CN109788437B

CN109788437B - Travel route management system and method

Info

Publication number: CN109788437B
Application number: CN201910003758.3A
Authority: CN
Inventors: 胡舜耕
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2019-01-03
Filing date: 2019-01-03
Publication date: 2021-02-02
Anticipated expiration: 2039-01-03
Also published as: CN109788437A

Abstract

The embodiment of the invention discloses a travel route management system and a travel route management method. Wherein, this system includes: the system comprises an acquisition device, a data platform and a cloud platform, wherein the acquisition device is used for: packaging the acquired mobile phone signaling data to obtain a signaling data packet, and sending the signaling data packet to a data platform; the data platform is to: preprocessing a received signaling data packet to obtain travel data, receiving an extraction request sent by a cloud platform, and sending the travel data to the cloud platform according to the extraction request; the cloud platform is used for: and sending an extraction request to the data platform, processing the received travel data to obtain an individual travel route set and/or a group travel route, and extracting information of the row data carried in the extraction request. Through the technical scheme provided by the embodiment, the travel condition of the user corresponding to the mobile phone is obtained according to the related data of the mobile phone, so that the traffic route and the like are planned fundamentally, and the technical defect of inconvenient travel is overcome fundamentally.

Description

Travel route management system and method

Technical Field

The embodiment of the invention relates to the technical field of data processing, in particular to a travel route management system and method.

Background

With the development of science and technology, on the one hand, the mobile phone becomes an essential product in daily life of people. And the applications of the mobile phone are also increasing continuously. For example, the upcoming arrival time of the bus is known through a mobile phone. On the other hand, the number of automobiles (including buses and private cars) is gradually increased, and the traffic congestion is more serious.

However, in the prior art, although the mobile phone enables people to relatively accurately master the arrival time of the vehicle, or learn which particular road is relatively smooth, so as to facilitate the traveling of people. However, in the process of implementing the invention, the inventor finds that at least the following problems exist:

people can only passively learn the arrival time of the vehicle through a mobile phone or passively learn the road congestion situation, but cannot realize the fundamental planning of traffic routes and the like according to the related data of the mobile phone, and still cannot fundamentally solve the problem of inconvenient traveling.

Disclosure of Invention

In order to solve the above technical problems, embodiments of the present invention provide a travel route management system and method.

According to an aspect of an embodiment of the present invention, an embodiment of the present invention provides a travel route management system, including: the system comprises an acquisition device, a data platform and a cloud platform, wherein,

the acquisition means is for: the method comprises the steps of packaging acquired mobile phone signaling data to obtain a signaling data packet, and sending the signaling data packet to a data platform, wherein the signaling data comprises: location area code LAC, mobile phone number, time and speed;

the data platform is to: preprocessing the received signaling data packet to obtain travel data, receiving an extraction request sent by the cloud platform, and sending the travel data to the cloud platform according to the extraction request;

the cloud platform is to: and sending the extraction request to the data platform, and processing the received travel data to obtain an individual travel route set and/or a group travel route, wherein the extraction request carries information for extracting the travel data.

The embodiment provides that: the method comprises the steps that an obtaining device obtains a signaling data packet according to mobile phone signaling data, the signaling data packet is sent to a data platform, the data platform preprocesses the signaling data packet to obtain trip data, the trip data are sent to a cloud platform according to an obtaining request, the cloud platform receives trip data corresponding to an extracting request and processes the trip data to obtain an individual trip route set and/or a group trip route, the trip condition of a user corresponding to a mobile phone is obtained according to mobile phone related data, planning of traffic routes and the like is achieved fundamentally, and therefore the technical defect of inconvenience in trip is solved fundamentally.

Further, the acquisition means comprises: LAC register, LAC monitor, speed sensor, data acquirer, and data transmitter, wherein,

the LAC register is used for: storing an initial location area code LAC;

the LAC monitor is configured to: monitoring the location area code LAC in the SIM card corresponding to the mobile phone number, updating the initial location area code LAC according to the location area code LAC when the location area code LAC is different from the initial location area code LAC, and sending the location area code LAC to the data acquirer;

the speed sensor is used for: acquiring the speed of the mobile phone corresponding to the SIM card, and sending the speed to the data acquirer;

the data obtainer is to: acquiring the location area code LAC, the mobile phone number, the speed and the time corresponding to the location area code LAC, packaging the location area code LAC, the mobile phone number, the speed and the time to obtain the signaling data packet, and sending the signaling data packet to the data sender;

the data transmitter is configured to: and sending the signaling data packet to the data platform.

Through the technical scheme provided by the embodiment, the technical effect of efficiently and accurately acquiring the mobile phone signaling data is achieved.

Further, the data platform comprises: a data listener, a data processor, wherein,

the data listener is configured to: monitoring the signaling data packet sent by the data sender, analyzing the signaling data packet to obtain analysis data, and sending the analysis data to the data processor;

the data processor is configured to: and integrating the analyzed data to obtain the trip data, and sending the trip data to the cloud platform after receiving the extraction request.

By the technical scheme provided by the embodiment, the signaling data packet can be timely acquired, so that the technical effect of improving the data processing efficiency is achieved.

Further, the cloud platform is specifically configured to:

extracting a target trip data set corresponding to a target individual from the trip data, wherein the trip data comprises the target trip data set;

fitting the target trip data set by taking a preset target date as a unit to obtain a fitting target trip route set corresponding to the target date;

and fitting the fitting target travel route set by taking a preset target time period as a unit to obtain an individual travel route set.

Further, the cloud platform is further specifically configured to:

if the first trip data and the second trip data corresponding to the target individual are adjacent data in the trip data, the first trip data comprises: the first mobile phone number, LACi, time i and speed i, and the second trip data comprises: and when the difference value between the time j and the time i is greater than the quotient of the distance Sij and a preset speed Vo, moving the second trip data out of the fitting target to form a route set.

Further, the cloud platform is further configured to:

processing the individual outgoing route set according to an inverted method to obtain an inverted individual outgoing route set;

according to a fitting method, if the first K-1 travel routes of the inverted individual travel route set are fitted and the fitting results of the first K-1 travel routes comprise more than half of elements in the kth travel route, nesting and reducing the elements which are not included in the fitting results of the first K-1 travel routes and belong to the kth travel route into the fitting results of the first K-1 travel routes to obtain a nested and reduced sequence;

and calculating the support degree according to the nested abbreviated sequence to obtain an individual travel route.

Further, the cloud platform is further configured to:

when the individual travel route set comprises a first element in the nested abbreviated sequence, adding a preset support threshold to the support corresponding to the first element, and when the individual travel route set does not comprise a second element in the nested abbreviated sequence, setting the support corresponding to the second element as the support threshold so as to obtain the individual travel route.

Further, the cloud platform is further specifically configured to:

obtaining individual travel routes corresponding to each individual to obtain a target individual travel route set;

and processing the target individual travel route set according to a key path analysis method to obtain the group travel route.

Further, the cloud platform is specifically configured to:

comparing the support degree corresponding to any element in the target individual travel route set with a preset integer threshold to obtain a comparison result, when the comparison result is greater than or equal to the preset integer threshold, retaining the element corresponding to the comparison result, and when the comparison result is smaller than the preset integer threshold, deleting the element corresponding to the comparison result so as to obtain an individual travel key route set;

and processing the individual trip key route set by a key route analysis method to obtain the group trip route.

Further, the cloud platform is further configured to:

and planning the bus route according to the individual travel route set and/or the group travel route to obtain a target bus route.

According to another aspect of the embodiments of the present invention, there is provided a travel route management method based on the system in any one of the above embodiments, the method including:

the method comprises the steps that an acquisition device packs acquired mobile phone signaling data to obtain a signaling data packet, and sends the signaling data packet to a data platform, wherein the signaling data comprises: location area code LAC, mobile phone number, time and speed;

the data platform preprocesses the received signaling data packet to obtain trip data, receives an extraction request sent by a cloud platform, and sends the trip data to the cloud platform according to the extraction request;

the cloud platform sends the extraction request to the data platform, and processes the received travel data to obtain an individual travel route set and/or a group travel route, wherein the extraction request carries information for extracting the travel data.

Further, the acquiring device packages the acquired mobile phone signaling data to obtain a signaling data packet, and sends the signaling data packet to a data platform, and the acquiring device specifically includes:

the LAC register stores an initial location area code LAC;

the LAC monitor monitors the location area code LAC in the SIM card corresponding to the mobile phone number, updates the initial location area code LAC according to the location area code LAC when the location area code LAC is different from the initial location area code LAC, and sends the location area code LAC to the data acquirer;

the speed sensor acquires the speed of the mobile phone corresponding to the SIM card and sends the speed to the data acquirer;

the data acquirer acquires the location area code LAC, the mobile phone number, the speed and the time corresponding to the location area code LAC, packs the location area code LAC, the mobile phone number, the speed and the time to obtain the signaling data packet, and sends the signaling data packet to a data sender;

and the data transmitter transmits the signaling data packet to the data platform.

Further, the data platform preprocesses the received signaling data packet to obtain trip data, receives an extraction request sent by a cloud platform, and sends the trip data to the cloud platform according to the extraction request, which specifically includes:

the data listener listens the signaling data packet sent by the data sender, analyzes the signaling data packet to obtain analysis data, and sends the analysis data to a data processor;

and the data processor integrates the analyzed data to obtain the trip data, and sends the trip data to the cloud platform after receiving the extraction request.

Further, the cloud platform processes the received travel data to obtain an individual travel route set, which specifically includes:

Further, the method further comprises:

if the first trip data and the second trip data corresponding to the target individual are adjacent data in the trip data, the first trip data comprises: the first mobile phone number, LACi, time i and speed i, and the second trip data comprises: and the cloud platform acquires the distance Sij between the base station corresponding to the LACi and the base station corresponding to the LCaj, and when the difference value between the time j and the time i is greater than the quotient of the distance Sij and a preset speed Vo, the second trip data is moved out of the fitting target to form a route set.

Further, the method further comprises:

the cloud platform processes the individual outgoing route set according to an inverted method to obtain an inverted individual outgoing route set;

according to a fitting method, if the first K-1 travel routes of the inverted individual travel route set are fitted, and the fitting results of the first K-1 travel routes comprise more than half of elements in the kth travel route, the cloud platform does not comprise the fitting results of the first K-1 travel routes, and the elements belonging to the kth travel route are nested and reduced to the fitting results of the first K-1 travel routes, so that a nested reduction sequence is obtained;

and the cloud platform calculates the support degree according to the nested abbreviated sequence to obtain an individual travel route.

Further, the cloud platform performs fitting processing according to the nested abbreviated sequence to obtain an individual travel route, and the method specifically includes:

Further, the cloud platform processes the received travel data to obtain a group travel route, which specifically includes:

Further, the processing the target individual travel route set according to a key path analysis method to obtain the group travel route specifically includes:

comparing the support degree corresponding to any element in the target individual travel route set with a preset integer threshold value to obtain a comparison result, when the comparison result is greater than or equal to the preset integer threshold value, reserving the element corresponding to the comparison result by the cloud platform, and when the comparison result is smaller than the preset integer threshold value, deleting the element corresponding to the comparison result so as to obtain an individual travel key route set;

and the cloud platform processes the individual trip key route set through a key route analysis method to obtain the group trip route.

Further, the method further comprises:

and the cloud platform plans the bus routes according to the individual travel route set and/or the group travel route to obtain a target bus route.

Drawings

Fig. 1 is a block diagram of a travel route management system according to an embodiment of the present invention;

fig. 2 is a block diagram of a travel route management system according to another embodiment of the present invention;

fig. 3 is a schematic flow chart of a travel route management method according to an embodiment of the present invention;

fig. 4 is a flowchart illustrating a travel route management method according to another embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

The embodiment of the invention provides a travel route management system and method.

According to an aspect of an embodiment of the present invention, an embodiment of the present invention provides a travel route management system.

The first embodiment:

referring to fig. 1, fig. 1 is a block diagram of a travel route management system according to an embodiment of the present invention.

As shown in fig. 1, the system includes: the system comprises an acquisition device, a data platform and a cloud platform, wherein,

the acquisition means is for: the method comprises the steps of packaging the acquired mobile phone signaling data to obtain a signaling data packet, and sending the signaling data packet to a data platform, wherein the signaling data comprises the following steps: location area code LAC, cell phone number, time and speed.

Fig. 2 is a block diagram of a travel route management system according to another embodiment of the present invention.

As can be seen from fig. 1 and 2, the acquiring apparatus includes: LAC register, LAC monitor, speed sensor, data acquirer, and data transmitter, wherein,

the LAC register is used to: the initial location area code LAC is stored.

The LAC register is initialized to be empty, that is, when the mobile phone is turned on, the LAC register does not have any location area code LAC. After the mobile phone is turned on, the LAC register has the initial location area code LAC. When the mobile phone is powered off, if the mobile phone is powered off, the LAC register can be automatically cleared.

The LAC monitor is used to: and monitoring a location area code LAC in the SIM card corresponding to the mobile phone number, updating the initial location area code LAC according to the location area code LAC when the location area code LAC is different from the initial location area code LAC, and sending the location area code LAC to the data acquirer.

Specifically, the method comprises the following steps: and when the mobile phone is started, the LAC monitor is started, and the LAC monitor monitors the location area code LAC in the SIM card according to a preset time interval, such as 0.1 s. It should be noted that the time interval can be set according to actual requirements, and 0.1s is only an exemplary illustration and is not to be construed as a limitation to the protection scope of the present embodiment. And after monitoring the location area code LAC, the LAC monitor compares the location area code LAC with the initial location area code LAC and compares whether the location area code LAC is consistent with the initial location area code LAC. And if the location area code LAC is not consistent with the initial location area code LAC, updating the initial location area code LAC by using the location area code LAC. Namely, the location area code LAC is replaced by the initial location area code LAC, and the location area code LAC is sent to the data acquirer. Of course, a comparison result that the location area code LAC is consistent with the initial location area code LAC may be obtained, and the location area code LAC may be directly sent to the data acquirer without updating.

The speed sensor is used for: and acquiring the speed of the mobile phone corresponding to the SIM card, and sending the speed to the data acquirer.

The speed sensor obtains the speed of the mobile phone, namely the moving speed of the mobile phone corresponding to the mobile phone number.

The data obtainer is to: and acquiring the location area code LAC, the mobile phone number, the speed and the time corresponding to the location area code LAC, packaging the location area code LAC, the mobile phone number, the speed and the time to obtain a signaling data packet, and sending the signaling data packet to a data sender.

The data transmitter is configured to: and sending the signaling data packet to a data platform.

The data platform is to: the method comprises the steps of preprocessing a received signaling data packet to obtain trip data, receiving an extraction request sent by a cloud platform, and sending the trip data to the cloud platform according to the extraction request.

As can be seen from fig. 1 and 2, the data platform includes: a data listener, a data processor, wherein,

the data listener is used for: and intercepting a signaling data packet sent by the data sender, analyzing the signaling data packet to obtain analysis data, and sending the analysis data to the data processor.

The data processor is for: and integrating the analyzed data to obtain the trip data, and sending the trip data to the cloud platform after receiving the extraction request.

Wherein, the data processor integrates the analysis data specifically comprises: the data processing module processes the analysis data according to a preset rule, such as: and adjusting the format of the analysis data, and making a table according to the adjusted analysis data so as to obtain the travel data. Of course, the data processor integrating the parsed data further includes: storing and keeping the analysis data.

The cloud platform is used for: and sending an extraction request to a data platform, processing the received travel data to obtain an individual travel route set and/or a group travel route, and extracting information of the row data carried in the extraction request.

It should be noted that the data platform and the cloud platform may be integrated into one platform.

Second embodiment:

based on the first embodiment, in this embodiment, the cloud platform is specifically configured to:

and extracting a target trip data set corresponding to the target individual from trip data, wherein the trip data comprises the target trip data set.

And fitting the target trip data set by taking a preset target date as a unit to obtain a fitting target trip route set corresponding to the target date.

And fitting the fitting target outgoing route set by taking a preset target time period as a unit to obtain an individual outgoing route set.

Specifically, the method comprises the following steps: the cloud platform can be divided into two functional modules, one functional module is an individual outgoing route fitting module, and the cloud platform obtains an individual outgoing route set through the functional modules. The other functional module is a group travel route fitting module, and the cloud platform obtains a group travel route through the functional module. The functions of the individual travel route fitting module are explained in detail:

and extracting a travel data set (namely a target travel data set) of the same mobile phone number (namely the target individual) from all the travel data. The target travel data set comprises all the travel data of the mobile phone number in the mobile phone number use period. Setting the date, such as 1/2017 to 12/31/2012, and setting the time period, such as 7 am to 8 am. And selecting travel data sets within a set date and a set time period T from all travel data sets corresponding to the mobile phone number. Arranging travel data sets with set dates and time periods T according to time sequence to obtain a standard travel data column { (mobile phone number, LACi, time i, speed i) | (i ═ 1,2,.. once.n) }. Let { (cell phone number, LACi, time i, speed i) | (i ═ 1,2,.. once, n) } be the reference individual trip fitting route. Let (cell phone number, LACi, time i, speed i) and (cell phone number, LACj, time j, speed j) be the adjacent trip data in the standard trip data column, i.e. at time i the smartphone moves from LACi to LACj, the moving speed is speed i. The base station distance Sij from LACi to LACj is obtained from the mobile communication network operator, and the recognized walking speed is set as v 0. If "time j-time i" is greater than Sij/v0, all travel data (cell phone number, LACj, time j, speed j) after time j (inclusive) are removed from the reference individual travel fitting route. Preferably, the "time j-time i" is much larger than Sij/v0, for example, if the "time j-time i" is larger than three times Sij/v0, all the travel data (cell phone number, LACj, time j, speed j) after time j (inclusive) are removed from the reference individual travel fitting route. If { (cell phone number, LACi, time i, speed i) | (i ═ 1,2,.. said., m) } no removable travel data, it is the individual travel fitted route within the period T of "date". Repeating the above operations, finding an individual trip fitting route of the mobile phone number in a time period T of a set date, and obtaining an individual trip quasi-combining route set { (date { (mobile phone number, LACi, time i, speed i) | (i ═ 1,2, ·.. times, m) } in the time period T of the set date. An individual outgoing route set { (date { (mobile phone number, LACi, time i, speed i) | (i ═ 1,2,........, m) }) is obtained based on an individual outgoing route virtual route set { (date, { (mobile phone number, LACi, time i, speed i) }) }.

The third embodiment:

the present embodiment is based on the second embodiment, and in the present embodiment, the cloud platform is further configured to:

and processing the individual outgoing route set according to an inverted method to obtain the inverted individual outgoing route set.

According to the fitting method, if the first K-1 travel routes of the inverted individual travel route set are fitted, and the fitting results of the first K-1 travel routes comprise more than half of elements in the kth travel route, the elements which are not included in the fitting results of the first K-1 travel routes and belong to the kth travel route are nested and reduced to the fitting results of the first K-1 travel routes, and a nested reduced sequence is obtained.

And calculating the support degree according to the nested abbreviated sequence to obtain the individual travel route.

Specifically, the method comprises the following steps: an outgoing route set { ((date, T), a mobile phone number, (LACi ═ 1,2, ·.., m)) } corresponding to a certain mobile phone number of a time period T is extracted from the individual outgoing route set. Fitting an individual travel route of an individual at the time period T by adopting a back fitting method: the individual outgoing route set is { ((date, T), a mobile phone number, (LACi | i ═ 1,2,. once.. m)) }, and the individual outgoing route set is arranged in reverse order according to the date sequence to obtain the inverted individual outgoing route set { (LACij | i ═ 1,2,. once.. so., mj) | j ═ 1,2,. once.. so., n }. And identifying the individual travel route of the individual in the time period T by L (mobile phone number, T). Let L (cell phone number, T) have an initial value of ((LACi1, 1) | i ═ 1, 2. Wherein 1 in (LACi1, 1) is called the support of LACi 1. Setting the front k-1 individual travel routes in the set of inverted individual travel routes to obtain: l (cell phone number, T) ((LACx, Countx) | x ═ 1, 2. Among them, Countx in (LACx, Countx) is called a supporting degree of LACx. The k-th individual travel route in the inverted individual travel route set is (LACik | i ═ 1, 2.... mk), and the method of fitting the k-th individual travel route is as follows: if more than half of the elements in the set { LACik | i ═ 1, 2.... ·, mk } are not in the set { LACx | x ═ 1, 2.... ·, p }, then the individual travel route of the individual at time period T is fitted to be: l (cell phone number, T) ((LACx, Countx) | x ═ 1, 2. If more than half of the elements in the set { LACik | i ═ 1, 2.. once, mk }, inclusive, are in the set { LACx | x ═ 1, 2.. once, p }, then a nested reduction is performed: first, (LACik | i ═ 1, 2.... mk) is nested into (LACx | x ═ 1, 2.... 7., p), which is the "merging" of two sequences, keeping the original order, and keeping one of the same elements, resulting in a nested sequence: (lacyy ═ 1, 2.... q). Next, the new sequence (lacyy ═ 1,2,.. q) is abbreviated. The new sequence was compared to the sequence (LACx | x ═ 1, 2.... p), and there were three cases as a result of the comparison: (1) there are several elements at the left end of LAC1, if there is only a single element, this element is retained, placed at the left end of LAC1, with its support set to 1; if there are multiple elements, all these elements are reduced to a new element, i.e. the set of all these elements is the new element, which is placed at the left end of LAC1, and its support degree is set to 1. (2) If only a single element exists, the element is reserved and is placed at the right end of the LACp, and the support degree of the element is set to be 1; if there are multiple elements, all these elements are reduced to a new element, i.e. the set of all these elements is the new element, and is placed at the right end of LACp, and its support degree is set to 1. (3) Several elements exist between the LACx and the LACx +1, if only a single element exists, the element is reserved and is placed between the LACx and the LACx +1, and the support degree is set to be 1; if there are multiple elements, all these elements are reduced to a new element, i.e. the set of all these elements is the new element, which is placed between LACx and LACx +1, with its support set to 1. After the above reduction, a nested reduction sequence is obtained, and is denoted as (LACz | z ═ 1, 2. And finally, calculating the support degree of the elements in the nested abbreviated sequence to obtain a fitting result. If the element LACz in the nested abbreviated sequence is the element LACx in { LACx | x ═ 1, 2.... times, p }, its support is Countz ═ Countx + 1; if the element LACz in the nested abbreviated sequence is a newly generated element, the support is 1. And (3) integrating the nested abbreviated sequence and the support degree to obtain an individual travel route of the fitted individual in the time period T: l (mobile phone number, T) ((LACz, Countz) | z ═ 1, 2.

The fourth embodiment:

based on the third embodiment, in this embodiment, the cloud platform is specifically configured to:

and obtaining the individual travel route corresponding to each individual to obtain a target individual travel route set.

And processing the target individual travel route set according to a key path analysis method to obtain group travel routes.

Specifically, the method comprises the following steps: acquiring an individual outgoing route set of each individual of a group in a time period T as follows: { (No. x, ((LACxz, Countxz) | z ═ 1,2, · r)) | x ═ 1,2, · s }. Wherein for any x, ((LACxz, Countxz) | z ═ 1, 2.. said., r) represents the individual travel route of the individual identified by the cell phone number no.x at time period T. An integer threshold is preset, the integer threshold is set according to actual requirements, and the integer threshold is N. For any element (LACxz, Countxz) in the individual travel route set for time period T, if Countxz ≧ N, the element LACxz is retained, otherwise, the element LACxz is deleted. After processing, obtaining the individual trip key route set of the time period T from the individual trip route set of the time period T: { (no.x, (LACxz | z ═ 1, 2.·, r)) | x ═ 1, 2.·, s }. Wherein, x, z and s, r thereof are consistent with the symbols in the individual travel route set of the time period T, but without loss of generality. And acquiring the group travel route of the time interval T by using a disjunction method. Removing the no.x from { (no.x, (LACxz | z ═ 1, 2.·, r)) | x ═ 1, 2.·, s) }, yielding: { (LACxz | z ═ 1, 2.·, r) | x ═ 1, 2.·, s) }. Acquiring elements existing in the individual travel critical route (LACxz | z ═ 1, 2.... r) of all time intervals T, and keeping the sequence of the elements in the original individual travel route to obtain: (LACi ═ 1, 2...., m), which is the group travel route for time period T.

Fifth embodiment:

the present embodiment is based on any one of the first to fourth embodiments. In this embodiment, the cloud platform is further configured to:

and planning the bus routes according to the individual travel route sets and/or the group travel routes to obtain a target bus route.

And when the bus route does not exist, planning the bus route directly according to the individual travel route set and/or the group travel route to obtain a target bus route.

And when the initial bus route exists, adjusting the initial bus route according to the individual travel route set and/or the group travel route to obtain a target bus route.

According to another aspect of the embodiment of the present invention, there is further provided a travel route management method based on the system in any one of the above embodiments.

Referring to fig. 3, fig. 3 is a flowchart illustrating a travel route management method according to an embodiment of the present invention.

As shown in fig. 3, the method includes:

s100: the obtaining device packs the obtained mobile phone signaling data to obtain a signaling data packet, and sends the signaling data packet to a data platform, wherein the signaling data comprises: location area code LAC, cell phone number, time and speed.

As can be seen from fig. 3 and 4, S100 specifically includes:

s110: the LAC register stores an initial location area code LAC.

S120: the LAC monitor monitors a location area code LAC in the SIM card corresponding to the mobile phone number, updates the initial location area code LAC according to the location area code LAC when the location area code LAC is different from the initial location area code LAC, and sends the location area code LAC to the data acquirer.

S130: and the speed sensor acquires the speed of the mobile phone corresponding to the SIM card and sends the speed to the data acquirer.

S140: the data acquirer acquires the location area code LAC, the mobile phone number, the speed and the time corresponding to the location area code LAC, packs the location area code LAC, the mobile phone number, the speed and the time to obtain a signaling data packet, and sends the signaling data packet to the data transmitter.

S150: and the data transmitter transmits the signaling data packet to the data platform.

S200: the data platform preprocesses the received signaling data packet to obtain the trip data, receives an extraction request sent by the cloud platform, and sends the trip data to the cloud platform according to the extraction request.

As can be seen from fig. 3 and 4, S200 specifically includes:

s210: the data listener listens to a signaling data packet sent by the data sender, analyzes the signaling data packet to obtain analysis data, and sends the analysis data to the data processor.

S220: and the data processor integrates the analyzed data to obtain the trip data, and sends the trip data to the cloud platform after receiving the extraction request.

S300: the cloud platform sends an extraction request to the data platform, processes the received travel data to obtain an individual travel route set and/or a group travel route, and the extraction request carries information of extracting row data.

In a possible implementation scheme, S300 specifically includes:

s310: the cloud platform extracts a target trip data set corresponding to a target individual from trip data, wherein the trip data comprises the target trip data set;

s320: the cloud platform performs fitting processing on the target trip data set by taking a preset target date as a unit to obtain a fitting target trip route set corresponding to the target date;

s330: and the cloud platform performs fitting processing on the fitting target outgoing route set by taking a preset target time period as a unit to obtain an individual outgoing route set.

In one possible implementation, after S320, the method further includes:

s340: if the first trip data and the second trip data corresponding to the target individual are adjacent data in the trip data, the first trip data comprises: the first mobile phone number, LACi, time i and speed i, the second trip data includes: and when the difference value between the time j and the time i is greater than the quotient of the distance Sij and the preset speed Vo, the second trip data is moved out of the fitting target to go out the route set.

In one possible implementation, after S330, the method further includes:

s1: the cloud platform processes the individual outgoing route set according to an inverted method to obtain an inverted individual outgoing route set;

s2: according to the fitting method, if the first K-1 travel routes of the inverted individual travel route set are fitted, and the fitting results of the first K-1 travel routes comprise more than half of elements in the kth travel route, the cloud platform is not included in the fitting results of the first K-1 travel routes, and the elements belonging to the kth travel route are nested and reduced to the fitting results of the first K-1 travel routes, so that a nested reduction sequence is obtained;

s3: and the cloud platform calculates the support degree according to the nested abbreviated sequence to obtain the individual travel route.

Wherein S3 includes: when the individual travel route set comprises a first element in the nested abbreviated sequence, the cloud platform adds a preset support threshold to the support corresponding to the first element, and when the individual travel route set does not comprise a second element in the nested abbreviated sequence, the cloud platform sets the support corresponding to the second element as the support threshold so as to obtain the individual travel route.

In a possible implementation scheme, S300 specifically includes:

s350: the cloud platform acquires individual travel routes corresponding to each individual to obtain a target individual travel route set;

s360: and the cloud platform processes the target individual travel route set according to a key path analysis method to obtain group travel routes.

Wherein, S360 includes: the cloud platform compares the support degree corresponding to any element in the target individual travel route set with a preset integer threshold value to obtain a comparison result, when the comparison result is greater than or equal to the preset integer threshold value, elements corresponding to the comparison result are reserved, when the comparison result is smaller than the preset integer threshold value, the elements corresponding to the comparison result are deleted to obtain a travel key route set, and the individual travel key route set is processed through a key route analysis method to obtain group travel routes.

In one possible implementation, after S300, the method further includes:

s370: and the cloud platform plans the bus routes according to the individual travel route set and/or the group travel route to obtain a target bus route.

The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

It should also be understood that, in the embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A travel route management system, characterized in that the system comprises: the system comprises an acquisition device, a data platform and a cloud platform, wherein,

the cloud platform is to: sending the extraction request to the data platform, and processing the received travel data to obtain an individual travel route set and/or a group travel route, wherein the extraction request carries information for extracting the travel data;

the cloud platform is specifically configured to:

2. A travel route management system according to claim 1, characterized in that said acquisition means comprises: LAC register, LAC monitor, speed sensor, data acquirer, and data transmitter, wherein,

the LAC register is used for: storing an initial location area code LAC;

3. A travel route management system according to claim 2, characterised in that the data platform comprises: a data listener, a data processor, wherein,

4. A travel route management system according to claim 3, wherein the cloud platform is further specifically configured to:

5. An travel route management system according to claim 4, wherein the cloud platform is further configured to:

according to a fitting method, if the first K-1 travel routes of the inverted individual travel route set are fitted and the fitting results of the first K-1 travel routes comprise more than half of elements in the kth travel route, nesting and reducing the elements which are not included in the fitting results of the first K-1 travel routes and belong to the kth travel route into the fitting results of the first K-1 travel routes to obtain a nested and reduced sequence; the first K-1 travel route fitting results are a set { LACx | x ═ 1,2,.., p }, the K-th travel route is a set { LACik | i ═ 1,2,.., mk }, and the element is any element in the set { LACik | i ═ 1,2,..., mk };

6. An travel route management system according to claim 5, wherein the cloud platform is further configured to:

when the individual travel route set comprises a first element in the nested abbreviated sequence, adding a preset support threshold to the support corresponding to the first element, and when the individual travel route set does not comprise a second element in the nested abbreviated sequence, setting the support corresponding to the second element as the support threshold so as to obtain the individual travel route; the individual outgoing route set is a set { LACx | x ═ 1,2,...., p }, and the nested abbreviated sequence is a set (LACz | z ═ 1,2,... r }, where a plurality of first elements are provided, a preset support threshold is added to the support corresponding to each first element, and where a plurality of second elements are provided, a preset support threshold is set to the support corresponding to each second element.

7. An travel route management system according to any one of claims 5 to 6, wherein the cloud platform is further specifically configured to:

8. The travel route management system according to claim 7, wherein the cloud platform is specifically configured to:

9. A travel route management method, characterized in that the method is based on the system of any one of claims 1-8, the method comprising:

the cloud platform sends the extraction request to the data platform, and processes the received travel data to obtain an individual travel route set and/or a group travel route, wherein the extraction request carries information for extracting the travel data;

the cloud platform processes the received travel data to obtain an individual travel route set, and the method specifically includes:

and fitting the fitted target travel route set by taking a preset target time period as a unit to obtain the individual travel route set.

10. The travel route management method according to claim 9, wherein the obtaining device packages the obtained mobile phone signaling data to obtain a signaling data packet, and sends the signaling data packet to a data platform, specifically comprising:

the LAC register stores an initial location area code LAC;

the LAC monitor monitors the location area code LAC in the SIM card corresponding to the mobile phone number, updates the initial location area code LAC according to the location area code LAC when the location area code LAC is different from the initial location area code LAC, and sends the location area code LAC to a data acquirer;

11. The method for managing a travel route according to claim 10, wherein the data platform preprocesses the received signaling data packet to obtain travel data, receives an extraction request sent by a cloud platform, and sends the travel data to the cloud platform according to the extraction request, specifically including: