CN110473132A - Balance evaluation method is lived in a kind of region duty based on mobile data - Google Patents

Balance evaluation method is lived in a kind of region duty based on mobile data Download PDF

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CN110473132A
CN110473132A CN201910793682.9A CN201910793682A CN110473132A CN 110473132 A CN110473132 A CN 110473132A CN 201910793682 A CN201910793682 A CN 201910793682A CN 110473132 A CN110473132 A CN 110473132A
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mobile phone
area
commuting
phone user
distance
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师思
陈明威
李晗
许敏
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SHANGHAI YUNDI INFORMATION TECHNOLOGY Co Ltd
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Abstract

The invention discloses a kind of, and balance evaluation method is lived in the region duty based on mobile data, the evaluation method is based on the mobile data in some city 1 month, identify the residence and place of working of mobile phone user, and then commuter data relevant to a certain region in the city are obtained, and then obtain time and the distance of each commuter；If the one way commuting time in the region 95% meets corresponding threshold value standard, then it is assumed that the region duty lives to balance；If the region is not up to duty and lives tension metrics, further analysis causes duty to live unbalanced reason: living to compare including the duty in Commuting Distance, region, occupant obtains employment self-sustaining ratio, the self-sustaining ratio of worker's inhabitation.The invention has the advantages that proposing with commuting time is main evaluation index, the integral framework for living in conjunction with other index comprehensive evaluation region duties such as Commuting Distance balance；Meanwhile providing and implementing the index system using mobile data, assess the method flow that equilibrium state is lived in a certain region duty.

Description

Mobile communication data-based regional position and position balance evaluation method
Technical Field
The invention belongs to the technical field of urban planning management, and particularly relates to a mobile communication data-based regional position and occupation balance evaluation method.
Background
Employment and residence are two important constituent elements in urban space structure, with the continuous promotion of economic development and urbanization process, the phenomenon of 'separation of jobs and lives' is increasingly aggravated, and commuting travel becomes the most important constituent part in urban traffic travel. The long-distance commuting trip aggravates the urban traffic jam problem in China, researches the position balance state of the area, and can provide decision basis for improving the urban traffic efficiency and reducing traffic jam and air pollution.
The data source of the traditional occupational balance research is mainly census or sample survey, the accuracy rate of census data is high, but the timeliness is poor, and the acquisition period is long; survey sample data is susceptible to the influence of sample size and sampling distribution unevenness, and the overall characteristics of regional position balance are difficult to reflect. The mobile communication data has the advantages of wide space coverage, large sample size, strong real-time performance and the like, and can reflect the regional position balance characteristics more truly.
Commonly used indexes of regional position balance measure are: most of the existing researches do not provide balance standards, but draw conclusions about relative balance or relative unbalance through longitudinal comparison of different units or transverse comparison among different areas. A set of complete and clear region occupation balance evaluation method with universality has important guiding significance for relieving the region occupation imbalance state.
Disclosure of Invention
The invention aims to provide a regional position balance evaluation method based on mobile communication data according to the defects of the prior art, the evaluation method comprises the steps of firstly utilizing 1 month mobile communication data of a certain city to obtain the commuting time and the commuting distance of commuting travel related to a certain region in the city, then evaluating the commuting time of the region, and if the position balance threshold standard is met, considering the regional position balance; if the position balance standard is not met, the indexes such as commuting distance, regional position ratio, employment self-sufficiency ratio of residents, residence self-sufficiency ratio of residents and the like are further evaluated, and a strategy direction is provided for relieving the unbalanced position of the regional position.
The purpose of the invention is realized by the following technical scheme:
a mobile communication data-based regional occupation balance evaluation method is characterized by comprising the following steps:
step 1: selecting a city X to be analyzed, an area A belonging to the city X and mobile communication data of any operator in the city X, and calculating the commuting time and the commuting distance of each mobile phone user;
step 2: according to the internal commuting one-way time consumption standard of the city X, calculating the ratio of times of commuting trips in the area A reaching the internal commuting one-way time consumption standard, and judging whether the internal commuting one-way time consumption standard is reached;
and step 3: calculating the average commuting distance in the area A, comparing the average commuting distance with the commuting distance standard of the city X, and judging whether the average commuting distance is the reason of imbalance of jobs and dwellings in the area A;
and 4, step 4: calculating the job-to-live ratio in the area A, and judging whether the job-to-live ratio is the cause of the imbalance of the job and the live in the area A;
and 5: and respectively calculating the employment self-sufficiency proportion of the residents and the occupation self-sufficiency proportion of the residents in the area A, and judging whether the occupation self-sufficiency proportion is the reason of imbalance of the residents in the area A.
The step 1 comprises the following steps:
selecting mobile communication data of all mobile phone users of a city X to be analyzed, an area A affiliated to the city X and any operator with the time span of 1 month in the city X, wherein the mobile communication data comprises a mobile phone identification number MSID, a timestamp TIMESTAMP, a position area ID, a base station longitude and a base station latitude; the mobile phone identification number MSID has uniqueness, and the location area ID and the base station ID jointly determine a unique base station;
filtering and screening ping-pong switching data and drift points in the mobile communication data, and then arranging the mobile communication data of each mobile phone user according to a time ascending sequence to obtain a mobile phone user track point time sequence; calculating the STAY TIME of a mobile phone user at each track point, selecting the track points with the STAY TIME longer than 30 minutes in the mobile phone user track point TIME sequence as STAY points, and generating a mobile phone user STAY point TIME sequence, wherein the mobile phone user STAY point TIME sequence comprises a mobile phone identification number MSID, a timestamp TIMESTAMP, a base station longitude, a base station latitude and a STAY TIME STAY _ TIME; two dwell points adjacent in time in the mobile phone user dwell point time sequence form a trip, the two dwell points adjacent to each other of a mobile phone user are matched with records in the mobile phone user track point time sequence through mobile phone identification numbers MSID and timestamp TIMESTAMP fields, a mobile phone user track point with a timestamp TIMESTAMP between the two dwell points is extracted, a mobile phone user trip track sequence is generated, the mobile phone user trip track sequence comprises all fields of the mobile phone user track point time sequence and trip number fields OD _ IND, and the mobile phone identification numbers MSID and the trip number fields OD _ IND uniquely determine the trip of one mobile phone user;
counting the accumulated stay time of each mobile phone user at different stay points at night based on the mobile phone user stay point time sequence, wherein the night is from 20:00 to 08:00 days, and selecting the stay point with the longest accumulated stay time at night to identify the stay point as the residence place of the mobile phone user; counting the accumulated stay time of each mobile phone user at different stay points in the daytime, wherein the daytime is 08:00 to 20:00 per day, and selecting the stay point with the longest accumulated stay time in the daytime and identifying the stay point as the work place of the mobile phone user;
identifying to obtain the residence RX of each mobile phone userp(p =1,2, …, M) and a work WXq(q =1,2, …, N), where M is the number of cell phone users whose residence is within the city X, and N is the number of cell phone users whose workplace is within the city X; screening the mobile phone users RA with the residence places in the area Aj(j =1,2, …, m) and a mobile telephone subscriber WA working in said area ak(k =1,2, …, n), wherein m is the residential siteMobile phone users RA in said area AjN is the number of the mobile phone users WA whose working places are in the area AkThe number of (2); extracting mobile phone user RAjAnd a mobile phone subscriber WAkA mobile phone user commuting travel track sequence of commuting travel between the residence and the workplace in the area A; assuming that the number of commuting trips meeting the commuting trip condition is K, the commuting time of the ith commuting trip is Ti, the commuting distance is Si, and i =1,2, … K; the commute duration refers to the duration spent by the mobile phone user when going out between a work place and a residence; the commuting distance means that the mobile phone user is in one time in the commuting trip, all the mobile phone user track points are arranged according to the time sequence, the shortest distance between two adjacent mobile phone user track points is calculated and accumulated to obtain the commuting distance.
The step 2 comprises the following steps:
the internal commuting one-way time consumption standard of the city X is Cx, and the ratio RT of the times of reaching the internal commuting one-way time consumption standard Cx in the commuting trip in the area A is calculatedA：
Wherein,if the number of times is in proportion to RTAThe position and live balance standard is more than or equal to 95%, and the position and live balance is achieved in the area A, and an evaluation result is output; if the number of times is in proportion to RTAIf the occupation balance standard is less than 95%, the occupation balance is not reached in the area A, and the step 3 is continuously executed.
The step 3 comprises the following steps:
given that the planned population size of the city X is P in units of ten thousand, and the commute distance standard of the city X is that the average trip distance of the commute trip per trip is not greater than Dx in units of km; calculating the regionAverage travel distance of Domain AWherein Si is the distance of the commute trip for the ith single trip;
if MSADx is not more than equal, promptly regional A's average trip distance satisfies the commute distance standard, then the commute distance does not cause regional A plays the unbalanced reason of live, and the regulation and control suggestion is: the traffic supply is improved, the mode structure is improved, and the commuting time is reduced;
if MSAIf the average trip distance of the area A does not meet the commuting distance standard, the reason for causing the unbalanced job and live of the area A is that the commuting distance does not meet the commuting distance standard, the reason for the commuting distance not meeting the commuting distance standard is further analyzed, and the step 4 is continuously executed.
The step 4 comprises the following steps:
calculating the job-to-live ratio RE of the area AA= (employment position number E of area A)AResidential population R of area AA）；
If the job duty ratio REAIf the number is less than 0.8, the cause of the imbalance of the positions of the areas A is that: job to live ratio REAOn the low side, the regulation recommendation is: the supply of houses is increased, and the duty ratio is improved;
if the ratio RE is less than or equal to 0.8AWhen the ratio is less than or equal to 1.2, the ratio REAIf the cause is not the imbalance of the job in the area A, continuing to execute the step 5;
if the job duty ratio REAIf the ratio is more than 1.2, the cause of the imbalance of occupations in the area A is the occupational ratio REAOn the high side, the regulation and control suggestion is: increase the post supply and reduce the duty ratio.
The step 5 comprises the following steps:
step 5.1: calculating the occupancy employment self-sufficiency proportion RSC of the residents in the area AA：
Calculating the occupancy self-sufficiency ratio WSC of the persons in the area AA：
Wherein,；
step 5.2: calculating the self-sufficiency ratio RSC of the residents in the city XX：
Calculating the resident self-sufficiency proportion WSC of the city XX：
Wherein,；
step 5.3: the occupant employment self-sufficiency ratio RSC of the city X is knownXThe tolerance amount of (2) is r, the ratio of the residents living in the house is WSCXThe tolerance amount of (a) is w;
if RSCA＜RSCX-r and WSCA≥WSCX-w, the cause of said imbalance of occupation of area a is the proportion of occupancy self-sufficiency RSC of the occupantsAOn the low side, the regulation recommendation is: improving the employment matching of residents locally;
if RSCA≥RSCX-r and WSCA＜WSCX-w, the proportion of occupancy self-sufficiency WSC of the persons causing the imbalance of the occupation of the area AAOn the low side, the regulation recommendation is: the living matching of the workers in the local is improved;
if RSCA＜RSCX-r and WSCA＜WSCXW is caused byThe imbalance of the occupation of the region A is caused by the employment self-sufficiency ratio RSC of the residentsAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAOn the low side, the regulation recommendation is: the employment matching of the residents in the local is improved, and the resident matching of the residents in the local is improved;
if RSCA≥RSCX-r and WSCA≥WSCX-w, the occupant employment self-sufficiency ratio RSCAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAIs not responsible for the imbalance of the positions of the area A.
The invention has the advantages that: a complete system for comprehensively evaluating the current situation of the regional work and live balance by taking the commuting time as a main evaluation index and combining other indexes such as the commuting distance and the like is provided; meanwhile, a method flow for evaluating the position and the living balance state of a certain area by implementing the index system by utilizing mobile communication data is provided.
Drawings
Fig. 1 is a flowchart illustrating a mobile communication data-based regional occupation balance evaluation method according to the present invention.
Detailed Description
The features of the present invention and other related features are described in further detail below by way of example in conjunction with the following drawings to facilitate understanding by those skilled in the art:
example (b): as shown in fig. 1, the present embodiment specifically relates to an area-occupation balance evaluation method based on mobile communication data, and the evaluation method specifically includes the following steps:
step 1, selecting mobile communication data of all mobile phone users of any operator with city X to be analyzed, area a affiliated to city X, and time span of 1 month in city X, wherein the mobile communication data comprises mobile phone identification number MSID, timestamp TIMESTAMP, and location area ID: LAC, base station ID, CELLID, base station longitude, LON and base station latitude LAT; the mobile communication data format for city X within 1 month is shown in the following table:
MSID TIMESTAMP LAC CELLID LON LAT
… … … … … …
316AD0E97F719B84D5790C45BCED9800 20190425000025 791563 31 120.0459 30.2259
08145B50950C0949FE4BB8E3D6C75C00 20190425000027 795645 11 119.7026 29.8077
3883282FE3F5C39E87A0D9BA7A95F800 20190425000023 795168 11 120.1632 30.1957
68044005AD9B75BA74FBBB89A5A35800 20190425000024 795703 11 120.2746 30.1193
82788E92F1A22042002B582D42EE5C00 20190425000057 55051 55035 120.2221 30.1834
14D30FFFF27F72DC5D2B513FF247A000 20190425000032 791802 11 120.2014 30.2427
9A20989477FC395D5D7118116360C800 20190425000031 836186 21 119.7165 30.2467
04A11B59BEE28D20D385648E0C4C3800 20190425000040 792034 31 120.2843 30.3722
092429908B719C1F5218091C28BE0800 20190425000033 837415 21 120.2034 30.2133
40D1AFE127FAF032E87378D360454400 20190425000033 836523 11 120.2940 30.3703
… … … … … …
the MSID is a mobile phone identification number, and the identification number of the same mobile phone is unique; TIMESTAMP generates a timestamp for the record in the format: year, month, day, hour, minute, second, for example, '20190425000025' indicates that the record generation time is 2019, month 4, day 25, 00 hour, 00 minute 25 second; the LAC and the CELLID jointly determine a location area where the current mobile phone is located; LON and LAT are the space longitude and latitude of the base station in the position area where the mobile phone is located;
the mobile communication data includes spatial position information of base stations where each mobile phone user is located at different moments, each base station forms a signal coverage area around the base station, and when the mobile phone user is located and covered by a plurality of base stations, a phenomenon that signals are switched back and forth between adjacent base stations is caused, which is called ping-pong switching. In addition, abnormal drift points possibly exist in the mobile communication data, which is represented by that a mobile phone user is switched to a base station far away from the current position in a very short time;
after ping-pong handover data and drift points in the original mobile communication data are filtered and screened, arranging the mobile communication data of each mobile phone user according to a time ascending sequence to obtain the mobile phone user track point time sequence results as follows:
MSID TIMESTAMP LON LAT
… … … …
0D75664AF5D7F328E2A106E3EC5ECC00 20190513034235 120.0221 30.2355
0D75664AF5D7F328E2A106E3EC5ECC00 20190513035059 119.9372 30.2520
0D75664AF5D7F328E2A106E3EC5ECC00 20190513035644 119.8830 30.2537
0D75664AF5D7F328E2A106E3EC5ECC00 20190513035846 119.8562 30.2514
0D75664AF5D7F328E2A106E3EC5ECC00 20190513043228 119.7620 30.3827
0D75664AF5D7F328E2A106E3EC5ECC00 20190513080419 119.7721 30.3293
0D75664AF5D7F328E2A106E3EC5ECC00 20190513090056 119.7620 30.3827
0D75664AF5D7F328E2A106E3EC5ECC00 20190513091657 119.7831 30.3064
0D75664AF5D7F328E2A106E3EC5ECC00 20190513102244 119.8173 30.2861
0D75664AF5D7F328E2A106E3EC5ECC00 20190513103603 119.8830 30.2537
… … … …
calculating the stay time of the mobile phone user at each track point, selecting the track points with the stay time of more than 30 minutes in the mobile phone user track point time sequence as the stay points, and generating the mobile phone user stay point time sequence as shown in the following table:
MSID TIMESTAMP LON LAT STAY_TIME
… … … … …
0D75664AF5D7F328E2A106E3EC5ECC00 20190513035846 119.8562 30.2514 2022
0D75664AF5D7F328E2A106E3EC5ECC00 20190513043228 119.7620 30.3827 12711
0D75664AF5D7F328E2A106E3EC5ECC00 20190513080419 119.7721 30.3293 3397
0D75664AF5D7F328E2A106E3EC5ECC00 20190513091657 119.7831 30.3064 3947
… … … … …
wherein, STAY _ TIME represents the STAY TIME, and the unit is second; matching two stop points adjacent to the mobile phone user time with records in the mobile phone user track point time sequence through MSID and TIMESTAMP fields, extracting TIMESTAMP mobile phone user track points between the two stop points, and generating a mobile phone user travel track sequence (for convenient display, the ID field of a base station position area and the ID field of a base station are omitted in a table) as follows:
MSID TIMESTAMP LON LAT OD_IND
… … … … …
0D75664AF5D7F328E2A106E3EC5ECC00 20190513035846 119.8562 30.2514 1
0D75664AF5D7F328E2A106E3EC5ECC00 20190513043228 119.7620 30.3827 1
0D75664AF5D7F328E2A106E3EC5ECC00 20190513043228 119.7620 30.3827 2
0D75664AF5D7F328E2A106E3EC5ECC00 20190513080419 119.7721 30.3293 2
0D75664AF5D7F328E2A106E3EC5ECC00 20190513080419 119.7721 30.3293 3
0D75664AF5D7F328E2A106E3EC5ECC00 20190513090056 119.7620 30.3827 3
0D75664AF5D7F328E2A106E3EC5ECC00 20190513091657 119.7831 30.3064 3
0D75664AF5D7F328E2A106E3EC5ECC00 20190513091657 119.7831 30.3064 4
0D75664AF5D7F328E2A106E3EC5ECC00 20190513102244 119.8173 30.2861 4
0D75664AF5D7F328E2A106E3EC5ECC00 20190513103603 119.8830 30.2537 4
… … … … …
wherein, OD _ IND represents OD trip number, MSID and OD _ IND jointly determine a track sequence of one trip of a mobile phone user;
selecting a track point with the longest accumulated stay time of the mobile phone user at night (20: 00 to 8:00 the next day every day), and identifying the track point as the residence of the mobile phone user;
selecting a track point with the longest accumulated stay time of the mobile phone user in the daytime (8: 00-20: 00 every day), and identifying the track point as the work place of the mobile phone user;
the identification results of the residence and the work place of the mobile phone user are as follows:
MSID HOME_LON HOME_LAT WORK_LON WORK_LAT
… … … … …
40D1AFE127FAF032E87378D360454400 120.2918 30.372 120.2900 30.3731
A4749354CD21117D5C484C6C65B72C00 120.1587 30.3225 120.1611 30.3199
1D02CCC74001B48D44AE055ED8D99000 120.1443 30.3155 120.1538 30.3049
F204B2A3643F65FBE5A0F98B1EAA9400 120.2498 30.3223 120.2512 30.3205
4F4E63810A0EF1FA5BB8829F6C195800 119.9293 30.0549 119.9258 30.0547
7369AD70FA9110B07C091A1477CF7000 120.1814 30.3746 120.1537 30.2634
FAF168322C62A99073749CF4C7D73000 120.0222 30.2355 120.3740 30.2828
4BBB75A55BD94A557E2FC91A3000C000 119.6684 29.8023 119.6737 29.8128
550C865E9FC15C853B548CC15E4EC800 120.0306 30.2923 120.0306 30.2923
F736B16AF09EC6ED97EE50166FEAC400 120.2574 30.4050 120.2683 30.4363
… … … … …
the HOME location system comprises a HOME location system, a WORK location system and a mobile phone user, wherein HOME _ LON and HOME _ LAT represent the spatial longitude and latitude of a place where the mobile phone user resides, and WORK _ LON and WORK _ LAT represent the spatial longitude and latitude of a place where the mobile phone user WORKs;
identifying to obtain the residence RX of each mobile phone userp(p =1,2, …, M) and a work WXq(q =1,2, …, N), where M is the number of cell phone users whose residence is within city X, M = 917982; n is the number of handset users working in city X, N = 912650;
screening mobile phone users RA with residence places in area Aj(j =1,2, …, m) and a handset user WA working in area ak(k =1,2, …, n), where m is the handset user RA having a residence within area ajM = 93186; n is a mobile phone user WA working in the area AkN = 92542;
extracting mobile phone user RAjAnd a mobile phone subscriber WAkFor commuting between residence and workplace in area AA mobile phone user commuting travel track sequence; the commuting travel meeting the commuting travel condition has K times, and K = 372744; taking the ith commuting out behavior example, the sequence of the commuting out trajectory is as follows:
MSID TIMESTAMP LON LAT STAY_TIME OD_IND
F736B16AF09EC6ED97EE50166FEAC400 20190513082754 120.2574 30.4050 2784 1
F736B16AF09EC6ED97EE50166FEAC400 20190513091418 120.2696 30.4065 20 1
F736B16AF09EC6ED97EE50166FEAC400 20190513091438 120.2833 30.4089 231 1
F736B16AF09EC6ED97EE50166FEAC400 20190513091829 120.2886 30.4172 16 1
F736B16AF09EC6ED97EE50166FEAC400 20190513091845 120.2992 30.4193 101 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092026 120.3015 30.4276 69 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092027 120.3006 30.4333 133 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092240 120.2994 30.4472 18 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092258 120.2938 30.4540 321 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092819 120.2976 30.4674 75 1
F736B16AF09EC6ED97EE50166FEAC400 20190513092834 120.2938 30.4540 768 1
F736B16AF09EC6ED97EE50166FEAC400 20190513094122 120.2792 30.4432 26 1
F736B16AF09EC6ED97EE50166FEAC400 20190513094148 120.2683 30.4363 11876 1
respectively calculating the time interval and the distance between the adjacent track points in the commuting trip track sequence to obtain the following results:
MSID TIMESTAMP LON LAT STAY_TIME OD_IND T(S) S(KM)
F736B16AF09EC6ED97EE50166FEAC400 20190513082754 120.2574 30.4050 2784 1
F736B16AF09EC6ED97EE50166FEAC400 20190513091418 120.2696 30.4065 20 1 20 1.3422
F736B16AF09EC6ED97EE50166FEAC400 20190513091438 120.2833 30.4089 231 1 231 1.0548
F736B16AF09EC6ED97EE50166FEAC400 20190513091829 120.2886 30.4172 16 1 16 1.0441
F736B16AF09EC6ED97EE50166FEAC400 20190513091845 120.2992 30.4193 101 1 101 0.9500
F736B16AF09EC6ED97EE50166FEAC400 20190513092026 120.3015 30.4276 69 1 69 0.6404
F736B16AF09EC6ED97EE50166FEAC400 20190513092027 120.3006 30.4333 133 1 133 1.5516
F736B16AF09EC6ED97EE50166FEAC400 20190513092240 120.2994 30.4472 18 1 18 0.9283
F736B16AF09EC6ED97EE50166FEAC400 20190513092258 120.2938 30.4540 321 1 321 1.5356
F736B16AF09EC6ED97EE50166FEAC400 20190513092819 120.2976 30.4674 75 1 75 1.5356
F736B16AF09EC6ED97EE50166FEAC400 20190513092834 120.2938 30.4540 768 1 768 1.8462
F736B16AF09EC6ED97EE50166FEAC400 20190513094122 120.2792 30.4432 26 1 26 1.2978
F736B16AF09EC6ED97EE50166FEAC400 20190513094148 120.2683 30.4363 11876 1
the commute time length Ti =20s +231s +16s +101s +69s +133s +18s +321s +75s +768s +26s = 1778s, the commute distance Si =1.1832km +1.3422km +1.0548km +1.0441km + 0.9500km +0.6404km +1.5516km +0.9283km +1.5356+1.5356km +1.8462km =13.6119km is calculated, and the commute time length Ti and the commute distance Si of each commute trip are calculated, i =1,2 and … K.
Step 2, evaluating the commuting duration index of the area a, and judging whether the area reaches the work and live balance standard:
the internal commuting one-way time consumption standard of the city X is Cx, and the number of times of reaching the internal commuting one-way time consumption standard Cx in commuting travel in the area A is calculated to be RTA：
Wherein,；
if the number of times is in proportion to RTAIf the position and live balance standard is more than or equal to 95%, the position and live balance is achieved in the area A, and an evaluation result is output; if the number of times is in proportion to RTAIf the occupation balance standard is less than 95%, the occupation balance in the area A is not reached, and the step 3 is continuously executed.
In this embodiment, the ratio of the number of times RT the internal commute one-way consumption criterion Cx is reached toA：
It can be found that the number of times is the ratio RTAIf the percentage is less than 95 percent, the occupation balance standard is not met, the occupation balance is not reached in the area A, and the step 3 is continuously executed.
Step 3, evaluating the commuting distance index of the area A, and judging whether the commuting distance index is a reason causing imbalance of the position of the area:
given that the planned population scale of city X is P in units of ten thousand, and the commute distance standard of city X is that the average trip distance of a one-way commute trip is not greater than Dx in units of km; calculating the average travel distance of the area AWherein Si is the distance of the commuting trip of the ith one-way trip;
if MSADx is not more than equal, and the average trip distance of regional A satisfies the distance standard of commuting promptly, then the distance of commuting is not the reason that causes regional A to live unbalanced, and the regulation and control suggestion is: the traffic supply is improved, the mode structure is improved, and the commuting time is reduced;
if MSAIf the average trip distance of the area A does not meet the commuting distance standard, the reason for unbalanced occupation of the area A is that the commuting distance does not meet the commuting distance standard, the reason for the commuting distance not meeting the commuting distance standard is further analyzed, and the step 4 is continuously executed.
In this embodiment, the commute distance criterion for city X is that the average trip distance for a single trip commute trip is no greater than 9km, and the average commute trip distance for region a isApparently MSAIf > 9km, i.e. area a does not meet the commute distance criterion, step 4 needs to be continued to further analyze the reason for the commute distance not meeting the criterion.
Step 4, calculating the occupation ratio of the area A, and judging whether the calculated occupation ratio is the reason of unbalance of the occupation ratio of the area A:
calculating the job-to-live ratio RE of the area AA= (employment position number E of area A)AResidential population R of area AA）；
If the job duty ratio REAIf the number is less than 0.8, the cause of imbalance of the positions of the areas A is that: job to live ratio REAOn the low side, the regulation recommendation is: the supply of houses is increased, and the duty ratio is improved;
if the ratio RE is less than or equal to 0.8AWhen the ratio is less than or equal to 1.2, the ratio REAIf the cause is not the imbalance of the job in the area A, continuing to execute the step 5;
if the job duty ratio REAIf > 1.2, the cause of the imbalance of occupations in the region A is the occupational ratio REAOn the high side, the regulation and control suggestion is: increase the post supply and reduce the duty ratio.
In the present embodiment, the job duty ratio RE of the area A is calculatedA= (employment position number E of area A)AResidential population R of area AA) = (25.6 ten thousand/26.3 ten thousand) =0.97 because 0.8 ≦ duty ratio REA< 1.2, indicating that the job title is not responsible for imbalance in job title for region A, step 5 needs to be performed.
Step 5, respectively calculating the employment self-sufficiency proportion and the occupation self-sufficiency proportion of the residents in the area A, and judging whether the proportions are the reasons for imbalance of the occupation of the area:
step 5.1: calculating the occupancy employment self-sufficiency ratio RSC in the area AA：
Calculating the occupancy self-sufficiency ratio WSC of the occupants in the area AA：
Wherein,；
step 5.2: computingCity X resident employment self-sufficiency ratio RSCX：
Calculating the resident self-sufficiency ratio WSC of city XX：
Wherein,；
step 5.3: the ratio RSC of the known city X to the self-sufficiency of the occupant's employmentXThe tolerance amount of (2) is r, the ratio of the residents living in the house is WSCXThe tolerance amount of (a) is w;
if RSCA＜RSCX-r and WSCA≥WSCX-w, the cause of imbalance of occupations in area A is RSC, the ratio of occupational self-sufficiency of the occupantsAOn the low side, the regulation recommendation is: improving the employment matching of residents locally;
if RSCA≥RSCX-r and WSCA＜WSCXW, the imbalance of occupation in area A is caused by the occupancy self-sufficiency ratio WSC of the peopleAOn the low side, the regulation recommendation is: the living matching of the workers in the local is improved;
if RSCA＜RSCX-r and WSCA＜WSCX-w, the cause of imbalance of occupations in area A is RSC, the ratio of occupational self-sufficiency of the occupantsAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAOn the low side, the regulation recommendation is: the employment matching of the residents in the local is improved, and the resident matching of the residents in the local is improved;
if RSCA≥RSCX-r and WSCA≥WSCX-w, the occupant employment self-sufficiency ratio RSCAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAIs not responsible for the imbalance of the positions of the area A.
In the present embodiment, the occupant employment self-sufficiency ratio RSC in the area a is calculatedA：
Calculating the occupancy self-sufficiency ratio WSC of the occupants in the area AA：
Similarly, in the present embodiment, the resident employment self-sufficiency proportion RSC of the city X is calculatedX：
Calculating the resident self-sufficiency ratio WSC of city XX：
The known residential self-sufficiency proportion tolerance amount r =0.06 and the residential self-sufficiency proportion tolerance amount w =0.08 of the city X;
by RSCA=0.916，RSCX-r =0.991-0.06=0.931, yielding RSCA< RSCX-r. This indicates that the cause of imbalance in the positions of region a is: the proportion of employment self-sufficiency of the residents is low.
And is composed of WSCA=0.922，WSCX-r =0.997-0.08=0.917, yielding WSCA>WSCX-w. This indicates that the proportion of occupants living in zone a is within a reasonable range.
From the above results, the cause of imbalance of the accommodation in the area a is: the self-sufficiency proportion of the employment of the residents is low, and the regulation and control suggestion is as follows: improve the employment matching of the residents locally.

Claims (6)

1. A mobile communication data-based regional occupation balance evaluation method is characterized by comprising the following steps:
step 1: selecting a city X to be analyzed, an area A belonging to the city X and mobile communication data of any operator in the city X, and calculating the commuting time and the commuting distance of each mobile phone user;
step 2: according to the internal commuting one-way time consumption standard of the city X, calculating the ratio of times of commuting trips in the area A reaching the internal commuting one-way time consumption standard, and judging whether the internal commuting one-way time consumption standard is reached;
and step 3: calculating the average commuting distance in the area A, comparing the average commuting distance with the commuting distance standard of the city X, and judging whether the average commuting distance is the reason of imbalance of jobs and dwellings in the area A;
and 4, step 4: calculating the job-to-live ratio in the area A, and judging whether the job-to-live ratio is the cause of the imbalance of the job and the live in the area A;
and 5: and respectively calculating the employment self-sufficiency proportion of the residents and the occupation self-sufficiency proportion of the residents in the area A, and judging whether the occupation self-sufficiency proportion is the reason of imbalance of the residents in the area A.
2. The method for evaluating the balance of employment of an area based on mobile communication data as claimed in claim 1, wherein said step 1 comprises the steps of:
selecting mobile communication data of all mobile phone users of a city X to be analyzed, an area A affiliated to the city X and any operator with the time span of 1 month in the city X, wherein the mobile communication data comprises a mobile phone identification number MSID, a timestamp TIMESTAMP, a position area ID, a base station longitude and a base station latitude; the mobile phone identification number MSID has uniqueness, and the location area ID and the base station ID jointly determine a unique base station;
filtering and screening ping-pong switching data and drift points in the mobile communication data, and then arranging the mobile communication data of each mobile phone user according to a time ascending sequence to obtain a mobile phone user track point time sequence; calculating the STAY TIME of a mobile phone user at each track point, selecting the track points with the STAY TIME longer than 30 minutes in the mobile phone user track point TIME sequence as STAY points, and generating a mobile phone user STAY point TIME sequence, wherein the mobile phone user STAY point TIME sequence comprises a mobile phone identification number MSID, a timestamp TIMESTAMP, a base station longitude, a base station latitude and a STAY TIME STAY _ TIME; two dwell points adjacent in time in the mobile phone user dwell point time sequence form a trip, the two dwell points adjacent to each other of a mobile phone user are matched with records in the mobile phone user track point time sequence through mobile phone identification numbers MSID and timestamp TIMESTAMP fields, a mobile phone user track point with a timestamp TIMESTAMP between the two dwell points is extracted, a mobile phone user trip track sequence is generated, the mobile phone user trip track sequence comprises all fields of the mobile phone user track point time sequence and trip number fields OD _ IND, and the mobile phone identification numbers MSID and the trip number fields OD _ IND uniquely determine the trip of one mobile phone user;
counting the accumulated stay time of each mobile phone user at different stay points at night based on the mobile phone user stay point time sequence, wherein the night is from 20:00 to 08:00 days, and selecting the stay point with the longest accumulated stay time at night to identify the stay point as the residence place of the mobile phone user; counting the accumulated stay time of each mobile phone user at different stay points in the daytime, wherein the daytime is 08:00 to 20:00 per day, and selecting the stay point with the longest accumulated stay time in the daytime and identifying the stay point as the work place of the mobile phone user;
identifying to obtain the residence RX of each mobile phone userp(p =1,2, …, M) and a work WXq(q =1,2, …, N), where M is the number of cell phone users whose residence is within the city X, and N is the number of cell phone users whose workplace is within the city X; screening the mobile phone users RA with the residence places in the area Aj(j =1,2, …, m) and a mobile telephone subscriber WA working in said area ak(k =1,2, …, n), where m is the handset user RA with the residence in the area ajN is the number of the mobile phone users WA whose working places are in the area AkNumber ofAn amount; extracting mobile phone user RAjAnd a mobile phone subscriber WAkA mobile phone user commuting travel track sequence of commuting travel between the residence and the workplace in the area A; assuming that the number of commuting trips meeting the commuting trip condition is K, the commuting time of the ith commuting trip is Ti, the commuting distance is Si, and i =1,2, … K; the commute duration refers to the duration spent by the mobile phone user when going out between a work place and a residence; the commuting distance means that the mobile phone user is in one time in the commuting trip, all the mobile phone user track points are arranged according to the time sequence, the shortest distance between two adjacent mobile phone user track points is calculated and accumulated to obtain the commuting distance.
3. The method according to claim 2, wherein the step 2 comprises the steps of:
the internal commuting one-way time consumption standard of the city X is Cx, and the ratio RT of the times of reaching the internal commuting one-way time consumption standard Cx in the commuting trip in the area A is calculatedA：
Wherein,if the number of times is in proportion to RTAThe position and live balance standard is more than or equal to 95%, and the position and live balance is achieved in the area A, and an evaluation result is output; if the number of times is in proportion to RTAIf the occupation balance standard is less than 95%, the occupation balance is not reached in the area A, and the step 3 is continuously executed.
4. The method according to claim 3, wherein the step 3 comprises the steps of:
as is known in the artThe planning population scale of the city X is P, the unit is ten thousand, and the commute distance standard of the city X is that the average trip distance of the commute trip of one trip is not more than Dx, and the unit is km; calculating the average travel distance of the area AWherein Si is the distance of the commute trip for the ith single trip;
if MSADx is not more than equal, promptly regional A's average trip distance satisfies the commute distance standard, then the commute distance does not cause regional A plays the unbalanced reason of live, and the regulation and control suggestion is: the traffic supply is improved, the mode structure is improved, and the commuting time is reduced;
if MSAIf the average trip distance of the area A does not meet the commuting distance standard, the reason for causing the unbalanced job and live of the area A is that the commuting distance does not meet the commuting distance standard, the reason for the commuting distance not meeting the commuting distance standard is further analyzed, and the step 4 is continuously executed.
5. The method according to claim 4, wherein the step 4 comprises the steps of:
calculating the job-to-live ratio RE of the area AA= (employment position number E of area A)AResidential population R of area AA）；
If the job duty ratio REAIf the number is less than 0.8, the cause of the imbalance of the positions of the areas A is that: job to live ratio REAOn the low side, the regulation recommendation is: the supply of houses is increased, and the duty ratio is improved;
if the ratio RE is less than or equal to 0.8AWhen the ratio is less than or equal to 1.2, the ratio REAIf the cause is not the imbalance of the job in the area A, continuing to execute the step 5;
if the job duty ratio REAIf the ratio is more than 1.2, the cause of the imbalance of occupations in the area A is the occupational ratio REAOn the high side, the regulation and control suggestion is: increase the post supply and reduce the duty ratio.
6. The method according to claim 5, wherein the step 5 comprises the steps of:
step 5.1: calculating the occupancy employment self-sufficiency proportion RSC of the residents in the area AA：
Calculating the occupancy self-sufficiency ratio WSC of the persons in the area AA：
Wherein,；
step 5.2: calculating the self-sufficiency ratio RSC of the residents in the city XX：
Calculating the resident self-sufficiency proportion WSC of the city XX：
Wherein,；
step 5.3: the occupant employment self-sufficiency ratio RSC of the city X is knownXThe tolerance amount of (2) is r, the ratio of the residents living in the house is WSCXThe tolerance amount of (a) is w;
if RSCA＜RSCX-r and WSCA≥WSCX-w, cause of imbalance in the position of said area ARSC ratio for residents' employmentAOn the low side, the regulation recommendation is: improving the employment matching of residents locally;
if RSCA≥RSCX-r and WSCA＜WSCX-w, the proportion of occupancy self-sufficiency WSC of the persons causing the imbalance of the occupation of the area AAOn the low side, the regulation recommendation is: the living matching of the workers in the local is improved;
if RSCA＜RSCX-r and WSCA＜WSCX-w, the cause of said imbalance of occupation of area a is the proportion of occupancy self-sufficiency RSC of the occupantsAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAOn the low side, the regulation recommendation is: the employment matching of the residents in the local is improved, and the resident matching of the residents in the local is improved;
if RSCA≥RSCX-r and WSCA≥WSCX-w, the occupant employment self-sufficiency ratio RSCAWSC (Wireless sensor network) proportional to living self-sufficiency of residentsAIs not responsible for the imbalance of the positions of the area A.
CN201910793682.9A 2019-08-27 2019-08-27 Balance evaluation method is lived in a kind of region duty based on mobile data Pending CN110473132A (en)

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