CN102595323B - Method for obtaining resident travel characteristic parameter based on mobile phone positioning data - Google Patents
Method for obtaining resident travel characteristic parameter based on mobile phone positioning data Download PDFInfo
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Abstract
The invention discloses a method for obtaining a resident travel characteristic parameter based on mobile phone positioning data. The method comprises the following steps of: (1) collecting mobile phone positioning data; (2) filtering the mobile phone positioning data, matching the mobile phone positioning data to traffic zones, and obtaining the matched mobile phone positioning data; (3) using users as units, ordering the matched mobile phone positioning data in one day by time, merging the continuous data in the same one traffic zone into one piece, and obtaining mobile phone positioning pretreatment data; (4) according to the number of emerged pieces and influence duration, judging residing points, restoring a travel path between two residing points, and obtaining the travel distance and the travel speed, and then obtaining a travel log table of all users; (5) on the basis of the matched mobile phone positioning data, statistically obtaining a place of residence and workplace result table; and (6) and conjointly analyzing the travel log table and the place of residence and workplace result table, and obtaining resident travel characteristic parameters. The method has the characteristics of low cost, large sample quantity, high precision and high time validity.
Description
Technical field
The present invention relates to traffic information collection and processing technology field, specifically a kind of acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data.
Background technology
Resident trip survey, refer in survey area, extract a certain proportion of citizen and carry out trip situation complete investigation in a day, so as to grasp urban transportation trip total amount, the Resident Trip Characteristics such as consumption, trip distance while mainly there is attraction source, trip purpose, mode structure, spatial and temporal distributions, trip.
Resident trip survey is an important foundation sex work of city integrated traffic programme, it is the Main Means of grasping urban transportation feature and rule, the science that can be is formulated Transportation Develop ment Strategy, policy, technical regulation important evidence is provided, analysis city total arrangement, traffic Evolution are played a key effect, socio-economic development research is with a wide range of applications.
Traditional resident trip survey implementation step generally comprises, first set up specialized agency unified responsible, and the data before investigating is prepared (as population distribution, administrative division, soil utilization etc.), then carry out survey plan design (as drafting survey area, traffic zone division, sampling, Table Design etc.), being to carry out investigator's training afterwards, is finally implement in full (as visit to the parents of schoolchildren or young workers, phone inquiry, postcard, worker's inquiry and the monthly ticket survey etc.) of manual research.Each step of resident trip survey is very crucial, if careless and inadvertent or inconsiderate, will directly affect the final result of investigation.In general, the shortcoming of traditional resident trip survey method mainly comprises:
(1) need to expend a large amount of human and material resources, carry out the cycle long (implementing from preparing to).
(2) huge owing to expending, thereby investigation interval time large (being generally more than 5 years), Data Update is not prompt enough.
(3) precision of achievement is subject to multi-factor restrict, comprising sample size (sample rate is generally in urban population 5%), sample bias, investigator's sense of responsibility, sample of users cooperate degree, logging data and check data accuracy etc., the result precision often obtaining is lower.
Along with the development of global positioning system (GPS) technology, traffic in recent years researcher is applied to traffic trip investigation by GPS equipment, and precise position information and the temporal information of utilizing GPS equipment to provide, carry out trip characteristics analysis to survey group.But utilizing GPS equipment to carry out traffic study still has many inferior positions:
(1) need to additionally purchase GPS equipment.
(2) under indoor, bridge, cannot image data under the environment such as subway.
(3) sample size is less, cannot carry out on a large scale.
In recent years, mobile phone popularity rate improves day by day, according to national the Ministry of Industry and Information Technology statistics, by 2011 the end of the year China's mobile phone popularity rate reached 73.6%, thereby for utilizing mobile phone locator data to carry out traffic trip analysis, provide the foundation.
The Chinese invention patent that the existing technology of utilizing mobile phone locator data Extraction parts trip characteristics parameter is 200910092031.3 as application number, it obtains trip origin and destination, and can not be from the global feature parameter of comprehensive embodiment resident trip survey, its method needs to use " event type " information, and obliterated data happens occasionally in practical communication process, have a strong impact on analysis result quality, its method is very limited in actual applications.To also have application number be 200910048300.6 Chinese invention patent, it is paid close attention to and detects traffic behavior, i.e. and Real-time Road traffic speed is applied to the field of traffic-information service.
In view of problem and the defect of above-mentioned existing technology existence, the inventor is actively studied and is innovated, inventing a kind of low cost, sample size is large, precision is high, the acquisition methods of ageing strong, the more objective Resident Trip Characteristics parameter based on mobile phone locator data of data result.
Summary of the invention
In order to solve the above-mentioned problems in the prior art, the invention provides a kind of acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data.The inventive method has low cost, sample size is large, precision is high, ageing strong feature.
In order to solve the problems of the technologies described above, the present invention has adopted following technical scheme:
The acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data, comprises the steps:
(1) mobile phone locator data is collected;
(2) data preliminary treatment: mobile phone locator data is filtered, delete the failed data in location, according to the longitude of mobile phone locator data and latitude, mobile phone locator data is matched in corresponding traffic zone, set up the membership of each mobile phone locator data and traffic zone, obtain mating rear mobile phone locator data;
(3) based on mobile phone locator data after coupling, take user as unit, mobile phone locator data after the coupling of a day is sorted according to timestamp field is ascending;
After the 1st article of coupling, mobile phone locator data starts to process, and mobile phone locator data after continuous some the couplings that are positioned at same traffic zone is merged into data, obtains mobile phone location preprocessed data, until mobile phone locator data after 1 coupling of most end; Wherein, in the preprocessed data of mobile phone location respectively after the coupling of record and merging mobile phone locator data corresponding enter entering the moment, leaving the number of mobile phone locator data after the coupling of departure time, mean longitude, mean latitude and merging of this traffic zone of this traffic zone, that also records respectively each traffic zone frontly affects the moment and affects the moment afterwards, and this traffic zone affect duration; Wherein,
Mean longitude and average minute of latitude are not got the longitude of mobile phone locator data and the mean value of latitude after these some couplings;
Frontly affect the middle moment that enters moment and a upper mobile phone and locate the preprocessed data departure time that the moment gets this mobile phone location preprocessed data; Article 1, the front moment assignment that affects of traffic zone, preprocessed data place, mobile phone location is the moment that enters at first this traffic zone;
The rear middle moment that enters the moment that affects departure time that the moment gets this mobile phone location preprocessed data and next mobile phone and locate preprocessed data; The rear moment assignment that affects of traffic zone, preprocessed data place, 1 mobile phone location of most end is finally to leave the moment of this traffic zone;
Affect duration and get rear moment and the front difference that affects the moment of affecting;
Process as stated above mobile phone locator data after all users' coupling, obtain mobile phone location preprocessed data table;
(4) Trip chain identification
Based on mobile phone location preprocessed data table, take user as unit, by the mobile phone location preprocessed data of a day, according to entering, moment field is ascending to sort;
From the 1st article of mobile phone location of this user, preprocessed data starts to process, if the 1st article of mobile phone location preprocessed data enter moment threshold value in moment >=morning, using the 1st article of traffic zone that data are corresponding as a dwell point; Continue to process downwards, if the number of mobile phone locator data after the coupling merging >=resident records number threshold value and affects duration >=resident duration threshold value, using traffic zone corresponding these data as a dwell point;
In chronological order, a upper dwell point to next dwell point, is considered as once going on a journey, start of record traffic zone, settled some traffic zone and the middle relevant information of consumption during through point and trip, wherein,
A upper dwell point is starting point traffic zone, and next dwell point is settled some traffic zone;
What during trip, consumption was got settled some traffic zone enters the departure time that the moment deducts starting point traffic zone;
Based on existing road network, calculate continuously the starting point traffic zone through once trip, each through the shortest path between point and settled some traffic zone, wherein geographical position is determined with mean longitude and mean latitude respectively in He Qidian traffic zone in starting point traffic zone, the section endpoint number information of the continuous process based on shortest path, statistics obtains trip distance;
Calculate line speed, during trip speed=trip distance/trip, consume;
Process as stated above all users' mobile phone location preprocessed data, obtain all users' trip record sheet;
(5) residence and place of working are differentiated:
Based on mobile phone locator data table after coupling, extract certain user data of continuous a week, statistics judges between residence the number of times that inherent each traffic zone of period occurs; The residence that the traffic zone that this occurrence number is maximum is this user;
Based on mobile phone locator data table after coupling, extract the data of the continuous the inside of a week of certain user, statistics judges between place of working the number of times that inherent each traffic zone of period occurs; The place of working that the traffic zone that this occurrence number is maximum is this user;
Obtain residence and place of working result table;
(6) trip characteristics parameter obtains
To go on a journey record sheet and residence and place of working result table Conjoint Analysis, obtain user's trip characteristics parameter.
Further, record residence and differentiate ratio, be i.e. traffic zone, residence occurrence number and the ratio that judges total degree in the period.Ratio is differentiated on writing task ground, i.e. traffic zone, place of working occurrence number and the ratio that judges total degree in the moment.Residence differentiates ratio and ratio is differentiated in place of working, as characterizing the index of differentiating credible result degree.
Compared with prior art, beneficial effect of the present invention is:
The Data Source of the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data of the present invention is based on mobile phone locator data, consumption, trip distance, travel route choice etc. when the Resident Trip Characteristics parameter of obtaining can comprise urban transportation trip total amount, spatial and temporal distributions, trip.The inventive method has low cost, sample size is large, precision is high, the ageing advantage such as strong.Face urbanization process fast, need to grasp in real time Resident Trip Characteristics, to meet the demand of Urban Traffic Planning.The inventive method, for resident trip survey provides a kind of brand-new technological means, makes full use of the large sample mobile phone locator data of magnanimity, by setting up, continues observation mechanism, constantly follows the tracks of the differentiation of resident trip rule.
The resident diagnostics acquisition methods based on mobile phone locator data that the present invention proposes, refer to based on mobile phone locator data (mobile communication system inside produces and records), in conjunction with fundamental geographical information of communication, carry out the extraction of Resident Trip Characteristics, thereby provide a kind of new technological means for resident trip survey.The method can embody the situation of movement with artificial probe unit, and sample rate is high, can provide " panorama sketch " of user distribution and traffic trip in survey area.
The resident diagnostics parameter acquiring method based on mobile phone locator data that the present invention proposes, based on city mobile phone locator data and fundamental geographical information of communication, can process while obtaining urban transportation trip total amount, spatial and temporal distributions, trip the Resident Trip Characteristics such as consumption, trip distance, travel route choice.
The resident diagnostics parameter acquiring method based on mobile phone locator data that the present invention proposes, has following significant advantage:
(1) do not need extra procuring equipment, make full use of based mobile communication facility, comprehensive survey expense is relatively low.
(2) automation implementation, needs less manpower.
(3) belong to passive data acquisition, and survey area baseband signal all standing, analysis result is more objective, accurate.
(4) sample size is large, substantially can cover in urban survey region everyone.
(5) the Data Update cycle short, support more neatly dynamic traffic planning, Organization And Management, realize the urban service of hommization more.
The inventive method has systematically solved the problem of utilizing mobile phone locator data to carry out Resident Trip Characteristics parameter extraction.The significant advantages such as that the method has is practical, efficiency of algorithm is high, result precision height, can promote the future development that resident trip survey shortened to more objective, lower cost, update cycle.Be suitable for applying of each city, have a extensive future.
Accompanying drawing explanation
Fig. 1 is the flow chart of the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data of the present invention;
Fig. 2 is used the distribution schematic diagram of the inventive method to the original position location of user A;
Fig. 3 is for being used the inventive method to user A Trip chain recognition result schematic diagram.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail, but not as a limitation of the invention.
Mobile phone locator data in the present invention refers to, in mobile communication process, utilizes cellular basestation mode to realize to the obtaining of mobile phone real time position, conventionally with longitude and latitude mode record.Mobile phone position data collecting, often adopts event trigger mechanism, as dials or receive calls, receive and dispatch note, across LAC region, specific duration, forces the modes such as location, and therefore, the time interval often can not guarantee very standard.Fig. 1 is the flow chart of the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data of the present invention.As shown in Figure 1, the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data, comprises the steps:
(1) mobile phone locator data is collected.
Data field generally includes mobile phone pseudo-code, timestamp, longitude, latitude, state etc., and wherein, mode field is that 1 expression is located successfully, and mode field is that 0 expression is located unsuccessfully.In the present invention, think, a corresponding user of mobile phone, determines according to mobile phone pseudo-code whether mobile phone locator data belongs to same user.Following table 1 is the part mobile phone locator data of user A.
Table 1
| Mobile phone pseudo-code | Timestamp | Longitude | Latitude | State |
| A | 13:35:21 | 116.5322 | 39.77763 | 1 |
| A | 13:39:49 | 116.5322 | 39.77769 | 1 |
| A | 13:45:26 | 116.5322 | 39.77762 | 1 |
| A | 13:50:27 | 116.5322 | 39.77760 | 1 |
| A | 13:54:46 | 116.5271 | 39.77463 | 1 |
| A | 14:00:15 | 116.5309 | 39.77815 | 1 |
| A | 14:04:46 | 116.5270 | 39.77463 | 1 |
| A | 14:10:25 | 116.5288 | 39.77422 | 1 |
| A | 14:14:46 | 116.5271 | 39.77467 | 1 |
| A | 14:19:43 | 0 | 0 | 0 |
| A | 14:25:36 | 116.5288 | 39.77426 | 1 |
| A | 14:30:22 | 116.5309 | 39.77808 | 1 |
| A | 14:35:13 | 116.5288 | 39.77426 | 1 |
| A | 14:40:33 | 116.5288 | 39.77427 | 1 |
| A | 14:45:13 | 116.5288 | 39.77426 | 1 |
| A | 14:49:50 | 116.5288 | 39.77424 | 1 |
| A | 14:54:46 | 116.5288 | 39.77426 | 1 |
| A | 14:59:49 | 116.5270 | 39.77457 | 1 |
| A | 15:05:19 | 116.5288 | 39.77426 | 1 |
| A | 15:09:43 | 0 | 0 | 0 |
| A | 15:15:27 | 116.5254 | 39.79493 | 1 |
| A | 15:19:46 | 116.5254 | 39.79491 | 1 |
(2) traffic zone data, road net data arrange.
The division of traffic zone, should utilize the feature of character and programming and distribution to determine according to land scale, the soil in planning region, generally using administrative subregion, artificial works and natural boundary as border, traffic zone.
Road net data, is the graduation road network with topological relation, and conventionally with GIS form, category of roads is divided into through street, trunk roads, secondary distributor road, branch road.Traffic zone data and road net data can obtain from resident trip survey unit conventionally.
(3) data preliminary treatment.
(3.1) data filtering.Record (mode field is 0) failed location is deleted.
(3.2) traffic zone coupling.According to the longitude of mobile phone locator data and the definite geographical position of latitude and the inclusion relation of traffic zone, set up the membership of each mobile phone locator data and traffic zone.Obtain mobile phone locator data table after coupling as shown in table 2 below.
Table 2
| Mobile phone pseudo-code | Timestamp | Longitude | Latitude | State | Traffic zone |
| A | 13:35:21 | 116.5322 | 39.77763 | 1 | 219823 |
| A | 13:39:49 | 116.5322 | 39.77769 | 1 | 219823 |
| A | 13:45:26 | 116.5322 | 39.77762 | 1 | 219823 |
| A | 13:50:27 | 116.5322 | 39.77760 | 1 | 219823 |
| A | 13:54:46 | 116.5271 | 39.77463 | 1 | 240625 |
| A | 14:00:15 | 116.5309 | 39.77815 | 1 | 240625 |
| A | 14:04:46 | 116.5270 | 39.77463 | 1 | 240625 |
| A | 14:10:25 | 116.5288 | 39.77422 | 1 | 240625 |
| A | 14:14:46 | 116.5271 | 39.77467 | 1 | 240625 |
| A | 14:25:36 | 116.5288 | 39.77426 | 1 | 240625 |
| A | 14:30:22 | 116.5309 | 39.77808 | 1 | 240625 |
| A | 14:35:13 | 116.5288 | 39.77426 | 1 | 240625 |
| A | 14:40:33 | 116.5288 | 39.77427 | 1 | 240625 |
| A | 14:45:13 | 116.5288 | 39.77426 | 1 | 240625 |
| A | 14:49:50 | 116.5288 | 39.77424 | 1 | 240625 |
| A | 14:54:46 | 116.5288 | 39.77426 | 1 | 240625 |
| A | 14:59:49 | 116.5270 | 39.77457 | 1 | 240625 |
| A | 15:05:19 | 116.5288 | 39.77426 | 1 | 240625 |
| A | 15:15:27 | 116.5254 | 39.79493 | 1 | 240621 |
| A | 15:19:46 | 116.5254 | 39.79491 | 1 | 240621 |
Fig. 2 is used the distribution schematic diagram of the inventive method to the original position location of user A.
(3.3) based on mobile phone locator data table after coupling, take user as unit, mobile phone locator data after the coupling of a day is sorted according to timestamp field is ascending.
(3.4) from the 1st article of data beginning reason, mobile phone locator data after continuous some the couplings that are positioned at same traffic zone is merged into data, obtain mobile phone location preprocessed data, until mobile phone locator data after 1 coupling of most end; The number (num) of mobile phone locator data after the coupling of enter the moment (start_time), the departure time (end_time) of leaving this traffic zone that enters this traffic zone, mean longitude (lon), mean latitude (lat) and merging that wherein, in the preprocessed data of mobile phone location, record is corresponding with mobile phone locator data after the coupling merging respectively; Wherein mean longitude (lon) and mean latitude (lat) are got respectively the longitude of mobile phone locator data and the mean value of latitude after these some couplings,
Until 1 data of most end.
(3.5) that in the preprocessed data of mobile phone location, also records respectively this traffic zone frontly affects the moment (in_time) and affects the moment (out_time) afterwards, and this traffic zone affect duration (interval).
Frontly affect the moment (in_time) and get middle moment of enter the moment (start_time) and departure time (end_time) of upper mobile phone location preprocessed data of this mobile phone location preprocessed data; Rear affect departure time (end_time) that the moment (out_time) gets this mobile phone location preprocessed data and next mobile phone location preprocessed data enter the moment in middle moment of (start_time).For the processing of special circumstances:
Article 1, to affect moment (in_time) assignment be the moment that enters at first this traffic zone for mobile phone location preprocessed data front;
It is finally to leave the moment of this traffic zone that 1 mobile phone of most end location preprocessed data rear affects moment (out_time) assignment.
Affect duration (interval) and get rear moment (out_time) and the front difference that affects moment (in_time) of affecting.
(3.6) process as stated above all users' data, obtain mobile phone location preprocessed data table as shown in table 3 below.
(4) Trip chain identification.
(4.1), based on mobile phone location preprocessed data table, take user as unit, by the mobile phone location preprocessed data of a day, according to entering, moment field is ascending to sort.
(4.2) judge dwell point.The 1st article of mobile phone location preprocessed data from this user starts to process, if the 1st article mobile phone location preprocessed data enter moment >=threshold value (being set to 6:00) in the moment in the morning, using the 1st article of traffic zone that data are corresponding as a dwell point; Continue to process downwards, if number (num) >=of mobile phone locator data is resident after the coupling of the merging of certain mobile phone location preprocessed data, records number threshold value (being set to 2) and affect the resident duration threshold value of duration (interval) >=(being set to 2700 seconds), using traffic zone corresponding these data as a dwell point.
With upper threshold value, can rationally arrange based on data actual conditions.
(4.3) trip identification.In chronological order, a upper dwell point (starting point) is arrived to next dwell point (settled point), be considered as once going on a journey, recording-related information (comprising the traffic zone numbering of starting point and settled point, front moment, rear moment, mean longitude, the mean latitude etc. of affecting of affecting), and middle process point.
What during trip, consumption (time_trip) was got settled some traffic zone enters the departure time that the moment deducts starting point traffic zone.
(4.4) path restore.Based on existing road network, calculate continuously the starting point traffic zone through once trip, each through the shortest path between point and settled some traffic zone, wherein geographical position is determined with mean longitude and mean latitude respectively in He Qidian traffic zone in starting point traffic zone, the section endpoint number information of the continuous process based on shortest path, statistics obtains trip distance (length_trip).
(4.5) calculate line speed, consumption (time_trip) during trip speed (speed_trip)=trip distance (length_trip)/trip.
(4.6) process as stated above all users' data, obtain trip record sheet as shown in table 4 below.
Fig. 3 is used the inventive method to the user A Trip chain recognition result schematic diagram that three trips form between residence, place of working and dwell point.
(5) residence and place of working are differentiated.
(5.1) based on mobile phone locator data table after the coupling of traffic zone, extract certain user data of continuous a week, statistics judges between residence the number of times that inherent each traffic zone of period (being set to 23:00 to 6:00 next day) occurs.Record the traffic zone numbering that occurrence number is maximum, and the ratio (ratio_home) of occurrence number and interior total degree of judgement period.This traffic zone is identified as this user's residence, and this ratio is as characterizing the index of differentiating credible result degree.
(5.2) based on mobile phone locator data table after the coupling of traffic zone, extract the data of the continuous the inside of a week of certain user (being generally Mon-Fri), statistics judges between place of working the number of times that inherent each traffic zone of period (being set to 9:00 to 17:00) occurs.Record the traffic zone numbering that occurrence number is maximum, and the ratio of occurrence number and interior total degree of judgement period.（ratio_work）。This traffic zone is identified as this user's place of working, and this ratio is as characterizing the index of differentiating credible result degree.
(5.3) process as stated above all users' data.Obtain residence as shown in table 5 below and place of working result table.
Table 5
(6) user's trip characteristics parameter extraction is analyzed with comprehensive.
(6.1) in conjunction with go on a journey record sheet and residence and place of working result table, carry out Conjoint Analysis, obtain different classes of user's detailed trip characteristics parameter.
Trip characteristics parameter mainly comprises beginning-of-line, consumption, trip moment (comprising the moment of setting out, moment in transit and due in) etc. while going on a journey settled point, trip distance, trip.
Collect a certain amount of cellphone subscriber, by with the customer attribute information Conjoint Analysis such as residence, place of working, can obtain different attribute user's trip characteristics, the user that to obtain such as place of working be a certain administrative area, its workaday trip rate (average daily trip number of times), average trip distance, consumption, Departure time distribution etc. while on average going on a journey, for another example residence is the user in city, down town, its workaday trip rate (average daily trip number of times), average trip distance, on average go on a journey duration, Departure time distribution etc.
In actual applications, the trip characteristics parameter of meeting based on above-mentioned all types of user, sum in conjunction with such user in territory, the whole city expands sample, thereby obtain territory, the whole city in total trip requirements of analyzing in the period, as a sunrise places number, this is most important for carrying out the city integrated traffic programme matching with transport need.Trip characteristics parameter plays an important role in urban transportation operation and management, such as, that has grasped user goes out that beginning-of-line-settled point (Origin-Destination) distributes, Departure time distribution, just can reasonably configure freight volume and the departure intervals such as public transport, subway, thereby make Urban Transportation resource obtain optimum utilization.
If further mobile phone locator data is combined with land use data, also will obtain trip mode (as car, bus, subway etc.) and trip purpose (as gone to work, go to school, do shopping, go home etc.) etc.As:
(6.2), in conjunction with trip record sheet, take traffic zone, street, administrative region be object, carry out population and live and employment distribution, trip characteristics analysis etc.Or,
(6.3) summarized results.In conjunction with other statisticses, comprehensively analyze.
Beijing's collection volunteer 1000 people, gather its mobile phone locator data and test, contrasted the inventive method and additive method, comprise the aspects such as result precision and arithmetic speed.Experimental result shows, the resident diagnostics parameter acquiring method based on mobile phone locator data that the present invention proposes, and the rate of accuracy reached to 99% of residence and place of working identification, trip identification Average Accuracy reaches more than 95%, and all more existing similar approach is more excellent; Method provided by the invention, the existing algorithm of arithmetic speed improves more than 30%, has reached the level of practical application.In addition, based on method provided by the invention, more horn of plenty of the data class that can obtain, supports the multiple integrated application of resident trip survey.
In addition, utilizing the result of mobile phone locator data, can also be traffic dynamic model, and Dynamic OD data source is provided, and describes better traffic circulation situation (as the formation of congested nodes and dissipation), instructs solving practical problems, has wide market prospects.
Above embodiment is only exemplary embodiment of the present invention, is not used in restriction the present invention, and protection scope of the present invention is defined by the claims.Those skilled in the art can, in essence of the present invention and protection range, make various modifications or be equal to replacement the present invention, this modification or be equal to replacement and also should be considered as dropping in protection scope of the present invention.
Claims (2)
1. the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data, is characterized in that, comprises the steps:
(1) mobile phone locator data is collected;
(2) data preliminary treatment: mobile phone locator data is filtered, delete the failed data in location, according to the longitude of mobile phone locator data and latitude, mobile phone locator data is matched in corresponding traffic zone, set up the membership of each mobile phone locator data and traffic zone, obtain mating rear mobile phone locator data;
(3) based on mobile phone locator data after coupling, take user as unit, mobile phone locator data after the coupling of a day is sorted according to timestamp field is ascending;
After the 1st article of coupling, mobile phone locator data starts to process, and mobile phone locator data after continuous some the couplings that are positioned at same traffic zone is merged into data, obtains mobile phone location preprocessed data, until mobile phone locator data after 1 coupling of most end; Wherein, in the preprocessed data of mobile phone location respectively after the coupling of record and merging mobile phone locator data corresponding enter entering the moment, leaving the number of mobile phone locator data after the coupling of departure time, mean longitude, mean latitude and merging of this traffic zone of this traffic zone, that also records respectively each traffic zone frontly affects the moment and affects the moment afterwards, and this traffic zone affect duration; Wherein,
Mean longitude and average minute of latitude are not got the longitude of mobile phone locator data and the mean value of latitude after these some couplings;
Frontly affect the middle moment that enters moment and a upper mobile phone and locate the preprocessed data departure time that the moment gets this mobile phone location preprocessed data; Article 1, the front moment assignment that affects of traffic zone, preprocessed data place, mobile phone location is the moment that enters at first this traffic zone;
The rear middle moment that enters the moment that affects departure time that the moment gets this mobile phone location preprocessed data and next mobile phone and locate preprocessed data; The rear moment assignment that affects of traffic zone, preprocessed data place, 1 mobile phone location of most end is finally to leave the moment of this traffic zone;
Affect duration and get rear moment and the front difference that affects the moment of affecting;
Process as stated above mobile phone locator data after all users' coupling, obtain mobile phone location preprocessed data table;
(4) Trip chain identification
Based on mobile phone location preprocessed data table, take user as unit, by the mobile phone location preprocessed data of a day, according to entering, moment field is ascending to sort;
From the 1st article of mobile phone location of this user, preprocessed data starts to process, if the 1st article of mobile phone location preprocessed data enter moment threshold value in moment >=morning, using the 1st article of traffic zone that data are corresponding as a dwell point; Continue to process downwards, if the number of mobile phone locator data after the coupling merging >=resident records number threshold value and affects duration >=resident duration threshold value, using traffic zone corresponding these data as a dwell point;
In chronological order, a upper dwell point to next dwell point, is considered as once going on a journey, start of record traffic zone, settled some traffic zone and the middle relevant information of consumption during through point and trip, wherein,
A upper dwell point is starting point traffic zone, and next dwell point is settled some traffic zone;
What during trip, consumption was got settled some traffic zone enters the departure time that the moment deducts starting point traffic zone;
Based on existing road network, calculate continuously the starting point traffic zone through once trip, each through the shortest path between point and settled some traffic zone, wherein geographical position is determined with mean longitude and mean latitude respectively in He Qidian traffic zone in starting point traffic zone, the section endpoint number information of the continuous process based on shortest path, statistics obtains trip distance;
Calculate line speed, during trip speed=trip distance/trip, consume;
Process as stated above all users' mobile phone location preprocessed data, obtain all users' trip record sheet;
(5) residence and place of working are differentiated:
Based on mobile phone locator data table after coupling, extract certain user data of continuous a week, statistics judges between residence the number of times that inherent each traffic zone of period occurs; The residence that the traffic zone that this occurrence number is maximum is this user;
Based on mobile phone locator data table after coupling, extract the data of the continuous the inside of a week of certain user, statistics judges between place of working the number of times that inherent each traffic zone of period occurs; The place of working that the traffic zone that this occurrence number is maximum is this user;
Obtain residence and place of working result table;
(6) trip characteristics parameter obtains
To go on a journey record sheet and residence and place of working result table Conjoint Analysis, obtain user's trip characteristics parameter.
2. the acquisition methods of the Resident Trip Characteristics parameter based on mobile phone locator data according to claim 1, it is characterized in that, record respectively as the occurrence number of the traffic zone in residence and place of working and account for the ratio of total degree separately, using this ratio as characterizing the index of differentiating credible result degree.
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