A traffic data processing method and device

Abstract

The application provides a traffic data processing method and device, the method comprises the following steps: obtaining license plate information and vehicle attribute information; obtaining travel information corresponding to the license plate information, the travel information at least comprising one or more of the following information: information of a highway toll station passed, time information corresponding to entering and leaving different highway toll stations, and vehicle state information; determining the license plate number's home, the starting point and the destination of each trip based on one or more of the following information: the vehicle attribute information, the information of the highway toll station passed, the time information and the vehicle state information; constructing a traffic chain corresponding to the vehicle based on at least the following information: the license plate information, the license plate number's home, the starting point and the destination of each trip, the information of the highway toll station passed and the time information; and constructing a target database based on at least the traffic chain. The traffic data processing method can recognize and process the traffic chain based on traffic data, and can construct a corresponding database.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer recognition technology, and in particular to a traffic data processing method and apparatus. Background Technology

[0002] Highway toll station data is a typical example of big data. Developing applicable data analysis technologies and systems is a fundamental prerequisite for reducing computational load and deeply exploring its value. Based on the closed-loop organizational characteristics of most transportation chains, this study designed a transportation chain identification technology and reconstructed the highway toll station data structure around this technology, forming a highway flow database that includes city attribute tables, highway toll station attribute tables, license plate number attribute tables, multi-modal travel chain attribute tables, and transportation chain attribute tables. This lays the technical foundation for subsequent research, especially for the analysis of individual travel and transportation behavior.

[0003] Traffic chain identification is fundamental to individual travel and transportation activities. The complexity of its identification technology lies in the fact that existing highway toll station data is designed for ease of toll collection and management, using a record-by-record approach and exhibiting provincial segmentation. Therefore, efficient traffic chain identification technology should begin with reconstructing the data structure, and designing this new data structure is a process of repeated trial and error. Considering the existence of numerous traffic data in real life with similar structures to highway toll station data, such as public transport card data and Didi Chuxing data, research into traffic chain identification technology can provide valuable insights for processing other traffic big data. Summary of the Invention

[0004] This invention provides a traffic data processing method and apparatus that can identify and process traffic chains based on traffic data and construct a corresponding database.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a traffic data processing method, characterized by comprising: Obtain license plate number information and vehicle attribute information; Obtain travel information corresponding to the license plate number, the travel information including at least one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information; The vehicle's location, origin, and destination for each trip are determined based on one or more of the vehicle attribute information, highway toll station information, time information, and vehicle status information. The traffic chain of the corresponding vehicle is constructed based at least on the license plate number information, the license plate number's place of origin, the origin and destination of each trip, as well as the information of the highway toll stations and time information along the route; A target database shall be constructed based at least on the aforementioned transportation chain.

[0006] As an optional embodiment, obtaining the license plate number information and vehicle attribute information includes: Obtain license plate number information, vehicle type information, and vehicle model information.

[0007] As an optional embodiment, obtaining the travel information corresponding to the license plate number includes: The system obtains information on the highway toll stations along the route of the vehicle corresponding to the license plate number during each trip within a target time period, the corresponding entry and exit times of different highway toll stations, and the vehicle's load status. The target time period is at least in days.

[0008] As an optional embodiment, the method further includes: At least the obtained vehicle attribute information and travel information should be uniformly encoded; Based on the coded vehicle attribute information and travel information, the location of the license plate number, as well as the origin and destination of each trip, are determined.

[0009] As an optional embodiment, determining the license plate number's origin based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: The vehicle type is determined based on the vehicle attribute information, and the vehicle type includes trucks and buses. Based on the time information, the information of the highway toll stations along the route is processed to obtain the information of the highway toll stations that the vehicle passes through in sequence for each trip. Based on the information of highway toll stations along the route of each vehicle's trip, the location of the first highway toll station the vehicle enters on its first trip of the day is determined, and the frequency of each location in a target time period is calculated, with the target time period based on a day as the basic unit. When the vehicle type is a passenger vehicle, the location corresponding to the highest frequency will be determined as the location of the license plate number. When the vehicle type is a truck, the load status information of the vehicle when passing through each highway toll station in sequence during each trip is determined based on the highway toll station information and vehicle status information of each trip. Based on the frequency of statistics and the load status information of each trip, the location with the highest frequency and the largest load is determined as the place of origin of the license plate number.

[0010] As an optional embodiment, determining the origin and destination of each trip based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: Based on the information of highway toll stations along the route and the time information, the information of the first highway toll station that meets the time sequence for each trip route and the entry and exit time of each first highway toll station are determined. The information of the first highway toll station includes the location and the type of toll station. The toll station type includes county toll stations within the province and provincial border toll stations. When determining that the corresponding trip is an intra-provincial trip based on the information of the first highway toll station and the entry and exit time, the location of the first highway toll station where the trip begins will be determined as the starting point of the trip, and the location of the first highway toll station where the trip ends will be determined as the destination of the trip.

[0011] As an optional embodiment, the method further includes: When determining a second highway toll station that is a provincial border highway toll station based on the information of the first highway toll station, the entry and exit times and the province information of the second highway toll station are determined based on the information of the first highway toll station and the entry and exit times. Based on the entry and exit times and province information of the second highway toll station, determine whether there are two target second highway toll stations with an entry and exit interval time less than a preset time value and different province information. The entry and exit times of the second target second highway toll station among the two target second highway toll stations are retained, or the entry and exit records of both second highway toll stations are deleted simultaneously. The location of the first highway toll station and its entry / exit time for each trip will be determined by retaining the information of the first highway toll station and its entry / exit time, or the information of the first highway toll station and its entry / exit time, and the information of the second highway toll station and its entry / exit time. At the same time, the location of the first or second highway toll station for the last exit will be determined as the destination of this trip.

[0012] As an optional embodiment, the origin and destination include the origin and destination of the entire journey, as well as the origin and destination of the travel path formed by the distance between two adjacent highway toll stations. The construction of the traffic chain for the corresponding vehicle based on the license plate number information, the license plate number's origin, the origin and destination of each trip, and the information on highway toll stations and times along the route includes: The departure and arrival times are determined based on the origin and destination, highway toll station information, and time information of each trip. Based on the license plate information, the license plate location, the origin and destination of each trip, and the departure and arrival times, a traffic chain is constructed according to a target format. The target format includes recording the license plate information, the license plate location, the origin and departure time of each trip, the destination and arrival time of each trip in sequence. Multiple transportation chains with consecutive departure and destination points and consecutive times within the same day are merged, and the information of the corresponding departure point, departure time, destination, and arrival time is reconstructed to form departure sequence, departure time sequence, destination sequence, and arrival time sequence.

[0013] As an optional embodiment, the construction of the target database based at least on the transportation chain includes: A first data table is constructed based on the vehicle attribute information; A second data table is constructed based on the city or county attribute information of each of the aforementioned highway toll stations. The first data table is linked with the license plate information in the transportation chain, and the second data table is linked with each highway toll station involved in the transportation chain. A target database is constructed based on the traffic chain that connects the first data table and the second data table.

[0014] Another embodiment of the present invention also provides a traffic data processing device, comprising: The first acquisition module is used to obtain license plate number information and vehicle attribute information; The second obtaining module is used to obtain travel information corresponding to the license plate number information. The travel information includes at least one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information. The first determining module is used to determine the license plate number's location, the origin and destination of each trip, based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information. The first construction module is used to construct the traffic chain of the corresponding vehicle based at least on the license plate number information, the license plate number location, the origin and destination of each trip, as well as the highway toll station information and time information along the route. The second construction module is used to construct a target database based at least on the traffic chain. Based on the disclosure of the above embodiments, it can be understood that the beneficial effects of the embodiments of the present invention include identifying and determining the origin, destination, departure time, arrival time, and license plate number of each trip by obtaining vehicle license plate number information, vehicle attribute information, and travel information. At this time, a traffic chain corresponding to each license plate number can be constructed based on this, and a database can be constructed based on the traffic chains corresponding to different vehicles to facilitate the management and traceability of vehicle traffic data.

[0015] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0016] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the present application and form part of the specification. They are used together with the embodiments of the present application to explain the application and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating the traffic data processing method in an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram illustrating the application process of the traffic data processing method in this embodiment of the invention.

[0019] Figure 3 This is a diagram of the traffic chain structure in an embodiment of the present invention.

[0020] Figure 4 This is a traffic chain structure diagram according to another embodiment of the present invention.

[0021] Figure 5 This is a topology diagram of the traffic chain in an embodiment of the present invention.

[0022] Figure 6 This is a structural block diagram of the traffic data processing device in an embodiment of the present invention. Detailed Implementation

[0023] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings, but these are not intended to limit the scope of the invention.

[0024] It should be understood that various modifications can be made to the embodiments disclosed herein. Therefore, the following description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this disclosure will be apparent to those skilled in the art.

[0025] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present disclosure and, together with the general description of the present disclosure given above and the detailed description of the embodiments given below, serve to explain the principles of the present disclosure.

[0026] These and other features of the invention will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0027] It should also be understood that although the invention has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of the invention, which have the features described in the claims and are therefore all within the scope of protection defined herein.

[0028] The above and other aspects, features and advantages of this disclosure will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0029] Specific embodiments of the present disclosure are described thereafter with reference to the accompanying drawings; however, it should be understood that the disclosed embodiments are merely examples of the present disclosure and can be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure the present disclosure. Therefore, the specific structural and functional details disclosed herein are not intended to be limiting, but merely to serve as the basis and representative basis for the claims to teach those skilled in the art to use the present disclosure in a variety of substantially any suitable detailed structures.

[0030] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in still another embodiment,” all of which may refer to one or more of the same or different embodiments according to this disclosure.

[0031] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0032] Traffic activities manifest in space and time as the orderly movement of passengers or goods between a series of nodes, forming a chain structure, i.e., a traffic chain. Due to the many differences in the nature and characteristics of travel and transportation activities, traffic chains can be distinguished and may include travel chains and transportation chains; in this embodiment, they are collectively referred to as traffic chains.

[0033] From the perspective of the origin and destination of transportation activities, most transportation chains have a closed structure. For example, travel is generally organized around families, while transportation activities are often organized around logistics stations. Therefore, a complete trip or transportation involves at least two segments: a journey to and a return journey. That is, from a network scale perspective, a trip from city A to city B often corresponds to a return trip from city B to city A. In this case, current solutions cannot reflect the true origin and destination of the trip, i.e., whether it is a trip from A to B or from B to A; and because of the lack of judgment on individual attributes, such as whether a trip is a journey to or from home and which city the individual belongs to, effective analysis of vehicle behavior is not possible.

[0034] To solve the above problems, such as Figure 1 As shown, an embodiment of the present invention provides a traffic data processing method, including: Obtain license plate number information and vehicle attribute information; Obtain travel information corresponding to the license plate number, the travel information including at least one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information; The vehicle's location, origin, and destination for each trip are determined based on one or more of the vehicle attribute information, highway toll station information, time information, and vehicle status information. The traffic chain of the corresponding vehicle is constructed based at least on the license plate number information, the license plate number's place of origin, the origin and destination of each trip, as well as the information of the highway toll stations and time information along the route; A target database shall be constructed based at least on the aforementioned transportation chain.

[0035] Specifically, this embodiment focuses on the analysis of individual behavior, including extracting individual behavioral trajectories and identifying complete travel or transportation activities as the basic analytical object for individual traffic behavior. For example, as shown above, the solution in this embodiment mainly identifies the origin, destination, departure time, arrival time, and license plate location of each trip by obtaining vehicle license plate information, vehicle attribute information, and travel information. Based on this, a traffic chain corresponding to each license plate can be constructed, and a database can be built based on the traffic chains corresponding to different vehicles. The method based on this embodiment can effectively manage vehicle traffic data and facilitate subsequent traceability.

[0036] For example, obtaining the license plate number information and vehicle attribute information includes: Obtain license plate number information, vehicle type information, and vehicle model information.

[0037] The vehicle type information includes trucks and buses.

[0038] The travel information obtained corresponding to the license plate number includes: The system obtains information on the highway toll stations along the route of the vehicle corresponding to the license plate number during each trip within a target time period, the corresponding entry and exit times of different highway toll stations, and the vehicle's load status. The target time period is at least in days.

[0039] The vehicle load status information mainly includes the load information of trucks.

[0040] In one embodiment, the method further includes: At least the obtained vehicle attribute information and travel information should be uniformly encoded; Based on the coded vehicle attribute information and travel information, the location of the license plate number, as well as the origin and destination of each trip, are determined.

[0041] This embodiment encodes the obtained initial data and establishes the inherent relationships between the data, achieving the following objectives: ① simplifying the algorithm and improving data processing efficiency and accuracy; ② avoiding direct involvement of personal privacy. The re-encoded fields include, but are not limited to, license plate number and its location, entrance and exit stations and their respective counties / districts, as well as entrance and exit times.

[0042] In addition, before processing traffic data, the data can be cleaned and differentiated. For example, this may include: ① deleting invalid records, including records with missing key fields, erroneous records, records that exceed the research period, and other types of invalid records; ② differentiating travel behavior and transportation behavior based on vehicle type code and vehicle model code; ③ differentiating intercity traffic and non-intercity traffic based on whether the origin and destination of a trip or transportation are the same.

[0043] Furthermore, the determination of the license plate number's origin based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: The vehicle type is determined based on the vehicle attribute information, and the vehicle type includes trucks and buses. Based on the time information, the information of the highway toll stations along the route is processed to obtain the information of the highway toll stations that the vehicle passes through in sequence for each trip. Based on the information of highway toll stations along the route of each vehicle's trip, the location of the first highway toll station the vehicle enters on its first trip of the day is determined, and the frequency of each location in a target time period is calculated, with the target time period based on a day as the basic unit. When the vehicle type is a passenger vehicle, the location corresponding to the highest frequency will be determined as the location of the license plate number. When the vehicle type is a truck, the load status information of the vehicle when passing through each highway toll station in sequence during each trip is determined based on the highway toll station information and vehicle status information of each trip. Based on the frequency of statistics and the load status information of each trip, the location with the highest frequency and the largest load is determined as the place of origin of the license plate number.

[0044] For example, as mentioned earlier, the location of a license plate number typically represents the starting and ending point of a complete travel chain. For passenger vehicles, the county / district with the highest number of departures between 6:00 AM and 12:00 PM can be defined as the location of that license plate. That is, if a vehicle with license plate number B always departs from county / district A in the morning to other areas, then the location of license plate number B is considered to be county / district A. For freight vehicles, given that strict time restrictions on freight vehicle entry in some cities can affect the spatiotemporal organization of freight flow, the county / district with the highest number of departures throughout the day can be defined as the location of that license plate. When there are multiple counties / districts with the same number of departures, the county / district with the heaviest load among the most frequent departures can be considered as the location of the license plate.

[0045] In another embodiment, determining the origin and destination of each trip based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: Based on the information of highway toll stations along the route and the time information, the information of the first highway toll station that meets the time sequence for each trip route and the entry and exit time of each first highway toll station are determined. The information of the first highway toll station includes the location and the type of toll station. The toll station type includes county toll stations within the province and provincial border toll stations. When determining that the corresponding trip is an intra-provincial trip based on the information of the first highway toll station and the entry and exit time, the location of the first highway toll station where the trip begins will be determined as the starting point of the trip, and the location of the first highway toll station where the trip ends will be determined as the destination of the trip.

[0046] Furthermore, the method also includes: When determining a second highway toll station that is a provincial border highway toll station based on the information of the first highway toll station, the entry and exit times and the province information of the second highway toll station are determined based on the information of the first highway toll station and the entry and exit times. Based on the entry and exit times and province information of the second highway toll station, determine whether there are two target second highway toll stations with an entry and exit interval time less than a preset time value and different province information. The entry and exit times of the second target second highway toll station among the two target second highway toll stations are retained, or the entry and exit records of both second highway toll stations are deleted simultaneously. The location of the first highway toll station and its entry / exit time for each trip will be determined by retaining the information of the first highway toll station and its entry / exit time, or the information of the first highway toll station and its entry / exit time, and the information of the second highway toll station and its entry / exit time. At the same time, the location of the first or second highway toll station for the last exit will be determined as the destination of this trip.

[0047] For example, taking some regions in my country as examples, these regions all have cross-provincial border issues, thus exhibiting two types of traffic flows: intra-provincial traffic flow and inter-provincial traffic flow. The origin and destination of intra-provincial traffic flows can be directly identified through recorded entry and exit toll stations on highways, while inter-provincial traffic flows require further data processing for identification. This is because inter-provincial traffic must pass through toll stations at provincial borders to reach its destination. Therefore, the first recorded destination of an inter-provincial trip is usually the toll station at the provincial border. Accordingly, when determining an inter-provincial trip, all vehicle records are first selected, and the entry and exit toll stations are rearranged chronologically based on time information. Trips occurring outside the study area and records whose travel times do not meet the requirements are deleted, such as excluding data generated before the target date. Specifically, if the entry point of the first record is located at a toll station at the provincial border, it is considered that the data was generated before the target date, and this data would result in the loss of the trip's origin information. Therefore, this part of the record is deleted.

[0048] Secondly, the obtained travel information is differentiated into intra-provincial and inter-provincial traffic flows. In this step, it's checked whether the exit point of the highway toll station is located at a provincial border. If not, the record represents an intra-provincial trip, in which case the first entry point of the trip can be taken as the departure point, and the last exit point as the destination. If the exit point is located at a provincial border, then the next record is checked to determine the final destination.

[0049] Next, records that meet the requirements in the travel information are merged, such as merging cross-provincial traffic flow records to determine the final destination. Generally, the distance between two adjacent toll stations at a provincial border is less than 10 kilometers (travel time is usually less than 30 minutes). Therefore, if the entry station of the next record is a highway toll station in another neighboring province, and the time interval between the two stations is less than 30 minutes (but not limited to 30 minutes), the two records are merged to generate a new record. The entry station of the new record is the entry station of the first record, and the exit station is the exit station of the second record. If the requirements are not met, the record is deleted because the travel trajectory is interrupted, the destination is unclear, and the construction of the traffic chain is affected. The entry and exit stations of the new record represent the origin and destination of only one cross-provincial trip. In the case of two or more cross-provincial trips, this process is repeated until the final destination is determined.

[0050] Optionally, since the journey from province A to province B requires exiting the highway toll station at the provincial border of province A and then entering the highway toll station at the border of province B, a boundary station mapping dictionary can be established during the data preprocessing stage to facilitate subsequent cross-border flow processing. This dictionary will construct the connection relationships between highway toll stations in different provinces, label cross-border flows, and implement unified coding.

[0051] like Figure 2 , Figure 3As shown, the origin and destination include the origin and destination of the entire journey, as well as the origin and destination of the travel path formed by the distance between two adjacent highway toll stations. The construction of the traffic chain for the corresponding vehicle based on the license plate number information, the license plate number's origin, the origin and destination of each trip, and the information on highway toll stations and times along the route includes: The departure and arrival times are determined based on the origin and destination, highway toll station information, and time information of each trip. Based on the license plate information, the license plate location, the origin and destination of each trip, and the departure and arrival times, a traffic chain is constructed according to a target format. The target format includes recording the license plate information, the license plate location, the origin and departure time of each trip, the destination and arrival time of each trip in sequence. Multiple transportation chains with consecutive departure and destination points and consecutive times within the same day are merged, and the information of the corresponding departure point, departure time, destination, and arrival time is reconstructed to form departure sequence, departure time sequence, destination sequence, and arrival time sequence.

[0052] For example, for the preprocessed data, the data structure is reconstructed using the license plate number as the primary key. Each reconstructed record includes six basic pieces of information: license plate number, origin, departure location sequence, departure time sequence, destination sequence, and arrival time sequence. Figure 2 As shown. For two consecutive records involving border highway toll stations, identification and judgment are made based on the border station comparison dictionary constructed above, or based on highway toll station information along the route and entry / exit times: if the locations corresponding to the border highway toll stations in the two records match, and the difference in entry / exit times between the two toll stations is less than 30 minutes, then the two records are merged, or the cross-border flow annotations of these two records are deleted, and they are treated as non-cross-border flows, for example... Figure 3 As shown.

[0053] In another embodiment, the construction of the target database based at least on the traffic chain includes: A first data table is constructed based on the vehicle attribute information; A second data table is constructed based on the city or county attribute information of each of the aforementioned highway toll stations. The first data table is linked with the license plate information in the transportation chain, and the second data table is linked with each highway toll station involved in the transportation chain. A target database is constructed based on the traffic chain that connects the first data table and the second data table.

[0054] The first data table, also known as the license plate number attribute table, records the vehicle model and type corresponding to each license plate number. This data table is linked to the license plate number so that the license plate number attribute table can be retrieved when the user clicks on the license plate number information.

[0055] The second data table is equivalent to a city node attribute table, which can include fields such as county / district (primary key), GDP, population, number of civilian vehicles, and road network density. This second data table can be linked with the field information of highway toll stations, so that when a user clicks on highway toll station information with a certain field, the corresponding second data table can be retrieved to understand the attribute information of the toll station's location.

[0056] As an optional embodiment, this embodiment also constructs a corresponding transportation chain topology model. For example, a topology structure is constructed using a trip or transportation as three basic elements: origin, destination, and route. In this topology structure, each trip can be simplified as an edge (representing the number of trips) connecting two nodes (representing city nodes). Given the number of edges and the number of nodes, a set of potential organizational patterns for the transportation chain will be formed, which can be found in the following references. Figure 4 As shown. Continue to combine Figure 4 As shown in the diagram, obtaining the set of topological patterns is essentially a permutation and combination with constraints. These constraints include: ① The starting point is a home, and a home can only appear at the starting point and the ending point; ② Adjacent points cannot be the same (i.e., the starting point and the destination cannot be the same). Taking E (edges / number of trips) = 6 as an example, there are a total of 4 cases and 15 patterns.

[0057] Case ①: When N (nodes, representing cities) is 6, there is 1 pattern: abcdef.

[0058] Case 2: When N is 5, there are 6 patterns: abcbde / acbdbe / acdbeb / abcdbe / acbdeb / abcdeb.

[0059] Case ③: When N is 4, there are 7 patterns: abcbdb / abcbcd / abcbdc / abcdbc / abdcbc / abcdcb / adbcbc.

[0060] Case 4: When N is 3, there is 1 pattern: abcbcb.

[0061] In theory, the number of travel chain patterns is exponentially related to the number of trips. Based on data analysis, intercity trips with no more than 6 trips account for over 99.99% of total trips. Therefore, this paper focuses on identifying organizational patterns with no more than 6 trips.

[0062] It should be noted that the above patterns are all topological patterns. Except for the first letter 'a', which indicates that the license plate number's location is irreplaceable, the other letters only reflect differences in order, not differences in location or attributes. That is, abcdbd and adcbdb are the same pattern. Some patterns can be identified simply by judging the values ​​of E and N. When multiple organizational patterns exist given E and N, pattern discrimination must be strictly performed according to the origin sequence.

[0063] Based on the above topological model, such as Figure 5 As shown, database construction may include: The extracted transportation chains are used to generate new data tables according to different topological organization patterns. Key fields include license plate number, entrance station number, exit station number, and indicators describing the spatiotemporal organization of the transportation chain, such as departure time, arrival time, travel duration, and dwell time. Using this data table as the core, other data are organized to construct a new relational database. The main data tables include: ① License Plate Number Attribute Table: Includes vehicle information such as license plate number (primary key), license plate location, number of trips, vehicle type, and vehicle class. ② Toll Station Attribute Table: Includes fields such as toll station number (primary key), name, route, city / county, whether it is a provincial border station, and its geographical coordinates. ③ City Node Attribute Table: Includes fields such as county / district (primary key), GDP, population, number of civilian vehicles, and road network density. The various data tables can be linked together. For example, the license plate number field can be used to link the license plate number attribute table and the traffic chain attribute table; the entry station number or exit station number field can be used to link the toll station attribute table and the traffic chain attribute table; and the county / district field can be used to link the city node attribute table and the toll station attribute table.

[0064] like Figure 6 As shown, another embodiment of the present invention also provides a traffic data processing device 100, comprising: The first acquisition module is used to obtain license plate number information and vehicle attribute information; The second obtaining module is used to obtain travel information corresponding to the license plate number information. The travel information includes at least one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information. The first determining module is used to determine the license plate number's location, the origin and destination of each trip, based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information. The first construction module is used to construct the traffic chain of the corresponding vehicle based at least on the license plate number information, the license plate number location, the origin and destination of each trip, as well as the highway toll station information and time information along the route. The second construction module is used to construct a target database based at least on the traffic chain.

[0065] As an optional embodiment, obtaining the license plate number information and vehicle attribute information includes: Obtain license plate number information, vehicle type information, and vehicle model information.

[0066] As an optional embodiment, obtaining the travel information corresponding to the license plate number includes: The system obtains information on the highway toll stations along the route of the vehicle corresponding to the license plate number during each trip within a target time period, the corresponding entry and exit times of different highway toll stations, and the vehicle's load status. The target time period is at least in days.

[0067] As an optional embodiment, the device further includes: The encoding module is used to uniformly encode at least the obtained vehicle attribute information and travel information; The first determining module is also used to determine the license plate number's location, the origin and destination of each trip, based on the encoded vehicle attribute information and travel information.

[0068] As an optional embodiment, determining the license plate number's origin based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: The vehicle type is determined based on the vehicle attribute information, and the vehicle type includes trucks and buses. Based on the time information, the information of the highway toll stations along the route is processed to obtain the information of the highway toll stations that the vehicle passes through in sequence for each trip. Based on the information of highway toll stations along the route of each vehicle's trip, the location of the first highway toll station the vehicle enters on its first trip of the day is determined, and the frequency of each location in a target time period is calculated, with the target time period based on a day as the basic unit. When the vehicle type is a passenger vehicle, the location corresponding to the highest frequency will be determined as the location of the license plate number. When the vehicle type is a truck, the load status information of the vehicle when passing through each highway toll station in sequence during each trip is determined based on the highway toll station information and vehicle status information of each trip. Based on the frequency of statistics and the load status information of each trip, the location with the highest frequency and the largest load is determined as the place of origin of the license plate number.

[0069] As an optional embodiment, determining the origin and destination of each trip based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: Based on the information of highway toll stations along the route and the time information, the information of the first highway toll station that meets the time sequence for each trip route and the entry and exit time of each first highway toll station are determined. The information of the first highway toll station includes the location and the type of toll station. The toll station type includes county toll stations within the province and provincial border toll stations. When determining that the corresponding trip is an intra-provincial trip based on the information of the first highway toll station and the entry and exit time, the location of the first highway toll station where the trip begins will be determined as the starting point of the trip, and the location of the first highway toll station where the trip ends will be determined as the destination of the trip.

[0070] As an optional embodiment, the device further includes: The second determining module is used to determine the entry and exit times and the province information of the second highway toll station when determining the second highway toll station, which includes a provincial border highway toll station, based on the first highway toll station information and the entry and exit times. The third determining module is used to determine whether there are two target second highway toll stations with an entry and exit time less than a preset time value and different province information based on the entry and exit time and the province information of the second highway toll station. The processing module is used to retain the entry and exit times of the second target second highway toll station which is entered later among the two target second highway toll stations, or to delete the entry and exit records of both second highway toll stations at the same time. The fourth determination module is used to determine the location of the first highway toll station where the first entry is made, and the location of the first or second highway toll station where the first exit is made, based on the retained information of the first highway toll station and its entry and exit time for each trip, or the information of the first and second highway toll stations and their entry and exit times. At the same time, the location of the first or second highway toll station where the last exit is made, is determined as the destination of the trip.

[0071] As an optional embodiment, the origin and destination include the origin and destination of the entire journey, as well as the origin and destination of the travel path formed by the distance between two adjacent highway toll stations. The construction of the traffic chain for the corresponding vehicle based on the license plate number information, the license plate number's origin, the origin and destination of each trip, and the information on highway toll stations and times along the route includes: The departure and arrival times are determined based on the origin and destination, highway toll station information, and time information of each trip. Based on the license plate information, the license plate location, the origin and destination of each trip, and the departure and arrival times, a traffic chain is constructed according to a target format. The target format includes recording the license plate information, the license plate location, the origin and departure time of each trip, the destination and arrival time of each trip in sequence. Multiple transportation chains with consecutive departure and destination points and consecutive times within the same day are merged, and the information of the corresponding departure point, departure time, destination, and arrival time is reconstructed to form departure sequence, departure time sequence, destination sequence, and arrival time sequence.

[0072] As an optional embodiment, the construction of the target database based at least on the transportation chain includes: A first data table is constructed based on the vehicle attribute information; A second data table is constructed based on the city or county attribute information of each of the aforementioned highway toll stations. The first data table is linked with the license plate information in the transportation chain, and the second data table is linked with each highway toll station involved in the transportation chain. A target database is constructed based on the traffic chain that connects the first data table and the second data table.

[0073] Another embodiment of the present invention also provides an electronic device, comprising: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the traffic data processing method as described in any of the embodiments above.

[0074] Another embodiment of the present invention also provides a storage medium including a stored program, wherein, when the program is executed, a device including the storage medium is controlled to perform the traffic data processing method as described in any of the embodiments above.

[0075] This invention also provides a computer program product, which is tangibly stored on a computer-readable medium and includes computer-readable instructions. When executed, these computer-executable instructions cause at least one processor to perform a traffic data processing method as described in the embodiments above. It should be understood that the various solutions in this embodiment have the corresponding technical effects in the above method embodiments, and will not be repeated here.

[0076] It should be noted that the computer storage medium in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access storage medium (RAM), a read-only storage medium (ROM), an erasable programmable read-only storage medium (EPROM or flash memory), an optical fiber, a portable compact disk read-only storage medium (CD-ROM), an optical storage medium, a magnetic storage medium, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program configured for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, antenna, optical fiber, RF, etc., or any suitable combination thereof.

[0077] One or more embodiments in this application are intended to cover all such substitutions, modifications, and variations falling within the broad scope of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of one or more embodiments in this application should be included within the protection scope of this application. The above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the present invention; the protection scope of the present invention is defined by the claims.

[0078] The above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the present invention. The scope of protection of the present invention is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to the present invention within its spirit and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of the present invention.

Claims

1. A traffic data processing method, characterized in that, include: Obtain license plate number information and vehicle attribute information; Obtain travel information corresponding to the license plate number, the travel information including one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information; Based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information, the license plate number's origin, the start point, and the destination of each trip are determined; wherein, The method of determining the license plate number's origin based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: The vehicle type is determined based on the vehicle attribute information, and the vehicle type includes trucks and buses. Based on the time information, the information of the highway toll stations along the route is processed to obtain the information of the highway toll stations that the vehicle passes through in sequence for each trip. Based on the information of highway toll stations along the route of each vehicle's trip, the location of the first highway toll station the vehicle enters on its first trip of the day is determined, and the frequency of each location in a target time period is calculated, with the target time period based on a day as the basic unit. When the vehicle type is a passenger vehicle, the location corresponding to the highest frequency will be determined as the location of the license plate number. When the vehicle type is a truck, the load status information of the vehicle when passing through each highway toll station in sequence during each trip is determined based on the highway toll station information and vehicle status information of each trip. Based on the frequency of statistics and the load status information of each trip, the location with the highest frequency and the largest load is determined as the place of origin of the license plate number; The method of determining the origin and destination of each trip based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: Based on the information of highway toll stations along the route and the time information, the information of the first highway toll station that meets the time sequence for each trip route and the entry and exit time of each first highway toll station are determined. The information of the first highway toll station includes the location and the type of toll station. The toll station type includes county toll stations within the province and provincial border toll stations. When determining the corresponding trip as an intra-provincial trip based on the information of the first highway toll station and the entry and exit time, the location of the first highway toll station where the trip begins will be determined as the starting point of the trip, and the location of the first highway toll station where the trip ends will be determined as the destination of the trip. Based on the license plate number information, the license plate number's origin, the origin and destination of each trip, as well as the information on highway toll stations and time information, a traffic chain for the corresponding vehicle is constructed. A target database is constructed based on the aforementioned transportation chain.

2. The traffic data processing method according to claim 1, characterized in that, The acquisition of license plate number information and vehicle attribute information includes: Obtain license plate number information, vehicle type information, and vehicle model information.

3. The traffic data processing method according to claim 1, characterized in that, The travel information obtained corresponding to the license plate number includes: The system obtains information on the highway toll stations along the route of the vehicle corresponding to the license plate number during each trip within a target time period, the corresponding entry and exit times of different highway toll stations, and the vehicle's load status. The target time period is based on a day.

4. The traffic data processing method according to claim 1, characterized in that, The method further includes: The obtained vehicle attribute information and travel information are uniformly encoded; Based on the coded vehicle attribute information and travel information, the location of the license plate number, as well as the origin and destination of each trip, are determined.

5. The traffic data processing method according to claim 1, characterized in that, The method further includes: When determining a second highway toll station that is a provincial border highway toll station based on the information of the first highway toll station, the entry and exit times and the province information of the second highway toll station are determined based on the information of the first highway toll station and the entry and exit times. Based on the entry and exit times and province information of the second highway toll station, determine whether there are two target second highway toll stations with an entry and exit interval time less than a preset time value and different province information. The entry and exit times of the second target second highway toll station among the two target second highway toll stations are retained, or the entry and exit records of both second highway toll stations are deleted simultaneously. The location of the first highway toll station and its entry / exit time for each trip will be determined by retaining the information of the first highway toll station and its entry / exit time, or the information of the first highway toll station and its entry / exit time, and the information of the second highway toll station and its entry / exit time. At the same time, the location of the first or second highway toll station for the last exit will be determined as the destination of this trip.

6. The traffic data processing method according to claim 1, characterized in that, The origin and destination include the origin and destination of the entire journey, as well as the origin and destination of the travel path formed by the distance between two adjacent highway toll stations. The construction of the traffic chain for the corresponding vehicle based on the license plate number information, the license plate number's origin, the origin and destination of each trip, and the information on highway toll stations and times along the route includes: The departure and arrival times are determined based on the origin and destination, highway toll station information, and time information of each trip. Based on the license plate information, the license plate location, the origin and destination of each trip, and the departure and arrival times, a traffic chain is constructed according to a target format. The target format includes recording the license plate information, the license plate location, the origin and departure time of each trip, the destination and arrival time of each trip in sequence. Multiple transportation chains with consecutive departure and destination points and consecutive times within the same day are merged, and the information of the corresponding departure point, departure time, destination, and arrival time is reconstructed to form departure sequence, departure time sequence, destination sequence, and arrival time sequence.

7. The traffic data processing method according to claim 1, characterized in that, The construction of the target database based on the transportation chain includes: A first data table is constructed based on the vehicle attribute information; A second data table is constructed based on the city or county attribute information of each of the aforementioned highway toll stations. The first data table is linked with the license plate information in the transportation chain, and the second data table is linked with each highway toll station involved in the transportation chain. A target database is constructed based on the traffic chain that connects the first data table and the second data table.

8. A traffic data processing device, characterized in that, include: The first acquisition module is used to obtain license plate number information and vehicle attribute information; The second obtaining module is used to obtain travel information corresponding to the license plate number information. The travel information includes one or more of the following: information on highway toll stations along the route, time information for entering and exiting different highway toll stations, and vehicle status information. The first determining module is used to determine the license plate number's origin, the origin and destination of each trip, based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information; wherein... The method of determining the license plate number's origin based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: The vehicle type is determined based on the vehicle attribute information, and the vehicle type includes trucks and buses. Based on the time information, the information of the highway toll stations along the route is processed to obtain the information of the highway toll stations that the vehicle passes through in sequence for each trip. Based on the information of highway toll stations along the route of each vehicle's trip, the location of the first highway toll station the vehicle enters on its first trip of the day is determined, and the frequency of each location in a target time period is calculated, with the target time period based on a day as the basic unit. When the vehicle type is a passenger vehicle, the location corresponding to the highest frequency will be determined as the location of the license plate number. When the vehicle type is a truck, the load status information of the vehicle when passing through each highway toll station in sequence during each trip is determined based on the highway toll station information and vehicle status information of each trip. Based on the frequency of statistics and the load status information of each trip, the location with the highest frequency and the largest load is determined as the place of origin of the license plate number; The method of determining the origin and destination of each trip based on one or more of the vehicle attribute information, highway toll station information along the route, time information, and vehicle status information includes: Based on the information of highway toll stations along the route and the time information, the information of the first highway toll station that meets the time sequence for each trip route and the entry and exit time of each first highway toll station are determined. The information of the first highway toll station includes the location and the type of toll station. The toll station type includes county toll stations within the province and provincial border toll stations. When determining the corresponding trip as an intra-provincial trip based on the information of the first highway toll station and the entry and exit time, the location of the first highway toll station where the trip begins will be determined as the starting point of the trip, and the location of the first highway toll station where the trip ends will be determined as the destination of the trip. The first construction module is used to construct the traffic chain of the corresponding vehicle based on the license plate number information, the license plate number location, the origin and destination of each trip, as well as the highway toll station information and time information along the route. The second construction module is used to construct a target database based on the traffic chain.

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