarter carries out the book of final entry；
(7) travel through the data set in all of Xc, respectively obtain website IiAt every day in a certain moment dj
It is in numbering n of congestion statej, crowding c in bus0, public transport road location Ii, system time
dj, crowded multiplicity pjPublic transport travelling data sequence, and record total data sequence number and be designated as m；Its
Middle website IiAt every day in a certain moment djCrowded multiplicity pj=(nj/nL) × 100%；
(8) by website IiAt every day in a certain moment djIt is in all public transport travelling datas of congestion state
Sequence collects, and obtains website IiEach moment is in new numbering n of congestion stateL, bus
Interior crowding c0, public transport road location Ii, system time tij, crowded multiplicity pijPublic transport driving
Data sequence L.
It is further preferred that according to bus station crowding data acquisition lines crowding, specifically walk
Rapid as follows:
(1) position range (R of a certain circuit R is determineda, Rb), ergodic data sequence L, will symbol
The data set of zygonema road position range forms new numbering nr, crowding c in bus0, public transport row
Truck position Ii, system time tij, crowded multiplicity pijData sequence Lr, without meeting line
The data set of road position range, then the crowding coefficient of this circuit is 0；
(2) ergodic data sequence Lr, moment scope is belonged to the time range of this circuit order of classes or grades at school,
I.e. tij∈(ta, tb) data set carry out screening new numbering n of compositionp, crowding c in bus0、
Public transport road location Ii, system time dij, crowded multiplicity pijData sequence LpIf, this number
It is empty according to sequence, then proves that the crowding coefficient of this order of classes or grades at school is 0, otherwise calculate circuit according to this ordered series of numbers
The crowding coefficients R of Rp=np/nr；
(3) outlet line R is at order of classes or grades at school (ta, tb) crowding coefficients Rp。
The invention has the beneficial effects as follows, the video acquisition passenger flow uploaded by analysis mobile unit is crowded
Degree (i.e. crowding in bus), and analyze gathering around of a certain website of a certain moment according to passenger flow crowding
Squeeze multiplicity (probability of crowded appearance) and the congestion quotiety of a certain order of classes or grades at school of a certain circuit, obtain with this
Go out the crowding situation of website and circuit.The present invention is possible not only to overcome existing acquisition method of congestion degree
Deficiency, passenger flow crowding in car is carried out more accurate collection analysis, and can be according in car
Crowding situation analysis draws website and circuit crowding situation, eliminates the accidental factor of vehicle crowding,
Make the public transport crowding data collected more rapid, more accurately, possess real-time and specific aim,
Public traffic management is made to dispatch more rapid, more efficient, more scientific, intuitive and universality.
Further aspect of the present invention, by the description of detailed description below, is able to clear
Ground is recorded.
Accompanying drawing explanation
Fig. 1 is the theory diagram of public transport crowding harvester of the present invention；
Fig. 2 is the bus station acquisition method of congestion degree flow chart of the present invention；
Fig. 3 is the circuit acquisition method of congestion degree flow chart of the present invention.
Reference numeral illustrates:
10. board information terminal；20. video cameras；30. gate controlled switches；40. central servers；11.
In car, crowding analyzes module；12. video monitoring module；13.GPS module；14. control modules；
15. mobile communication modules.
Detailed description of the invention
As it is shown in figure 1, public transport crowding harvester based on intelligent video includes that on-vehicle information is eventually
End 10, video camera 20, gate controlled switch 30 and central server 40.Board information terminal 10 is provided with
In car, crowding analyzes module 11, video monitoring module 12, GPS module 13, control module 14
With mobile communication module 15, in car, crowding analysis module 11 is connected with control module 14, GPS
Module 13 is connected with control module 14, and mobile communication module 15 is connected with control module 14, depending on
Frequently monitoring module 12 is connected with crowding analysis module 11 in car.Gate controlled switch 30 is crowded with in car
Degree is analyzed module 11 and is connected, and video camera 20 is connected with video monitoring module 12, central server 40
It is connected with mobile communication module 15.
Video camera 20 is used for shooting in car video and this video signal is sent to video monitoring module
12, in video signal is sent to car by video monitoring module 12, crowding analyzes module 11, gathers around in car
Squeeze degree to analyze module 11 and calculate crowding data in bus according to video signal.Control module 14
Control mobile communication module 15 and crowding data in bus are sent to central server 40.Mobile
Communication module 15 uses the mobile communication technologies such as GPRS.Gate controlled switch 30 is used for obtaining door contact interrupter
Status information, after closing of the door, crowding analysis module 11 carries out the calculating of crowding, car door opening
Stop calculating crowding.
Referring to figs. 2 and 3, utilize said apparatus to carry out public transport crowding collection based on intelligent video
Method comprises the following steps:
Step one, utilizes and has the public transport crowding harvester of crowding acquisition function in car,
With crowding c, public affairs in predetermined period taken at regular intervals numbering n, bus in bus driving process
Truck position, Bank of Communications I, the data message of system time d, obtain public transport travelling data sequence X.Lead to again
Cross mobile communication technology and each data message collected is sent to the center service of data processing centre
On device.In bus, crowding c is to have the public transport crowding collection of crowding acquisition function in car
The video image that device is uploaded with a predetermined period has gathered.
Step 2, the public transport travelling data sequence that the central server of data processing centre is obtained with
The vehicle Attendance Sheet of public transport data service center contrasts, and is submitted to by underproof for work attendance vehicle
Data weed out.
The data finally given are stored in the data base of central server by step 3.
Step 4, data in analysis statisticaling data storehouse thus carry out the collection of bus station crowding.
In this step, crowding acquisition step in bus station is as follows:
1) due to certain of intensity of passenger flow (i.e. unit are seating capacity) in crowding is car in car
Linear transformation, therefore definable formula: intensity of passenger flow q=k1+k2C, wherein k1, k2Can be by actual field
Experiment value between crowding and the number of scape determines.National regulation intensity of passenger flow is more than 8 people/m2For
Crowded, the public transport crowding numerical value being calculated correspondence by above formula is crowding in bus
Threshold value ct, it is defined as crowded more than the public transport driving states of this threshold value.Fill according to public transport crowding collection
Put public transport travelling data sequence X (crowding c in numbering n, bus, the public transport driving position of submission
Put I, system time d), crowding c in traversal retrieval bus >=ctAnd meet dividing of user's request
Analysis statistics date range (is designated as (da,db)) data, obtain being in the public transport driving number of congestion state
According to sequence X c (numbering nc, crowding c in bus0, public transport road location I, system time d).
2) a certain website I is determinediPosition range (Iia,Iib), and according to public transport travelling data sequence
Xc (numbering nc, crowding c in bus0, public transport in public transport road location I, system time d)
Road location I judges that this data set, whether in this site-bound, and must be arrived at a station according to judged result
Point IiIt is in the public transport travelling data sequence X of congestion stateL(numbering nL, crowding c in bus0、
Public transport road location Ii, system time d).
3) by website IiIt is in the public transport travelling data sequence X of congestion stateLDuring according to difference every day
Quarter carries out the book of final entry.
4) travel through the data set in all of Xc, respectively obtain website IiAt every day in a certain moment dj
It is in public transport travelling data sequence (numbering n of congestion statej, crowding c in bus0, public transport
Road location Ii, system time dj, crowded multiplicity pj), and record total data sequence number and be designated as m.
Wherein website IiAt every day in a certain moment djCrowded multiplicity pj=(nj/nL) × 100%.Certain
One website crowded multiplicity sometime in a day is the highest, turns out the congested conditions of this website
The most serious.
5) by website IiAt every day in a certain moment djIt is in all public transport travelling data sequences of congestion state
Row collect, and obtain website IiEach moment is in new public transport travelling data sequence L of congestion state
(numbering nL, crowding c in bus0, public transport road location Ii, system time tij, crowded repetition
Degree pij)。
Step 5, carries out circuit crowded on the basis of drawing bus station crowding data further
The collection of degree, specifically comprises the following steps that
1) position range (R of a certain circuit R is determineda, Rb), ergodic data sequence L (numbering
nL, crowding c in bus0, public transport road location Ii, system time dij, crowded multiplicity pij),
The data set of coincidence circuit position range is formed new data sequence Lr(numbering nr, in bus
Crowding c0, public transport road location Ii, system time tij, crowded multiplicity pij), without symbol
The data set of zygonema road position range, then the crowding coefficient of this circuit is 0.
2) ergodic data sequence Lr, moment scope is belonged to the time range of this circuit order of classes or grades at school, i.e.
tij∈(ta, tb) data set carry out the screening new data sequence L of compositionp(numbering np, bus
Interior crowding c0, public transport road location Ii, system time dij, crowded multiplicity pij).If this number
It is empty according to sequence, then proves that the crowding coefficient of this order of classes or grades at school is 0, otherwise calculate circuit according to this ordered series of numbers
The crowding coefficients R of Rp=np/nr.Crowding coefficient is the biggest, then crowded at this order of classes or grades at school of this circuit
Situation is the most serious.
3) outlet line R is at order of classes or grades at school (ta, tb) crowding coefficients Rp。
The above is not limited to the present invention only to the preferred embodiments of the present invention, right
For those skilled in the art, the present invention can have various modifications and variations.Every at this
In the range of bright claim limits, any modification, equivalent substitution and improvement etc. done, all should
Within protection scope of the present invention.
Claims (2)
1. apply the based on intelligent video of public transport crowding harvester based on intelligent video for one kind
Public transport acquisition method of congestion degree, it is characterised in that described public transport crowding based on intelligent video is adopted
Acquisition means includes board information terminal, video camera, gate controlled switch and central server, described vehicle-mounted
In information terminal is provided with car, crowding analyzes module, video monitoring module, GPS module, control module
And mobile communication module, in described car, crowding analysis module is connected with described control module, described
GPS module is connected with described control module, and described mobile communication module is connected with described control module,
Described video monitoring module is analyzed module with crowding in described car and is connected；Described gate controlled switch and institute
In stating car, crowding analyzes module connection, and described video camera is connected with described video monitoring module, institute
State central server to be connected with described mobile communication module；
Described public transport acquisition method of congestion degree comprises the following steps:
(1) utilize described public transport crowding harvester, preset with one in bus driving process
Crowding c, public transport road location I, system time d in cycle taken at regular intervals numbering n, bus
Data message, obtain public transport travelling data sequence X, then will be collected by mobile communication module
Each data message be sent on central server, in bus, crowding c is that public transport crowding is adopted
The video image that acquisition means is uploaded with a predetermined period has gathered；
(2) public transport travelling data sequence central server obtained and public transport data service center
Vehicle Attendance Sheet contrasts, and the data that underproof for work attendance vehicle is submitted to is weeded out；
(3) data finally given are stored in the data base of central server；
(4) crowding threshold value c in definition bust, it is defined as more than the public transport driving states of this threshold value
Crowded, according to public transport travelling data sequence X, crowding c in traversal retrieval bus >=ctAnd meet
Analytic statistics date range (the d of user's requesta,db) data, obtain being in the numbering of congestion state
nc, crowding c in bus0, public transport road location I, the public transport travelling data sequence of system time d
Row Xc；
(5) a certain website I is determinediPosition range (Iia,Iib), and according to public transport travelling data sequence
In row Xc public transport road location I judge this data set whether in this site-bound, and according to sentencing
Disconnected result obtains website IiIt is in numbering n of congestion stateL, crowding c in bus0, public transport row
Truck position Ii, the public transport travelling data sequence X of system time dL；
(6) by website IiIt is in the public transport travelling data sequence X of congestion stateLDifferent according to every day
Moment carries out the book of final entry；
(7) travel through the data set in all of Xc, respectively obtain website IiAt every day in a certain moment dj
It is in numbering n of congestion statej, crowding c in bus0, public transport road location Ii, system time
dj, crowded multiplicity pjPublic transport travelling data sequence, and record total data sequence number and be designated as m；Its
Middle website IiAt every day in a certain moment djCrowded multiplicity pj=(nj/nL) × 100%；
(8) by website IiAt every day in a certain moment djIt is in all public transport travelling datas of congestion state
Sequence collects, and obtains website IiEach moment is in new numbering n of congestion stateL, bus
Interior crowding c0, public transport road location Ii, system time tij, crowded multiplicity pijPublic transport driving
Data sequence L.
Acquisition method the most according to claim 1, it is characterised in that gather around according to bus station
Squeeze degrees of data and gather circuit crowding, specifically comprise the following steps that
(1) position range (R of a certain circuit R is determineda, Rb), ergodic data sequence L, will symbol
The data set of zygonema road position range forms new numbering nr, crowding c in bus0, public transport row
Truck position Ii, system time tij, crowded multiplicity pijData sequence Lr, without meeting line
The data set of road position range, then the crowding coefficient of this circuit is 0；
(2) ergodic data sequence Lr, moment scope is belonged to the time range of this circuit order of classes or grades at school,
I.e. tij∈(ta, tb) data set carry out screening new numbering n of compositionp, crowding c in bus0、
Public transport road location Ii, system time dij, crowded multiplicity pijData sequence LpIf, this number
It is empty according to sequence, then proves that the crowding coefficient of this order of classes or grades at school is 0, otherwise calculate circuit according to this ordered series of numbers
The crowding coefficients R of Rp=np/nr；
(3) outlet line R is at order of classes or grades at school (ta, tb) crowding coefficients Rp。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410562978.7A CN104269060B (en) | 2014-10-21 | A kind of public transport crowding harvester based on intelligent video and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410562978.7A CN104269060B (en) | 2014-10-21 | A kind of public transport crowding harvester based on intelligent video and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104269060A CN104269060A (en) | 2015-01-07 |
| CN104269060B true CN104269060B (en) | 2017-01-04 |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360534A (en) * | 2011-09-23 | 2012-02-22 | 福建工程学院 | Method for collecting public traffic congestion status information in real time |
| CN102646329A (en) * | 2012-04-12 | 2012-08-22 | 深圳华宏联创科技有限公司 | Intelligent public traffic system |
| CN202694567U (en) * | 2012-01-10 | 2013-01-23 | 深圳华宏联创科技有限公司 | System for accessing bus information via hand-held terminal |
| CN103680129A (en) * | 2013-12-06 | 2014-03-26 | 深圳先进技术研究院 | Method and system for monitoring operation of public transport vehicle |
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102360534A (en) * | 2011-09-23 | 2012-02-22 | 福建工程学院 | Method for collecting public traffic congestion status information in real time |
| CN202694567U (en) * | 2012-01-10 | 2013-01-23 | 深圳华宏联创科技有限公司 | System for accessing bus information via hand-held terminal |
| CN102646329A (en) * | 2012-04-12 | 2012-08-22 | 深圳华宏联创科技有限公司 | Intelligent public traffic system |
| CN103680129A (en) * | 2013-12-06 | 2014-03-26 | 深圳先进技术研究院 | Method and system for monitoring operation of public transport vehicle |
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Inventor after: Yu Xihan Inventor after: Pan Dawei Inventor after: Niu Yuanjie Inventor after: Ji Zengguang Inventor before: Pan Dawei Inventor before: Li Guoping Inventor before: Li Chengxiang Inventor before: Wang Xuewen |
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Denomination of invention: A bus congestion acquisition device and method based on Intelligent Video Effective date of registration: 20220408 Granted publication date: 20170104 Pledgee: Weihai Branch of China Merchants Bank Co.,Ltd. Pledgor: SHANDONG KAER ELECTRIC Co.,Ltd. Registration number: Y2022980003973 |