CN109886532B

CN109886532B - Driving route planning method, device, computer equipment and storage medium

Info

Publication number: CN109886532B
Application number: CN201910013079.4A
Authority: CN
Inventors: 吴壮伟
Original assignee: Ping An Technology Shenzhen Co Ltd
Current assignee: Ping An Technology Shenzhen Co Ltd
Priority date: 2019-01-07
Filing date: 2019-01-07
Publication date: 2023-10-27
Anticipated expiration: 2039-01-07
Also published as: CN109886532A; WO2020143160A1

Abstract

The invention discloses a driving route planning method, a driving route planning device, computer equipment and a storage medium. The method comprises the following steps: acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list historical data in a constructed linked list; cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set; and obtaining paths with frequency ranking of paths in the path statistics data set positioned before a preset first ranking threshold value to form a first path set, and counting a direct connection path formed by a starting point and a terminal point corresponding to each path in the first path set to obtain a first planning line set. According to the method, the traffic frequency of each road is analyzed by the dimension data with fine granularity, so that more accurate route planning can be constructed.

Description

Driving route planning method, device, computer equipment and storage medium

Technical Field

The present invention relates to the field of data analysis technologies, and in particular, to a driving route planning method, a driving route planning device, a computer device, and a storage medium.

Background

Currently, when urban road planning is performed, the urban road is generally planned according to building distribution or other factors, which results in that the planned road route may cause traffic jam due to unreasonable road route. The route with frequent traffic jam is generally a road with high traffic frequency, for example, a common route of a plurality of vehicles is a-b-c-d, which means that the route from the starting point a to the ending point d is a high traffic frequency, and if the influence of the traffic frequency is not considered in planning, the planned road route may not solve the traffic jam problem.

Disclosure of Invention

The embodiment of the invention provides a driving route planning method, a driving route planning device, computer equipment and a storage medium, which aim to solve the problem that in the prior art, when an urban road is planned, the planning is generally carried out according to factors such as building distribution, and the like, so that the planned road route can cause traffic jam due to the fact that the actual traffic flow of each road is not considered.

In a first aspect, an embodiment of the present invention provides a driving route planning method, including:

Acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list historical data in a constructed linked list;

cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set; and

and acquiring paths of which the frequency ranking of the paths is positioned in front of a preset first ranking threshold value in the path statistics data set to form a first path set, and counting a direct connection path formed by a starting point and an end point corresponding to each path in the first path set to obtain a first planning line set.

In a second aspect, an embodiment of the present invention provides a driving route planning apparatus, including:

the data storage unit is used for acquiring the acquired user path data, converting the user path data into linked list data and storing the linked list data in the corresponding linked list historical data in the constructed linked list;

the data cutting unit is used for cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to the linked list historical data corresponding to each user in the linked list and a preset cutting time interval value, and counting the plurality of sections of paths to obtain a path statistical data set; and

The first route set acquisition unit is used for acquiring the routes of which the frequency ranks of the routes in the route statistical data set are positioned before a preset first ranking threshold value to form a first route set, and counting the direct connection routes formed by the starting point and the end point corresponding to each route in the first route set to obtain a first planning route set.

In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the driving route planning method according to the first aspect.

In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores a computer program, which when executed by a processor, causes the processor to perform the driving route planning method according to the first aspect.

The embodiment of the invention provides a driving route planning method, a driving route planning device, computer equipment and a storage medium. Acquiring acquired user path data, converting the user path data into linked list data, and storing the linked list data in linked list history data corresponding to a constructed linked list; cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set; and obtaining paths with frequency ranking of paths in the path statistics data set positioned before a preset first ranking threshold value to form a first path set, and counting a direct connection path formed by a starting point and a terminal point corresponding to each path in the first path set to obtain a first planning line set. According to the method, the traffic frequency of each road is analyzed by the dimension data with fine granularity, so that more accurate route planning can be constructed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic diagram of an application scenario of a driving route planning method according to an embodiment of the present invention;

fig. 2 is a flow chart of a driving route planning method according to an embodiment of the present invention;

fig. 3 is another flow chart of a driving route planning method according to an embodiment of the present invention;

fig. 4 is a schematic sub-flowchart of a driving route planning method according to an embodiment of the present invention;

fig. 5 is another schematic sub-flowchart of a driving route planning method according to an embodiment of the present invention;

fig. 6 is a schematic block diagram of a driving route planning device according to an embodiment of the present invention;

FIG. 7 is another schematic block diagram of a driving route planning apparatus according to an embodiment of the present invention;

fig. 8 is a schematic block diagram of a subunit of the driving route planning apparatus according to the embodiment of the present invention;

FIG. 9 is a schematic block diagram of another subunit of a driving route planning apparatus according to an embodiment of the present invention;

fig. 10 is a schematic block diagram of a computer device according to an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

Referring to fig. 1 and fig. 2, fig. 1 is a schematic view of an application scenario of a driving route planning method according to an embodiment of the present invention, and fig. 2 is a schematic flow chart of the driving route planning method according to an embodiment of the present invention, where the driving route planning method is applied to a server, and the method is executed by application software installed in the server.

As shown in fig. 2, the method includes steps S110 to S130.

S110, acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list historical data in the constructed linked list.

In this embodiment, after the server receives the user path data acquired by the front-end acquisition device and converted, the user path data corresponding to each user is stored in a linked list manner, so as to effectively monitor the path of each user.

In one embodiment, as shown in fig. 4, step S110 includes steps S111-S115.

And S111, receiving user path data obtained by identifying the acquired vehicle picture, and storing the user path data into a created temporary database.

In this embodiment, a front-end acquisition device (such as a monitoring camera) disposed on a road acquires a plurality of vehicle pictures, identifies the vehicle pictures, and then uploads the vehicle pictures to a server, and the server receives user path data including license plate numbers and then stores the user path data in a temporary database created in the server. Because the uploading server is the user path data, the vehicle picture is not required to be uploaded, and the data transmission quantity is reduced.

In order to more clearly understand the usage scenario of the technical solution (for example, to monitor the traffic route track of the user), the following description will refer to the terminal. In the application, the technical scheme is described in terms of standing on a server.

The first is a server in which message middleware and a linked list are deployed. The message middleware is used for receiving the user path data uploaded by the front-end acquisition device, analyzing and processing the user path data into linked list data, and then sending the linked list data to the linked list for storage.

And secondly, the front-end acquisition device is used for acquiring user path data and uploading the user path data to the message middleware, for example, after the vehicle pictures acquired by the monitoring cameras are locally identified by license plates, the acquired user path data can be analyzed and comprises information such as license plates, names of the current intersections and time points of the current intersections, namely, the vehicle pictures acquired by the monitoring cameras at least comprise information such as license plates, names of the current intersections and time points of the current intersections, wherein the license plates can be used as unique identification codes of users, the names of the current intersections and the time points of the current intersections can be used as linked list data to be processed corresponding to the unique identification codes of the users. For example, the monitoring camera set at the intersection a shoots the vehicle picture of the vehicle a at the intersection a, the license plate recognition is performed by the monitoring camera set at the intersection a to obtain the license plate number of the vehicle a, and at this time, the user path data can be formed according to the license plate number of the vehicle a, the intersection name of the intersection a (i.e. the name of the current intersection), and the time when the monitoring camera set at the intersection a shoots the vehicle picture of the vehicle a at the intersection a (i.e. the time point of passing through the current intersection).

In one embodiment, the step S111 of receiving the user path data obtained by identifying the collected vehicle picture, and storing the user path data in the created temporary database includes:

receiving user path data obtained by identifying the acquired vehicle pictures through a message middleware, and storing the user path data into a temporary database created in the message middleware; the message middleware is a distributed publishing and subscribing message middleware; the user path data comprises license plate numbers, names of the current crossing, and time points of the current crossing.

In this embodiment, the message middleware is a distributed publish-subscribe message middleware (a distributed publish-subscribe message middleware, i.e. a Kafka message middleware), and the Kafka message middleware can be visually understood as a large pool, so that messages of various types are continuously produced, stored and consumed, i.e. a producer writes the messages into a queue (i.e. a pool visually understood), and a consumer removes the messages from the queue to perform service logic. The Kafka message middleware is used as temporary storage data of the user path data, so that the user path data can be effectively processed and processed correspondingly.

S112, acquiring the user path data from the temporary database according to a preset fetch cycle, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code.

In this embodiment, the user path data obtained by identifying the vehicle picture is stored in the temporary database, and in order to consume the user path data in the temporary database, the user path data needs to be obtained from the temporary database according to a preset access period, and the user path data is stored in the target area after being processed. When the user path data is acquired from the temporary database, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code; the to-be-processed linked list data comprise names of the passed current intersections and time points of the passed current intersections.

After user path data is received and stored in Kafka message middleware, the incremental data is temporarily stored in a temporary database, when the incremental data deposited in the temporary database reaches a certain amount, the incremental user path data is acquired from the temporary database according to a preset access period, the user path data is updated to a linked list after being analyzed, and the user path data processed by the temporary database is deleted, so that the repeated insertion of the data into the linked list is avoided.

For a clearer understanding of the present application, a linked list is used to store data, and a linked list is described below.

One chain table data can be established for each user in the chain table, each chain table data only stores the related data of the user corresponding to the chain table data, and a plurality of chain table data can form one chain table.

The concrete storage of the linked list is expressed as:

(1) the nodes of the linear table being held by a set of arbitrary memory cells (the set of memory cells being either continuous or discontinuous)

(2) The logical and physical order of nodes in the linked list are not necessarily the same. In order to correctly represent the logical relationship between nodes, while storing each node value, address (or location) information (referred to as a pointer or chain) indicating its subsequent node must also be stored.

Chain storage is one of the most common storage modes, and can be used to represent not only linear tables, but also various non-linear data structures.

The linked list comprises a data field (namely a data field) and a next field (namely a pointer field); the data field of each link table data in the link table is used for storing the data field of the node value, such as the name of the passing current crossing and the time point of the passing current crossing, which are included in the user path data; the next field is used to store a pointer field (chain field) of an address (location) directly following the node.

In one embodiment, step S112 further includes:

judging whether the linked list data to be processed corresponding to the unique user identification code is a plurality of groups of linked list data or not;

if the to-be-processed linked list data corresponding to the unique user identification code is a plurality of groups of linked list data, ordering the linked list data contained in the plurality of groups of linked list data according to a time ascending order mode to obtain ordered linked list data;

and if the to-be-processed linked list data corresponding to the unique user identification code is not a plurality of groups of linked list data, acquiring the to-be-processed linked list data.

In this embodiment, after a plurality of sets of data are fetched from the temporary database, each set of data corresponds to a unique user identification code, and each set of data can be processed according to the format of the linked list data, that is, when each set of data is fetched from the temporary database, the linked list data to be processed in the set of data is encapsulated into the data field of the linked list data, and the pointer field of the linked list data is initially set to be a null value. At this time, the identification attribute of the linked list data is set as a unique user identification code, and each group of user path data from the temporary database can be processed into the linked list data through the process.

Obviously, if multiple groups of data correspond to the same user unique identification code, whether the to-be-processed linked list data corresponding to the user unique identification code is multiple groups of linked list data is indicated. For example, a certain user unique identification code (e.g. denoted as user A1) is parsed in the Kafka message middleware, which corresponds to the user A1 passing through the bayonet a at 2018, 6, 1, 10:00:00; the user A1 passes through the bayonet b in the period 09:00:00 of 1.6.2018, which means that the to-be-processed linked list data analyzed by the user A1 at this time includes 2 groups of linked list data, and 2 linked list storage units need to be added in linked list historical data corresponding to the user so as to store linked list data at different time points respectively. The two pieces of data are corresponding to linked list data to be processed of the user A1, when the linked list data are ordered according to time sequence, the data A1 is arranged before the linked list data through the bayonet b in the period of 09:00:00 of 1 st month of 6 th 2018; user A1 is arranged behind the user A by the bayonet a in the period of 10:00:00 of 1.6.1.2018, so that the user path data can be stored in time sequence by inserting the linked list after time sequence adjustment of a plurality of groups of linked list data.

S113, traversing and judging whether the linked list history data corresponding to the unique user identification code exists in the locally stored linked list.

In this embodiment, traversing and judging whether there is a linked list history data corresponding to the unique user identification code in a locally stored linked list (the locally stored linked list is each linked list stored in the server) is to judge whether there is a history data corresponding to the unique user identification code in the linked list; if the linked list history data corresponding to the unique user identification code does not exist in the linked list, an initial linked list needs to be newly built in the linked list, and then the linked list data to be processed is correspondingly inserted into the initial linked list; if the linked list historical data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the corresponding linked list historical data for storage.

And S114, if the linked list history data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the linked list history data for storage.

In one embodiment, the step S114 includes:

acquiring each linked list data in the linked list historical data and a time point, corresponding to each linked list data, passing through a current intersection;

Acquiring each linked list data in the linked list data to be processed and a time point, corresponding to each linked list data, passing through a current intersection;

and sequencing the obtained linked list historical data and the obtained linked list data to be processed according to the ascending order of the time point passing through the current intersection, inserting each linked list data in the linked list data to be processed into the linked list historical data, and correspondingly adjusting the pointer field of each linked list data.

In this embodiment, the data field of the linked list is the time point+bayonet; starting from the head of the linked list, continuously finding out the node designated by the next domain (namely the pointer domain), and reserving two pointer values each time of movement, wherein one pointer t1 is a node which stays at the current node, and the other pointer t2 is a node which stays at the next domain; and comparing whether the target time is between the time corresponding to the node pointed by t1 and t2, if so, adding a new node between the nodes pointed by t1 and t2, and storing the current data.

And continuously updating the newly added data to the linked list data corresponding to the unique user identification code, thereby realizing the update of the single user linked list data. The newly added linked list data is supplemented to the time sequence linked list data of the user by traversing the linked list data corresponding to each unique user identification code, so that the latest linked list data (comprising time and bayonets) is obtained, and the transit time of the user on different road sections (road sections are formed between bayonets) based on the linked list data of the user, namely a road section transit time table is obtained.

In one embodiment, as shown in fig. 4, after step S113, the method further includes:

s115, if the linked list has no linked list history data corresponding to the user unique identification code, establishing initial linked list data corresponding to the linked list according to the user unique identification code, and inserting the linked list data to be processed corresponding to the user unique identification code into the initial linked list data.

In this embodiment, if there is no link list history data corresponding to the unique user identifier in the link list, it indicates that the vehicle corresponding to the unique user identifier is monitored and shot for the first time, an initial link list needs to be newly built in the link list, the identifier attribute of the initial link list is set as the unique user identifier, and then the link list data to be processed is inserted into the initial link list.

In one embodiment, before step S1141, the method further includes:

and positioning an application container engine according to the unique user identification code, and acquiring linked list historical data stored in the application container engine.

In this embodiment, a plurality of application container engines (i.e. Docker containers) may be established in the server, each application container engine is named with a unique user identifier as an identification attribute, and correspondingly stores linked list data corresponding to the unique user identifier. By starting one Docker container for each user and then deploying and starting the Docker container program, the large-scale user can update the linked list quickly.

S120, cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to the linked list historical data corresponding to each user in the linked list and a preset cutting time interval value, and counting the plurality of sections of paths to obtain a path statistical data set.

In one embodiment, as shown in fig. 5, step S120 includes:

s121, acquiring node data included in linked list historical data corresponding to each user in the linked list;

s122, judging whether the difference value between the time values corresponding to any adjacent node data exceeds the cutting time interval value;

and S123, deleting the pointer relationship between the corresponding adjacent node data if the difference value between the time values corresponding to the adjacent node data exceeds the cutting time interval value, so as to obtain a multi-segment path.

In this embodiment, the linked list includes a large number of linked list history data of users, where the linked list history data of each user represents the history path data of the user, so that it can accurately reflect when the user passes through the gate. Each node data in the linked list history data of each user comprises a data field and a next field, wherein the data field is used for storing the data field of the node value, such as the name of the currently passing crossing and the time of passing the current crossing, which are included in the user path data. In this way, once the time interval of two adjacent nodes in the linked list historical data of a certain user exceeds the preset cutting time interval value (for example, the cutting time interval value is taken to be 2 hours), cutting off the chain connection relationship between the two adjacent nodes in the chain data formed by the linked list historical data (namely, clearing the pointing relationship of pointers between the two adjacent nodes); if the time interval of two adjacent node data in the linked list historical data does not exceed the preset cutting time interval value, the chain connection relation of the two adjacent node data is maintained. The linked list historical data of each user can be cut into a plurality of sections of paths through the preset cutting time interval value, and linked list historical data of a plurality of different users are cut through the mode, so that the linked list historical data corresponding to each user can be obtained and cut into a plurality of sections of paths, and the plurality of sections of paths are counted to obtain a path statistics data set.

Since it is possible to know which paths the path statistics data includes and the probability value corresponding to each path in the path statistics data set, the path prediction can be performed according to the paths in the path statistics data in the subsequent step.

S130, obtaining paths with frequency ranking of paths in the path statistics data set positioned before a preset first ranking threshold value to form a first path set, and counting direct connection paths formed by a starting point and an end point corresponding to each path in the first path set to obtain a first planning line set.

In this embodiment, when the time dimension is not considered, some paths with higher frequency of paths may be obtained from the path statistics data set, where the paths with higher frequency indicate that the probability of the user passing through the paths is very high, for example, the actual route of the path is a-b-c-d, and in order to improve the traffic efficiency of the path, it may be suggested to directly construct a path directly connected with a-d, so that the traffic efficiency is greatly improved, and traffic congestion is reduced.

For example, when the frequency ranking of the paths in the path statistics set is located in the path before the preset first ranking threshold value to form the first path set, for example, the frequency of the path a-b-c-d is 10000 times, the frequency of the path d-e-f-g is 20000 times, the frequency of the path m-l-n is 40000 times, and the first ranking threshold value is set to 4, and the frequency ranking of the paths m-l-n, d-e-f-g, a-b-c-d is located in the path statistics set in the top 3 bits (i.e. the frequency ranking is located in the preset first ranking threshold value), so that the first path set is formed by the 3 paths of the paths m-l-n, d-e-f-g, a-b-c-d, and then the first planning line set is formed by the paths m-n, d-g, a-d. Through the mode, the route with extremely high traffic flow can be effectively screened out, and the route is used as the basis for constructing the road with the direct connection between the starting point and the terminal point.

In one embodiment, as shown in fig. 3, step S130 further includes:

and S140, obtaining paths, of which the frequency ranking of the paths in the searching time period is positioned before a preset second ranking threshold value, in the path statistics data set so as to form a second path set, and counting the direct connection paths formed by the starting point and the end point corresponding to each path in the second path set so as to obtain a second planning line set.

In this embodiment, when considering the time dimension, some paths with higher frequency in the search time period (such as 7:30-9:00 am and 5:30-7:30 pm) may be obtained from the path statistics data, where the paths with higher frequency indicate that the probability of the user passing through the paths is very high, for example, the actual route of the path is a-b-c-d, and in order to improve the traffic efficiency of the path, it may be suggested to directly construct a path directly connected with a-d, so that the traffic efficiency may be greatly improved, and traffic congestion is reduced.

According to the method, the traffic frequency of each road is analyzed by the dimension data with fine granularity, so that more accurate route planning can be constructed.

The embodiment of the invention also provides a driving route planning device which is used for executing any embodiment of the driving route planning method. Specifically, referring to fig. 6, fig. 6 is a schematic block diagram of a driving route planning apparatus according to an embodiment of the present invention. The driving route planning device 100 may be configured in a server.

As shown in fig. 6, the driving route planning device 100 includes a data storage unit 110, a data cutting unit 120, and a first route set acquisition unit 130.

The data storage unit 110 is configured to obtain the collected user path data, convert the user path data into linked list data, and store the linked list data in the corresponding linked list history data in the constructed linked list.

In one embodiment, as shown in fig. 8, the data storage unit 110 includes a data temporary storage unit 111, a data parsing unit 112, a linked list traversing unit 113, and a data inserting unit 114.

The data temporary storage unit 111 is configured to receive user path data obtained by identifying the acquired vehicle picture, and store the user path data in the created temporary database.

For example, after license plate recognition is locally performed on a vehicle picture acquired by the monitoring camera, the license plate recognition is uploaded to a server, and the acquired user path data can be analyzed to include information such as license plate numbers, names of the current intersections, time points of the current intersections, and the like, namely the vehicle picture acquired by the monitoring camera at least includes information such as license plate numbers, names of the current intersections, time points of the current intersections, and the like, wherein the license plate numbers can be used as unique user identification codes, and the names of the current intersections and the time points of the current intersections can be used as to-be-processed linked list data corresponding to the unique user identification codes. For example, the monitoring camera set at the intersection a shoots the vehicle picture of the vehicle a at the intersection a, the license plate recognition is performed by the monitoring camera set at the intersection a to obtain the license plate number of the vehicle a, and at this time, the user path data can be formed according to the license plate number of the vehicle a, the intersection name of the intersection a (i.e. the name of the current intersection), and the time when the monitoring camera set at the intersection a shoots the vehicle picture of the vehicle a at the intersection a (i.e. the time point of passing through the current intersection).

In an embodiment, the data temporary storage unit 111 is further configured to:

The data parsing unit 112 is configured to obtain the user path data from the temporary database according to a preset access period, parse and obtain a user unique identifier corresponding to the user path data, and to-be-processed linked list data corresponding to the user unique identifier.

In one embodiment, the data storage unit 110 further includes:

the multi-group linked list data judging unit is used for judging whether the linked list data to be processed corresponding to the unique user identification code is the multi-group linked list data or not;

the data sorting unit is used for sorting the linked list data included in the multiple groups of linked list data according to a time ascending order mode if the linked list data to be processed corresponding to the unique user identification code is the multiple groups of linked list data, so as to obtain sorted linked list data;

And the data acquisition unit is used for acquiring the to-be-processed linked list data if the to-be-processed linked list data corresponding to the unique user identification code is not a plurality of groups of linked list data.

And the linked list traversing unit 113 is configured to traverse and determine whether linked list history data corresponding to the unique user identification code exists in the locally stored linked list.

In this embodiment, traversing and judging whether there is a linked list history data corresponding to the unique user identification code in the locally stored linked list is to judge whether there is a history data corresponding to the unique user identification code in the linked list; if the linked list history data corresponding to the unique user identification code does not exist in the linked list, an initial linked list needs to be newly built in the linked list, and then the linked list data to be processed is correspondingly inserted into the initial linked list; if the linked list historical data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the corresponding linked list historical data for storage.

And the data inserting unit 114 is configured to insert the to-be-processed linked list data into the linked list history data for storage if there is linked list history data corresponding to the unique user identifier in the linked list.

In one embodiment, the data insertion unit 114 includes:

the historical data acquisition unit is used for acquiring each linked list data in the linked list historical data and a time point, corresponding to each linked list data, passing through the current intersection;

The current data acquisition unit is used for acquiring each linked list data in the linked list data to be processed and a time point, corresponding to each linked list data, passing through a current intersection;

the sequential inserting unit is used for sequencing the acquisition of the linked list historical data and the acquisition of the linked list data to be processed according to the ascending order of the time point passing through the current intersection, inserting each linked list data in the linked list data to be processed into the linked list historical data, and correspondingly adjusting the pointer field of each linked list data.

In one embodiment, as shown in fig. 8, the data storage unit 110 further includes:

and the link list data new unit 115 is configured to establish initial link list data corresponding to the link list according to the unique user identifier if no link list history data corresponding to the unique user identifier exists in the link list, and insert the link list data to be processed corresponding to the unique user identifier into the initial link list data.

In one embodiment, the data storage unit 110 further includes:

and the storage container positioning unit is used for positioning the application container engine according to the unique user identification code and acquiring the linked list historical data stored in the application container engine.

The data cutting unit 120 is configured to cut the linked list history data corresponding to each user into multiple paths according to a preset cutting time interval value and count multiple paths to obtain a path statistics data set according to the linked list history data corresponding to each user in the linked list.

In one embodiment, as shown in fig. 9, the data cutting unit 120 includes:

a node data obtaining unit 121, configured to obtain each node data included in the linked list history data corresponding to each user in the linked list;

a time difference value judging unit 122, configured to judge whether a difference value between time values corresponding to any adjacent node data exceeds the cutting time interval value;

and the linked list data cutting unit 123 is configured to delete the pointer relationship between the corresponding adjacent node data to obtain a multi-segment path if the difference between the time values corresponding to the adjacent node data exceeds the cutting time interval value.

In this embodiment, the linked list includes a large number of linked list history data of users, where the linked list history data of each user represents the history path data of the user, so that it can accurately reflect when the user passes through the gate. Each node data in the linked list history data of each user comprises a data field and a next field, wherein the data field is used for storing the data field of the node value, such as the name of the currently passing crossing and the time of passing the current crossing, which are included in the user path data. Thus, once the time interval between two adjacent nodes in the linked list historical data of a certain user exceeds the preset cutting time interval value (for example, the cutting time interval value is taken to be 2 hours), the chain connection relationship between the two adjacent nodes in the chain data formed by the linked list historical data is cut off (namely, the pointing relationship of pointers between the two adjacent nodes is cleared). The linked list historical data of each user can be cut into a plurality of sections of paths through the preset cutting time interval value, and linked list historical data of a plurality of different users are cut through the mode, so that the linked list historical data corresponding to each user can be obtained and cut into a plurality of sections of paths, and the plurality of sections of paths are counted to obtain a path statistics data set.

The first route set obtaining unit 130 is configured to obtain a route in the route statistics data set, where the frequency ranking of the route is located before a preset first ranking threshold, so as to form a first route set, and count a direct connection route formed by a start point and an end point corresponding to each route in the first route set, so as to obtain a first planned route set.

In one embodiment, as shown in fig. 7, the driving route planning device 100 further includes:

and a second route set obtaining unit 140, configured to obtain paths in the path statistics data set, where the frequency ranking of the paths in the search time period is located before a preset second ranking threshold, so as to form a second path set, and count a direct connection route formed by a start point and an end point corresponding to each path in the second path set, so as to obtain a second planned route set.

The device analyzes the traffic frequency of each road by using the dimension data of fine granularity, and is beneficial to constructing more accurate route planning.

The above-described driving route planning device may be implemented in the form of a computer program which can be run on a computer apparatus as shown in fig. 10.

Referring to fig. 10, fig. 10 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device 500 is a server. The server may be an independent server or a server cluster formed by a plurality of servers.

With reference to FIG. 10, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.

The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, may cause the processor 502 to perform a driving route planning method.

The processor 502 is used to provide computing and control capabilities to support the operation of the overall computer device 500.

The internal memory 504 provides an environment for the execution of a computer program 5032 in the non-volatile storage medium 503, which computer program 5032, when executed by the processor 502, causes the processor 502 to perform a driving route planning method.

The network interface 505 is used for network communications, such as providing for transmission of user path data, etc. It will be appreciated by those skilled in the art that the structure shown in FIG. 10 is merely a block diagram of some of the structures associated with the present inventive arrangements and does not constitute a limitation of the computer device 500 to which the present inventive arrangements may be applied, and that a particular computer device 500 may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.

Wherein the processor 502 is configured to execute a computer program 5032 stored in a memory to perform the following functions: acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list historical data in a constructed linked list; cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set; and obtaining paths with frequency ranking of paths in the path statistics data set positioned before a preset first ranking threshold value to form a first path set, and counting a direct connection path formed by a starting point and a terminal point corresponding to each path in the first path set to obtain a first planning line set.

In an embodiment, after executing the step of obtaining the paths in the path statistics data set, the processor 502 ranks the paths before a preset ranking threshold to form a first path set, and forms a direct connection path between a start point and an end point corresponding to each path in the first path set to obtain a first planned path set, the processor further executes the following operations: and acquiring paths of which the frequency ranking of the paths is positioned before a preset second ranking threshold value in the searching time period in the path statistics data set to form a second path set, and counting the direct connection paths formed by the starting point and the end point corresponding to each path in the second path set to obtain a second planning line set.

In one embodiment, the processor 502 performs the following operations when performing the step of cutting the linked list history data corresponding to each user into multiple paths according to the preset cutting time interval value: acquiring node data included in linked list historical data corresponding to each user in the linked list; judging whether the difference value between the time values corresponding to any adjacent node data exceeds the cutting time interval value or not; if the difference value between the time values corresponding to the adjacent node data exceeds the cutting time interval value, deleting the pointer relationship between the corresponding adjacent node data to obtain a multi-segment path.

In one embodiment, when executing the step of acquiring the collected user path data, the processor 502 converts the user path data into linked list data and stores the linked list data in the linked list history data corresponding to the constructed linked list, the following operations are executed: receiving user path data obtained by identifying the acquired vehicle pictures, and storing the user path data into a created temporary database; acquiring the user path data from the temporary database according to a preset fetch cycle, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code; traversing and judging whether linked list historical data corresponding to the unique user identification code exists in a locally stored linked list; if the linked list historical data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the linked list historical data for storage.

In one embodiment, after performing the traversing and determining whether there is linked list history data corresponding to the user unique identifier in the locally stored linked list, the processor 502 further performs the following operations: if the linked list history data corresponding to the unique user identification code does not exist in the linked list, initial linked list data are established in the linked list according to the unique user identification code, and the linked list data to be processed corresponding to the unique user identification code are inserted into the initial linked list data.

In one embodiment, the processor 502 performs the following operations when performing the step of inserting the linked list data to be processed into the linked list history data for storage: acquiring each linked list data in the linked list historical data and a time point, corresponding to each linked list data, passing through a current intersection; acquiring each linked list data in the linked list data to be processed and a time point, corresponding to each linked list data, passing through a current intersection; and sequencing the obtained linked list historical data and the obtained linked list data to be processed according to the ascending order of the time point passing through the current intersection, inserting each linked list data in the linked list data to be processed into the linked list historical data, and correspondingly adjusting the pointer field of each linked list data.

In one embodiment, before executing the step of obtaining each linked list data in the linked list history data and the time point of each linked list data passing through the current intersection, the processor 502 further executes the following operations: and positioning an application container engine according to the unique user identification code, and acquiring linked list historical data stored in the application container engine.

Those skilled in the art will appreciate that the embodiment of the computer device shown in fig. 10 is not limiting of the specific construction of the computer device, and in other embodiments, the computer device may include more or less components than those shown, or certain components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may include only a memory and a processor, and in such embodiments, the structure and function of the memory and the processor are consistent with the embodiment shown in fig. 10, and will not be described again.

It should be appreciated that in embodiments of the present invention, the processor 502 may be a central processing unit (Central Processing Unit, CPU), the processor 502 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf Programmable gate arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a non-volatile computer readable storage medium. The computer readable storage medium stores a computer program, wherein the computer program when executed by a processor performs the steps of: acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list historical data in a constructed linked list; cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set; and obtaining paths with frequency ranking of paths in the path statistics data set positioned before a preset first ranking threshold value to form a first path set, and counting a direct connection path formed by a starting point and a terminal point corresponding to each path in the first path set to obtain a first planning line set.

In an embodiment, after the obtaining paths with the frequency ranking of the paths in the path statistics data set before the preset ranking threshold to form a first path set and forming a direct connection path between a start point and an end point corresponding to each path in the first path set to obtain a first planned path set, the method further includes: and acquiring paths of which the frequency ranking of the paths is positioned before a preset second ranking threshold value in the searching time period in the path statistics data set to form a second path set, and counting the direct connection paths formed by the starting point and the end point corresponding to each path in the second path set to obtain a second planning line set.

In an embodiment, the cutting the linked list history data corresponding to each user into multiple paths according to the preset cutting time interval value includes: acquiring node data included in linked list historical data corresponding to each user in the linked list; judging whether the difference value between the time values corresponding to any adjacent node data exceeds the cutting time interval value or not; if the difference value between the time values corresponding to the adjacent node data exceeds the cutting time interval value, deleting the pointer relationship between the corresponding adjacent node data to obtain a multi-segment path.

In one embodiment, the acquiring the collected user path data, converting the user path data into linked list data, and storing the linked list data in corresponding linked list history data in the constructed linked list, includes: receiving user path data obtained by identifying the acquired vehicle pictures, and storing the user path data into a created temporary database; acquiring the user path data from the temporary database according to a preset fetch cycle, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code; traversing and judging whether linked list historical data corresponding to the unique user identification code exists in a locally stored linked list; if the linked list historical data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the linked list historical data for storage.

In one embodiment, after traversing and determining whether there is linked list history data corresponding to the unique user identification code in the locally stored linked list, the method further includes: if the linked list history data corresponding to the unique user identification code does not exist in the linked list, initial linked list data are established in the linked list according to the unique user identification code, and the linked list data to be processed corresponding to the unique user identification code are inserted into the initial linked list data.

In an embodiment, the inserting the to-be-processed linked list data into the linked list history data for storage includes: acquiring each linked list data in the linked list historical data and a time point, corresponding to each linked list data, passing through a current intersection; acquiring each linked list data in the linked list data to be processed and a time point, corresponding to each linked list data, passing through a current intersection; and sequencing the obtained linked list historical data and the obtained linked list data to be processed according to the ascending order of the time point passing through the current intersection, inserting each linked list data in the linked list data to be processed into the linked list historical data, and correspondingly adjusting the pointer field of each linked list data.

In an embodiment, the obtaining each linked list data in the linked list historical data and before the time point of passing through the current intersection corresponding to each linked list data further includes: and positioning an application container engine according to the unique user identification code, and acquiring linked list historical data stored in the application container engine.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus, device and unit described above may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein. Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the units is merely a logical function division, there may be another division manner in actual implementation, or units having the same function may be integrated into one unit, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.

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

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

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

While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.

Claims

1. A driving route planning method, characterized by comprising:

cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value in the linked list according to the linked list historical data corresponding to each user, and counting the plurality of sections of paths to obtain a path statistical data set;

and

obtaining paths of which the frequency ranking of the paths is positioned in front of a preset first ranking threshold value in the path statistics data set to form a first path set, and counting a direct connection path formed by a starting point and an end point corresponding to each path in the first path set to obtain a first planning line set;

Cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to a preset cutting time interval value, wherein the steps comprise: acquiring node data included in linked list historical data corresponding to each user in the linked list;

judging whether the difference value between the time values corresponding to any adjacent node data exceeds the cutting time interval value or not;

if the difference value between the time values corresponding to the adjacent node data exceeds the cutting time interval value, deleting the pointer relationship between the corresponding adjacent node data to obtain a multi-segment path;

the acquiring the acquired user path data, converting the user path data into linked list data, and storing the linked list data in the linked list history data corresponding to the constructed linked list, including: receiving user path data obtained by identifying the acquired vehicle pictures, and storing the user path data into a created temporary database;

acquiring the user path data from the temporary database according to a preset fetch cycle, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code;

Traversing and judging whether linked list historical data corresponding to the unique user identification code exists in a locally stored linked list;

if the linked list historical data corresponding to the unique user identification code exists in the linked list, inserting the linked list data to be processed into the linked list historical data for storage.

2. The driving route planning method according to claim 1, wherein the obtaining the paths in the path statistics data set, where the frequency ranking of the paths is located before a preset ranking threshold, so as to form a first path set, and after obtaining the first planned route set by forming a direct connection route by a start point and an end point corresponding to each path in the first path set, further includes: and acquiring paths of which the frequency ranking of the paths is positioned before a preset second ranking threshold value in the searching time period in the path statistics data set to form a second path set, and counting the direct connection paths formed by the starting point and the end point corresponding to each path in the second path set to obtain a second planning line set.

3. The driving route planning method according to claim 1, wherein after traversing and judging whether there is linked list history data corresponding to the user unique identification code in the locally stored linked list, further comprising: if the linked list history data corresponding to the unique user identification code does not exist in the linked list, initial linked list data are established in the linked list according to the unique user identification code, and the linked list data to be processed corresponding to the unique user identification code are inserted into the initial linked list data.

4. The driving route planning method according to claim 1, wherein the inserting the link table data to be processed into the link table history data for storage includes: acquiring each linked list data in the linked list historical data and a time point, corresponding to each linked list data, passing through a current intersection;

5. The driving route planning method according to claim 4, wherein the obtaining each linked list data in the linked list history data and before a time point of passing through a current intersection corresponding to each linked list data further comprises: and positioning an application container engine according to the unique user identification code, and acquiring linked list historical data stored in the application container engine.

6. A driving route planning apparatus, characterized by comprising:

the data cutting unit is used for cutting the linked list historical data corresponding to each user into a plurality of sections of paths according to the linked list historical data corresponding to each user in the linked list and a preset cutting time interval value, and counting the plurality of sections of paths to obtain a path statistical data set; the first route set acquisition unit is used for acquiring a route of which the frequency ranking of the route in the route statistics data set is positioned before a preset first ranking threshold value so as to form a first route set, and counting a direct connection route formed by a starting point and an end point corresponding to each route in the first route set so as to obtain a first planning route set;

the data cutting unit includes:

the node data acquisition unit is used for acquiring node data included in the linked list historical data corresponding to each user in the linked list;

a time difference judging unit for judging whether the difference between the time values corresponding to any adjacent node data exceeds the cutting time interval value;

The linked list data cutting unit is used for deleting pointer relations between the corresponding adjacent node data if the difference value between the time values corresponding to the adjacent node data exceeds the cutting time interval value, so as to obtain a multi-section path;

the data storage unit comprises a data temporary storage unit, a data analysis unit, a linked list traversing unit and a data inserting unit;

the data temporary storage unit is used for receiving user path data obtained by identifying the acquired vehicle pictures and storing the user path data into the created temporary database;

the data analysis unit is used for acquiring the user path data from the temporary database according to a preset fetch cycle, analyzing and acquiring a user unique identification code corresponding to the user path data and to-be-processed linked list data corresponding to the user unique identification code;

the linked list traversing unit is used for traversing and judging whether linked list historical data corresponding to the unique user identification code exists in the locally stored linked list;

and the data insertion unit is used for inserting the to-be-processed linked list data into the linked list historical data for storage if the linked list historical data corresponding to the unique user identification code exists in the linked list.

7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the driving route planning method according to any one of claims 1 to 5 when executing the computer program.

8. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, causes the processor to perform the driving route planning method according to any one of claims 1 to 5.