CN111199644A - Method and system for automatically fitting people and vehicles - Google Patents
Method and system for automatically fitting people and vehicles Download PDFInfo
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- CN111199644A CN111199644A CN202010010671.1A CN202010010671A CN111199644A CN 111199644 A CN111199644 A CN 111199644A CN 202010010671 A CN202010010671 A CN 202010010671A CN 111199644 A CN111199644 A CN 111199644A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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Abstract
The invention provides a method and a system for automatically fitting a man and a vehicle, which are used for acquiring position information of a card port and vehicle passing data in an appointed area, and acquiring information that an appointed mobile phone number passes through a base station in a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station; taking the unique identification code of the base station as a main key, and counting time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station; carrying out duplicate removal processing on the introduced base station according to the unique identification code to obtain a base station set, and then carrying out traversal processing on the base station set to remove the invalid base station; grouping effective base stations according to the grouping quantity set during data fitting of each introduced base station, and performing intersection processing on a plurality of obtained sets to obtain vehicle sets which simultaneously appear near each group of randomly extracted base stations; and merging the vehicle sets obtained by repeatedly setting the times, counting the occurrence times of each vehicle, and determining the vehicle with the largest occurrence time as the target vehicle.
Description
Technical Field
The disclosure belongs to the technical field of man-vehicle fitting positioning, and relates to a method and a system for automatically fitting a man and a vehicle.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In some occasions, for example, police officers often need to find criminal suspects to capture the criminal suspects in the process of handling cases. However, after a criminal suspect has a crime, the criminal suspect generally does not drive the vehicle under the name of the criminal suspect and the vehicle under the name of the criminal suspect to move, and often drives the rental vehicle to move. Therefore, it is very important to find the vehicle taken by the criminal suspect according to the mobile phone movement information of the criminal suspect.
Disclosure of Invention
The invention provides a method and a system for automatically fitting people and vehicles, which aim to search vehicles taken by related personnel according to mobile phone movement information and realize positioning.
According to some embodiments, the following technical scheme is adopted in the disclosure:
a method for automatically performing human-vehicle fitting comprises the following steps:
acquiring position information of a card port and vehicle passing data in a designated area;
acquiring information that a specified mobile phone number passes through a base station within a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station;
taking the unique identification code of the base station as a main key, and counting time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station;
carrying out duplicate removal processing on the introduced base station according to the unique identification code to obtain a base station set, and then carrying out traversal processing on the base station set to remove the invalid base station;
grouping effective base stations according to the grouping quantity set during data fitting of each introduced base station, and performing intersection processing on a plurality of obtained sets to obtain vehicle sets which simultaneously appear near each group of randomly extracted base stations;
and merging the vehicle sets obtained by repeatedly setting the times, counting the occurrence times of each vehicle, and determining the vehicle with the largest occurrence time as the target vehicle.
As an alternative embodiment, the information of the location of the card in the designated area specifically includes a unique identification code of the card and longitude and latitude of the card.
In an alternative embodiment, the data of the bayonet passing vehicles in the designated area comprises a bayonet unique identification code, a vehicle unique identification code and bayonet passing time information.
As an alternative embodiment, when counting time set information of time when a specified mobile phone number enters a base station and time when the specified mobile phone number leaves the base station, when the mobile phone number passes through a certain base station for multiple times, in the set, the corresponding value of the base station is a plurality of data segments, and each data segment starts from the time when the mobile phone number enters the base station for the corresponding time and ends at the time when the mobile phone number leaves the base station for the corresponding time.
As an alternative embodiment, the specific process of removing the invalid base station includes:
taking out a base station J, searching a base station K closest to the base station J in the set V, and then calculating the distance S between J and K;
searching for a bayonet which is less than or equal to S/2 away from the base station J from all bayonets, if the bayonet can be found, considering the base station J as an effective base station, and adding the base station J into the set V1; if the base station J cannot be found, the base station J is considered as an invalid base station, and the base station J directly jumps out of the cycle;
and repeating the steps until all the base stations are traversed to obtain all the effective base station base combinations V.
As an alternative embodiment, the specific process of grouping the active base station sets includes: setting the grouping number M, and calculating the distance between every two base stations in the effective base station set V1 to obtain two base stations A, B with the longest distance and the distance L between the two base stations A, B; then, taking A as the center of a circle, grouping the base stations with the length of the distance A being less than or equal to L/M into one group, grouping the base stations with the length of the distance A being less than or equal to 2L/M into one group, and so on, and respectively grouping the base stations with the length of the distance A being 3L/M and 4L/M, L into one group, wherein the total group is M; and if the number of the base stations after the de-duplication is less than M, the base stations are respectively in one group.
As an alternative implementation, each packet is sequentially subjected to traversal loop processing, and the specific process includes:
obtaining a group, and if the number of the base stations in the group is null, directly skipping the sub-taking cycle; if not, randomly taking out a base station J from the packet;
according to the position information of the base station J, a base station K closest to the base station is searched in the effective base station set V1, and the distance S between the base stations J and K is calculated;
searching all bayonets with the distance smaller than S/2 from the base station J in all the bayonets to obtain a set KK;
randomly taking out an entering time and an leaving time from time set information of a specified mobile phone number passing through a base station J, and analyzing the entering time T1-T and the leaving time T2+ T according to the set base station extension analysis time T; acquiring a passing vehicle set of each gate in the set KK within (T1-T, T2+ T) time, performing union set processing on the vehicle sets, performing de-weighting to obtain a set Map, and directly skipping the cycle if the number of the vehicles in the Map finally obtained is 0;
and processing all the groups according to the steps to obtain the vehicle set corresponding to each group.
A system for automated human-vehicle fitting, comprising:
the parameter acquisition module is configured to acquire card port position information and vehicle passing data in a designated area; acquiring information that a specified mobile phone number passes through a base station within a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station;
the time counting module is configured to count time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station by taking the unique identification code of the base station as a main key;
the duplication removing module is configured to perform duplication removing processing on the imported base stations according to the unique identification codes to obtain a base station set, and then perform traversal processing on the base station set to remove invalid base stations;
the grouping module is configured to group the effective base stations according to the grouping number set during data fitting of each introduced base station, and perform intersection processing on a plurality of obtained sets to obtain vehicle sets which are simultaneously near each group of randomly extracted base stations;
and the determining module is configured to combine the vehicle sets obtained by repeating the set times, count the occurrence times of each vehicle and determine the vehicle with the largest occurrence time as the target vehicle.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of automated human-vehicle fitting.
A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions; the computer readable storage medium stores instructions adapted to be loaded by a processor and to perform the method for automated human-vehicle fitting.
Compared with the prior art, the beneficial effect of this disclosure is:
according to the method, the trajectory data of the position of the mobile phone where the specified mobile phone number is located does not need to be analyzed manually, and automatic analysis can be directly performed;
according to the method, the data of the card port does not need to be manually analyzed according to the position information of the mobile phone, and the card port is manually selected for matching analysis;
according to the method, a large amount of analysis processing is not needed to be carried out on the road junction video monitoring manually according to the position information of the mobile phone, and only the data of the road junction is needed to be automatically analyzed and processed according to the data of the road junction.
This openly has saved a large amount of manpower and materials, has improved location efficiency, for finding appointed cell-phone number fast and possess the vehicle that personnel took, provides powerful support.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
Fig. 1 is a flow chart of a method of the present disclosure.
The specific implementation mode is as follows:
the present disclosure is further described with reference to the following drawings and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
A method for automatically performing human-vehicle fitting comprises the following steps:
firstly, access to the position information of the card port in the designated area mainly comprises the unique identification code of the card port, the longitude and latitude of the card port and other information. And the real-time access card port vehicle passing data comprises information such as a card port unique identification code, a vehicle unique identification code, card port passing time and the like.
Secondly, when the mobile phone owner needs to be fitted to take the vehicle according to the mobile phone position movement information, information that the mobile phone passes through the base station within a period of time, including information of the unique identification code of the base station, the longitude and latitude of the base station, the time that the mobile phone enters the base station, the time that the mobile phone leaves the base station and the like, needs to be imported into the system.
Thirdly, taking the unique identification code of the base station as a main key, and counting time set information of the time when the mobile phone enters the base station and the time when the mobile phone leaves the base station. If the mobile phone passes through the base station T twice, in the set, the corresponding value of the base station T is: "T1 _ T2; T3-T4', T1 is the first time of entering the base station, T2 is the first time of leaving the base station, T3 is the second time of entering the base station, and T4 is the second time of leaving the base station.
Fourthly, carrying out duplicate removal processing on the introduced base stations according to the unique identification codes to obtain a base station set V, and then carrying out traversal processing on the V to remove invalid base stations. The treatment process is as follows:
1. and taking out a base station J, searching a base station K closest to the base station J in the set V, and then calculating the distance S between J and K.
2. Searching for a bayonet which is less than or equal to S/2 away from the base station J from all bayonets, if the bayonet can be found, considering the base station J as an effective base station, and adding the base station J into the set V1; and if the base station J cannot be found, the base station J is considered as an invalid base station, and the loop is directly jumped out.
3. Repeating 1 and 2 until all base stations are traversed, and obtaining all effective base station base numbers V1.
And fifthly, grouping the effective base stations according to the grouping number M set during data fitting of the imported base station. If M is set to be 5, the distance between two base stations in the effective base station set V1 is calculated to obtain two base stations A, B with the longest distance and the distance L between them. And then, taking the A as the center of a circle, grouping the base stations with the length of less than or equal to L/5 of the distance A into one group, grouping the base stations with the length of less than or equal to 2L/5 of the distance A into one group, and so on, and respectively grouping the base stations with the lengths of 3L/5, 4L/5 and L of the distance A into one group, wherein the total number of the base stations is 5. And if the number of the base stations after the de-duplication is less than M, the base stations are respectively in one group.
Sixthly, performing traversal cycle processing on each packet obtained in the fifth step in sequence, wherein the cycle process is as follows:
1. obtaining a group, and if the number of the base stations in the group is null, directly skipping the sub-taking cycle; if not, a base station J is randomly taken from the packet.
2. And searching the base station K closest to the base station in the effective base station set V1 according to the position information of the extracted base station J, and calculating the distance S between the base stations J and K.
3. And searching all the bayonets with the distance to the base station J smaller than S/2 in all the bayonets to obtain a set KK.
4. And randomly taking an entering time and an leaving time from the time set information (the set calculated in the third step) of the mobile phone passing through the base station J. Assuming that the access time randomly taken out at this time is T1 and T2, the access time is T1-T and the leaving time is T2+ T according to the base station extension analysis time T set by the system. And then acquiring a passing vehicle set of each gate in the set KK within (T1-T, T2+ T), merging the vehicle sets, and performing deduplication to obtain a set Map. And if the number of the vehicles in the Map is 0, skipping the cycle directly.
5. And processing all the groups according to 1-4 steps to obtain a vehicle set corresponding to each group.
And seventhly, performing intersection processing on the multiple sets obtained in the fifth step to obtain a vehicle set Cmap which simultaneously appears near each group of base stations extracted randomly.
And eighthly, repeating the operations of the sixth step and the seventh step according to the repeated calculation times S set by the system to finally obtain S Cmap sets.
And ninthly, combining the S Cmap sets, and counting the occurrence times of each vehicle. The more the number of occurrences, the greater the possibility that the owner will take the vehicle.
The following product examples are also provided:
a system for automated human-vehicle fitting, comprising:
the parameter acquisition module is configured to acquire card port position information and vehicle passing data in a designated area; acquiring information that a specified mobile phone number passes through a base station within a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station;
the time counting module is configured to count time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station by taking the unique identification code of the base station as a main key;
the duplication removing module is configured to perform duplication removing processing on the imported base stations according to the unique identification codes to obtain a base station set, and then perform traversal processing on the base station set to remove invalid base stations;
the grouping module is configured to group the effective base stations according to the grouping number set during data fitting of each introduced base station, and perform intersection processing on a plurality of obtained sets to obtain vehicle sets which are simultaneously near each group of randomly extracted base stations;
and the determining module is configured to combine the vehicle sets obtained by repeating the set times, count the occurrence times of each vehicle and determine the vehicle with the largest occurrence time as the target vehicle.
A computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute a method of automated human-vehicle fitting.
A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions; the computer readable storage medium stores instructions adapted to be loaded by a processor and to perform the method for automated human-vehicle fitting.
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 storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) 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 a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (10)
1. A method for automatically fitting a man and a vehicle is characterized by comprising the following steps: the method comprises the following steps:
acquiring position information of a card port and vehicle passing data in a designated area;
acquiring information that a specified mobile phone number passes through a base station within a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station;
taking the unique identification code of the base station as a main key, and counting time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station;
carrying out duplicate removal processing on the introduced base station according to the unique identification code to obtain a base station set, and then carrying out traversal processing on the base station set to remove the invalid base station;
grouping effective base stations according to the grouping quantity set during data fitting of each introduced base station, and performing intersection processing on a plurality of obtained sets to obtain vehicle sets which simultaneously appear near each group of randomly extracted base stations;
and merging the vehicle sets obtained by repeatedly setting the times, counting the occurrence times of each vehicle, and determining the vehicle with the largest occurrence time as the target vehicle.
2. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: the position information of the card port in the designated area specifically comprises a unique identification code of the card port and longitude and latitude of the card port.
3. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: and the data of passing the vehicle through the bayonet in the designated area comprises a unique identification code of the bayonet, a unique identification code of the vehicle and the passing time information of the bayonet.
4. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: when counting time set information of time when a specified mobile phone number enters a base station and time when the specified mobile phone number leaves the base station, when the mobile phone number passes through a certain base station for multiple times, in the set, the corresponding value of the base station is a plurality of data segments, and each data segment starts from the time when the mobile phone number enters the base station for the corresponding time and ends from the time when the mobile phone number leaves the base station for the corresponding time.
5. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: the specific process of removing the invalid base station comprises the following steps:
taking out a base station J, searching a base station K closest to the base station J in the set V, and then calculating the distance S between J and K;
searching for a bayonet which is less than or equal to S/2 away from the base station J from all bayonets, if the bayonet can be found, considering the base station J as an effective base station, and adding the base station J into the set V1; if the base station J cannot be found, the base station J is considered as an invalid base station, and the base station J directly jumps out of the cycle;
and repeating the steps until all the base stations are traversed to obtain all the effective base station base combinations V.
6. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: the specific process of grouping the active base station set comprises the following steps: setting the grouping number M, and calculating the distance between every two base stations in the effective base station set V1 to obtain two base stations A, B with the longest distance and the distance L between the two base stations A, B; then, taking A as the center of a circle, grouping the base stations with the length of the distance A being less than or equal to L/M into one group, grouping the base stations with the length of the distance A being less than or equal to 2L/M into one group, and so on, and respectively grouping the base stations with the length of the distance A being 3L/M and 4L/M, L into one group, wherein the total group is M; and if the number of the base stations after the de-duplication is less than M, the base stations are respectively in one group.
7. The method of claim 1, wherein the human-vehicle fitting is performed automatically by: and sequentially performing traversal cycle processing on each group, wherein the specific process comprises the following steps:
obtaining a group, and if the number of the base stations in the group is null, directly skipping the sub-taking cycle; if not, randomly taking out a base station J from the packet;
according to the position information of the base station J, a base station K closest to the base station is searched in the effective base station set V1, and the distance S between the base stations J and K is calculated;
searching all bayonets with the distance smaller than S/2 from the base station J in all the bayonets to obtain a set KK;
randomly taking out an entering time and an leaving time from time set information of a specified mobile phone number passing through a base station J, and analyzing the entering time T1-T and the leaving time T2+ T according to the set base station extension analysis time T; acquiring a passing vehicle set of each gate in the set KK within (T1-T, T2+ T) time, performing union set processing on the vehicle sets, performing de-weighting to obtain a set Map, and directly skipping the cycle if the number of the vehicles in the Map finally obtained is 0;
and processing all the groups according to the steps to obtain the vehicle set corresponding to each group.
8. The utility model provides a system for automatic people's car is fit, characterized by: the method comprises the following steps:
the parameter acquisition module is configured to acquire card port position information and vehicle passing data in a designated area; acquiring information that a specified mobile phone number passes through a base station within a period of time, wherein the information comprises a unique identification code of the base station, time for the mobile phone to enter the base station and time for the mobile phone to leave the base station;
the time counting module is configured to count time set information of time when a specified mobile phone number enters the base station and time when the specified mobile phone number leaves the base station by taking the unique identification code of the base station as a main key;
the duplication removing module is configured to perform duplication removing processing on the imported base stations according to the unique identification codes to obtain a base station set, and then perform traversal processing on the base station set to remove invalid base stations;
the grouping module is configured to group the effective base stations according to the grouping number set during data fitting of each introduced base station, and perform intersection processing on a plurality of obtained sets to obtain vehicle sets which are simultaneously near each group of randomly extracted base stations;
and the determining module is configured to combine the vehicle sets obtained by repeating the set times, count the occurrence times of each vehicle and determine the vehicle with the largest occurrence time as the target vehicle.
9. A computer-readable storage medium characterized by: stored with instructions adapted to be loaded by a processor of a terminal device and to perform a method of automated human-vehicle fitting according to any one of claims 1-7.
10. A terminal device is characterized in that: the system comprises a processor and a computer readable storage medium, wherein the processor is used for realizing instructions; a computer readable storage medium for storing a plurality of instructions adapted to be loaded by a processor and to perform a method of automated human-vehicle fitting as claimed in any one of claims 1 to 7.
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| CN117576795A (en) * | 2024-01-17 | 2024-02-20 | 浙江大学建筑设计研究院有限公司 | Parking arrearage payment method based on mobile phone signaling data and parking lot management data |
| CN117576795B (en) * | 2024-01-17 | 2024-04-19 | 浙江大学建筑设计研究院有限公司 | Parking arrearage payment method based on mobile phone signaling data and parking lot management data |
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