CN112747767A - Travel mode determination method and device and computer readable storage medium - Google Patents

Travel mode determination method and device and computer readable storage medium Download PDF

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CN112747767A
CN112747767A CN201911041956.5A CN201911041956A CN112747767A CN 112747767 A CN112747767 A CN 112747767A CN 201911041956 A CN201911041956 A CN 201911041956A CN 112747767 A CN112747767 A CN 112747767A
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user
point
grid
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starting point
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王峰
朱悦
高兆庆
朱晨曦
沈淑娴
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Tianyi Cloud Technology Co Ltd
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China Telecom Corp Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/36—Input/output arrangements for on-board computers
    • G01C21/3691—Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/34—Route searching; Route guidance
    • G01C21/3407—Route searching; Route guidance specially adapted for specific applications

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Abstract

The disclosure relates to a travel mode determining method and device and a computer readable storage medium, and relates to the technical field of computers. The method of the present disclosure comprises: determining the position information of the user at different moments according to the signaling data of the terminal of the user; determining a starting point and an end point of a section of travel of a user according to the position information of the user at different moments; and determining the traffic mode of the user in the travel according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the regional characteristics corresponding to the starting point and the end point.

Description

Travel mode determination method and device and computer readable storage medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for determining a travel mode, and a computer-readable storage medium.
Background
The traffic mode information of the user trip has an important role in the field of traffic planning and management. Big data modeling analysis is a product of the information era, operators can obtain data widely distributed by users, and the problem that how to accurately mine the traffic mode of the users through the acquisition and analysis of mobile phone signaling data is needed to be solved at present.
Disclosure of Invention
One technical problem to be solved by the present disclosure is: how to determine the user's travel mode through the signaling data of the user terminal.
According to some embodiments of the present disclosure, a travel mode determining method is provided, including: determining the position information of the user at different moments according to the signaling data of the terminal of the user; determining a starting point and an end point of a section of travel of a user according to the position information of the user at different moments; and determining the traffic mode of the user in the travel according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the regional characteristics corresponding to the starting point and the end point.
In some embodiments, determining the start point and the end point of a travel of the user according to the position information of the user at different time comprises: determining grids to which the position information of the user at different moments belongs; wherein each grid comprises a region of a preset range; and determining the starting point and the end point of a section of journey of the user according to the time information of the user on each grid.
In some embodiments, determining the start point and the end point of a trip of the user based on the time information of the user at each grid comprises: updating the position information of the user at different moments into the central longitude and latitude of the corresponding grid, and obtaining the updated longitude and latitude at different moments; determining the stay time of the same longitude and latitude as the stay time of the user on the corresponding grid according to each time corresponding to the same longitude and latitude; and respectively determining the two grids with the user stay time length exceeding the threshold as the starting point and the end point of a section of travel.
In some embodiments, the region characteristics corresponding to the start point and the end point include: the province where the starting point is located and the province where the terminal point is located, the city where the terminal point is located contains information of grids corresponding to sites, and the sites comprise at least one of railway stations and airports.
In some embodiments, the grid corresponding to a site is determined by the following method: determining the minimum circumscribed circle of a polygon corresponding to the station; the radius of the minimum circumscribed circle is extended by a preset length to obtain an updated circumscribed circle; and taking the grid covered by the updated circumscribed circle as the grid corresponding to the site.
In some embodiments, determining the minimum circumscribed circle of the polygon corresponding to the station comprises: selecting three vertexes from the vertexes of the polygon corresponding to the station point; if the selected three vertexes are on the same straight line, taking a connecting line of two vertexes with the largest distance in the selected three vertexes as the diameter of the minimum circumscribed circle of the selected three vertexes to determine the minimum circumscribed circle of the selected three vertexes; and taking the largest one of the minimum circumcircles of any three vertexes corresponding to the station as the minimum circumcircle of the polygon corresponding to the station.
In some embodiments, determining the transportation mode of the user in the travel according to the distance between the starting point and the ending point, the time from the starting point to the ending point of the user, and the area characteristics corresponding to the starting point and the ending point comprises: determining the traffic mode of the user in the section of the travel according to the distance between the starting point and the end point, the time from the starting point to the end point of the user, the area characteristics corresponding to the starting point and the end point, and the area characteristics of the grids passed by the user in the section of the travel; the area characteristics corresponding to the starting point and the end point comprise: at least one of information of a grid corresponding to a site included in a city where the starting point is located, information of whether the starting point belongs to the grid corresponding to the site, information of a grid corresponding to a site included in a city where the ending point is located, and information of whether the ending point belongs to the grid corresponding to the site; the area characteristics of the grid that the user passes through in this segment of travel include: and whether the grid passed by the user in the trip belongs to the grid corresponding to the site or not.
In some embodiments, determining the mode of transportation of the user on the trip includes: determining that the traffic mode of the user in the section of the journey is an airplane mode, a high-speed rail mode, a train mode or other modes; in the case that the transportation mode is other mode, the method further comprises the following steps: determining the path characteristics of the public bus from the city where the starting point is located to the city where the end point is located according to historical sample data from the city where the starting point is located to the city where the end point is located; determining whether the traffic mode of the user in the travel section is the public bus or not according to the similarity between the grid information passed by the user in the travel section and the path characteristics of the public bus; and in the case that the transportation mode of the user in the journey is not the public bus, determining that the transportation mode of the user in the journey is self-driving.
In some embodiments, determining the path characteristics of the public bus from the city where the starting point is located to the city where the ending point is located according to historical sample data from the city where the starting point is located to the city where the ending point is located comprises: determining that the city from the starting point to the departure starting point passes through each grid according to historical sample data to form a first grid set, and determining that the city from the arrival end point passes through each grid to the end point to form a second grid set; determining a starting point of the bus according to the occurrence frequency of each grid in the first grid set, and determining an end point of the bus according to the occurrence frequency of each grid in the second grid set;
in some embodiments, determining whether the transportation mode of the user in the travel section is the bus according to the similarity between the grid information passed by the user in the travel section and the path characteristics of the bus comprises: determining the Jacard coefficient of the characteristic point set of the user passing through the section of travel and the path characteristic point set of the public bus as the similarity of the raster information of the user passing through the section of travel and the path characteristic of the public bus; the user passes through the feature point set in the section of travel, and the feature point set is a set formed by the user passing through each grid from the starting point to the city where the starting point is away from, and passing through each grid from the city where the terminal point is reached to the terminal point; determining that the traffic mode of the user in the travel is the bus under the condition that the similarity is greater than the similarity threshold; the similarity threshold is determined according to the Jacard coefficient of the first raster set and the Jacard coefficient of the second raster set corresponding to the historical sample data and the path feature point set of the public bus.
According to other embodiments of the present disclosure, there is provided a travel mode determining apparatus, including: the position determining module is used for determining the position information of the user at different moments according to the signaling data of the terminal of the user; the system comprises a journey determining module, a starting point and an ending point of a section of journey of a user are determined according to position information of the user at different moments; and the traffic mode determining module is used for determining the traffic mode of the user in the section of the journey according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the regional characteristics corresponding to the starting point and the end point.
According to still other embodiments of the present disclosure, there is provided a travel mode determining apparatus, including: a processor; and a memory coupled to the processor for storing instructions that, when executed by the processor, cause the processor to perform a method of determining a travel pattern as in any of the preceding embodiments.
According to still further embodiments of the present disclosure, there is provided a non-transitory computer readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method for determining travel patterns of any of the foregoing embodiments.
The method and the device determine the position information of the user at different moments according to the signaling data of the terminal of the user, further determine the starting point and the end point of a section of travel of the user, and further determine the traffic mode of the user in the section of travel according to the distance and the time of the starting point and the end point and by combining the area characteristics corresponding to the starting point and the end point. The invention provides a data mining method for determining a user's travel transportation mode according to signaling data of a user's terminal, which can more accurately determine the user's travel mode.
Other features of the present disclosure and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 shows a flow chart of a method for determining a travel pattern according to some embodiments of the present disclosure.
Fig. 2 is a flowchart illustrating a travel mode determination method according to another embodiment of the disclosure.
Fig. 3 shows a schematic structural diagram of a travel mode determination apparatus according to some embodiments of the present disclosure.
Fig. 4 is a schematic structural diagram of a travel mode determination apparatus according to another embodiment of the present disclosure.
Fig. 5 is a schematic structural diagram of a travel mode determination device according to still other embodiments of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The present disclosure proposes a scheme for determining a user's travel mode according to signaling data of a user's terminal, which is described below with reference to fig. 1.
Fig. 1 is a flowchart of some embodiments of a travel mode determination method according to the present disclosure. As shown in fig. 1, the method of this embodiment includes: steps S102 to S106.
In step S102, the location information of the user at different times is determined according to the signaling data of the user' S terminal.
Through signaling data interacted between the terminal and the base station, the position information of the user at different moments can be determined in a base station positioning or triangulation manner, for example, the position information is longitude and latitude.
In step S104, a start point and an end point of a trip of the user are determined according to the position information of the user at different times.
In some embodiments, the grid to which the user's location information at different times belongs is determined. And determining the starting point and the end point of a section of journey of the user according to the time information of the user on each grid. Further, updating the position information of the user at different moments into the central longitude and latitude of the corresponding grid, and obtaining the updated longitude and latitude at different moments; determining the stay time of the same longitude and latitude as the stay time of the user on the corresponding grid according to each time corresponding to the same longitude and latitude; and respectively determining the two grids with the user stay time length exceeding the threshold as the starting point and the end point of a section of travel.
In some embodiments, the location information of the user at different times may be rasterized, for example, the map is rasterized according to a preset range (preset length and width), that is, each grid includes an area of the preset range, and the longitude and latitude coordinates of each location point falling in the grid are replaced with the longitude and latitude coordinates of the center of the grid, so that the grid to which the user belongs at different times may be determined. Furthermore, according to the time corresponding to the same longitude and latitude, the entering time, leaving time and staying time of the user in each grid, the area information of the grid and the like are obtained. For example, the relevant information for each location information is denoted as { l }id,lit,lir,lik,lis,licAnd i is more than or equal to 1 and less than or equal to N, i is a positive integer and represents the number of the position information, and N is the total number of the position information. lidIndicating the grid to which the ith piece of position information belongs, litIndicating entry into grid lidTime of (l)irIndicating leaving grid lidTime, likIs shown in grid lidLength of residence,/isRepresentation grid lidAll of the provinces of province, licRepresentation grid lidBelongs to the city.
Further, a grid with a dwell time exceeding a threshold may be determined, and if there are more than two grids with dwell times exceeding a threshold, then multiple trips may be determined. The start point and the end point of a trip can be determined by the two grids with the smallest difference between the entry time (or the exit time), the grid with the first entry time (or the exit time) being the start grid. Or, the cities to which different grids belong can be distinguished, and in the grid sets belonging to different cities, stay time exceeding a threshold value is respectively selectedAnd the grid with the greatest dwell time, i.e. max lirAnd likAnd if the number of the grids is more than Threshold, selecting grids belonging to different cities as a starting point and an end point respectively.
In step S106, the traffic mode of the user in the trip is determined according to the distance between the starting point and the ending point, the time from the starting point to the ending point, and the area characteristics corresponding to the starting point and the ending point.
The distance between the starting point and the end point can be determined according to the path track from the user to the starting point to the end point. The average speed of the user can be determined according to the distance between the starting point and the end point and the time from the starting point to the end point of the user. The traffic mode of the user in the travel can be determined according to the average speed of the user and the area characteristics corresponding to the starting point and the end point. The region characteristics corresponding to the starting point and the end point include: the province where the starting point is located and the province where the terminal point is located, and the city where the terminal point is located contains grid information corresponding to sites, wherein the sites comprise at least one of railway stations and airports.
After the starting point and the end point of a user's journey are determined, the relationship from the starting point to the end point (OD) of the user can be established, in the following description, the starting point is represented by point O, the end point is represented by point D, and the OD relationship structure is as follows:
grid number of O dots: ol(ii) a O point longitude and latitude coordinate (x'l,y′l) (ii) a The province of point O: a. thej(ii) a O points belong to the city: a. theju(ii) a Point O entry time: l'it(ii) a Point O departure time: l'ir
Grid number of D points Dl(ii) a D point latitude and longitude coordinates (x ″)l,y″l) (ii) a The province to which point D belongs: a. theh(ii) a Point D belongs to the city: a. thehv(ii) a Point D entry time: l ″)it(ii) a Point D departure time: l ″)ir
Grid set passed in time from O point to D point: b isOD(ii) a OD distance: dOD
In order to determine the transportation mode of the user, station information such as a train station or an airport is also referred to. Therefore, a grid corresponding to the site needs to be determined. In some embodiments, the minimum circumcircle of the polygon corresponding to the station is determined; the radius of the minimum circumscribed circle is extended by a preset length to obtain an updated circumscribed circle; and taking the grid covered by the updated circumscribed circle as the grid corresponding to the site. Further, selecting three vertexes from the vertexes of the polygon corresponding to the station point; if the selected three vertexes are on the same straight line, taking a connecting line of two vertexes with the largest distance in the selected three vertexes as the diameter of the minimum circumscribed circle of the selected three vertexes to determine the minimum circumscribed circle of the selected three vertexes; and taking the largest one of the minimum circumcircles of any three vertexes corresponding to the station as the minimum circumcircle of the polygon corresponding to the station.
For example, the station latitude and longitude coordinate is (x)1,y1),(x2,y2)…(xn,yn) The coordinate points are used as polygon vertexes to form a polygon, the minimum circumscribed circle of the polygon is found, the method for solving the minimum circumscribed circle of the polygon can be converted into n (n is more than or equal to 3) points which are different from each other in the plane, and the minimum circle covering the n points is solved. Any 3 points from the n points. If the 3 points are on the same straight line, the circle with the diameter of the connecting line segment of the 2 points with the largest distance among the 3 points is the smallest circle covering the 3 points. If the 3 points are not on the same straight line, a triangle can be constructed by taking the 3 points as vertexes, and if the triangle formed by the 3 points is an acute triangle, the circumscribed circle of the acute triangle is the smallest circle covering the 3 points. If the triangle formed by the 3 points is a right-angled triangle or an obtuse triangle, a circle with the connecting line segment of the 2 points with the largest distance among the 3 points as the diameter is the smallest circle covering the 3 points. Can be picked out from n points
Figure BDA0002253085660000071
And each 3-point group can obtain a minimum circle covering the 3-point group, and the circle with the largest radius in the circles is the minimum circle covering the n points, namely the minimum circumcircle of the polygon corresponding to the railway station. And (4) outwards expanding the radius of the circumscribed circle by w meters to obtain a new site range, thereby obtaining the grid set after site expansion.
Further, a grid set corresponding to the city site where the O point and the D point are located can be established. For example, the grid set of an O-point urban railway station: cO(ii) a O point urban airport grid set: dO(ii) a D, point urban railway station grid set: cD(ii) a D, point urban airport grid collection: dD(ii) a Grid set composed of all railway stations: c; grid set of all airports: D.
several embodiments of determining the user's mode of transportation are described in detail below.
Based on average speed of user
Figure BDA0002253085660000081
Province A of originjAnd the destination point is province AhInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether empty or not, the user's mode of transportation may be determined for some cases, such as the following.
(1) When in use
Figure BDA0002253085660000082
And A isj≠AhAnd is
Figure BDA0002253085660000083
In the time, the transportation mode of the trip is as follows: an aircraft. For example, V1300km/h, can be determined from the test results, and is not limited to the illustrated example.
(2) When in use
Figure BDA0002253085660000084
And A isj≠AhAnd is
Figure BDA0002253085660000085
And is
Figure BDA0002253085660000086
In the time, the transportation mode of the trip is as follows: high-speed rail.
(3) When in use
Figure BDA0002253085660000087
And A isj≠AhAnd is
Figure BDA0002253085660000089
And is
Figure BDA0002253085660000088
In the time, the transportation mode of the trip is as follows: and others.
(4) When in use
Figure BDA00022530856600000810
And A isj＝AhAnd is
Figure BDA00022530856600000811
In the time, the transportation mode of the trip is as follows: high-speed rail.
(5) When in use
Figure BDA00022530856600000812
And A isj＝AhAnd is
Figure BDA00022530856600000813
In the time, the transportation mode of the trip is as follows: and others.
(II) average speed according to users
Figure BDA00022530856600000814
Distance d between starting point and end pointODInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether empty or not, the user's mode of transportation may be determined for some cases, such as the following.
(1) When in use
Figure BDA00022530856600000815
And d isOD≤d1And is
Figure BDA00022530856600000816
In the time, the transportation mode of the trip is as follows: high-speed rail. E.g. d1300km, which can be determined from the test results, is not limited to the illustrated example.
(2) When in use
Figure BDA00022530856600000817
And d isOD≤d1And is
Figure BDA00022530856600000818
In the time, the transportation mode of the trip is as follows: and others.
(III) average speed according to users
Figure BDA00022530856600000819
Whether the end point belongs to the grid corresponding to the site, i.e. whether d existsl∈CDOr dl∈DDThe traffic pattern of the user in some cases may be determined, for example, as follows.
(1) When in use
Figure BDA00022530856600000820
And d isl∈CDIn the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA0002253085660000091
And d isl∈CDIn the time, the transportation mode of the trip is as follows: a train.
(IV) average speed according to users
Figure BDA0002253085660000092
Distance d between starting point and end pointODProvince of origin AjAnd the destination point is province AhWhether the end point belongs to the grid corresponding to the site, i.e. whether d existsl∈CDOr dl∈DDThe traffic pattern of the user in some cases may be determined, for example, as follows.
(1) When in use
Figure BDA0002253085660000093
And d isl∈DDAnd A isj≠AhAnd d isOD≥d1In the time, the transportation mode of the trip is as follows:an aircraft.
(V) average speed according to users
Figure BDA0002253085660000094
Province A of originjAnd the destination point is province AhInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether the destination is empty or not, whether the destination belongs to the grid corresponding to the site or not, namely whether d exists or notl∈CDOr dl∈DDThe traffic pattern of the user in some cases may be determined, for example, as follows.
(1) When in use
Figure BDA0002253085660000095
And d isl∈DDAnd A isj＝AhAnd is
Figure BDA0002253085660000096
In the time, the transportation mode of the trip is as follows: high-speed rail. For example, V2The value of 100km/h can be determined according to the test result, and is not limited to the illustrated example.
(2) When in use
Figure BDA0002253085660000097
And d isl∈DDAnd A isj＝AhAnd is
Figure BDA0002253085660000098
In the time, the transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA0002253085660000099
And d isl∈DDAnd A isj＝AhAnd is
Figure BDA00022530856600000910
In the time, the transportation mode of the trip is as follows: and others.
(VI) average speed according to users
Figure BDA00022530856600000911
Distance d between starting point and end pointODProvince of origin AjAnd the destination point is province AhInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether the destination is empty or not, whether the destination belongs to the grid corresponding to the site or not, namely whether d exists or notl∈CDOr dl∈DDThe traffic pattern of the user in some cases may be determined, for example, as follows.
(1) When in use
Figure BDA00022530856600000912
And d isl∈DDAnd A isj≠AhAnd d isoD≤d1And is
Figure BDA00022530856600000913
In the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA00022530856600000914
And d isl∈DDAnd A isj≠AhAnd d isoD≤d1And is
Figure BDA00022530856600000915
In the time, the transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA0002253085660000101
And d isl∈DDAnd A isj≠AhAnd d isoD≤d1And is
Figure BDA0002253085660000102
In the time, the transportation mode of the trip is as follows: and others.
The above six judgment modes are that the traffic mode of the user is determined according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the area characteristics corresponding to the end point, or the traffic mode of the user is determined according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the area characteristics corresponding to the starting point and the end point. The area characteristics corresponding to the starting point include: the province of the starting point, the region characteristics corresponding to the terminal include: and the province where the terminal is located, the city where the terminal is located contains information of the grid corresponding to the site, and at least one item of information of whether the terminal belongs to the grid corresponding to the site.
If the traffic mode cannot be determined based on the information, the traffic mode of the user in the section of the journey is further determined according to the distance between the starting point and the end point, the time from the starting point to the end point of the user, the area characteristics corresponding to the starting point and the end point, and the area characteristics of the grids passed by the user in the section of the journey. The region characteristics corresponding to the starting point and the end point include: at least one of information of a grid corresponding to a site included in a city where the starting point is located, information of whether the starting point belongs to the grid corresponding to the site, information of a grid corresponding to a site included in a city where the ending point is located, and information of whether the ending point belongs to the grid corresponding to the site; the area characteristics of the grid that the user passes through in this segment of travel include: and whether the grid passed by the user in the trip belongs to the grid corresponding to the site or not.
That is, when
Figure BDA0002253085660000103
And is
Figure BDA0002253085660000104
And is
Figure BDA0002253085660000105
How to determine the transportation mode of the user based on the above information is described below.
(VII) average speed according to user
Figure BDA0002253085660000106
Whether the end point belongs to the grid corresponding to the site or not, namely whether d existsl∈CDOr dl∈DDThe terminal point corresponds to the site in the cityOf the grid, i.e. CDWhether empty and/or DDWhether the grid is empty or not, whether the passed grid belongs to the grid corresponding to the site or not, namely BODWhether or not C is
Figure BDA0002253085660000107
BODWhether or not D is equal to
Figure BDA0002253085660000108
The traffic pattern of the user may be determined in some cases, for example, as follows.
(1) When in use
Figure BDA0002253085660000109
And is
Figure BDA00022530856600001011
And is
Figure BDA00022530856600001010
And is
Figure BDA00022530856600001012
Figure BDA00022530856600001013
And is
Figure BDA00022530856600001014
And is
Figure BDA00022530856600001015
In the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA00022530856600001016
And is
Figure BDA00022530856600001017
And is
Figure BDA00022530856600001018
And is
Figure BDA00022530856600001019
And is
Figure BDA00022530856600001020
Figure BDA00022530856600001021
And is
Figure BDA00022530856600001022
In the time, the transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA0002253085660000111
And is
Figure BDA0002253085660000112
And is
Figure BDA0002253085660000113
And is
Figure BDA0002253085660000114
And is
Figure BDA0002253085660000115
Figure BDA0002253085660000116
And is
Figure BDA0002253085660000117
In the time, the transportation mode of the trip is as follows: and others.
(VIII) average speed according to user
Figure BDA0002253085660000118
Distance d from starting point to terminalODProvince of origin AjAnd the destination point is province AhWhether the end point belongs to the grid corresponding to the site or not, namely whether d existsl∈CDOr dl∈DDGrid information corresponding to sites contained in city where destination is locatedThen, i.e. CDWhether empty and/or DDWhether the grid is empty or not, whether the passed grid belongs to the grid corresponding to the site or not, namely BODWhether or not C is
Figure BDA0002253085660000119
BODWhether or not D is equal to
Figure BDA00022530856600001110
The traffic pattern of the user may be determined in some cases, for example, as follows.
(1) When in use
Figure BDA00022530856600001111
And is
Figure BDA00022530856600001113
And is
Figure BDA00022530856600001112
And is
Figure BDA00022530856600001114
And is
Figure BDA00022530856600001115
Figure BDA00022530856600001116
And d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001117
In the time, the transportation mode of the trip is as follows: an aircraft.
(2) When in use
Figure BDA00022530856600001118
And is
Figure BDA00022530856600001119
And is
Figure BDA00022530856600001120
And is
Figure BDA00022530856600001121
Figure BDA00022530856600001122
And is
Figure BDA00022530856600001123
And d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001124
And is
Figure BDA00022530856600001125
In the time, the transportation mode of the trip is as follows: high-speed rail.
(3) When in use
Figure BDA00022530856600001126
And is
Figure BDA00022530856600001127
And is
Figure BDA00022530856600001128
And is
Figure BDA00022530856600001129
And is
Figure BDA00022530856600001130
Figure BDA00022530856600001131
And d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001132
And is
Figure BDA00022530856600001133
In the time, the transportation mode of the trip is as follows: a train.
(4) When in use
Figure BDA00022530856600001134
And is
Figure BDA00022530856600001135
And is
Figure BDA00022530856600001136
And is
Figure BDA00022530856600001137
And is
Figure BDA00022530856600001138
Figure BDA00022530856600001139
And d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001140
And is
Figure BDA00022530856600001141
In the time, the transportation mode of the trip is as follows: and others.
(5) When in use
Figure BDA00022530856600001142
And is
Figure BDA00022530856600001145
And is
Figure BDA00022530856600001144
And is
Figure BDA00022530856600001143
Figure BDA00022530856600001146
And is
Figure BDA00022530856600001147
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001148
In the time, the transportation mode of the trip is as follows: high-speed rail.
(6) When in use
Figure BDA00022530856600001149
And is
Figure BDA00022530856600001150
And is
Figure BDA00022530856600001151
And is
Figure BDA00022530856600001152
And is
Figure BDA00022530856600001153
Figure BDA00022530856600001154
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001155
In the time, the transportation mode of the trip is as follows: a train.
(7) When in use
Figure BDA00022530856600001156
And is
Figure BDA00022530856600001157
And is
Figure BDA00022530856600001158
And is
Figure BDA00022530856600001159
And is
Figure BDA00022530856600001160
Figure BDA00022530856600001161
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001162
In the time, the transportation mode of the trip is as follows: and others.
(nine) average speed according to user
Figure BDA00022530856600001163
Province A of originjAnd the destination point is province AhWhether the end point belongs to the grid corresponding to the site or not, namely whether d existsl∈CDOr dl∈DDInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether the grid is empty or not, whether the passed grid belongs to the grid corresponding to the site or not, namely BODWhether or not C is
Figure BDA0002253085660000121
BODWhether or not D is equal to
Figure BDA0002253085660000122
The traffic pattern of the user may be determined in some cases, for example, as follows.
(1) When in use
Figure BDA0002253085660000123
And is
Figure BDA0002253085660000124
And is
Figure BDA0002253085660000125
And is
Figure BDA0002253085660000126
Figure BDA0002253085660000127
And is
Figure BDA0002253085660000128
And A isj＝AhAnd is
Figure BDA0002253085660000129
In the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA00022530856600001210
And is
Figure BDA00022530856600001211
And is
Figure BDA00022530856600001212
And is
Figure BDA00022530856600001213
And is
Figure BDA00022530856600001214
Figure BDA00022530856600001215
And A isj＝AhAnd is
Figure BDA00022530856600001216
In the time, the transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA00022530856600001217
And is
Figure BDA00022530856600001218
And is
Figure BDA00022530856600001219
And is
Figure BDA00022530856600001220
And is
Figure BDA00022530856600001221
Figure BDA00022530856600001222
And A isj＝AhAnd is
Figure BDA00022530856600001223
In the time, the transportation mode of the trip is as follows: and others.
(ten) average speed according to user
Figure BDA00022530856600001224
Distance d from starting point to terminalODProvince of origin AjAnd the destination point is province AhWhether the end point belongs to the grid corresponding to the site or not, namely whether d existsl∈CDOr dl∈DDInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether the grid is empty or not, whether the starting point belongs to the grid corresponding to the site or not, namely whether o exists or notl∈COOr ol∈DOWhether the grid passed through belongs to the grid corresponding to the site, i.e. BODWhether or not C is
Figure BDA00022530856600001225
BODWhether or not D is equal to
Figure BDA00022530856600001226
The traffic pattern of the user may be determined in some cases, for example, as follows.
(1) When in use
Figure BDA00022530856600001227
And is
Figure BDA00022530856600001228
And is
Figure BDA00022530856600001229
And is
Figure BDA00022530856600001230
Figure BDA00022530856600001231
And is
Figure BDA00022530856600001232
And o isl∈COAnd is
Figure BDA00022530856600001233
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001234
In the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA00022530856600001235
And is
Figure BDA00022530856600001236
And is
Figure BDA00022530856600001237
And is
Figure BDA00022530856600001238
And is
Figure BDA00022530856600001239
Figure BDA00022530856600001240
And o isl∈COAnd is
Figure BDA00022530856600001241
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001242
This time, the timeThe transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA00022530856600001243
And is
Figure BDA00022530856600001244
And is
Figure BDA00022530856600001245
And is
Figure BDA00022530856600001246
And is
Figure BDA00022530856600001247
Figure BDA00022530856600001248
And o isl∈COAnd is
Figure BDA00022530856600001249
And d isOD<d1And A isj≠AhAnd is
Figure BDA00022530856600001250
In the time, the transportation mode of the trip is as follows: and others.
(4) When in use
Figure BDA00022530856600001251
And is
Figure BDA00022530856600001252
And is
Figure BDA00022530856600001253
And is
Figure BDA00022530856600001254
And is
Figure BDA00022530856600001255
Figure BDA0002253085660000131
And is
Figure BDA0002253085660000132
And o isl∈DOAnd d isOD≥d1And A isj≠AhAnd is
Figure BDA0002253085660000133
In the time, the transportation mode of the trip is as follows: an aircraft.
(5) When in use
Figure BDA0002253085660000134
And is
Figure BDA0002253085660000135
And is
Figure BDA0002253085660000136
And is
Figure BDA0002253085660000137
Figure BDA0002253085660000138
And is
Figure BDA0002253085660000139
And is
Figure BDA00022530856600001310
And o isl∈DOAnd d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001311
Figure BDA00022530856600001312
And is
Figure BDA00022530856600001313
In the time, the transportation mode of the trip is as follows: high-speed rail.
(6) When in use
Figure BDA00022530856600001314
And is
Figure BDA00022530856600001315
And is
Figure BDA00022530856600001316
And is
Figure BDA00022530856600001317
And is
Figure BDA00022530856600001318
Figure BDA00022530856600001319
And is
Figure BDA00022530856600001320
And o isl∈DOAnd d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001321
And is
Figure BDA00022530856600001322
In the time, the transportation mode of the trip is as follows: a train.
(7) When in use
Figure BDA00022530856600001323
And is
Figure BDA00022530856600001324
And is
Figure BDA00022530856600001325
And is
Figure BDA00022530856600001326
And is
Figure BDA00022530856600001327
Figure BDA00022530856600001328
And is
Figure BDA00022530856600001329
And o isl∈DOAnd d isOD≥d1And A isj≠AhAnd is
Figure BDA00022530856600001330
And is
Figure BDA00022530856600001331
In the time, the transportation mode of the trip is as follows: and others.
(eleven) average speed according to user
Figure BDA00022530856600001332
Province A of originjAnd the destination point is province AhWhether the end point belongs to the grid corresponding to the site or not, namely whether d existsl∈CDOr dl∈DDInformation of the grid corresponding to the site included in the city where the destination is located, i.e. CDWhether empty and/or DDWhether the grid is empty or not, whether the starting point belongs to the grid corresponding to the site or not, namely whether o exists or notl∈COOr ol∈DOWhether the grid passed through belongs to the grid corresponding to the site, i.e. BODWhether or not C is
Figure BDA00022530856600001333
BODWhether or not D is equal to
Figure BDA00022530856600001334
The traffic pattern of the user may be determined in some cases, for example, as follows.
(1) When in use
Figure BDA00022530856600001335
And is
Figure BDA00022530856600001336
And is
Figure BDA00022530856600001337
And is
Figure BDA00022530856600001338
Figure BDA00022530856600001339
And is
Figure BDA00022530856600001340
And o isl∈COAnd is
Figure BDA00022530856600001341
And A isj＝AhAnd is
Figure BDA00022530856600001342
In the time, the transportation mode of the trip is as follows: high-speed rail.
(2) When in use
Figure BDA00022530856600001343
And is
Figure BDA00022530856600001344
And is
Figure BDA00022530856600001345
And is
Figure BDA00022530856600001346
And is
Figure BDA00022530856600001347
Figure BDA00022530856600001348
And o isl∈COAnd is
Figure BDA00022530856600001349
And A isj＝AhAnd is
Figure BDA00022530856600001350
In the time, the transportation mode of the trip is as follows: a train.
(3) When in use
Figure BDA00022530856600001351
And is
Figure BDA00022530856600001352
And is
Figure BDA00022530856600001353
And is
Figure BDA00022530856600001354
And is
Figure BDA00022530856600001355
Figure BDA00022530856600001356
And o isl∈COAnd is
Figure BDA00022530856600001357
And A isj＝AhAnd is
Figure BDA00022530856600001358
In the time, the transportation mode of the trip is as follows: and others.
(4) When in use
Figure BDA00022530856600001359
And is
Figure BDA00022530856600001360
And is
Figure BDA00022530856600001361
And is
Figure BDA00022530856600001362
Figure BDA00022530856600001363
And is
Figure BDA00022530856600001364
And o isl∈COAnd is
Figure BDA00022530856600001365
And is
Figure BDA00022530856600001366
In the time, the transportation mode of the trip is as follows: high-speed rail.
(5) When in use
Figure BDA0002253085660000141
And is
Figure BDA0002253085660000142
And is
Figure BDA0002253085660000143
And is
Figure BDA0002253085660000144
And is
Figure BDA0002253085660000145
Figure BDA0002253085660000146
And o isl∈COAnd is
Figure BDA0002253085660000147
And is
Figure BDA0002253085660000148
In the time, the transportation mode of the trip is as follows: a train.
(6) When in use
Figure BDA0002253085660000149
And is
Figure BDA00022530856600001410
And is
Figure BDA00022530856600001411
And is
Figure BDA00022530856600001412
And is
Figure BDA00022530856600001413
Figure BDA00022530856600001414
And o isl∈COAnd is
Figure BDA00022530856600001415
And is
Figure BDA00022530856600001416
In the time, the transportation mode of the trip is as follows: and others.
(7) When in use
Figure BDA00022530856600001417
And is
Figure BDA00022530856600001418
And is
Figure BDA00022530856600001444
And is
Figure BDA00022530856600001420
Figure BDA00022530856600001421
And is
Figure BDA00022530856600001422
And is
Figure BDA00022530856600001423
And is
Figure BDA00022530856600001424
And is
Figure BDA00022530856600001425
In the time, the transportation mode of the trip is as follows: high-speed rail.
(8) When in use
Figure BDA00022530856600001426
And is
Figure BDA00022530856600001427
And is
Figure BDA00022530856600001428
And is
Figure BDA00022530856600001429
Figure BDA00022530856600001430
And is
Figure BDA00022530856600001431
And is
Figure BDA00022530856600001432
And is
Figure BDA00022530856600001433
And is
Figure BDA00022530856600001434
In the time, the transportation mode of the trip is as follows: and others.
(9) When in use
Figure BDA00022530856600001435
And is
Figure BDA00022530856600001436
And is
Figure BDA00022530856600001437
And is
Figure BDA00022530856600001438
And is
Figure BDA00022530856600001439
Figure BDA00022530856600001440
And is
Figure BDA00022530856600001441
And is
Figure BDA00022530856600001442
And is
Figure BDA00022530856600001443
In the time, the transportation mode of the trip is as follows: and others.
The modes determine that the traffic mode of the user in the travel is an airplane mode, a high-speed rail mode, a train mode or other modes. Other modes include a bus or a self-driving mode. How to determine whether the transportation mode is bus or self-driving in the case where the transportation mode is other mode is described below with reference to fig. 2.
As shown in fig. 2, the method of this embodiment includes: steps S202 to S206.
In step S202, the route characteristics of the public bus from the city where the start point is located to the city where the end point is located are determined based on the history sample data from the city where the start point is located to the city where the end point is located.
In some embodiments, the first grid set is formed by determining that each grid passes from the starting point to the city where the starting point is away from the starting point according to historical sample data, and the second grid set is formed by determining that each grid passes from the city where the terminal point is reached to the terminal point. Determining a starting point of the bus according to the occurrence frequency of each grid in the first grid set, and determining an end point of the bus according to the occurrence frequency of each grid in the second grid set;
for example, data of users in cities where the points O and D are located within a preset time (last 3 months) is extracted as historical sample data, and the users are extracted from the point O to the point DThe grid of the city in which the O point is located constitutes a set (including the O point), and is marked as Eo. Extracting the city where each user reaches D point to form a set (containing D point) by a grid from the D point, and recording the set as Ed. Will EoThe grid with the highest occurrence frequency is determined as the starting point of the bus, and E is setdThe grid with the highest frequency of occurrence is determined as the end point of the bus.
Further, the path feature points other than the start point and the end point of the bus are determined according to the frequency of occurrence of each grid in the first grid set and the frequency of occurrence of each grid in the second grid set. For example, a preset number of grids that pass after the start point of the bus in the first grid set and have the highest frequency of occurrence are used as path feature points, and a preset number of grids that pass before the start point of the bus in the second grid set and have the highest frequency of occurrence are used as path feature points. For example, the preset number is 5, and the set of path feature points is Gj(eo1，eo2、eo3、eo4、eo5、ed1、ed2、ed3、ed4、ed5) More than one set of path feature points.
In step S204, it is determined whether the transportation mode of the user in the travel is the bus based on the similarity between the grid information passed by the user in the travel and the route characteristics of the bus.
In some embodiments, the Jacard coefficient of the user passing through the feature point set and the path feature point set of the bus in the section of travel is determined as the similarity between the raster information passed through by the user in the section of travel and the path feature of the bus; the user passes through the feature point set in the travel section, and the feature point set is a set formed by the user passing through each grid from the starting point to the city where the starting point is away from the user, and passing through each grid from the city where the terminal point is reached to the terminal point. Determining that the traffic mode of the user in the travel is the bus under the condition that the similarity is greater than the similarity threshold; the similarity threshold is determined according to the Jacard coefficient of the first raster set and the Jacard coefficient of the second raster set corresponding to the historical sample data and the path feature point set of the public bus.
For example, the feature point set of the user is Hod＝Eo∪EdThe following formula can be used to calculate the Jaccard distance (Jaccard distance) of the user's route feature point set passing through the feature point set and the public bus in the section of the route.
Figure BDA0002253085660000151
The Jacard coefficients of the feature point set of each user and the path feature point set of the public bus in the historical sample data can also be obtained by calculation, the Jacard coefficients corresponding to each user are averaged, the average value and the minimum value are further averaged, and the obtained similarity threshold value is recorded as: f.
In step S206, in a case where the transportation style of the user on the trip is not the bus, it is determined that the transportation style of the user on the trip is self-driving.
When J (H) of the userod,Gj)<Γ, the user travel mode is: and (4) self-driving. When J (H) of the userod,Gj) When being more than or equal to gamma, the user trip mode is as follows: a public bus.
The method of the above embodiment determines the position information of the user at different times according to the signaling data of the user terminal, further determines the starting point and the ending point of a section of the journey of the user, and further determines the traffic mode of the user in the section of the journey according to the distance and the time of the starting point and the ending point and by combining the area characteristics corresponding to the starting point and the ending point. The method of the embodiment provides a data mining method for determining the travel transportation mode of the user according to the signaling data of the terminal of the user, and can determine the travel mode of the user more accurately.
According to the method of the embodiment, through correlation of different data, the fitted variables comprise the OD spacing distance of the sample, the moving speed per hour, the relation between the D point position and the traffic station and the like, and the cross-domain traffic mode of the user is judged by jointly modeling through the series of variables. The data has authenticity and validity based on the mobile phone data collected by telecommunication, and a large number of base stations for collecting data are built among cities, so that the data are collected timely and comprehensively covered domestically. The identification algorithm applies big data analysis technology and has reliability. The mobile phone data is rasterized, the site range is enlarged, the algorithms such as the space-time transition discrimination and the like have strict mathematical extrapolation processes, actual verification is obtained, and the accuracy is higher.
The present disclosure also provides a travel mode determination apparatus, which is described below with reference to fig. 3.
Fig. 3 is a block diagram of some embodiments of a travel pattern determining apparatus of the present disclosure. As shown in fig. 3, the apparatus 30 of this embodiment includes: a location determination module 310, a trip determination module 320, and a mode of transportation determination module 330.
A location determining module 310, configured to determine location information of the user at different times according to signaling data of the terminal of the user.
The trip determining module 320 is configured to determine a starting point and an ending point of a section of a trip of the user according to the position information of the user at different times.
In some embodiments, the travel determination module 320 is configured to determine grids to which the user's location information at different times belongs; wherein each grid comprises a region of a preset range; and determining the starting point and the end point of a section of journey of the user according to the time information of the user on each grid.
In some embodiments, the route determining module 320 is configured to update the location information of the user at different times to the central longitude and latitude of the corresponding grid, so as to obtain updated longitude and latitude at different times; determining the stay time of the same longitude and latitude as the stay time of the user on the corresponding grid according to each time corresponding to the same longitude and latitude; and respectively determining the two grids with the user stay time length exceeding the threshold as the starting point and the end point of a section of travel.
And the transportation mode determining module 330 is configured to determine a transportation mode of the user in the trip according to the distance between the starting point and the ending point, the time from the starting point to the ending point, and the area characteristics corresponding to the starting point and the ending point.
In some embodiments, the region characteristics corresponding to the start point and the end point include: the province where the starting point is located and the province where the terminal point is located, the city where the terminal point is located contains information of grids corresponding to sites, and the sites comprise at least one of railway stations and airports.
In some embodiments, the transportation mode determining module 330 is configured to determine a minimum circumscribed circle of a polygon corresponding to the station; the radius of the minimum circumscribed circle is extended by a preset length to obtain an updated circumscribed circle; and taking the grid covered by the updated circumscribed circle as the grid corresponding to the site.
In some embodiments, the transportation mode determination module 330 is configured to select three vertices from the vertices of the polygon corresponding to the station point; if the selected three vertexes are on the same straight line, taking a connecting line of two vertexes with the largest distance in the selected three vertexes as the diameter of the minimum circumscribed circle of the selected three vertexes to determine the minimum circumscribed circle of the selected three vertexes; and taking the largest one of the minimum circumcircles of any three vertexes corresponding to the station as the minimum circumcircle of the polygon corresponding to the station.
In some embodiments, the transportation mode determining module 330 is configured to determine the transportation mode of the user in the trip according to the distance between the starting point and the ending point, the time from the starting point to the ending point of the user, the area characteristics corresponding to the starting point and the ending point, and the area characteristics of the grid that the user passes through in the trip; the area characteristics corresponding to the starting point and the end point comprise: at least one of information of a grid corresponding to a site included in a city where the starting point is located, information of whether the starting point belongs to the grid corresponding to the site, information of a grid corresponding to a site included in a city where the ending point is located, and information of whether the ending point belongs to the grid corresponding to the site; the area characteristics of the grid that the user passes through in this segment of travel include: and whether the grid passed by the user in the trip belongs to the grid corresponding to the site or not.
In some embodiments, the transportation mode determination module 330 is configured to determine that the transportation mode of the user on the trip is an airplane, high-speed rail, train, or other mode; under the condition that the transportation mode is other modes, determining the path characteristics of the public bus from the city where the starting point is located to the city where the terminal point is located according to historical sample data from the city where the starting point is located to the city where the terminal point is located; determining whether the traffic mode of the user in the travel section is the public bus or not according to the similarity between the grid information passed by the user in the travel section and the path characteristics of the public bus; and in the case that the transportation mode of the user in the journey is not the public bus, determining that the transportation mode of the user in the journey is self-driving.
In some embodiments, the transportation mode determining module 330 is configured to determine that each grid passes through from the starting point to the city where the starting point is located according to historical sample data to form a first grid set, and determine that each grid passes through from the city where the terminal point is located to the terminal point to form a second grid set; determining a starting point of the bus according to the occurrence frequency of each grid in the first grid set, and determining an end point of the bus according to the occurrence frequency of each grid in the second grid set;
in some embodiments, the transportation mode determining module 330 is configured to determine the jaccard coefficient of the feature point set of the trip of the user and the path feature point set of the bus as the similarity between the raster information of the trip of the user and the path feature of the bus; the user passes through the feature point set in the section of travel, and the feature point set is a set formed by the user passing through each grid from the starting point to the city where the starting point is away from, and passing through each grid from the city where the terminal point is reached to the terminal point; determining that the traffic mode of the user in the travel is the bus under the condition that the similarity is greater than the similarity threshold; the similarity threshold is determined according to the Jacard coefficient of the first raster set and the Jacard coefficient of the second raster set corresponding to the historical sample data and the path feature point set of the public bus.
The travel mode determination apparatus in the embodiment of the present disclosure may be implemented by various computing devices or computer systems, and is described below with reference to fig. 4 and 5.
Fig. 4 is a block diagram of some embodiments of a travel pattern determining apparatus of the present disclosure. As shown in fig. 4, the apparatus 40 of this embodiment includes: a memory 410 and a processor 420 coupled to the memory 410, the processor 420 being configured to perform the method for determining a travel pattern in any of the embodiments of the present disclosure based on instructions stored in the memory 410.
Memory 410 may include, for example, system memory, fixed non-volatile storage media, and the like. The system memory stores, for example, an operating system, an application program, a Boot Loader (Boot Loader), a database, and other programs.
Fig. 5 is a block diagram of another embodiment of a travel mode determining apparatus according to the present disclosure. As shown in fig. 5, the apparatus 50 of this embodiment includes: memory 510 and processor 520 are similar to memory 410 and processor 420, respectively. An input output interface 530, a network interface 540, a storage interface 550, and the like may also be included. These interfaces 530, 540, 550 and the connections between the memory 510 and the processor 520 may be, for example, via a bus 560. The input/output interface 530 provides a connection interface for input/output devices such as a display, a mouse, a keyboard, and a touch screen. The network interface 540 provides a connection interface for various networking devices, such as a database server or a cloud storage server. The storage interface 550 provides a connection interface for external storage devices such as an SD card and a usb disk.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

Claims (13)

1. A travel mode determination method comprises the following steps:
determining the position information of a user at different moments according to the signaling data of the user terminal;
determining a starting point and an end point of a section of travel of the user according to the position information of the user at different moments;
and determining the traffic mode of the user in the travel according to the distance between the starting point and the end point, the time from the starting point to the end point of the user, and the area characteristics corresponding to the starting point and the end point.
2. The determination method according to claim 1,
the determining the starting point and the ending point of a section of travel of the user according to the position information of the user at different moments comprises:
determining grids to which the position information of the user at different moments belongs; wherein each grid comprises a region of a preset range;
and determining the starting point and the end point of a section of travel of the user according to the time information of the user in each grid.
3. The determination method according to claim 2,
the determining a starting point and an ending point of a section of travel of the user according to the time information of the user in each grid comprises:
updating the position information of the user at different moments into the central longitude and latitude of the corresponding grid, and obtaining the updated longitude and latitude at different moments;
determining the stay time of the same longitude and latitude as the stay time of the user on the corresponding grid according to each time corresponding to the same longitude and latitude;
and respectively determining the two grids with the user stay time length exceeding a threshold value as the starting point and the end point of a section of travel.
4. The determination method according to claim 2,
the region characteristics corresponding to the starting point and the end point comprise: the province where the starting point is located and the province where the terminal point is located, and the city where the terminal point is located contains grid information corresponding to sites, wherein the sites comprise at least one of railway stations and airports.
5. The determination method according to claim 4,
the grid corresponding to the station is determined by adopting the following method:
determining the minimum circumscribed circle of a polygon corresponding to the station;
extending the radius of the minimum circumscribed circle by a preset length to obtain an updated circumscribed circle;
and taking the grid covered by the updated circumcircle as the grid corresponding to the site.
6. The determination method according to claim 5,
the determining the minimum circumcircle of the polygon corresponding to the station includes:
selecting three vertexes from the vertexes of the polygon corresponding to the station point;
if the selected three vertexes are on the same straight line, taking a connecting line of two vertexes with the largest distance in the selected three vertexes as the diameter of the minimum circumscribed circle of the selected three vertexes to determine the minimum circumscribed circle of the selected three vertexes;
and taking the largest one of the minimum circumcircles of any three vertexes corresponding to the station as the minimum circumcircle of the polygon corresponding to the station.
7. The determination method according to claim 2,
the step of determining the traffic mode of the user in the travel according to the distance between the starting point and the end point, the time from the starting point to the end point of the user, and the area characteristics corresponding to the starting point and the end point comprises the following steps:
determining the traffic mode of the user in the section of the journey according to the distance between the starting point and the end point, the time from the starting point to the end point of the user, the area characteristics corresponding to the starting point and the end point and the area characteristics of the grids passed by the user in the section of the journey;
wherein, the region characteristics corresponding to the starting point and the end point comprise: the information of the grid corresponding to the site in the city where the starting point is located, the information of whether the starting point belongs to the grid corresponding to the site, the information of the grid corresponding to the site in the city where the end point is located, and the information of whether the end point belongs to at least one of the grids corresponding to the site; the area characteristics of the grid that the user passes through in the section of travel include: and the information whether the grid passed by the user in the section of the journey belongs to the grid corresponding to the site or not.
8. The determination method according to claim 2,
the determining the traffic mode of the user in the travel section comprises the following steps:
determining that the traffic mode of the user in the travel is an airplane mode, a high-speed rail mode, a train mode or other modes;
in the case that the transportation mode is other mode, the method further comprises the following steps:
according to historical sample data from the city where the starting point is located to the city where the end point is located, determining the path characteristics of the public bus from the city where the starting point is located to the city where the end point is located;
determining whether the traffic mode of the user in the travel section is the bus or not according to the similarity between the grid information passed by the user in the travel section and the path characteristics of the bus;
and determining that the traffic mode of the user in the journey is self-driving under the condition that the traffic mode of the user in the journey is not the public bus.
9. The determination method according to claim 8,
the determining, according to history sample data from the city where the starting point is located to the city where the ending point is located, the path feature of the public bus from the city where the starting point is located to the city where the ending point is located includes:
determining that the city where the starting point is located passes through each grid from the starting point to the city where the starting point is located according to the historical sample data to form a first grid set, and determining that the city where the terminal point is located passes through each grid from the city where the terminal point is located to the terminal point to form a second grid set;
and determining the starting point of the bus according to the appearance frequency of each grid in the first grid set, and determining the end point of the bus according to the appearance frequency of each grid in the second grid set.
10. The determination method according to claim 8,
the determining whether the transportation mode of the user in the travel section is the public bus according to the similarity between the grid information passed by the user in the travel section and the path characteristics of the public bus comprises the following steps:
determining the Jacard coefficient of the characteristic point set of the user passing through the section of travel and the path characteristic point set of the public bus as the similarity of the raster information of the user passing through the section of travel and the path characteristic of the public bus; the user passes through the feature point set in the travel, wherein the feature point set is a set formed by the user passing through each grid from the starting point to the city where the starting point is located and passing through each grid from the city where the ending point is located to the ending point;
determining that the traffic mode of the user in the travel is the bus under the condition that the similarity is larger than a similarity threshold value;
and determining the similarity threshold value according to the Jacard coefficient of the first raster set and the Jacard coefficient of the second raster set corresponding to the historical sample data and the path feature point set of the public bus.
11. A travel mode determination device comprises;
the position determining module is used for determining the position information of the user at different moments according to the signaling data of the terminal of the user;
the trip determining module is used for determining a starting point and an end point of a section of trip of the user according to the position information of the user at different moments;
and the traffic mode determining module is used for determining the traffic mode of the user in the section of the journey according to the distance between the starting point and the end point, the time from the starting point to the end point of the user and the area characteristics corresponding to the starting point and the end point.
12. An apparatus for determining a travel pattern, comprising:
a processor; and
a memory coupled to the processor for storing instructions that, when executed by the processor, cause the processor to perform a method of determining a travel pattern according to any one of claims 1-10.
13. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the steps of the method of any one of claims 1-10.
CN201911041956.5A 2019-10-30 2019-10-30 Travel mode determination method and device and computer readable storage medium Pending CN112747767A (en)

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CN106327000A (en) * 2015-06-30 2017-01-11 阿里巴巴集团控股有限公司 Method and system for identifying trip mode
CN107040894A (en) * 2017-04-21 2017-08-11 杭州市综合交通研究中心 A kind of resident trip OD acquisition methods based on mobile phone signaling data
CN110377687A (en) * 2019-07-26 2019-10-25 智慧足迹数据科技有限公司 User's trip mode method of discrimination, device and server

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110178702A1 (en) * 2010-01-20 2011-07-21 Sony Ericsson Mobile Communications Ab Optimum travel times
CN106327000A (en) * 2015-06-30 2017-01-11 阿里巴巴集团控股有限公司 Method and system for identifying trip mode
CN106197458A (en) * 2016-08-10 2016-12-07 重庆邮电大学 A kind of cellphone subscriber's trip mode recognition methods based on mobile phone signaling data and navigation route data
CN107040894A (en) * 2017-04-21 2017-08-11 杭州市综合交通研究中心 A kind of resident trip OD acquisition methods based on mobile phone signaling data
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