CN113163361A - Vehicle information processing method and device and server - Google Patents
Vehicle information processing method and device and server Download PDFInfo
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Abstract
The invention provides a vehicle information processing method, a device and a server, wherein the method comprises the following steps: acquiring network node data and measurement reports of all the Internet of vehicles equipment and network node data and measurement reports of all the terminals in a preset time period, and acquiring motion state sequences of all the Internet of vehicles equipment and motion state sequences of all the terminals according to the network node data and the measurement reports of all the Internet of vehicles equipment; obtaining the running tracks of all the Internet of vehicles equipment according to the motion state sequences of all the Internet of vehicles equipment, and obtaining the running tracks of all the terminals according to the motion state sequences of all the terminals; and obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals, determining the similarity of each track pair, and judging that the track pairs have an association relation with the corresponding Internet of vehicles equipment and the terminals when the similarity of the track pairs is greater than or equal to a preset similarity threshold value.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a vehicle information processing method, a vehicle information processing device and a server.
Background
In recent years, a human-vehicle association big data application system is established by integrating and sharing information resources such as intelligent monitoring records of vehicles in various places, and the association relationship between people and vehicles is determined.
In the prior art, the identity registration information of a frequently-used driver is determined by extracting the acquisition data generated in a specified time range from a vehicle information snapshot system and an MAC probe acquisition system and tracing the operator registration information of a mobile phone of the driver through an MAC address, so that the association of frequently-used passengers is realized.
However, in the prior art, not only a large number of acquisition points need to be set, but also equipment which needs vehicle information capturing capability needs to be configured at the acquisition points, which results in higher cost for determining the association relationship between people and vehicles in the prior art.
Disclosure of Invention
The invention aims to provide a vehicle information processing method, a vehicle information processing device and a vehicle information processing server, which reduce the cost for determining the association relationship between people and vehicles.
In a first aspect, the present invention provides a vehicle information processing method including:
the method comprises the steps of obtaining network node data and measurement reports of all the vehicle networking equipment in a preset time period, obtaining network node data and measurement reports of all terminals in the preset time period, obtaining ordered network data of all the vehicle networking equipment according to the network node data and the measurement reports of all the vehicle networking equipment, and obtaining ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals;
obtaining motion state sequences of all the Internet of vehicles according to the ordered network data of all the Internet of vehicles, obtaining motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining driving tracks of all the Internet of vehicles according to the motion state sequences of all the Internet of vehicles, and obtaining driving tracks of all the terminals according to the motion state sequences of all the terminals;
and obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals, and determining the similarity of each track pair, wherein each track pair comprises the running track of one Internet of vehicles equipment and the running track of one terminal, and if the similarity of the track pair is greater than or equal to a preset similarity threshold value, judging that the track pair corresponds to the Internet of vehicles equipment and the terminal and has an association relationship.
In one possible design, the obtaining the driving trajectories of all the internet of vehicles devices according to the motion state sequence of all the internet of vehicles devices includes:
acquiring first road network data according to all main service cell identifications in the motion state sequence of each Internet of vehicles device, wherein the first road network data comprises at least one road section and each road section end point;
determining a starting point, all path points and an end point of each piece of Internet of vehicles equipment according to the motion state sequence of each piece of Internet of vehicles equipment, and obtaining a driving track of each piece of Internet of vehicles equipment according to the starting point, all path points and the end point of each piece of Internet of vehicles equipment;
correspondingly, the obtaining the driving tracks of all the terminals according to the motion state sequences of all the terminals includes:
acquiring second network data according to all main service cell identifications in the motion state sequence of each terminal, wherein the second network data comprise at least one road section and each road section endpoint;
and determining a starting point, all path points and an end point of each terminal according to the motion state sequence of each terminal, and obtaining a driving track of each terminal according to the starting point, all path points and the end point of each terminal.
In one possible design, the obtaining the motion state sequence of all the vehicle networking devices according to the ordered network data of all the vehicle networking devices includes:
according to the main service cell identification in the ordered network data of each Internet of vehicles device, obtaining the position information and the signaling time of a target cell corresponding to the Internet of vehicles device;
determining signaling time when the Internet of vehicles equipment is in a motion state according to the position information and the signaling time of a target cell corresponding to the Internet of vehicles equipment by using a finite state machine, and screening ordered network data according to the signaling time when the Internet of vehicles equipment is in the motion state to obtain a motion state sequence of the Internet of vehicles equipment;
correspondingly, the obtaining the motion state sequence of all the terminals according to the ordered network data of all the terminals includes:
acquiring position information and signaling time of a target cell corresponding to each terminal according to a main service cell identifier in each terminal ordered network data;
and determining the signaling time when the terminal is in a motion state according to the position information of the target cell corresponding to the terminal and the signaling time of the finite state machine, and screening the ordered network data of the terminal according to the signaling time when the terminal is in the motion state to obtain a motion state sequence of the terminal.
In one possible design, the obtaining the ordered network data of all the pieces of vehicle networking equipment according to the network node data and the measurement report of all the pieces of vehicle networking equipment and obtaining the ordered network data of all the pieces of terminal according to the network node data and the measurement report of all the pieces of terminal includes:
obtaining network data of each Internet of vehicles device according to the network node data and the measurement report of all the Internet of vehicles devices, and obtaining network data of each terminal according to the network node data and the measurement report of all the terminals;
and sequencing the network data of each piece of the vehicle networking equipment according to the signaling time to obtain the ordered network data of each piece of the vehicle networking equipment, and sequencing the network data of each terminal according to the signaling time to obtain the ordered network data of each terminal.
In one possible design, before the obtaining the network node data and the measurement report of all the pieces of vehicle networking equipment within the preset time period, the method further includes:
screening the network node data and the measurement reports of all the Internet of vehicles equipment according to a preset data frame format, and screening the network node data and the measurement reports of all the terminals according to the preset data frame format;
correspondingly, the obtaining of the ordered network data of all the pieces of vehicle networking equipment according to the network node data and the measurement reports of all the pieces of vehicle networking equipment and the obtaining of the ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals includes:
and obtaining the ordered network data of each piece of vehicle networking equipment according to the screened network node data and measurement reports of all pieces of vehicle networking equipment, and obtaining the ordered network data of each terminal according to the screened network node data and measurement reports of all the terminals.
In one possible design, each motion state sequence contains at least one set of position data, where each set of position data includes a signaling time, a primary serving cell identification, and a primary serving cell position.
In a second aspect, an embodiment of the present invention provides a vehicle information processing apparatus including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring network node data and measurement reports of all the vehicle networking equipment in a preset time period, acquiring network node data and measurement reports of all terminals in the preset time period, acquiring ordered network data of all the vehicle networking equipment according to the network node data and the measurement reports of all the vehicle networking equipment, and acquiring ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals;
the obtaining module is used for obtaining the motion state sequences of all the vehicle networking devices according to the ordered network data of all the vehicle networking devices, obtaining the motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining the driving tracks of all the vehicle networking devices according to the motion state sequences of all the vehicle networking devices, and obtaining the driving tracks of all the terminals according to the motion state sequences of all the terminals;
and the judging module is used for obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals and determining the similarity of each track pair, wherein each track pair comprises the running track of one Internet of vehicles equipment and the running track of one terminal, and if the similarity of the track pair is greater than or equal to a preset similarity threshold value, the correlation between the corresponding Internet of vehicles equipment and the corresponding terminal of the track pair is judged.
In a third aspect, an embodiment of the present invention provides a server, including a memory and at least one processor;
the memory is used for storing computer execution instructions;
at least one processor configured to execute computer-executable instructions stored by the memory such that the at least one processor implements the vehicle information processing method according to any one of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a computer executes instructions, and when a processor executes the computer to execute the instructions, the vehicle information processing method according to any one of the first aspect is implemented.
In a fifth aspect, an embodiment of the present invention provides a computer program product, which includes a computer program that, when executed by a processor, implements the vehicle information processing method according to any one of the first aspect.
According to the vehicle information processing method, the device and the server provided by the embodiment of the invention, all track pairs are obtained according to the running tracks of all the vehicle networking devices and the running tracks of all the terminals by obtaining the network node data and the measurement reports of all the vehicle networking devices in the preset time period and the network node data and the measurement reports of all the terminals, the similarity of each track pair is determined, and when the similarity of the track pairs is greater than or equal to the preset similarity threshold value, the track is judged to have the association relationship with the corresponding vehicle networking devices and terminals, so that the cost for judging the association relationship of people and vehicles is reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram of a network architecture to which a vehicle information processing method according to an embodiment of the present invention is applied;
FIG. 2 is a first flowchart of a vehicle information processing method according to an embodiment of the present invention;
FIG. 3 is a diagram of a finite state machine according to an embodiment of the present invention;
FIG. 4 is a flowchart of a vehicle information processing method according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a road network according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a driving track of an Internet of vehicles device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a vehicle information processing apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
With the above figures, certain embodiments of the invention have been illustrated and described in more detail below. The drawings and the description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate it by those skilled in the art with reference to specific embodiments.
In the prior art, overlapped acquisition points are determined according to a navigation map, and acquired data generated in a specified time range is extracted from a vehicle information snapshot system and an MAC probe acquisition system from the overlapped acquisition points; and importing the vehicle image and the obtained MAC address of the mobile terminal, carrying out slice statistics on the acquired data according to a time sequence, calculating the overlapping rate, setting a reference threshold value, and tracing the operator registration information of the mobile phone through the MAC address when the calculated overlapping rate of a certain MAC falls into the reference threshold value, so as to determine the identity registration information of the commonly used driver and realize the association of commonly used passengers. However, in the prior art, not only a large number of acquisition points need to be set, but also equipment which needs vehicle information capturing capability needs to be configured at the acquisition points, so that a large amount of capital investment is needed, and the cost for determining the association relationship between people and vehicles is high.
Aiming at the defect, the technical concept provided by the application is as follows: the method and the system have the advantages that the incidence relation of the people and the vehicles is judged by using the existing network node data and the existing measurement report of the operator, so that the cost for judging the incidence relation of the people and the vehicles is reduced.
Fig. 1 is a schematic diagram of a network architecture to which the vehicle information processing method according to the embodiment of the present invention is applied. As shown in fig. 1, the application scenario of the vehicle information processing method includes: a server 10 and at least one base station 20. The base station 20 maintains a soft mining system and an Operation and Maintenance Center (OMC) system. The soft acquisition system is used for acquiring data of all the Internet of vehicles and data of all the terminals. And the OMC system is used for collecting the measurement reports of all the Internet of vehicles and the measurement reports of all the terminals. The base station 20 sends the acquired network node data and measurement reports of all the car networking devices and the acquired network node data and measurement reports of all the terminals to the server 10, so that the server 10 judges the association relationship between people and vehicles according to the received communication data of all the car networking devices and the terminals. The vehicle networking equipment is installed on the vehicle, network node data and measurement reports of the vehicle networking equipment are generated by the vehicle networking equipment through data services provided by an operator in the driving process of the vehicle, and the driving track of the vehicle can be reflected from the side. The terminal is a mobile phone used by a user, the driving track of the user can be judged by utilizing the communication data of the terminal, and the correlation relation of the person and the vehicle can be judged by the driving track of the vehicle and the driving track of the user.
Fig. 2 is a first flowchart of a vehicle information processing method according to an embodiment of the present invention. The execution subject of the method of the embodiment may be the server in fig. 1, as shown in fig. 2, the vehicle information processing method provided by the embodiment of the invention includes the following steps:
s201: the method comprises the steps of obtaining network node data and measurement reports of all the vehicle networking devices in a preset time period, obtaining network node data and measurement reports of all the terminals in the preset time period, obtaining ordered network data of all the vehicle networking devices according to the network node data and the measurement reports of all the vehicle networking devices, and obtaining ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals.
In the embodiment of the present invention, for example, a preset time period is set to be one year, and network node data (MME) and Measurement Reports (MR) of all pieces of vehicle networking equipment in the last year, and MME data and MR Measurement reports of all pieces of terminals in the last year are obtained. Specifically, the soft acquisition system acquires the MME data of all the Internet of vehicles and the MME data of all the terminals, and the OMC system acquires the MR measurement reports of all the Internet of vehicles and the MR measurement reports of all the terminals. According to the clear MME and MR original data formats and file requirements in the technical requirements of LTE wireless network main equipment, MME data is collected through a soft acquisition system, a data file is output at regular time, and network node data of all Internet of vehicles and all terminals are obtained after the file is analyzed. After the MR data generation switch is turned on, the OMC system generates a piece of MR data at regular time, namely, a piece of data file is generated for each base station of each type of task within a specified time. The data File is transmitted to a designated File server through downloading from an OMC or a transmission mode such as a File Transfer Protocol (FTP), and after the File is analyzed, MR measurement reports of all the vehicle networking devices and all the terminals are obtained.
In the embodiment of the invention, the network data of each piece of vehicle networking equipment is obtained according to the network node data and the measurement report of all pieces of vehicle networking equipment, and the network data of each terminal is obtained according to the network node data and the measurement report of all the terminals. The MR data comprises signaling time, the network data of each Internet of vehicles device is sequenced according to the signaling time to obtain ordered network data of each Internet of vehicles device, and the network data of each terminal is sequenced according to the signaling time to obtain ordered network data of each terminal.
Illustratively, the MME data and the MR measurement report are associated according to MME UE S1AP ID in all the MME data of the Internet of vehicles equipment and MME UE S1AP ID in the MR measurement report, network data of each Internet of vehicles equipment is obtained according to IMSI, and the network data is sorted according to signaling time, so that ordered network data of each Internet of vehicles equipment is obtained. Correspondingly, the MME data and the MR measurement report are associated according to the unique identification MME UE S1AP ID of the UE on the MME side S1 interface in the MME data of all the terminals and the MME UE S1AP ID in the MR measurement report, the network data of each terminal is obtained according to the IMSI, and the network data is sequenced according to the signaling time, so that the ordered network data of each terminal is obtained.
S202: the method comprises the steps of obtaining motion state sequences of all the Internet of vehicles according to the ordered network data of all the Internet of vehicles, obtaining motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining running tracks of all the Internet of vehicles according to the motion state sequences of all the Internet of vehicles, and obtaining the running tracks of all the terminals according to the motion state sequences of all the terminals.
In the embodiment of the invention, after the ordered network data of each piece of car networking equipment is obtained, the position information and the signaling time of the target cell corresponding to the car networking equipment are obtained according to the main service cell identification in the ordered network data of each piece of car networking equipment, the signaling time when the car networking equipment is in the motion state is determined according to the position information and the signaling time of the target cell corresponding to the car networking equipment by the finite state machine, and the ordered network data is screened according to the signaling time when the car networking equipment is in the motion state to obtain the motion state sequence of the car networking equipment. Correspondingly, after the ordered network data of each terminal is obtained, the main service cell identification in the ordered network data of each terminal obtains the position information and the signaling time of the target cell corresponding to the terminal, the signaling time when the terminal is in the motion state is determined according to the position information and the signaling time of the target cell corresponding to the terminal by the finite state machine, and the ordered network data of the terminal is screened according to the signaling time when the terminal is in the motion state to obtain the motion state sequence of the terminal.
Specifically, the finite state machine provided by the embodiment of the present invention is used for determining the state of the target at any time. When the finite state machine obtains an input character, the target is switched from the current state to another state, or remains in the current state. Any finite state machine can be described by using a state transition diagram, and fig. 3 is a schematic diagram of a finite state machine according to an embodiment of the present invention. As shown in fig. 3, the nodes in the graph represent one state in a finite state machine, and the directed weighted edges represent the change of state when a character is input. If there is no directed edge corresponding to the current state and the input character in the graph, the finite state machine will enter a 'death state', and the finite state machine will keep the 'death state' all the time thereafter. There are also two special states in the state transition diagram: state 1 is referred to as the "start state" and represents the initial state of the finite state machine. State 6 is referred to as the "end state" and indicates that the entered character sequence was successfully recognized. When a finite state machine is started, the finite state machine must first be placed in a "start state" and then a series of characters are entered, and finally the finite state machine will reach an "end state" or an "extinction state". In particular, the "start state" may also be taken as the accept state, so that an empty input sequence is also acceptable. In a conventional finite-state machine model, there is generally an "accepting state", and the finite-state machine can be switched from the "accepting state" to another state, and only after the last character is recognized, will the decision whether to accept the input character string be made according to the final state.
In the embodiment of the invention, the signaling time of the car networking equipment in the motion state is determined according to the finite state machine, and the ordered network data is screened according to the signaling time of the car networking equipment in the motion state, so that the motion state sequence of the car networking equipment is obtained. Correspondingly, the signaling time of the terminal in the motion state is determined according to the finite state machine, and the ordered network data of the terminal is screened according to the signaling time of the terminal in the motion state, so as to obtain the motion state sequence of the terminal. Illustratively, each motion state sequence contains at least one set of location data, wherein each set of location data includes a signaling time, a primary serving cell identification, and a primary serving cell location. And obtaining the driving tracks of all the vehicle networking equipment according to the signaling time, the main service cell identification and the main service cell position in the motion state sequence of all the vehicle networking equipment, and obtaining the driving tracks of all the terminals according to the signaling time, the main service cell identification and the main service cell position in the motion state sequence of all the terminals.
S203: and if the similarity of the track pairs is greater than or equal to a preset similarity threshold value, judging that the track pairs have an association relation with the corresponding Internet of vehicles equipment and the corresponding terminals.
In the embodiment of the invention, the driving tracks of all the internet of vehicles devices and the driving tracks of all the terminals are paired pairwise, so that all track pairs are obtained, wherein each track pair comprises the driving track of one internet of vehicles device and the driving track of one terminal. Calculating the similarity of the two tracks by adopting a dynamic programming algorithm, taking a plurality of road sections contained in the driving track of the vehicle networking equipment in each track pair as a plurality of subsequences, taking a plurality of road sections contained in the driving track of the terminal in each track pair as a plurality of subsequences, and calculating the longest common subsequence of the plurality of subsequences of the vehicle networking equipment and the plurality of subsequences of the terminal in each track pair to obtain the similarity of the track pairs, wherein the recursive structure of the longest common subsequence is shown as formula (1):
wherein, x [ i ] is a sub-sequence composed of all road sections of a driving track of the vehicle networking equipment, y [ j ] is a sub-sequence composed of all road sections of a terminal driving track, each track pair is composed of x [ i ] and y [ j ], i and j are respectively positive integers, LCS [ i ] [ j ] is a public sub-sequence in the track pair, max { LCS [ i ] [ j-1], LCS [ i-1] [ j ] } is a longest public sub-sequence in the track pair, and the similarity of the track pair is obtained according to the ratio of the number of the road sections contained in the longest public sub-sequence to the sum of all the road sections contained in x [ i ] and y [ j ].
In the embodiment of the invention, after the similarity of all track pairs is obtained according to the method, if the similarity of the track pairs is greater than or equal to the preset similarity threshold, it is determined that the track pairs have an association relationship with corresponding car networking equipment and terminals.
It can be known from the above embodiment that, by obtaining the network node data and the measurement reports of all the pieces of vehicle networking equipment within the preset time period and the network node data and the measurement reports of all the terminals, and obtaining the motion state sequences of all the pieces of vehicle networking equipment and the motion state sequences of all the terminals, all the track pairs are obtained according to the running tracks of all the pieces of vehicle networking equipment and the running tracks of all the terminals, and the similarity of each track pair is determined, and when the similarity of the track pairs is greater than or equal to the preset similarity threshold, it is determined that the track pairs correspond to the pieces of vehicle networking equipment and the terminals, and an association relationship exists between the track pairs and the terminals. The invention judges the association relationship of the people and the vehicles by using the existing network node data and the measurement report of the operator, thereby reducing the cost for judging the association relationship of the people and the vehicles.
Fig. 4 is a flowchart of a vehicle information processing method according to an embodiment of the present invention. As shown in fig. 4, on the basis of the vehicle information processing method provided in the embodiment of fig. 2, the method for obtaining the driving trajectories of all the internet of vehicles devices according to the motion state sequence of all the internet of vehicles devices in S202 specifically includes the following steps:
s401: and obtaining first road network data according to all the main service cell identifications in the motion state sequence of each Internet of vehicles device, wherein the first road network data comprises at least one road section and each road section endpoint.
In the embodiment of the invention, the first road network data is obtained by loading road networks in the range according to the range of all main service cell positions in the motion state sequence. The first road network data is composed of road sections and road section end points, the road sections are from a starting road section end point to an ending road section end point, and each road section end point can be connected with a plurality of road ends, so that a road network is formed. As shown in fig. 5, fig. 5 is a schematic diagram of a road network according to an embodiment of the present invention.
S402: and determining a starting point, all path points and an end point of the Internet of vehicles according to the motion state sequence of each Internet of vehicles device, and obtaining a driving track of the Internet of vehicles device according to the starting point, all path points and the end point of the Internet of vehicles device.
In the embodiment of the invention, the starting point (last static state), the end point (next static state) and the approach point (positioning points at intervals of time and distance) of the internet of vehicles are found out from the motion state sequence of the internet of vehicles, and the corresponding set of the end points of the approach is found out from the road network according to the precision of the starting point, the end point and the approach point. And connecting all the road section end point sets according to the obtained road section end point set sequence, storing the progress information of all the nodes in the process until the node of the last road section end point set is obtained and is the node with the minimum cost, and reversely finding a path as the driving track of the vehicle networking equipment. As shown in fig. 6, fig. 6 is a schematic view of a driving track of the car networking device provided by the present invention. Illustratively, in the embodiment of the invention, a multi-section motion cue algorithm is adopted, a plurality of fuzzy reference points are referred, and an optimal path is identified and found in the precision range of the reference points as the driving track of the vehicle networking equipment through integral identification.
According to the embodiment, the driving track of the Internet of vehicles equipment is positioned by adopting a multi-section motion cue algorithm, so that the accuracy of the recognized driving track result is improved.
In a possible implementation manner, second road network data is obtained according to all main service cell identifiers in the motion state sequence of each terminal, wherein the second road network data comprises at least one road segment and each road segment endpoint; and determining a starting point, all path points and a final point of each terminal according to the motion state sequence of each terminal, and obtaining a driving track of each terminal according to the starting point, all path points and the final point of each terminal. The method for obtaining the driving track of the terminal is similar to the method provided in the embodiment of fig. 4, and is not described herein again.
In a possible implementation manner, before obtaining the motion state sequences of all the pieces of car networking equipment and the motion state sequences of all the terminals, the network node data and the measurement reports of all the pieces of car networking equipment are screened according to a preset data frame format, and the network node data and the measurement reports of all the terminals are screened according to the preset data frame format. As shown in table 1, table 1 shows a data frame format of MME data in a preset data frame format.
TABLE 1
| eci | start-time | end-time | IMSI | MME UE S1AP ID | SRVTYPE |
Eci denotes a primary service cell identifier, where start-time and end-time are respectively the start time and end time of the signaling time, IMSI is an international mobile subscriber identity, and MME UE S1AP ID is a unique identifier of the UE on the S1 interface on the MME side. SRVTYPE is a server type.
As shown in table 2, table 2 is a data frame format of an MR measurement report in a preset data frame format.
TABLE 2
Eci denotes a main serving cell identifier, time is a time point of signaling, MME UE S1AP ID is a unique identifier of the UE on an MME side S1 interface, lteScRSRP is reference signal received power, lteScRSRQ is reference signal received quality of the main serving cell, lteScTadv is time advance of the main serving cell, lteScAOA is eNB antenna arrival angle, tencell1. emctearfcn is frequency point of the neighbor cell1, ltneclli 1. ltencpcci is physical cell identifier of the neighbor cell1, tencell1. ltcenrsrp is reference signal received power, and lttencell1. ltencq is reference signal received quality of the neighbor cell1.
It can be known from the above embodiments that the network node data and the measurement reports of all the pieces of car networking equipment are screened through the preset data frame format, and the network node data and the measurement reports of all the terminals are screened according to the preset data frame format, only the communication parameters related to the driving track are reserved, the number of data processing is reduced, and the efficiency of data processing is improved.
Fig. 7 is a schematic structural diagram of a vehicle information processing apparatus according to an embodiment of the present invention. As shown in fig. 7, the vehicle information processing apparatus includes: an obtaining module 701, an obtaining module 702 and a determining module 703; the acquiring module 701 is used for acquiring network node data and measurement reports of all the pieces of vehicle networking equipment within a preset time period, acquiring network node data and measurement reports of all the terminals within the preset time period, acquiring ordered network data of all the pieces of vehicle networking equipment according to the network node data and the measurement reports of all the pieces of vehicle networking equipment, and acquiring ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals; an obtaining module 702, configured to obtain motion state sequences of all pieces of car networking equipment according to the ordered network data of all pieces of car networking equipment, obtain motion state sequences of all pieces of terminals according to the ordered network data of all pieces of terminals, obtain travel tracks of all pieces of car networking equipment according to the motion state sequences of all pieces of car networking equipment, and obtain travel tracks of all pieces of terminals according to the motion state sequences of all pieces of terminals; the determining module 703 is configured to obtain all track pairs according to the driving tracks of all the pieces of vehicle networking equipment and the driving tracks of all the terminals, and determine the similarity of each track pair, where each track pair includes a driving track of one piece of vehicle networking equipment and a driving track of one terminal, and if the similarity of a track pair is greater than or equal to a preset similarity threshold, it is determined that there is an association relationship between the corresponding piece of vehicle networking equipment and the corresponding terminal.
In this embodiment, the vehicle information processing apparatus may adopt the methods of all the embodiments described above, and the technical solutions and the technical effects thereof are similar and will not be described herein again.
In an embodiment of the present invention, the obtaining module 702 is specifically configured to: obtaining first road network data according to all main service cell identifications in the motion state sequence of each vehicle networking device, wherein the first road network data comprises at least one road section and each road section end point; determining a starting point, all path points and an end point of each piece of Internet of vehicles equipment according to the motion state sequence of each piece of Internet of vehicles equipment, obtaining a driving track of the pieces of Internet of vehicles equipment according to the starting point, all path points and the end point of each piece of Internet of vehicles equipment, and obtaining second road network data according to all main service cell identifiers in the motion state sequence of each terminal, wherein the second road network data comprises at least one road section and each road section end point; and determining a starting point, all path points and an end point of each terminal according to the motion state sequence of each terminal, and obtaining a driving track of each terminal according to the starting point, all path points and the end point of each terminal.
In an embodiment of the present invention, the obtaining module 702 is specifically configured to: according to the main service cell identification in the ordered network data of each Internet of vehicles device, obtaining the position information and the signaling time of a target cell corresponding to the Internet of vehicles device; determining signaling time when the vehicle networking equipment is in a motion state according to the position information and the signaling time of a target cell corresponding to the vehicle networking equipment by using a finite state machine, and screening ordered network data according to the signaling time when the vehicle networking equipment is in the motion state to obtain a motion state sequence of the vehicle networking equipment; acquiring position information and signaling time of a target cell corresponding to each terminal according to a main service cell identifier in each terminal ordered network data; and determining the signaling time of the terminal in the motion state according to the position information of the target cell corresponding to the terminal and the signaling time of the finite state machine, and screening the ordered network data of the terminal according to the signaling time of the terminal in the motion state to obtain the motion state sequence of the terminal.
In an embodiment of the present invention, the obtaining module 701 is specifically configured to: obtaining network data of each piece of vehicle networking equipment according to the network node data and the measurement report of all pieces of vehicle networking equipment, and obtaining the network data of each terminal according to the network node data and the measurement report of all the terminals; and sequencing the network data of each Internet of vehicles device according to the signaling time to obtain the ordered network data of each Internet of vehicles device, and sequencing the network data of each terminal according to the signaling time to obtain the ordered network data of each terminal.
In one embodiment of the present invention, the vehicle information processing apparatus further includes a filtering module configured to: and screening the network node data and the measurement reports of all the Internet of vehicles equipment according to a preset data frame format, and screening the network node data and the measurement reports of all the terminals according to the preset data frame format.
The apparatus provided in this embodiment may be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.
Fig. 8 is a schematic structural diagram of a server according to an embodiment of the present invention. As shown in fig. 8, the server of the present embodiment includes: a processor 801, a memory 802 and a computer program stored in the memory 802 and operable on the processor 801, the processor 801 implementing the following steps when executing the computer program: the method comprises the steps of obtaining network node data and measurement reports of all the vehicle networking equipment in a preset time period, obtaining network node data and measurement reports of all terminals in the preset time period, obtaining ordered network data of all the vehicle networking equipment according to the network node data and the measurement reports of all the vehicle networking equipment, and obtaining ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals; obtaining the motion state sequences of all the Internet of vehicles according to the ordered network data of all the Internet of vehicles, obtaining the motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining the running tracks of all the Internet of vehicles according to the motion state sequences of all the Internet of vehicles, and obtaining the running tracks of all the terminals according to the motion state sequences of all the terminals; and obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals, and determining the similarity of each track pair, wherein each track pair comprises the running track of one Internet of vehicles equipment and the running track of one terminal, and if the similarity of the track pair is greater than or equal to a preset similarity threshold value, judging that the corresponding Internet of vehicles equipment and the terminal of the track pair have an association relationship.
In one possible design, the processor 801, when executing the computer program, further performs the following steps: obtaining first road network data according to all main service cell identifications in the motion state sequence of each Internet of vehicles device, wherein the first road network data comprises at least one road section and each road section endpoint; determining a starting point, all path points and an end point of each piece of car networking equipment according to the motion state sequence of each piece of car networking equipment, obtaining a driving track of the car networking equipment according to the starting point, all path points and the end point of the car networking equipment, and obtaining second road network data according to all main service cell identifiers in the motion state sequence of each terminal, wherein the second road network data comprises at least one road section and each road section end point; and determining a starting point, all path points and an end point of each terminal according to the motion state sequence of each terminal, and obtaining the driving track of each terminal according to the starting point, all path points and the end point of each terminal.
In one possible design, the processor 801, when executing the computer program, further performs the following steps: according to the main service cell identification in the ordered network data of each Internet of vehicles device, obtaining the position information and the signaling time of a target cell corresponding to the Internet of vehicles device; determining signaling time when the vehicle networking equipment is in a motion state according to the position information and the signaling time of a target cell corresponding to the vehicle networking equipment by using a finite state machine, and screening ordered network data according to the signaling time when the vehicle networking equipment is in the motion state to obtain a motion state sequence of the vehicle networking equipment; according to the main service cell identification in the ordered network data of each terminal, obtaining the position information and the signaling time of a target cell corresponding to the terminal; and determining the signaling time when the terminal is in a motion state according to the position information of the target cell corresponding to the terminal and the signaling time of the finite state machine, and screening the ordered network data of the terminal according to the signaling time when the terminal is in the motion state to obtain a motion state sequence of the terminal.
In one possible design, the processor 801, when executing the computer program, further performs the following steps: obtaining network data of each piece of vehicle networking equipment according to the network node data and the measurement report of all pieces of vehicle networking equipment, and obtaining the network data of each terminal according to the network node data and the measurement report of all the terminals; and sequencing the network data of each piece of the vehicle networking equipment according to the signaling time to obtain the ordered network data of each piece of the vehicle networking equipment, and sequencing the network data of each terminal according to the signaling time to obtain the ordered network data of each terminal.
Reference may be made in particular to the description relating to the method embodiments described above.
In one possible design, the memory 802 may be separate or integrated with the processor 801.
When the memory 802 is provided separately, the server further includes a bus 803 for connecting the memory 802 and the processor 801.
The embodiment of the invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the vehicle information processing method is realized.
Embodiments of the present invention further provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the vehicle information processing method as described above is implemented.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules 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 modules may be selected according to actual needs to implement the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware mode, and can also be realized in a mode of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a processor to execute some steps of the methods described in the embodiments of the present application.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Those of ordinary skill in the art will understand that: all or a portion of the steps for implementing the above-described method embodiments may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A vehicle information processing method characterized by comprising:
the method comprises the steps of obtaining network node data and measurement reports of all the vehicle networking equipment in a preset time period, obtaining network node data and measurement reports of all terminals in the preset time period, obtaining ordered network data of all the vehicle networking equipment according to the network node data and the measurement reports of all the vehicle networking equipment, and obtaining ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals;
obtaining the motion state sequences of all the Internet of vehicles according to the ordered network data of all the Internet of vehicles, obtaining the motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining the running tracks of all the Internet of vehicles according to the motion state sequences of all the Internet of vehicles, and obtaining the running tracks of all the terminals according to the motion state sequences of all the terminals;
and obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals, and determining the similarity of each track pair, wherein each track pair comprises the running track of one Internet of vehicles equipment and the running track of one terminal, and if the similarity of the track pair is greater than or equal to a preset similarity threshold value, judging that the track pair corresponds to the Internet of vehicles equipment and the terminal to have an association relationship.
2. The method of claim 1, wherein obtaining the driving trajectories of all the internet of vehicles devices according to the motion state sequence of all the internet of vehicles devices comprises:
obtaining first road network data according to all main service cell identifications in the motion state sequence of each Internet of vehicles device, wherein the first road network data comprises at least one road section and each road section endpoint;
determining a starting point, all path points and an end point of each piece of Internet of vehicles equipment according to the motion state sequence of each piece of Internet of vehicles equipment, and obtaining a driving track of each piece of Internet of vehicles equipment according to the starting point, all path points and the end point of each piece of Internet of vehicles equipment;
correspondingly, the obtaining of the driving tracks of all the terminals according to the motion state sequences of all the terminals includes:
acquiring second road network data according to all main service cell identifications in the motion state sequence of each terminal, wherein the second road network data comprises at least one road section and each road section endpoint;
and determining a starting point, all path points and an end point of each terminal according to the motion state sequence of each terminal, and obtaining a driving track of each terminal according to the starting point, all path points and the end point of each terminal.
3. The method of claim 1, wherein obtaining the sequence of motion states of all Internet of vehicles devices from the ordered network data of all Internet of vehicles devices comprises:
according to the main service cell identification in the ordered network data of each Internet of vehicles device, obtaining the position information and the signaling time of a target cell corresponding to the Internet of vehicles device;
determining signaling time when the vehicle networking equipment is in a motion state according to the position information and the signaling time of a target cell corresponding to the vehicle networking equipment by using a finite state machine, and screening ordered network data according to the signaling time when the vehicle networking equipment is in the motion state to obtain a motion state sequence of the vehicle networking equipment;
correspondingly, the obtaining the motion state sequences of all the terminals according to the ordered network data of all the terminals includes:
acquiring position information and signaling time of a target cell corresponding to each terminal according to a main service cell identifier in each terminal ordered network data;
and determining the signaling time when the terminal is in a motion state according to the position information of the target cell corresponding to the terminal and the signaling time of the finite state machine, and screening the ordered network data of the terminal according to the signaling time when the terminal is in the motion state to obtain a motion state sequence of the terminal.
4. The method of claim 1, wherein the obtaining ordered network data of all the vehicle networking devices from the network node data and the measurement reports of all the vehicle networking devices and obtaining ordered network data of all the terminals from the network node data and the measurement reports of all the terminals comprises:
obtaining network data of each piece of vehicle networking equipment according to the network node data and the measurement report of all pieces of vehicle networking equipment, and obtaining the network data of each terminal according to the network node data and the measurement report of all the terminals;
and sequencing the network data of each piece of the vehicle networking equipment according to the signaling time to obtain the ordered network data of each piece of the vehicle networking equipment, and sequencing the network data of each terminal according to the signaling time to obtain the ordered network data of each terminal.
5. The method of claim 1, further comprising, prior to said obtaining network node data and measurement reports for all of the devices in the vehicle networking system within a preset time period:
screening the network node data and the measurement reports of all the Internet of vehicles equipment according to a preset data frame format, and screening the network node data and the measurement reports of all the terminals according to the preset data frame format;
correspondingly, the obtaining of the ordered network data of all the pieces of vehicle networking equipment according to the network node data and the measurement reports of all the pieces of vehicle networking equipment and the obtaining of the ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals includes:
and obtaining the ordered network data of each piece of the vehicle networking equipment according to the screened network node data and the screened measurement report of all the pieces of the vehicle networking equipment, and obtaining the ordered network data of each terminal according to the screened network node data and the screened measurement report of all the terminals.
6. The method according to any one of claims 1 to 3, wherein each motion state sequence comprises at least one set of position data, wherein each set of position data comprises a signaling time, a primary serving cell identity and a primary serving cell position.
7. A vehicle information processing apparatus characterized by comprising:
the system comprises an acquisition module, a measurement module and a processing module, wherein the acquisition module is used for acquiring network node data and measurement reports of all the vehicle networking equipment in a preset time period, acquiring network node data and measurement reports of all terminals in the preset time period, acquiring ordered network data of all the vehicle networking equipment according to the network node data and the measurement reports of all the vehicle networking equipment, and acquiring ordered network data of all the terminals according to the network node data and the measurement reports of all the terminals;
the obtaining module is used for obtaining the motion state sequences of all the Internet of vehicles according to the ordered network data of all the Internet of vehicles, obtaining the motion state sequences of all the terminals according to the ordered network data of all the terminals, obtaining the running tracks of all the Internet of vehicles according to the motion state sequences of all the Internet of vehicles, and obtaining the running tracks of all the terminals according to the motion state sequences of all the terminals;
and the judging module is used for obtaining all track pairs according to the running tracks of all the Internet of vehicles equipment and the running tracks of all the terminals and determining the similarity of each track pair, wherein each track pair comprises the running track of one Internet of vehicles equipment and the running track of one terminal, and if the similarity of the track pair is greater than or equal to a preset similarity threshold value, the correlation between the corresponding Internet of vehicles equipment and the corresponding terminal of the track pair is judged.
8. A server, comprising a memory and at least one processor;
the memory is used for storing computer execution instructions;
at least one processor configured to execute computer-executable instructions stored by the memory to cause the at least one processor to perform the vehicle information processing method of any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that a computer-executable instruction is stored therein, which when executed by a processor, implements the vehicle information processing method according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program realizes the vehicle information processing method of any one of claims 1 to 6 when executed by a processor.
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Application publication date: 20210723 |