CN104766473A - Traffic trip feature extraction method based on multi-mode public transport data matching - Google Patents
Traffic trip feature extraction method based on multi-mode public transport data matching Download PDFInfo
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Abstract
The invention relates to a traffic trip feature extraction method based on multi-mode public transport data matching. According to the traffic trip feature extraction method based on multi-mode public transport data matching, the concept of a public transport commuting trip chain is introduced, and resident commuting trip feather information such as the commuting trip time, the commuting trip distance and the transfer characteristics is obtained by conducting data pre-processing and matching, public transport trip chain structure extraction, commuting trip behavior judgment, trip origin-destination determination and trip feather information matching according to the multi-source data including ground public transport, rail transport and public bike card swiping data, public transport GPS data, public transport stations, line basic data and the like. According to the traffic trip feature extraction method based on multi-mode public transport data matching, the resident commuting trip condition can be mastered by public transport operating enterprises and government competent departments accurately, the support is provided for optimizing urban public transport lines and making public transport policies, and the traffic trip feature extraction method has great significance in improving commuting trip efficiency of residents.
Description
Technical field
The invention belongs to public transport operational monitoring field, relate to a kind of transit trip feature calculation based on multi-mode public transport Data Matching and analytical approach.
Background technology
Commuter is the main body of Public Transport Service, and grasping its trip characteristics is the basis of rationally throwing in public transport transport power, formulating public transit network optimization method measure.Along with the popularization of intelligent public transportation system, public transport multi-source data (as IC-card data, public transport gps data etc.) is extensively gathered, these data have recorded the transit trip process of resident, have established good data basis for extracting its trip characteristics.Application number is the acquisition methods that patent discloses a kind of resident travel characteristic parameter based on mobile phone location data of CN201210074506, data in mobile phone is mated with traffic zone, and continuous print data are merged, according to the number merged and the trip route affecting duration also original subscriber, obtain trip distance, trip speed.But the acquisition methods of resident travel characteristic parameter disclosed in this patent, accurately cannot identify the classification of user, namely accurately can not distinguish and travel frequently and non-commuting subscriber, and directly calculate the parameters such as row distance according to revised mobile phone location data, the error of calculation can be caused bigger than normal.Application number be CN200910190637 patent discloses the dynamic trip characteristics modeling method of a kind of population space-time based on multisource data fusion, by map datum, mobile phone location data and floating vehicle data fusion, set up population trip characteristics spatial analytical model, obtain population distribution and the distribution of population trip characteristics.But the dynamic trip characteristics modeling method of population space-time disclosed in this patent, and the trip characteristics of non-resident use public transport, and the population trip characteristics obtained is macroscopic aspect, does not reach the precision of particular user at the trip characteristics in certain trip stage.
The public transport of the big and medium-sized cities of most domestic includes routine bus system, track traffic and public bicycles three kinds of modes, and routine bus system comprises flat fare public transport and pricing for segment public transport two type usually.How effectively these magnanimity isomeric datas are mated in association, excavate public transport commuter feature, also lack the method system of complete set at present.
Summary of the invention
The present invention proposes the concept of " transit trip chain ", and introduce " trip stage " to realize expressing the refinement of transit trip process.The present invention on the basis of multi-source data association coupling, propose differentiated by Trip chain structure extraction, commuter, trip stage origin and destination determine and the step such as trip characteristics information matches, obtain the complete method of resident's public transport commuter feature.
Based on the transit trip feature extracting method of multi-mode public transport Data Matching, comprise the following steps:
Step 1: the pre-service of public transport multi-source data with mate.
Valid data in screening mass data, improve the quality of data, and utilize relevant field to carry out Data Integration with associating to mate.
Step 1.1: public transport brushing card data pre-service.
The brushing card data field of routine bus system, track traffic and public bicycles three class mode is different, and routine bus system is divided into a ticket public transport and pricing for segment public transport two class.According to the implication of all kinds of brushing card data field, therefrom need extract the relevant user's card number of resident trip, exchange hour, the by bus field such as circuit, site number, and be incorporated in same tables of data.To swipe the card type for distinguishing difference, add unique mark to every class brushing card data: a ticket routine bus system is labeled as " B1 ", and pricing for segment routine bus system is labeled as " B2 ", track traffic is labeled as " R ", and public bicycles is labeled as " Z ".The field of the brushing card data table after integration is as shown in table 1, and the field that information is incomplete is set to sky temporarily.
Table 1 public transport brushing card data integrates literary name section
Step 1.2: the public transport arrival time based on public transport gps data is determined.
According to granted patent " the public transport travelling speed extracting method based on the bus GPS data " (patent No.: 2012102664718) that this copyright owner has, based on public transport GPS locator data and public bus network basic data, made up by map match, segmental arc, website mate, the step such as travel direction differentiation, the time of the arrival website of public transit vehicle can be obtained.
Step 1.3: multi-mode public transport website spatial relationship is mated.
Because track traffic and public bicycles brushing card data have recorded the information of trip origin and destination, and the trip origin and destination information recorded in routine bus system brushing card data is complete, and site information of partly getting on or off the bus need go to infer by transfer process.Therefore, the present invention utilizes the website coordinate data of routine bus system, track traffic and public bicycles, establishes the spatial relationship table of three class public traffic stations, determines the transfer procedural information of resident with this.Different according to the radianting capacity of dissimilar website, the routine bus system website attractived region that the present invention determines is 360m, and the attractived region of track traffic website is 770m, and the attractived region of public bicycles website is 300m.In the corresponding attractived region threshold value of all kinds of website, the information such as the circuit by bus of in addition going on a journey, according to the shortest principle of transfer distance, determine the website of getting on or off the bus of transfer process, idiographic flow as shown in Figure 1.Public traffic station spatial relationship literary name section is as follows:
Table 2 public traffic station spatial relationship table
Step 1.4: between any website of track traffic, stroke distances is determined.
Resident does not need to swipe the card in the transfer of track traffic inside, and this causes difficulty to acquisition passenger trip route.The present invention is based on resident trip can the hypothesis of the most Short protocol of select time, pass through Shortest Path Searching, determine known track traffic website OD between optimal path, again according to arbitrary neighborhood site distance in track traffic basic data from data, calculate any OD of track traffic website between stroke distances.
Step 2: transit trip chain structure is extracted.
Transit trip chain refers to from trip start site to object website, the once complete trip process be made up of by order of occurrence one or more transit trip stage.Transit trip chain belongs to inc strand, can the microprocess of reproducing passerby transit trip each time.Can be there is one or more transit trip chain for one day in traveler, a transit trip chain can comprise one or more trip stage.
The present invention is poor according to the exchange hour of adjacent two records of swiping the card of same user, judge that these two adjacent trip stages belong to transfer relation or adhere to two different Trip chain separately, accordingly each trip stage of traveler connected or divided, determining the basic structure of Trip chain.
Due to routine bus system, track traffic is different with the exchange hour implication recorded in public bicycles three class brushing card data: a ticket public transport (B1) have recorded pick-up time, pricing for segment public transport (B2) have recorded the time getting off, track traffic (R) have recorded enters the station and the departures time, public bicycles (Z) have recorded by means of car and returns the car the time, therefore there are 14 kinds of transfer types between three class trip modes, and contain different time ingredients (as the time in transit of different mode of transportation in the exchange hour difference of often kind of transfer type, the transfer time etc. of different transfer process), therefore the exchange hour difference limen value of often kind of transfer type is different.14 kinds transfer types exchange hour difference composition and threshold value as shown in table 3:
The adjacent trip stage transfer time threshold value of table 3
According to the exchange hour difference limen value in upper table, if the exchange hour in adjacent two trip stages is within threshold value, then think to there is transfer behavior between these two trip stages, both belong to same Trip chain; Otherwise, then think that both belong to different Trip chain.
Step 3: commuter behavior differentiates.
Owing to containing the record of swiping the card of various different trip purpose in brushing card data, therefore, need to lay down a regulation the travel behaviour filtered out for the purpose of travelling frequently.
Comparatively strong and have the features such as relatively more fixing occurrence frequency and time of origin according to resident's commuter Behavior law, the present invention proposes following commuter behavior decision rule on the basis of mass data analysis:
(1) extract five workaday brushing card datas in a week and divide into groups by user's card number;
(2) if same user (same card number) is in five working days of one week, have at least and within three days, maintain identical trip rule (referring to identical Trip chain order and Trip chain structure), then think that this user is commuter user, set up commuter user Sample Storehouse.
(3) commuting subscriber thinks commuter in the trip that the peak period of every workday occurs.
(4) commuter user Sample Storehouse monthly upgrades once.
Step 4: trip stage origin and destination are determined.
Use the trip stage of track traffic or public bicycles mode, can according to the site number recorded in its brushing card data, in addition the Back ground Information of track traffic and public bicycles website, both couplings can obtain its complete enter the station (by means of car) site name and departures (returning the car) site name.And the site information of getting on or off the bus of routine bus system brushing card data record is imperfect, the origin and destination in the trip stage of routine bus system mode be obtained, need through the coupling of following three steps:
Step 4.1: the public transport based on public transport arrival time is got on the bus or get-off stop coupling.
The brushing card data of one ticket public transport have recorded the passenger loading time, the brushing card data of pricing for segment public transport have recorded the time getting off of passenger, both are mated with the arrival time table (registration of vehicle arrives the time of each website) at passenger place public transit vehicle (being mated by car number), can obtain the get-off stop title of get on the bus site name and the pricing for segment bus passenger of a ticket bus passenger.
But, brushing card data record be time of IC card system, and public transit vehicle arrival time record is time of public transport gps system, and both exist certain deviation; And the impact of the factors such as process duration of swiping the card when considering that passenger getting off car can be swiped the card in advance, a large amount of passenger's queuing is got on the bus is long, needs to arrange when website mates rational threshold value, to ensure success ratio and the accuracy rate of coupling.The present invention, on the basis of the conditions such as the average stop spacing considering a ticket public transport and pricing for segment public transport respectively, determines following threshold value: a ticket public transport 2.8min, pricing for segment public transport 3.2min.Namely when the pick-up time of a ticket bus passenger and the difference of public transit vehicle arrival time are less than 2.8min, then by public transit vehicle to website coupling be the website of getting on the bus of passenger; When the time getting off of pricing for segment bus passenger and the difference of public transit vehicle arrival time are less than 3.2min, then the website coupling arrived by public transit vehicle is the get-off stop of passenger.
Step 4.2: the public transport based on public traffic station spatial relationship is got on the bus or get-off stop coupling.
For the get-off stop of a ticket public transport and the website of getting on the bus of pricing for segment public transport, a part can go to infer by the transfer process of trip on the basis of public traffic station spatial relationship table.Concrete deduction process is as follows:
(1) get-off stop of a ticket public transport is determined
For two adjacent trip stages of same Trip chain, if its transfer type belongs to: ticket Public Transport Transfer one ticket public transport (B1-B1), a ticket Public Transport Transfer track traffic (B1-R) or a ticket Public Transport Transfer public bicycles (B1-Z), these three kinds of situations all there is known (enter the station or the borrow car) website of getting on the bus after passenger changes to behavior, and the get-off stop of the ticket public transport taken before changing to behavior is unknown.At this, utilize the public traffic station spatial relationship table set up, website centered by (enter the station or the borrow car) website of getting on the bus after the behavior of changing to, other routine bus system websites within search center website attractived region; Again from these candidate bus stations, numbering of circuit belonging to it, the public bus network that screening is taken before changing to behavior with passenger numbers identical website (if having multiple, then get one that wherein distance central site is nearest), this website is passenger and takes the corresponding get-off stop of a ticket public transport.
(2) website of getting on the bus of pricing for segment public transport is determined
For two adjacent trip stages of same Trip chain, if its transfer type belongs to: pricing for segment Public Transport Transfer pricing for segment public transport (B2-B2), orbit traffic transfer pricing for segment public transport (R-B2) or public bicycles transfer pricing for segment public transport (Z-B2), these three kinds of situations all there is known (set off or the return the car) website of getting off before passenger changes to behavior, and the website the unknown of getting on the bus of the pricing for segment public transport taken after changing to behavior.Equally, the public traffic station spatial relationship table set up is utilized, website centered by (set off or the return the car) website of getting off before the behavior of changing to, other routine bus system websites within search center website attractived region; Again from these candidate bus stations, numbering of circuit belonging to it, the public bus network that screening is taken after changing to behavior with passenger numbers identical website (if having multiple, then get wherein apart from nearest one of central site), this website is passenger and takes pricing for segment public transport and to get on the bus accordingly website.
Step 4.3: the public transport based on travel pattern rule is got on the bus or get-off stop coupling.
According to the symmetry of commuter behavior, in traveler one day first time commuter starting point should be identical with the terminal of commuter last in a day, and the terminal of commuter should be identical with the starting point of last commuter for the first time.Accordingly, the present invention proposes a ticket public transport get-off stop of some types and pricing for segment and to get on the bus the determination methods of website, specific as follows:
(1) get-off stop of a ticket public transport is determined
If in traveler one day first time trip chaining last trip stage takes is a ticket public transport (B1), then using the start site of this traveler last trip chaining on the same day as central site, routine bus system website in search center website attractived region, filter out wherein belong to traveler take advantage of website on public bus network, it can be used as the get-off stop of traveler first time trip chaining.Profit uses the same method, and in traveler one day, the get-off stop of a ticket public transport taken also can be determined the last trip stage of last trip chaining.
(2) website of getting on the bus of pricing for segment public transport is determined
If in traveler one day first time trip chaining first trip stage take is pricing for segment public transport (B2), then using the end website of this traveler last trip chaining on the same day as central site, routine bus system website in search center website attractived region, filter out wherein belong to traveler take advantage of website on public bus network, it can be used as the website of getting on the bus of traveler first time trip chaining.Profit uses the same method, and in traveler one day, the website of getting on the bus of pricing for segment public transport taken also can be determined first trip stage of last trip chaining.
Concrete coupling flow process as shown in Figure 2.
Step 5: trip characteristics information matches.
On the basis of the trip stage origin and destination information that above step obtains, the data such as stroke distances between combined ground public transport arrival time table and any website of track traffic, each journey time in trip stage, the calculating of stroke distances can be completed, and then the public transport commuter feature of resident can be obtained.Concrete grammar is as follows:
(1) routine bus system trip is got on or off the bus time complexity curve
In previous step, the pick-up time of one ticket public transport (B1) and the time getting off of pricing for segment public transport (B2), use the time of IC card system, and routine bus system other time be gps system time in routine bus system arrival time table.Because the time of gps system is through overcorrect, accuracy is higher, standard simultaneously in order to calculate journey time is unified, revises in the present invention with the time getting off (IC card system time) of the time in routine bus system arrival time table (gps system time) to the pick-up time of a ticket public transport (B1) and pricing for segment public transport (B2).Modification method is: the get-off stop information of get on the bus website and the pricing for segment public transport (B2) of the ticket public transport (B1) utilizing trip stage match to obtain, by the fields match such as circuit number, car number, arrive the charge time of the time replacement passenger of respective site with vehicle in routine bus system arrival time table.
(2) journey time and stroke distances coupling
The journey time in each trip stage is passenger getting off car (set off or the return the car) time and the mistiming of (enter the station or borrow car) time of getting on the bus; And routine bus system, track traffic and public bicycles three kinds of modes are gone on a journey, the stroke distances in stage, obtains respectively by mating with stroke distances table and public bicycles website base data table between routine bus system line tower foundation tables of data, any website of track traffic.
By above each step, the field of the public transport commuter result of calculation table obtained, as shown in table 4:
Table 4 public transport commuter result of calculation table
The present invention has following beneficial effect: the concept proposing transit trip chain, mated by the association of public transport multi-source data, the key issues such as website space time information coupling that emphasis solves transfer behavior judgement, commuter is differentiated and routine bus system is got on or off the bus, are specifically described extraction step and the method for the Resident Trip Characteristics such as commuter time, commuter Distance geometry number of transfer.The present invention contributes to public transport operation enterprise and responsible departments of the government accurately grasp resident's commuter situation, for urban public transport line network optimization, public transport policy making etc. provide support, significant to raising resident commuter efficiency.
Accompanying drawing explanation
Fig. 1 is public traffic station spatial relationship coupling process flow diagram;
Fig. 2 is transit trip stage origin and destination coupling process flow diagram;
Fig. 3 is the transit trip feature extracting method process flow diagram based on multi-mode public transport Data Matching;
Embodiment
Below in conjunction with drawings and Examples, the present invention will be further described.
Based on the transit trip feature extracting method of multi-mode public transport Data Matching process flow diagram as shown in Figure 3, comprise the following steps:
Step 1: the pre-service of public transport multi-source data with mate.
Step 2: transit trip chain structure is extracted.
Step 3: commuter behavior differentiates.
Step 4: trip stage origin and destination are determined.
Step 5: trip characteristics information matches.
Provide application example of the present invention below.
For Beijing's continuous five workaday public transport service datas on 22 to September 26 September in 2014, computation and analysis is carried out to go-outside for civilian by bus feature.
(1) pre-service carrying out public transport multi-source data with mate
According to field meanings, extract resident trip relevant field, and be incorporated into a table from routine bus system, track traffic and public bicycles three class brushing card data, for every class brushing card data adds mark, result is as shown in table 5:
Table 5 public transport brushing card data integrates table
On the basis of public transport GPS locator data and public bus network data, by public transport travelling speed extracting method, the time of the arrival website of the public transit vehicle obtained, result is as shown in table 6:
Table 6 public transit vehicle arrival time table
For determining that resident changes to the information of process, utilize the website coordinate data of routine bus system, track traffic and public bicycles, the spatial relationship table of three class public traffic stations of foundation is as follows:
Table 7 public traffic station spatial relationship table
Based on arbitrary neighborhood site distance in track traffic basic data, according to Shortest Path Searching, the distance between any two websites of the track determined, as shown in table 8:
Stroke distances table between any website of table 8 track traffic
(2) transit trip chain structure is extracted
According to the exchange hour difference limen value that the present invention determines, if the exchange hour in adjacent two trip stages is within threshold value, then think to there is transfer behavior between these two trip stages, both belong to same Trip chain; Otherwise, then think that both belong to different Trip chain.Judge through above, the transit trip chain structure of extraction is as shown in table 9:
Table 9 transit trip chain information
| Date | AiOCC number | Trip chain structure | Trip chain order | Trip number of stages |
| 2014/9/22 | 00001082 | R-B2 | 1 | 2 |
| 2014/9/22 | 00001082 | R-B1-R | 2 | 3 |
| 2014/9/22 | 00009234 | R-B1 | 1 | 2 |
| 2014/9/22 | 00009234 | B1-R | 2 | 2 |
| 2014/9/22 | 00006068 | R | 1 | 1 |
| 2014/9/22 | 00006068 | R | 2 | 1 |
On the basis of Trip chain result, the information in each trip stage of extracting further is as shown in table 10:
Table 10 transit trip chain is respectively gone on a journey session information table
(3) commuter behavior is differentiated
Analyze continuous five workaday brushing card datas on 22 to September 26 September in 2014, if identical Trip chain order, the data of identical Trip chain structure occur more than 3 times (containing 3 times), then think that this user (AiOCC number) is commuting subscriber, the trip that commuting subscriber occurred in peak period is then commuter.
Table 11 commuter user message table
| AiOCC number | Trip chain order | Trip chain structure | There is number of days |
| 00001062 | 1 | B1 | 3 |
| 00001099 | 1 | B1-B2 | 3 |
| 00001100 | 1 | B1-Z | 3 |
| 00001156 | 2 | R | 4 |
(4) row order section origin and destination are determined
By utilize the site number of track traffic or public bicycles mate (by means of returning the car) out of the station website, based on public transport arrival time coupling public transport get on the bus or get-off stop, based on public traffic station spatial relationship coupling public transport get on the bus or get-off stop and based on travel pattern rule coupling public transport get on the bus or get-off stop four steps, obtain the origin and destination information in each trip stage, as shown in table 12:
Table 12 public transport is respectively gone on a journey stage origin and destination information table
(5) coupling trip characteristic information
On the basis of each trip stage origin and destination information, combined ground public transport arrival time table, data such as stroke distances between routine bus system line tower foundation data and any website of track traffic, to be got on or off the bus time complexity curve and journey time, stroke distances coupling by routine bus system trip, obtain public transport commuter feature calculation result, as shown in table 13:
Table 13 public transport commuter feature calculation result table
By above result of calculation, the trip characteristics information such as commuter time, commuter Distance geometry number of transfer that each trip is individual can be obtained, as above in table, card number is the traveler of 00001082, its first time Trip chain trip distance be 38.48km, travel time is 87.2min, owing to there being two trip stages, so this traveler first time Trip chain comprises once change to process.
On the basis of the individual trip characteristics of each trip, traveler is classified on different dimensions, analyze the statistical nature of the travel behaviour of different classes of traveler, and then the trip rule of whole city commuter person can be grasped.
Claims (3)
1., based on the transit trip feature extracting method of multi-mode public transport Data Matching, it is characterized in that: said method comprising the steps of:
Step 1: the pre-service of public transport multi-source data with mate;
Step 2: transit trip chain structure is extracted;
Step 3: commuter behavior differentiates;
Step 4: trip stage origin and destination are determined;
Step 5: trip characteristics information matches;
The pre-service of described step 1 public transport multi-source data is as follows with the method for mating,
Valid data in screening mass data, improve the quality of data, and utilize relevant field to carry out Data Integration with associating to mate;
(1) public transport brushing card data pre-service;
The brushing card data field of routine bus system, track traffic and public bicycles three class mode is different, and routine bus system is divided into a ticket public transport and pricing for segment public transport two class; According to the implication of all kinds of brushing card data field, therefrom need extract the relevant user's card number of resident trip, exchange hour, the by bus field such as circuit, site number, and be incorporated in same tables of data; To swipe the card type for distinguishing difference, add unique mark to every class brushing card data: a ticket routine bus system is labeled as " B1 ", and pricing for segment routine bus system is labeled as " B2 ", track traffic is labeled as " R ", and public bicycles is labeled as " Z "; The field of the brushing card data table after integration is as shown in table 1, and the field that information is incomplete is set to sky temporarily;
Table 1 public transport brushing card data integrates literary name section
(2) the public transport arrival time based on public transport gps data is determined;
Based on public transport GPS locator data and public bus network basic data, made up by map match, segmental arc, website mates, the step such as travel direction differentiation, obtain the time of the arrival website of public transit vehicle;
(3) multi-mode public transport website spatial relationship coupling;
Because track traffic and public bicycles brushing card data have recorded the information of trip origin and destination, and the trip origin and destination information recorded in routine bus system brushing card data is complete, and site information of partly getting on or off the bus need be gone to infer by transfer process; Therefore, utilize the website coordinate data of routine bus system, track traffic and public bicycles, establish the spatial relationship table of three class public traffic stations, determine the transfer procedural information of resident with this; Different according to the radianting capacity of dissimilar website, the routine bus system website attractived region determined is 360m, and the attractived region of track traffic website is 770m, and the attractived region of public bicycles website is 300m; In the corresponding attractived region threshold value of all kinds of website, the information such as the circuit by bus of in addition going on a journey, according to the shortest principle of transfer distance, determine the website of getting on or off the bus of transfer process; Public traffic station spatial relationship literary name section is as follows:
Table 2 public traffic station spatial relationship table
(4) between any website of track traffic, stroke distances is determined;
Resident does not need to swipe the card in the transfer of track traffic inside, and this causes difficulty to acquisition passenger trip route; Can the hypothesis of the most Short protocol of select time based on resident trip, pass through Shortest Path Searching, determine known track traffic website OD between optimal path, again according to arbitrary neighborhood site distance in track traffic basic data from data, calculate any OD of track traffic website between stroke distances;
The method that described step 2 transit trip chain structure is extracted is as follows,
Transit trip chain refers to from trip start site to object website, the once complete trip process be made up of by order of occurrence one or more transit trip stage; Transit trip chain belongs to inc strand, can the microprocess of reproducing passerby transit trip each time; Can be there is one or more transit trip chain for one day in traveler, a transit trip chain can comprise one or more trip stage;
Poor according to the exchange hour of adjacent two records of swiping the card of same user, judge that these two adjacent trip stages belong to transfer relation or adhere to two different Trip chain separately, accordingly each trip stage of traveler connected or divided, determining the basic structure of Trip chain;
Due to routine bus system, track traffic is different with the exchange hour implication recorded in public bicycles three class brushing card data: a ticket public transport (B1) have recorded pick-up time, pricing for segment public transport (B2) have recorded the time getting off, track traffic (R) have recorded enters the station and the departures time, public bicycles (Z) have recorded by means of car and returns the car the time, therefore there are 14 kinds of transfer types between three class trip modes, and contain different time ingredients in the exchange hour difference of often kind of transfer type, as the time in transit of different mode of transportation, the transfer time etc. of different transfer process, therefore the exchange hour difference limen value of often kind of transfer type is different, 14 kinds transfer types exchange hour difference composition and threshold value as shown in table 3:
The adjacent trip stage transfer time threshold value of table 3
According to the exchange hour difference limen value in upper table, if the exchange hour in adjacent two trip stages is within threshold value, then think to there is transfer behavior between these two trip stages, both belong to same Trip chain; Otherwise, then think that both belong to different Trip chain;
It is as follows that method for distinguishing is sentenced in the behavior of described step 3 commuter:
Owing to containing the record of swiping the card of various different trip purpose in brushing card data, therefore, need to lay down a regulation the travel behaviour filtered out for the purpose of travelling frequently;
Described step 4 method that stage origin and destination determine of going on a journey is as follows,
Use the trip stage of track traffic or public bicycles mode, can according to the site number recorded in its brushing card data, in addition the Back ground Information of track traffic and public bicycles website, both couplings can obtain its complete enter the station site name and departures site name; And the site information of getting on or off the bus of routine bus system brushing card data record is imperfect, the origin and destination in the trip stage of routine bus system mode be obtained, need through the coupling of following three steps:
(1) public transport based on public transport arrival time is got on the bus or get-off stop coupling;
The brushing card data of one ticket public transport have recorded the passenger loading time, the brushing card data of pricing for segment public transport have recorded the time getting off of passenger, both mate with the arrival time table of passenger place public transit vehicle, can obtain the get-off stop title of get on the bus site name and the pricing for segment bus passenger of a ticket bus passenger;
But, brushing card data record be time of IC card system, and public transit vehicle arrival time record is time of public transport gps system, and both exist certain deviation; And the impact of the factors such as process duration of swiping the card when considering that passenger getting off car can be swiped the card in advance, a large amount of passenger's queuing is got on the bus is long, needs to arrange when website mates rational threshold value, to ensure success ratio and the accuracy rate of coupling; On the basis of the conditions such as the average stop spacing considering a ticket public transport and pricing for segment public transport respectively, determine following threshold value: a ticket public transport 2.8min, pricing for segment public transport 3.2min; Namely when the pick-up time of a ticket bus passenger and the difference of public transit vehicle arrival time are less than 2.8min, then by public transit vehicle to website coupling be the website of getting on the bus of passenger; When the time getting off of pricing for segment bus passenger and the difference of public transit vehicle arrival time are less than 3.2min, then the website coupling arrived by public transit vehicle is the get-off stop of passenger;
(2) public transport based on public traffic station spatial relationship is got on the bus or get-off stop coupling;
For the get-off stop of a ticket public transport and the website of getting on the bus of pricing for segment public transport, a part can go to infer by the transfer process of trip on the basis of public traffic station spatial relationship table; Concrete deduction process is as follows:
1) get-off stop of a ticket public transport is determined
For two adjacent trip stages of same Trip chain, if its transfer type belongs to: ticket Public Transport Transfer one ticket public transport (B1-B1), a ticket Public Transport Transfer track traffic (B1-R) or a ticket Public Transport Transfer public bicycles (B1-Z), these three kinds of situations all there is known (enter the station or the borrow car) website of getting on the bus after passenger changes to behavior, and the get-off stop of the ticket public transport taken before changing to behavior is unknown; At this, utilize the public traffic station spatial relationship table set up, website centered by the website of getting on the bus after the behavior of changing to, other routine bus system websites within search center website attractived region; Again from these candidate bus stations, numbering of circuit belonging to it, the public bus network that screening is taken before changing to behavior with passenger numbers identical website, and this website is passenger and takes the corresponding get-off stop of a ticket public transport;
2) website of getting on the bus of pricing for segment public transport is determined
For two adjacent trip stages of same Trip chain, if its transfer type belongs to: pricing for segment Public Transport Transfer pricing for segment public transport (B2-B2), orbit traffic transfer pricing for segment public transport (R-B2) or public bicycles transfer pricing for segment public transport (Z-B2), these three kinds of situations all there is known the get-off stop before passenger changes to behavior, and the website the unknown of getting on the bus of the pricing for segment public transport taken after changing to behavior; Equally, the public traffic station spatial relationship table set up is utilized, website centered by the get-off stop before the behavior of changing to, other routine bus system websites within search center website attractived region; Again from these candidate bus stations, numbering of circuit belonging to it, the public bus network that screening is taken after changing to behavior with passenger numbers identical website, and this website is passenger and takes pricing for segment public transport and to get on the bus accordingly website;
(3) public transport based on travel pattern rule is got on the bus or get-off stop coupling;
According to the symmetry of commuter behavior, in traveler one day first time commuter starting point should be identical with the terminal of commuter last in a day, and the terminal of commuter should be identical with the starting point of last commuter for the first time; Accordingly, propose a ticket public transport get-off stop of some types and pricing for segment and to get on the bus the determination methods of website, specific as follows:
1) get-off stop of a ticket public transport is determined
If in traveler one day first time trip chaining last trip stage takes is a ticket public transport (B1), then using the start site of this traveler last trip chaining on the same day as central site, routine bus system website in search center website attractived region, filter out wherein belong to traveler take advantage of website on public bus network, it can be used as the get-off stop of traveler first time trip chaining; Profit uses the same method, and in traveler one day, the get-off stop of a ticket public transport taken also can be determined the last trip stage of last trip chaining;
2) website of getting on the bus of pricing for segment public transport is determined
If in traveler one day first time trip chaining first trip stage take is pricing for segment public transport (B2), then using the end website of this traveler last trip chaining on the same day as central site, routine bus system website in search center website attractived region, filter out wherein belong to traveler take advantage of website on public bus network, it can be used as the website of getting on the bus of traveler first time trip chaining; Profit uses the same method, and in traveler one day, the website of getting on the bus of pricing for segment public transport taken also can be determined first trip stage of last trip chaining;
The method of described step 5 trip characteristics information matches is as follows:
On the basis of the trip stage origin and destination information that above step obtains, the data such as stroke distances between combined ground public transport arrival time table and any website of track traffic, complete each journey time in trip stage, the calculating of stroke distances, and then obtain the public transport commuter feature of resident;
(1) routine bus system trip is got on or off the bus time complexity curve
In previous step, the pick-up time of one ticket public transport (B1) and the time getting off of pricing for segment public transport (B2), use the time of IC card system, and routine bus system other time be gps system time in routine bus system arrival time table; Because the time of gps system is through overcorrect, accuracy is higher, standard simultaneously in order to calculate journey time is unified, revises with the time getting off (IC card system time) of the time in routine bus system arrival time table (gps system time) to the pick-up time of a ticket public transport (B1) and pricing for segment public transport (B2);
(2) journey time and stroke distances coupling
The journey time in each trip stage is passenger getting off car (set off or the return the car) time and the mistiming of (enter the station or borrow car) time of getting on the bus; And routine bus system, track traffic and public bicycles three kinds of modes are gone on a journey, the stroke distances in stage, obtains respectively by mating with stroke distances table and public bicycles website base data table between routine bus system line tower foundation tables of data, any website of track traffic.
2. the transit trip feature extracting method based on multi-mode public transport Data Matching according to claim 1, it is characterized in that: comparatively strong and there is the features such as relatively more fixing occurrence frequency and time of origin according to resident's commuter Behavior law, the basis of mass data analysis propose commuter behavior decision rule:
(1) extract five workaday brushing card datas in a week and divide into groups by user's card number;
(2) if same user (same card number) is in five working days of one week, have at least and within three days, maintain identical trip rule (referring to identical Trip chain order and Trip chain structure), then think that this user is commuter user, set up commuter user Sample Storehouse;
(3) commuting subscriber thinks commuter in the trip that the peak period of every workday occurs;
(4) commuter user Sample Storehouse monthly upgrades once.
3. the transit trip feature extracting method based on multi-mode public transport Data Matching according to claim 1, it is characterized in that: the get on or off the bus modification method of time complexity curve of routine bus system trip is, the get-off stop information of get on the bus website and the pricing for segment public transport (B2) of the ticket public transport (B1) utilizing trip stage match to obtain, by the fields match such as circuit number, car number, arrive the charge time of the time replacement passenger of respective site with vehicle in routine bus system arrival time table.
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