CN110188923A - A kind of multi-mode bus passenger flow projectional technique based on big data technology - Google Patents
A kind of multi-mode bus passenger flow projectional technique based on big data technology Download PDFInfo
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Abstract
The invention belongs to field of intelligent transportation technology, and in particular to a kind of multi-mode bus passenger flow projectional technique based on big data technology.The method combines subway IC card data on the basis of bus IC card and GPS data, convergence analysis has been carried out to the bus trip passenger flow under various modes, and the derivation method got off a little is optimized, the new approaches for matching and getting off a little are proposed based on trip characteristics, and consider that multinomial factor carries out expansion sample to result.The method of the invention can more accurately derive the passenger flow OD distribution situation of multi-mode bus trip, it is more applicable for nowadays public transport+increasingly popular traffic environment of subway combination transit trip mode, help can be provided for the planning and optimization of Public Transport Trade.
Description
Technical field
The invention belongs to field of intelligent transportation technology, and in particular to a kind of multi-mode bus passenger flow based on big data technology
Projectional technique.
Background technique
Public transport has the characteristics that road occupancy is low, freight volume is big, green high-efficient, and in city, slow stifled protect freely changes with environment
Kind aspect has innate advantage.Many big cities all establish city intelligent public transit system, store in City ITS
There is mass data to can be used for calculating passenger flow.
In the prior art, patent " a kind of bus passenger OD projectional technique (application number based on intelligent public transportation system data
201610229224.9) a kind of bus passenger OD projectional technique based on intelligent public transportation system data " is disclosed, by merging intelligence
The energy multiple data sources of public transit system, analysis bus passenger trip space-time characterisation calculate passenger loading, get off, change to website, obtain
OD matrix between the website of the passenger of known get-off stop, and be distributed according to the get-off stop number of same bus loading zone point passenger to square
Battle array, which expands, to be calculated, and OD matrix between the bus station of full IC card sample is obtained.And it is inferior that the patent considers domestic public transport congested conditions
Visitor swipe the card be likely to occur in bus it is leaving from station after the case where, clearly distinguished transfer behavior, and dig using more days trip datas
Passenger's trip mode is dug, the get-off stop for improving single trip on the one calculates success rate, more reasonable reliable OD matrix is obtained,
Can be quickly obtained city bus whole network get on the bus, get off, transfer activity space-time data, can preferably serve big city public transport rule
Draw operation management.But this method still has following technical problem:
(1) passenger flow only having studied under the single trip mode of bus calculates, not yet considers how to excavate bus and ground
The multi-source data that iron combines, and derive the passenger flow situation of corresponding multi-mode integration public transportation system；
(2) it is not comprehensive that the judgment method a little of getting off and OD matrix expand quadrat method Consideration, in a judgement of getting off just for
Ordinary circumstance is analyzed, and sporadic traffic trip is had ignored, and calculates that success rate is to be improved；OD matrix, which expands in sample, only to be examined
Consider and expansion sample is carried out to the unsuccessful data of matching, has not considered non-the case where going on a journey of swiping the card, do not conform to the actual conditions.
Summary of the invention
In view of the above technical problems, the present invention provides a kind of multi-mode bus passenger flow reckoning side based on big data technology
Method；Subway IC card data are combined on the basis of bus IC card and GPS data, to the bus trip passenger flow under various modes
Convergence analysis has been carried out, and the derivation method got off a little has been optimized, has proposed and is got off a little based on trip characteristics to match
New approaches, and consider that multinomial factor carries out expansion sample to result；The method of the invention can more accurately derive multimode
It is gradually general to be more applicable for nowadays public transport+subway combination transit trip mode for the passenger flow OD distribution situation of formula bus trip
Time traffic environment, help can be provided for the planning and optimization of Public Transport Trade.
The present invention is achieved by the following technical solutions:
A kind of multi-mode bus passenger flow projectional technique based on big data technology, the method are based on IC card data set, GPS
Data set, website line basis data collection, derive the website of getting on the bus of passenger；It is right by analyzing the Trip chain feature of single passenger
Transfer behavior carries out analysis to reconstruct complete Trip chain；Based on trip characteristics, is swiped the card using single and record corresponding get off a little
Non- collection meter derive obtain Trip chain finally getting off a little；It a little a little obtains covering public transport with finally getting off for Trip chain in conjunction with getting on the bus
The OD matrix between the integrated public transport station of subway carries out expansion sample to the OD matrix and handles to obtain complete public transport visitor
Flow distribution.
Further, the website line basis data collection include subway terminal data collection, subway station track data collection,
Public bus network site data set, website serial number data collection；
The IC card data set includes: charge time, subway terminal number or public transit vehicle number, IC card number and for marking
Know the type of swiping the card of subway and public transport；The GPS data collection include: the GPS point sampling instant time, car number, working line,
Instantaneous longitude and instantaneous dimension.
Further, the method specifically includes:
Website of getting on the bus derives: IC card data set, GPS data collection, website line basis data collection is based on, according to public transport and ground
Public transport is got on the bus website and subway website of getting on the bus derives respectively by the characteristics of iron；
Trip chain reconstruct: according to passenger go on a journey in whether have transfer behavior, the record that will swipe the card is integrated, reconstruct passenger go out
The single record of no transfer behavior is directly considered as a Trip chain, a plurality of record for having transfer behavior is carried out by row chain
It is a Trip chain in conjunction with backsight；After reconstruct Trip chain include: passenger's same day only once brushing card data without transfer behavior when pair
The single answered, which is swiped the card, records the Trip chain of composition；Passenger is corresponding when having multiple brushing card data the same day and having transfer point a plurality of to swipe the card
Record merges the Trip chain of reconstruct；Passenger had the corresponding closure transit trip chain of multiple brushing card data, the closure same day
Transit trip chain includes the often property the sent out trip of commuting class and sporadic trip two types；
A final derivation of getting off: according to trip characteristics, will get off and be a little divided into: transfer point is closed strong trip and is closed weak
Trip point；The transfer point can be obtained after Trip chain reconstruct；The strong trip point of closure and the weak trip point of closure are used
In getting off a little for the non-transfer point of expression；The strong corresponding commuting class of trip point of closure often go on a journey by the property sent out, and indicates that passenger often goes on a journey
Place, can be obtained according to more days records of swiping the card；The corresponding sporadic trip of the weak trip point of closure, indicates passenger
The place of accidental trip can be swiped the card by analyzing front and back and record feature and obtain；It is closed according to the strong trip point of the closure with described
It closes weak trip point and further derives finally getting off a little for acquisition Trip chain；
Passenger flow OD matrix generates between standing: getting on the bus for each Trip chain extracted a little being got off a little with the final of Trip chain, is led
Enter in Excel tables of data, maintenance data perspective function obtains covering passenger flow OD between public transport and the integrated public transport station of subway
Matrix；
Passenger flow OD matrix the station is carried out to expand sample processing: can not be suitable for records of swiping the card certain in IC card data set
Benefit is matched to the case where public transport get-off stop, and for the group for completing payment trip by bank note, is respectively adopted different
Coefficient carries out expansion sample.
Further, in the step of website of getting on the bus derives:
Subway gets on the bus the derivation method of website are as follows: IC card data set record subway terminal number when swiping the card passes through subway
Terminal number matches the subway terminal number that IC card data set and subway terminal data are concentrated, and subway terminal data is concentrated
It further include corresponding site name being numbered with subway, and then obtain the website of getting on the bus when taking subway；
Public transport is got on the bus the derivation method of website: including car number matching, time match, three step of nearest site search；It is first
It first passes through IC card data set and obtains the bus car number that passenger takes, then by charge time and passenger in IC card data set
The GPS moment that ride-on vehicles GPS data is concentrated is converted into minute and compares, and finds GPS data concentration and charge time
Identical or immediate sampling instant finally determines that distance is most on working line based on the position coordinates under the sampling instant point
Close bus station, the website of getting on the bus when as taking pubic transport.
Further, the step of Trip chain reconstructs are as follows: swipe the card after record is ranked up to passenger, by judging two
Whether the distance interval and time interval of place for getting on/off meet threshold value to determine whether there is transfer behavior in adjacent record, are less than
Threshold value thinks that there are transfer behaviors；It is a Trip chain that a plurality of record for having transfer behavior, which is then combined backsight, will not had
There is the single record of transfer behavior to be directly considered as a Trip chain.
Further, Trip chain reconstructs step, specifically:
Step 1: being ranked up all records of swiping the card according to IC card numbers and charge time, extracts first note of swiping the card
Record is recorded as current research, is judged；
Step 2: judging whether current research record belongs to same card number with next record, if belonging to, enters step
Three；If being not belonging to, judge whether current record has been merged into a Trip chain with a upper record, if not having, by current record
It is considered as an individual Trip chain, next record is considered as current research record later, reenters step 2；
Step 3: the type of swiping the card for judging current research record is public transport or subway；
For public transport: calculating next record and get on the bus a little at a distance from all websites of current line, judge the smallest distance value
Whether it is less than threshold value, is used as independent Trip chain if not satisfied, then recording current research, enters step four；If being less than threshold value, obtain
It takes in current line website and gets on the bus apart from next record apart from a smallest website, be denoted as current line apart from minimum station
Point, and found with the minimum website of current line distance by the GPS data collection of vehicle apart from nearest sampled point, it will correspond to
At the time of at the time of be considered as vehicle and reach website, and then calculate get on the bus point moment and vehicle of next record and reach the current line
Difference at the time of distance minimum website, judges whether difference is less than threshold value, if being not less than, by current research record as independent
Trip chain enters step four；Otherwise current research is recorded to the current line distance that merges with next record, and will acquire
Minimum website is got off a little labeled as current research record, is denoted as transfer point, is entered step four；
For subway: directly calculating next record and get on the bus a little and difference at the time of current research record is got off and between
Every, be compared respectively with time threshold and distance threshold, if both less than threshold value, by current research record with next record close
And and getting off current record a little labeled as transfer point, enter step four, current research record be otherwise considered as independent trip
Enter step 4 after chain；
Step 4: judge next record whether be in entire IC card data set the last item record, if being unsatisfactory for item
Part, then be considered as current research record for next record, otherwise return step two further judges current record and next record
Whether merge, if having merged, directly terminate whole flow process, if not merging, is tied after next record is considered as independent Trip chain
Beam whole flow process.
Further, in the step of deriving of getting off, according to the strong trip point of the closure and the closure it is weak go out
Row point further derives the step of finally getting off of Trip chain, specifically:
Step 1: the Trip chain reconstructed in the step of extracting Trip chain reconstruct will have a mark of getting off for transfer behavior
It is denoted as transfer point；
Step 2: single Trip chain after reconstruct is successively extracted；
Step 3: being directed to single Trip chain, extracts the last item and swipes the card record, only once brushed if it is passenger's same day
The single trip of card data then directly extracts single and swipes the card record；
Step 4: it is got off a little based on the strong trip point judgement of closure: extracting getting on the bus in same card number more days records of swiping the card
Point, and successively sort by a frequency of occurrence of getting on the bus is descending, it is strong as closure to choose several forward websites of getting on the bus of sequence
It goes on a journey point, and finds the last item and swipe the card record institute in the line with the strong trip of the closure apart from nearest route website,
And calculate the strong trip point of the closure and with the strong trip point of the closure apart from nearest the distance between route website, it chooses full
Sufficient threshold value and finally the getting off a little as Trip chain apart from nearest route website, enter step eight；
If the last item is swiped the card, the route website recorded in the line is at a distance from the strong trip point of closure described in several
Threshold requirement is not satisfied, enters step five；
Step 5: the identical next continuous trip chained record of card number is judged whether there is, and if it exists, six are entered step,
If it does not exist, seven are entered step；
Step 6: being got off a little based on weak trip point judgement is closed: extracting getting on the bus a little in next continuous trip chained record,
It is closed weak trip point, finds the record institute that currently swipes the card and be closed weak trip point apart from nearest route station with described in the line
Point, and calculate the weak trip point of the closure and with the weak trip point of closure apart from nearest the distance between route website；If
Distance meets threshold requirement, getting off with the weak trip point of the closure apart from nearest route website as the final of Trip chain
Point, enters step eight；If not satisfied, entering step seven；
Step 7: it really gets off a little since the deficiency of information resources can not be obtained accurately, which does not operate；
Step 8: extracting next Trip chain, enter step three, until all Trip chains judge to complete, terminates.
Further, carrying out expansion sample processing to OD matrix the station includes:
The case where public transport get-off stop can not be smoothly matched to for records of swiping the card certain in IC card data set, using
One expands spline coefficient, and expression formula is as follows:
In formula,Expand spline coefficient for the first kind of route i；TiFor the brushing card data total amount of IC card data concentration line road i；Si
Pass through vehicle that is, during point is got off in derivation for the brushing card data total amount of the route i bus trip OD matrix derived
The record of swiping the card of identification route i is numbered, calculates and the line finally got off a little is derived from using a derivation step of finally getting off
Road i swipes the card the total amount of record；
For the group for completing payment trip by bank note, expansion sample is carried out using the second expansion spline coefficient；Second expands spline coefficient
Expression formula is as follows:
In formula,Expand spline coefficient for the second class of route i；UiSwipe the card what payment was gone on a journey using bank note and IC card for route i
All trip number total amounts；MiTrip number total amount corresponding to bank note fare income for route i.
Advantageous effects of the invention:
The passenger flow that passenger flow projectional technique often only considered routine bus system in the prior art calculates situation, and the present invention is mentioned
The trip mode that the method for confession combines routine bus system, rail traffic and the two is all analyzed, and multimode can be obtained
The passenger flow analysing situation of formula integration public transportation system.
The derivation method finally got off a little for Trip chain in the prior art be mostly based on website get on the bus number calculating get off
Probability obtains, and belongs to collection meter model, or the travel behaviour feature without considering traveler comprehensively, calculates that success rate needs to be mentioned
It is high；And the derivation method that Trip chain provided by the invention is finally got off a little based on passenger's trip characteristics propose, propose transfer point,
The strong trip point of closure and three kinds of point features of getting off of weak trip point are closed, are more bonded actual conditions, what is not only obtained final gets off a little
It is more accurate, it can more obtain the more information of single passenger's trip.
The method of the invention is carrying out having comprehensively considered two kinds of situations of missing information and bank note passenger when passenger flow OD expands sample,
Obtained Trip distribution and truth are closer.
Detailed description of the invention
Fig. 1 a- Fig. 1 e is that the data entity E-R that method described in the embodiment of the present invention uses describes figure；Wherein, Fig. 1 a is
Public bus network site data set E-R description figure；Fig. 1 b is subway terminal data collection E-R description figure；Fig. 1 c is subway station route
Data set E-R description figure；Fig. 1 d is GPS data collection E-R description figure；Fig. 1 e is IC card data set E-R description figure；
Fig. 2 is website reasoning flow figure of getting on the bus in the embodiment of the present invention；
Fig. 3 is that passenger changes to behavior schematic diagram in the embodiment of the present invention；
Fig. 4 is that Trip chain reconstructs flow chart in the embodiment of the present invention；
Fig. 5 is to derive a flow chart of getting off based on the strong and weak trip point of closure in the embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is explained in further detail.It should be appreciated that specific embodiment described herein is used only for explaining the present invention, and
It is not used in the restriction present invention.
On the contrary, the present invention covers any substitution done on the essence and scope of the present invention being defined by the claims, repairs
Change, equivalent method and scheme.Further, in order to make the public have a better understanding the present invention, below to of the invention thin
It is detailed to describe some specific detail sections in section description.Part without these details for a person skilled in the art
The present invention can also be understood completely in description.
For in the prior art, following technical problem existing for public traffic passenger flow projectional technique: (1) public transport is only had studied
Passenger flow under the single trip mode of vehicle calculates, not yet considers how to excavate the multi-source data that bus and subway combine, and derive
The passenger flow situation of corresponding multi-mode integration public transportation system.(2) belong to collection meter model mostly or do not consider comprehensively
It is not comprehensive that the travel behaviour feature of traveler, the judgment method a little of getting off and OD matrix expand quadrat method Consideration, calculates successfully
Rate and result precision are to be improved.
The embodiment of the present invention provides a kind of multi-mode bus passenger flow projectional technique based on big data technology, the method base
In IC card data set, GPS data collection, website line basis data collection, the website of getting on the bus of passenger is derived；By analyzing single passenger
Trip chain feature, exchange travel is to carry out analysis to reconstructing complete Trip chain；Based on trip characteristics, swiped the card using single
The corresponding non-collection meter got off a little of record, which derives, obtains finally getting off a little for Trip chain；It a little gets off with the final of Trip chain in conjunction with getting on the bus
Point obtains covering OD matrix between public transport and the integrated public transport station of subway, carries out expansion sample to the OD matrix and handles to have obtained
Whole public traffic passenger flow distribution.
In the present embodiment, the method includes websites of getting on the bus to derive, Trip chain reconstruct, finally get off and derive, stand between
Passenger flow OD matrix generates and carries out the step of expanding sample processing to passenger flow OD matrix the station.
Website derivation step of getting on the bus is rapid, specifically:
It, will be public the characteristics of according to public transport and subway based on IC card data set, GPS data collection, website line basis data collection
It hands in station point and subway website of getting on the bus is derived respectively；
Wherein, as shown in Fig. 1 a- Fig. 1 e: the IC card data set includes: charge time, subway terminal number or bus
Number, IC card number and the type of swiping the card for identifying subway and public transport；When the GPS data collection includes: GPS point sampling instant
Between, car number, working line, instantaneous longitude and instantaneous dimension；
The website line basis data collection includes subway terminal data collection, subway station track data collection, public bus network
Site data set；Specifically, the subway terminal data collection include subway terminal number, subway station title, website longitude and latitude,
Line name；Subway station track data collection include: subway terminal number, milepost, subway station title, website longitude and latitude,
Line name；The public bus network site data set includes: bus station title, site number, website longitude and latitude, route volume
Number, milepost, line direction (uplink and downlink).
Fig. 2 is website reasoning flow figure of getting on the bus, as shown in Fig. 2, judging that passenger adopts according to type of swiping the card in IC card data set
Public transport type is public transport or subway, and when type of swiping the card is subway, subway is got on the bus the derivation method of website are as follows: brush
IC card data set record subway terminal number when card, by subway terminal number by IC card data set and subway terminal data collection
In subway terminal number matched, subway terminal data concentration further includes numbering corresponding site name with subway, in turn
Obtain the website of getting on the bus when taking subway；
When type of swiping the card is public transport, public transport is got on the bus the derivation method of website: including car number matching, time match,
Three step of nearest site search；The bus car number that passenger takes is obtained by IC card data set first, then by IC card number
Minute is converted into according to the GPS moment for concentrating charge time and passenger's ride-on vehicles GPS data to concentrate and is compared, and is found
GPS data concentrates sampling instant identical or immediate with charge time, is finally sat based on the position under the sampling instant point
Mark the bus station for determining that distance is nearest on working line, the website of getting on the bus when as taking pubic transport.
Trip chain reconstructs step:
Trip in public transport passenger one day is usually the Trip chain based on origin and destination.General one record of swiping the card can push away
A get-off stop is exported, but not all get-off stop is with all represent trip purpose, passenger may need by one
Final point of destination is got to after secondary or multiple transfer, it is therefore desirable to carry out Trip chain reconstruct；
Fig. 3 is that passenger changes to behavior schematic diagram, as shown in figure 3, passenger is from inception point S1In T1Moment swipes the card in payment completion
Vehicle, public transport or subway circulation time t1To T2Moment reaches website X1It gets off, walking distance d, expends time t2In T3Moment reaches
Get on the bus website S2, waiting, which is stayed, in the website expends time t3, until T4Moment completes to swipe the card to get on the bus, final runing time t4In T5When
Reach terminal at quarter X2, complete this transit trip behavior.Therefore, website X1Be transfer website, not this trip end
Only get-off stop needs T this kind of situation1Moment and T4Two records of swiping the card at moment are merged into a Trip chain, weight
The committed step of structure Trip chain is to judge whether there is transfer point.
Trip chain reconstruct specifically: according to passenger go on a journey in whether have transfer behavior, the record that will swipe the card is integrated, reconstruct
The single record of no transfer behavior is directly considered as a Trip chain, will there is a plurality of note of transfer behavior by passenger's Trip chain
It is a Trip chain that record, which is combined backsight,；Trip chain includes: that passenger's same day, only once brushing card data was gone without transfer after reconstruct
For when corresponding single swipe the card the Trip chain that record constitutes；Passenger is corresponding more when having multiple brushing card data the same day and having transfer point
Item, which is swiped the card, records the Trip chain of merging reconstruct；Passenger had the corresponding closure transit trip chain of multiple brushing card data, institute the same day
Stating closure transit trip chain includes the often property the sent out trip of commuting class and sporadic trip two types；
When specific derivation, after being ranked up to record of swiping the card, between the distances by judging two adjacent record places for getting on/off
Every determining whether there is transfer behavior with whether time interval meets threshold value, by taking Fig. 3 as an example, the distance interval d in Fig. 3 is judged
With time interval t2+t3Whether it is less than threshold value, thinks that there are transfer behaviors less than threshold value.For subway data, in record of swiping the card
Information of getting off is covered, getting on the bus for can directly recording with next a little compares.For public transport data, needs first to find and work as
It gets on the bus in preceding route apart from next record a little nearest site information, is then judged again.Two of threshold value will finally be met
Record is merged into a Trip chain, lays the foundation for subsequent derivation trip point of destination.
The detailed step of Trip chain reconstruct is shown in Fig. 4, specifically:
Step 1: being ranked up all records of swiping the card according to IC card numbers and charge time, extracts first note of swiping the card
Record is recorded as current research, is judged；
Step 2: judging whether current research record belongs to same card number with next record, if belonging to, enters step
Three；If being not belonging to, judge whether current record has been merged into a Trip chain with a upper record, if not having, by current record
It is considered as an individual Trip chain, next record is considered as current research record later, reenters step 2；
Step 3: the type of swiping the card for judging current research record is public transport or subway；
For public transport: calculating next record and get on the bus a little at a distance from all websites of current line, judge the smallest distance value
Whether it is less than threshold value, is used as independent Trip chain if not satisfied, then recording current research, enters step four；If being less than threshold value, obtain
It takes in current line website and gets on the bus apart from next record apart from a smallest website, be denoted as current line apart from minimum station
Point, and found with the minimum website of current line distance by the GPS data collection of vehicle apart from nearest sampled point, it will correspond to
At the time of at the time of be considered as vehicle and reach website, and then calculate get on the bus point moment and vehicle of next record and reach the current line
Difference at the time of distance minimum website, judges whether difference is less than threshold value, if being not less than, by current research record as independent
Trip chain enters step four；Otherwise current research is recorded to the current line distance that merges with next record, and will acquire
Minimum website is got off a little labeled as current research record, is denoted as transfer point, is entered step four；
For subway: directly calculating next record and get on the bus a little and difference at the time of current research record is got off and between
Every, be compared respectively with time threshold and distance threshold, if both less than threshold value, by current research record with next record close
And and getting off current record a little labeled as transfer point, enter step four, current research record be otherwise considered as independent trip
Enter step 4 after chain；
Step 4: judge next record whether be in entire IC card data set the last item record, if being unsatisfactory for item
Part, then be considered as current research record for next record, otherwise return step two further judges current record and next record
Whether merge, if having merged, directly terminate whole flow process, if not merging, is tied after next record is considered as independent Trip chain
Beam whole flow process.
A final derivation step of getting off:
The derivation of city bus get-off stop is mainly on the basis of being completed website of getting on the bus and judge, based on city bus
The universal law and feature of passenger's trip carry out the judgement of get-off stop, are the key that carry out public transport station OD matrix derivation rank
Section.According to one day number taken pubic transport of passenger, trip can be divided into primary trip and repeatedly trip.
Primary trip refers to same day bus passenger brushing card data only once, and passenger may be by once going on a journey and complete to visit
Friend, which is perhaps on home leave and then inhabits terminus, nearby or by other modes of transportation realizes return, corresponding Trip chain reconstruct step
In rapid passenger's same day when only once brushing card data is without transfer behavior corresponding single swipe the card the Trip chain that record is constituted.
Repeatedly trip refer to passenger's same day bus card-reading number be more than twice, at this time correspond to two kinds of situations: one is because
It repeatedly swipes the card for transfer, it is corresponding when passenger had multiple brushing card data the same day and had transfer point in corresponding Trip chain reconstruct step
A plurality of record of swiping the card merges the Trip chain of reconstruct；Passenger had number of repeatedly swiping the card the same day in another then corresponding Trip chain reconstruct step
According to corresponding closure transit trip chain, such as commute traffic, travels to and fro between family and place of working, for another example sporadic trip
It handles affairs, is all made of public transport mode back and forth.
To sum up, will be got off according to trip characteristics and a little be divided into three types: the strong trip point of transfer point, closure and be closed it is weak go out
Row point；The judgment mode and derivation method of transfer point are shown in that Trip chain reconstructs step, are closed strong trip point and are closed weak trip point and use
In indicating getting off a little for single or multiple trips under non-transfer point, wherein the strong trip point of closure corresponds to commuting this kind of normal hair of traffic
Property trip, indicate the place often gone on a journey of passenger, to be obtained according to more days records of swiping the card, be closed weak trip point corresponding to occasionally
The working trip of hair property can be swiped the card by analyzing front and back and record feature and obtain.
Later use, which is closed strong trip point and is closed weak trip, further derives finally getting off a little for Trip chain, and step is shown in
Shown in Fig. 5, it is described in detail below:
Step 1: the Trip chain reconstructed in the step of extracting Trip chain reconstruct will have a mark of getting off for transfer behavior
It is denoted as transfer point；
Step 2: single Trip chain after reconstruct is successively extracted；
Step 3: being directed to single Trip chain, extracts the last item and swipes the card record, only once brushed if it is passenger's same day
The single trip of card data then directly extracts single and swipes the card record；
Step 4: it is got off a little based on the strong trip point judgement of closure: extracting getting on the bus in same card number more days records of swiping the card
Point, and successively sort by a frequency of occurrence of getting on the bus is descending, it is strong as closure to choose several forward websites of getting on the bus of sequence
It goes on a journey point, and finds the last item and swipe the card record institute in the line with the strong trip of the closure apart from nearest route website,
And calculate the strong trip point of the closure and with the strong trip point of the closure apart from nearest the distance between route website, it chooses full
Sufficient threshold value and finally the getting off a little as Trip chain apart from nearest route website, enter step eight；
If the last item is swiped the card, the route website recorded in the line is at a distance from the strong trip point of closure described in several
Threshold requirement is not satisfied, enters step five；
Step 5: the identical next continuous trip chained record of card number is judged whether there is, and if it exists, six are entered step,
If it does not exist, seven are entered step；
Step 6: being got off a little based on weak trip point judgement is closed: extracting getting on the bus a little in next continuous trip chained record,
It is closed weak trip point, finds the record institute that currently swipes the card and be closed weak trip point apart from nearest route station with described in the line
Point, and calculate the weak trip point of the closure and with the weak trip point of closure apart from nearest the distance between route website；If
Distance meets threshold requirement, getting off with the weak trip point of the closure apart from nearest route website as the final of Trip chain
Point, enters step eight；If not satisfied, entering step seven；
Step 7: it really gets off a little since the deficiency of information resources can not be obtained accurately, which does not operate；
Step 8: extracting next Trip chain, enter step three, until all Trip chains judge to complete, terminates.
Passenger flow OD matrix generation step between standing:
OD matrix refers to that city dweller counts the public transport station obtained according to trip purpose between urban public transport station
Between trip matrix, i.e., really trip origin and destination, wherein not including transfer point.Each trip that will be extracted in through the above steps
Chain get on the bus a little and and finally getting off a little based on the strong and weak trip point Trip chain of closure, import in Excel tables of data, use
The pivot function of Excel obtains covering passenger flow OD matrix between public transport and the integrated public transport station of subway；But it is above-mentioned
Passenger flow OD matrix cannot represent true complete Trip distribution situation between obtained station, there is both sides missing.On the one hand, by
In partial information resource and imperfect, will cause certain Based on Bus IC Card Data records can not smoothly be matched to public transport debarkation stop
Point if being a little not only not belonging to transfer point when getting off, but also is unsatisfactory for the case where being closed strong and weak trip point feature；On the other hand, it is based on
The Trip distribution that IC card data are derived by only represents the group that transit trip is carried out using IC card, and there are also partially pass through paper
The group that coin completes payment trip does not account for.Therefore, it is necessary to carry out expanding sample processing, and then generates and be most close to truth
Trip distribution situation.
Carry out expanding sample processing step to passenger flow OD matrix the station: the expansion sample of OD matrix will be based respectively on public transport line between standing
Two kinds of expansion spline coefficients are arranged in terms of above-mentioned two and carry out for road level.
The case where public transport get-off stop can not be smoothly matched to for records of swiping the card certain in IC card data set, using
One expands spline coefficient, and the first kind expands spline coefficient to derive between the station based on the IC card data of passenger flow OD matrix, calculates by adopting
Data volume is recorded with the swiping the card for each route finally got off a little that a derivation step is derived from of finally getting off, and and IC
The route of card data record is matched, and the volume of the flow of passengers of statistical correlation route.
Expression formula is as follows:
In formula,Expand spline coefficient for the first kind of route i；TiFor the brushing card data total amount of IC card data concentration line road i；Si
Pass through vehicle that is, during point is got off in derivation for the brushing card data total amount of the route i bus trip OD matrix derived
The record of swiping the card of identification route i is numbered, calculates and the line finally got off a little is derived from using a derivation step of finally getting off
Road i swipes the card the total amount of record；
For the group for completing payment trip by bank note, expansion sample is carried out using the second expansion spline coefficient；Second class expands sample system
Number is assuming that coin passenger goes on a journey and swipes the card under the completely the same situation of passenger's trip characteristics, based on all kinds of routes counted
Fare income expands sample to matrix station in route level.Second expansion spline coefficient expression formula is as follows:
In formula,Expand spline coefficient for the second class of route i；UiSwipe the card what payment was gone on a journey using bank note and IC card for route i
All trip number total amounts；MiTrip number total amount corresponding to bank note fare income for route i.
A kind of multi-mode bus passenger flow projectional technique based on big data technology provided by the invention, compared with prior art
At least there are following advantageous effects:
(1) public traffic passenger flow distributional analysis is combined using multi-mode: is sent out jointly in current rail traffic and routine bus system
Under the background of exhibition, this kind of multi-mode integrated combination transit trip mode of public transport+subway is more universal.The comprehensive benefit of this method
With public transport and subway brushing card data, the two is taken into consideration, can accurately extract single bus trip, single subway goes out
, more there is the multi-mode of realistic meaning in the origin and destination of a variety of trip modes such as row, public transport+bus trip, public transport+subway trip
Combine public traffic passenger flow distribution situation.
(2) derivation method of getting off based on trip characteristics: during point is got off in derivation, fully considered that trip is special
Sign.Each item record of swiping the card is analyzed in transfer behavior based on passenger before this, is reconstructed the complete Trip chain of user.Then
Based on the considerations of to the trip of passenger's single and multiple trip purpose, proposing often hair property and the strong and weak trip of sporadic corresponding closure
Point can be derived by getting off a little for most of Trip chain, count model compared to collection based on probability using power trip point,
Method accuracy rate is higher.
(3) consider that the passenger flow OD of reality factor expands quadrat method: often being lacked based on the Trip distribution that IC card data are derived
In truth, it is also necessary to which complete public traffic passenger flow distribution can just be obtained by carrying out expansion sample processing.This method is carried out to OD
It when expanding sample, not only allows for that the IC card data got off a little can not be obtained due to loss of learning, it is also contemplated that bank note user group.Base
In to multinomial reality factor the considerations of, this method expands sample result will be closer in truth.
Method innovation provided by the present invention subway IC card is combined on the basis of bus IC card and GPS data
Data have calculated that the passenger flow of city multi-mode public transport trip has carried out convergence analysis using public transport and subway mass data,
And the derivation method got off a little is optimized, the new approaches for matching and getting off a little are proposed based on trip characteristics, and are considered
Multinomial factor carries out expansion sample to result.Method can more accurately derive the passenger flow OD distribution feelings of multi-mode bus trip
Condition is more applicable for nowadays public transport+increasingly popular traffic environment of subway combination transit trip mode, can be public transport
The planning and optimization of industry provide help.
Claims (8)
1. a kind of multi-mode bus passenger flow projectional technique based on big data technology, which is characterized in that the method is based on IC card
Data set, GPS data collection, website line basis data collection, derive the website of getting on the bus of passenger；By the trip for analyzing single passenger
Chain feature, exchange travel are to carry out analysis to reconstruct complete Trip chain；Based on trip characteristics, swiped the card record pair using single
The non-collection meter that should be got off a little, which derives, obtains finally getting off a little for Trip chain；It is a little a little obtained with finally getting off for Trip chain in conjunction with getting on the bus
Cover OD matrix between public transport and the integrated public transport station of subway, expansion sample is carried out to the OD matrix and handles to obtain complete public affairs
Traffic Trip distribution altogether.
2. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 1, which is characterized in that
The website line basis data collection includes subway terminal data collection, subway station track data collection, public bus network station data
Collection, website serial number data collection；
The IC card data set includes: charge time, subway terminal number or public transit vehicle number, IC card number and is used to identify ground
The type of swiping the card of iron and public transport；The GPS data collection includes: the GPS point sampling instant time, car number, working line, instantaneous
Longitude and instantaneous dimension.
3. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 2, which is characterized in that
The method specifically includes:
Website of getting on the bus derives: IC card data set, GPS data collection, website line basis data collection is based on, according to public transport and subway
Public transport is got on the bus website and subway website of getting on the bus derives respectively by feature；
Trip chain reconstruct: according to passenger go on a journey in whether have transfer behavior, the record that will swipe the card is integrated, reconstruct passenger trip
The single record of no transfer behavior is directly considered as a Trip chain, will have a plurality of record of transfer behavior to tie by chain
Conjunction backsight is a Trip chain；Trip chain includes: correspondence when passenger's same day, only once brushing card data was without transfer behavior after reconstruct
Single swipe the card record constitute Trip chain；Passenger's corresponding a plurality of note of swiping the card when having multiple brushing card data the same day and having transfer point
Record merges the Trip chain of reconstruct；Passenger had multiple brushing card data corresponding closure transit trip chain the same day, and the closure is public
Traffic trip chain includes the often property the sent out trip of commuting class and sporadic trip two types altogether；
A final derivation of getting off: according to trip characteristics, will get off and be a little divided into: transfer point is closed strong trip and is closed weak trip
Point；The transfer point can be obtained after Trip chain reconstruct；The strong trip point of closure and the weak trip point of closure are used for table
Show getting off a little for non-transfer point；The strong corresponding commuting class of trip point of closure often go on a journey by the property sent out, and indicates the ground that passenger often goes on a journey
Point can be obtained according to more days records of swiping the card；The corresponding sporadic trip of the weak trip point of closure, indicates that passenger is accidental
The place of trip can be swiped the card by analyzing front and back and record feature and obtain；It is weak according to the strong trip point of the closure and the closure
Trip point, which further derives, obtains finally getting off a little for Trip chain；
Passenger flow OD matrix generates between standing: getting on the bus for each Trip chain extracted a little being got off a little with the final of Trip chain, is imported
In Excel tables of data, maintenance data perspective function obtains covering passenger flow OD square between public transport and the integrated public transport station of subway
Battle array；
Passenger flow OD matrix the station is carried out to expand sample processing: can not be smooth for records of swiping the card certain in IC card data set
The case where being fitted on public transport get-off stop, and for the group for completing payment trip by bank note, different coefficients is respectively adopted
Carry out expansion sample.
4. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 3, which is characterized in that
In the step of website of getting on the bus derives:
Subway gets on the bus the derivation method of website are as follows: IC card data set record subway terminal number when swiping the card passes through subway terminal
Number matches the subway terminal number that IC card data set and subway terminal data are concentrated, and subway terminal data concentration is also wrapped
It includes and numbers corresponding site name with subway, and then obtain the website of getting on the bus when taking subway；
Public transport is got on the bus the derivation method of website: including car number matching, time match, three step of nearest site search；It is logical first
It crosses IC card data set and obtains the bus car number that passenger takes, then take charge time in IC card data set and passenger
The GPS moment that the GPS data of vehicle is concentrated is converted into minute and compares, and finds GPS data and concentrates and charge time phase
Same or immediate sampling instant, finally determines that distance is nearest on working line based on the position coordinates under the sampling instant point
Bus station, the website of getting on the bus when as taking pubic transport.
5. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 3, which is characterized in that
The step of Trip chain reconstructs are as follows: swipe the card after record is ranked up to passenger, got on or off the bus in two adjacent records by judging
Whether the distance interval and time interval of point meet threshold value to determine whether there is transfer behavior, think to exist less than threshold value to change
Travel is；It is a Trip chain that a plurality of record for having transfer behavior, which is combined backsight, and the single of no transfer behavior is remembered
Record is directly considered as a Trip chain.
6. according to a kind of multi-mode bus passenger flow projectional technique based on big data technology of claim 3 or 5, feature exists
In, Trip chain reconstructs step, specifically:
Step 1: being ranked up all records of swiping the card according to IC card numbers and charge time, extracts first record of swiping the card and makees
For current research record, judged；
Step 2: judging whether current research record belongs to same card number with next record, if belonging to, enters step three；If
It is not belonging to, judges whether current record is merged into a Trip chain with a upper record and current record is considered as one if not having
Next record is considered as current research record later, reenters step 2 by the individual Trip chain of item；
Step 3: the type of swiping the card for judging current research record is public transport or subway；
For public transport: calculating next record and get on the bus a little at a distance from all websites of current line, whether judge the smallest distance value
Less than threshold value, it is used as independent Trip chain if not satisfied, then recording current research, enters step four；If being less than threshold value, acquisition is worked as
It gets on the bus apart from next record apart from a smallest website in front way station point, is denoted as the minimum website of current line distance；And
It is found with the minimum website of current line distance by the GPS data collection of vehicle apart from nearest sampled point, when will be corresponding
At the time of being considered as vehicle quarter and reach current line distance minimum website, and then calculates next record and get on the bus point moment and vehicle
The difference at the time of current line distance minimum website is reached, judges whether difference is less than threshold value, it, will be current if being not less than
Research record is used as independent Trip chain, enters step four；Otherwise current research is recorded and is merged with next record, and will acquire
Minimum website the getting off a little labeled as current research record of current line distance, is denoted as transfer point, enters step four；
For subway: directly calculate that next record is got on the bus a little and current research records a difference and distance interval at the time of getting off,
It is compared respectively with time threshold and distance threshold, if both less than threshold value, current research is recorded and is merged with next record,
And getting off current record a little labeled as transfer point, four are entered step, current research record is otherwise considered as independent Trip chain
Enter step 4 afterwards；
Step 4: judge next record whether be in entire IC card data set the last item record, if being unsatisfactory for condition,
Next record is considered as current research record, otherwise return step two further judges whether are current record and next record
Merge, if having merged, directly terminate whole flow process, if not merging, next record is considered as after independent Trip chain terminate it is whole
A process.
7. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 3, which is characterized in that
In the step of deriving of getting off, according to the strong trip point of the closure and the weak trip point of closure, further derivation is gone on a journey
The step of finally getting off of chain, specifically:
Step 1: the Trip chain reconstructed in the step of extracting Trip chain reconstruct will have getting off for transfer behavior to be a little labeled as
Transfer point；
Step 2: single Trip chain after reconstruct is successively extracted；
Step 3: being directed to single Trip chain, extracts the last item and swipes the card record, only once swiped the card on the same day number if it is passenger
According to single trip then directly extract single and swipe the card record；
Step 4: being got off a little based on the strong trip point judgement of closure: extracting getting on the bus a little in same card number more days records of swiping the card, and
It successively sorts by a frequency of occurrence of getting on the bus is descending, chooses several for sorting forward and get on the bus website as the strong trip of closure
Point, and find the last item and swipe the card record institute in the line with the strong trip of the closure apart from nearest route website, and count
Calculate the strong trip point of the closure and with the strong trip point of the closure apart from nearest the distance between route website, selection meets threshold
Value and finally the getting off a little as Trip chain apart from nearest route website, enter step eight；
If the last item is swiped the card record institute's route website in the line and closure described in several go on a journey by force at a distance from not
Meet threshold requirement, enters step five；
Step 5: the identical next continuous trip chained record of card number is judged whether there is, and if it exists, six are entered step, if not
In the presence of entering step seven；
Step 6: it is got off a little based on weak trip point judgement is closed: extracting getting on the bus a little in next continuous trip chained record, that is, close
It closes weak trip point, finds the record institute that currently swipes the card and be closed weak trip point apart from nearest route website with described in the line, and
Calculate the weak trip point of the closure and with the weak trip point of closure apart from nearest the distance between route website；If apart from full
Sufficient threshold requirement getting off a little as the final of Trip chain apart from nearest route website using with the weak trip point of the closure, entering
Step 8；If not satisfied, entering step seven；
Step 7: it really gets off a little since the deficiency of information resources can not be obtained accurately, which does not operate；
Step 8: extracting next Trip chain, enter step three, until all Trip chains judge to complete, terminates.
8. a kind of multi-mode bus passenger flow projectional technique based on big data technology according to claim 3, which is characterized in that
Carrying out expansion sample processing to OD matrix the station includes:
The case where public transport get-off stop can not be smoothly matched to for records of swiping the card certain in IC card data set, expands using first
Spline coefficient, expression formula are as follows:
In formula,Expand spline coefficient for the first kind of route i；TiFor the brushing card data total amount of IC card data concentration line road i；SiFor line
The brushing card data total amount for the bus trip OD matrix that road i has been derived passes through car number that is, during point is got off in derivation
It identifies the record of swiping the card of route i, calculates and the route i brush finally got off a little is derived from using a derivation step of finally getting off
Block the total amount of record；
For the group for completing payment trip by bank note, expansion sample is carried out using the second expansion spline coefficient；Second expands spline coefficient expression
Formula is as follows:
In formula,Expand spline coefficient for the second class of route i；UiFor route i using bank note and IC card swipe the card payment trip whole
Trip number total amount；MiTrip number total amount corresponding to bank note fare income for route i.
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