CN113566842A - Data processing method, device, equipment and storage medium - Google Patents
Data processing method, device, equipment and storage medium Download PDFInfo
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Abstract
The present disclosure provides a data processing method, apparatus, device and storage medium, which relates to the field of computer technology, and in particular to artificial intelligence technologies such as intelligent transportation, maps and automatic driving. The specific implementation scheme is as follows: determining candidate traffic objects from the road network data according to the weighing area and the weighing object type; and determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output. By the technical scheme, the characteristics of the target traffic object are enriched, the auxiliary description information is used for navigation, and richer and personalized navigation experience can be provided for a user.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to an artificial intelligence technology for intelligent transportation, maps, and automatic driving, and more particularly, to a data processing method, apparatus, device, and storage medium.
Background
With the development of intelligent terminals and internet technologies, the appearance of navigation maps provides convenience for the life of people. Specifically, the navigation map can not only plan a travel route for the user; the voice broadcasting can be carried out according to the attribute information of various traffic objects (such as speed limit signs, signal lamps and the like) on the travel route recorded in the road network data and by combining with a navigation engine, such as 'speed limit of a front road section is 60 m/s', 'right turn at a front intersection', and 'accident multi-occurrence area passing in front', and the like.
However, the voice information broadcasted by the navigation map to the user is compared with a single board at present, and the personalized navigation requirement of the user cannot be met.
Disclosure of Invention
The disclosure provides a data processing method, apparatus, device and storage medium.
According to an aspect of the present disclosure, there is provided a data processing method, including:
determining candidate traffic objects from the road network data according to the weighing area and the weighing object type;
and determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
According to another aspect of the present disclosure, there is provided a data processing apparatus including:
the candidate object determining module is used for determining candidate traffic objects from the road network data according to the weighing area and the weighing object type;
and the data processing module is used for determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a data processing method according to any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a data processing method according to any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the data processing method of any of the embodiments of the present disclosure.
According to the technology of the disclosure, richer and personalized navigation experience can be provided for users.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a flow chart of a data processing method provided according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of another data processing method provided in accordance with an embodiment of the present disclosure;
FIG. 3 is a flow chart of yet another data processing method provided in accordance with an embodiment of the present disclosure;
FIG. 4 is a flow chart of yet another data processing method provided in accordance with an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of a data processing apparatus provided in accordance with an embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device for implementing a data processing method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a flowchart of a data processing method provided according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for the situation of how to process data, and is particularly suitable for how to process road network data and the like, so that richer and personalized navigation experience can be provided for users. The method may be performed by a data processing apparatus, which may be implemented in software and/or hardware, and may be integrated in an electronic device carrying data processing functions, such as a server, and further may be a server of a navigation application. As shown in fig. 1, the data processing method provided in this embodiment may include:
s101, determining candidate traffic objects from road network data according to the measuring regions and the measuring object types.
The measurement area is a specific administrative division area, and may be a city-level area, a prefecture-level area, a provincial area, a country, or the like. The object is a traffic element in road network data, such as xx intersection, xx road, xx bridge and the like; further, according to the characteristics of the function, form, etc. of the traffic elements in the road network data, the traffic elements in the road network data may be divided into a plurality of object types, which may include at least one of a road, a bridge, a tunnel, an overpass, an intersection, a pedestrian bridge, etc. The measurement object type is a specific object of a certain type to be measured. The candidate traffic objects are all object data, which are located in the measurement area and belong to the measurement object type, in the road network data, such as all bridge data in a certain area.
In this embodiment, the measurement region and the measurement object type may be determined according to the service requirement, and then the candidate traffic object may be determined from the road network data according to the measurement region and the measurement object type. For example, if intersections ranked at the top 100 in the nationwide range need to be evaluated, the measurement range refers to the nationwide range, and the measurement object type is the intersection; and then all intersections are selected from road network data in the whole country as candidate traffic objects. If a tunnel with the longest length in a province needs to be found, the region is measured to be the region of the province, and the type of the measured object is the tunnel; and then all tunnels are selected from road network data of a certain province as candidate traffic objects.
Further, in this embodiment, the measurement area and the measurement object type may be determined when the road network data update event is monitored. For example, if the version of the road network data is identified to be changed, determining that a road network data updating event is monitored; at this time, the new version road network data and the old version road network data can be compared to determine the most changed region as the measurement region, and the type of any traffic element which is changed in the measurement region is used as the measurement object type.
S102, determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
The attribute information may include, but is not limited to, location information, measurement information, update time, and the like, and optionally, the location information may be spatial location information where the candidate traffic object is located, such as longitude and latitude information; the measurement information can be candidate traffic object size information (such as length and width), traffic flow information, or people flow information; the time information may be an opening time or a setup time of the candidate traffic object, etc. The target traffic object is a traffic object which is distinguished from other candidate objects in the candidate traffic objects, namely a traffic object with unique characteristics. The auxiliary description information is unique characteristic information of the target traffic object; the further auxiliary description information may include a measurement area, a measurement object type, and unique feature information.
In this embodiment, the attribute information of the measured area and the candidate traffic object may be input into a pre-trained neural network model to obtain a target traffic object and obtain auxiliary description information of the target traffic object; and then, the auxiliary description information of the target traffic object is adopted to supplement the attribute information of the target traffic object for navigation output.
For example, the attribute information (such as tunnel length, width, etc.) of a certain province and all tunnels in the province is input into a pre-trained neural network model, the neural network model processes the attribute information of all the tunnels, and a tunnel with unique characteristics, such as longest length or widest width, in a certain province is output; further, for example, "the tunnel with the longest length of a province" or "the tunnel with the widest width of a province" is used as the auxiliary description information of the tunnel, or several keywords of the province, the longest length and the tunnel are used as the auxiliary description information of the tunnel.
According to the technical scheme provided by the embodiment of the disclosure, candidate traffic objects are determined from road network data according to the measurement area and the measurement object type, then the target traffic object is determined from the candidate traffic objects according to the measurement area and the attribute information of the candidate traffic objects, and auxiliary description information of the target traffic object is generated for navigation output. According to the technical scheme, the target traffic object can be found from the candidate traffic objects based on the weighing area, the type of the weighing object and the attribute information of the candidate traffic object, and the auxiliary description information, namely the personalized description information of the target traffic object is generated, so that the characteristics of the target traffic object are enriched, the auxiliary description information is used for navigation, and richer and personalized navigation experience can be provided for a user.
On the basis of the above embodiment, in order to ensure the freshness of the auxiliary description information, since data in the road network may change, as an optional way of the embodiment of the present disclosure, after the auxiliary description information of the target traffic object is generated, an effective time may be configured for the auxiliary description information of the target traffic object.
The valid time is used for representing the valid time limit of the auxiliary description information, and may be set by a person skilled in the art according to actual conditions, and further may be automatically determined based on the update frequency of the road network data. The auxiliary description information of different objects has different valid time. For example, if the auxiliary description information of the target traffic object includes keywords such as a certain area, a high speed, an opening time, etc., the effective time may be configured to be 1 month, and the opening time may be used as a starting time. And when the effective time is reached, removing the auxiliary description information of the target traffic object to release the storage memory.
It can be understood that the effective time is configured for the auxiliary description information of the target traffic object, so that the freshness of the auxiliary description information of the target traffic object is ensured, the latest auxiliary description information can be provided for a user, and the navigation experience of the user is improved.
On the basis of the above embodiment, as a further optional manner of the embodiment of the present disclosure, after generating the auxiliary description information of the target traffic object, the storage identifier to which the target traffic object belongs may also be determined; and storing the auxiliary description information of the target traffic object in association with the attribute information based on the storage identification.
The storage identifier is a unique identifier used for representing attribute information of the storage target traffic object, or may be a unique identifier of road related information to which the storage target traffic object belongs.
For example, if the attribute information of the target traffic object is stored based on the database, the storage identifier may be expressed in the form of a primary key, where the primary key is used to uniquely characterize a basic table storing the attribute information of the target traffic object, where the attribute information in the basic table is generally static and unchangeable; the external key is constructed based on the main key, specifically, the main key can be used as the external key of a configuration table for storing the auxiliary description information of the target traffic object, wherein the auxiliary description information in the table can be added, deleted, modified and the like. Further, an intermediate table may be further provided, and the basic table and the configuration table are associated based on the primary key and the foreign key, where the primary key is unique, the foreign key may not be unique, and specifically, the primary key of the basic table may be used as the foreign key of the intermediate table, and the primary key in the configuration table may be used as the foreign key of the intermediate table. The intermediate table is used for simply storing information such as element types of the target traffic objects, the configuration table is used for storing auxiliary description information of the target traffic objects, and the basic table is used for storing attribute information of the target traffic objects. And further, the auxiliary description information and the attribute information of the target traffic object are stored in a correlated manner based on the relationship between the main key and the foreign key.
It can be understood that the auxiliary description information and the attribute information of the target traffic object are stored in an associated manner based on the storage identifier, and the auxiliary description information of the target traffic object can be flexibly adjusted without changing the attribute information of the target traffic object, so that personalized information can be provided for a user.
Fig. 2 is a flowchart of another data processing method provided according to an embodiment of the present disclosure, and this embodiment further explains in detail how to "determine a target traffic object from candidate traffic objects according to attribute information of a measurement area and the candidate traffic objects, and generate auxiliary description information of the target traffic object" on the basis of the above embodiment. As shown in fig. 2, the method for providing data processing according to the present embodiment may include:
s201, determining candidate traffic objects from road network data according to the measuring regions and the measuring object types.
S202, the candidate traffic objects are ranked according to the attribute information of the candidate traffic objects.
In this embodiment, the candidate traffic objects may be ranked according to the position information in the attribute information of the candidate traffic objects. For example, if the candidate traffic objects are all intersections in a certain measurement area, for each intersection, the distance between the intersection and the center of the measurement area (e.g., city center) is determined, and then all intersections in the certain measurement area are sorted according to the distance between each intersection and the center of the measurement area (e.g., city center).
Further, as an optional mode of the embodiment of the present disclosure, the candidate traffic objects may be ranked according to metric information in the attribute information of the candidate traffic objects. Specifically, the metric information in the attribute information of the candidate traffic objects may be statistically analyzed, and the candidate traffic objects may be ranked based on the statistical analysis result.
For example, the candidate traffic objects are all intersections in the measurement area, and the intersections are sorted according to the measurement information (such as intersection size) of all intersections from large to small or from small to large.
For another example, the candidate traffic objects are all roads in the measured area, and the roads are sorted according to the measurement information (such as road width or lane level) of all the roads in the order from large to small or from small to large.
Further, as another optional manner of the embodiment of the present disclosure, the candidate traffic objects may also be ranked according to time information in the attribute information of the candidate traffic objects. Optionally, the candidate traffic objects may be ranked according to their creation time.
Further, as another optional mode of the embodiment of the present disclosure, the candidate traffic objects may also be ranked according to metric information and creation time in the attribute information of the candidate traffic objects. Specifically, the candidate traffic objects are ranked by comprehensively considering metric information and establishment time in the attribute information of the candidate traffic objects.
S203, according to the sequencing result and the weighing area, determining a target traffic object from the candidate traffic objects, and generating auxiliary description information of the target traffic object.
In this embodiment, one or more traffic objects ranked in the front are selected from the candidate traffic objects as the target traffic object according to the ranking result, and then the auxiliary description information of the target traffic object is generated according to the ranking condition and the weighing area of the target traffic object.
For example, if the candidate traffic object is an intersection, according to the ranking result of the intersections in the measurement area, the intersection with the top ranking (the maximum or minimum intersection) is used as the target traffic object, and the auxiliary description information may include the measurement area, the maximum or minimum intersection, and the intersection.
For another example, if the candidate traffic object is a road, according to the ranking result of the roads in the measurement area, the road with the top ranking (the widest or narrowest road width and the highest lane level) is taken as the target traffic object, and the auxiliary description information may include the measurement area, the widest or narrowest road width, the highest lane level, and the road.
For another example, the traffic objects newly added may be selected from the traffic objects candidates as the target traffic object according to the ranking result of the time information of the traffic objects candidates, and the auxiliary description information of the target traffic object may be determined according to the time information of the target traffic object and the administrative division information. For example, the auxiliary description information may include a certain region of a province (i.e., a measurement area), the latest state, and the overpass.
According to the technical scheme provided by the embodiment of the disclosure, candidate traffic objects are determined from road network data according to the weighing area and the type of the weighing object, then the candidate traffic objects are ranked according to the attribute information of the candidate traffic objects, a target traffic object is determined from the candidate traffic objects according to the ranking result and the weighing area, and auxiliary description information of the target traffic object is generated. According to the technical scheme, the candidate traffic objects are sequenced, the target traffic object can be found from the candidate traffic objects more clearly, and the auxiliary description information, namely the personalized description information of the target traffic object is generated, so that the characteristics of the target traffic object are enriched, the auxiliary description information is used for navigation, and richer and personalized navigation experience can be provided for a user.
Fig. 3 is a flowchart of another data processing method provided according to an embodiment of the present disclosure, and this embodiment further explains how to "determine a target traffic object from candidate traffic objects according to the measurement area and the attribute information of the candidate traffic objects, and generate auxiliary description information of the target traffic object" based on the above embodiment. As shown in fig. 3, the method for providing data processing according to the present embodiment may include:
s301, determining candidate traffic objects from the road network data according to the weighing areas and the weighing object types.
S302, determining a target traffic object from the candidate traffic objects according to at least one of the user track data, the traffic violation data and the interest point data, and the attribute information of the measuring area and the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
The user trajectory data refers to user historical trajectory data and can be acquired from a navigation application used by a user. The so-called traffic violation data may be obtained from the relevant department, the relevant software or a device, such as an electronic eye. The point of interest data may be a hospital, a mall, an attraction, a school, etc.
In this embodiment, the user trajectory data, the interest point data, and the attribute information of the measurement area and the candidate traffic object may be input into a pre-trained neural network model, processed by the neural network model to obtain the target traffic object, and generate the auxiliary description information of the target traffic object. Furthermore, the target traffic object can be determined from the candidate traffic objects and auxiliary description information of the target traffic object can be generated according to the user track data, the interest point data, the user thermodynamic diagram data and the attribute information of the weighing area and the candidate traffic objects. For example, in the long distance navigation process, the target traffic object is a scenic spot, and the auxiliary description information thereof may include the highest heat, a certain scenic spot, and a measurement area.
Optionally, the user trajectory data, the traffic violation data, and the attribute information of the measurement area and the candidate traffic object may be input into a pre-trained neural network model, processed by the neural network model to obtain the target traffic object, and generate the auxiliary description information of the target traffic object.
Optionally, the candidate traffic objects may be ranked according to the user trajectory data and metric information in the attribute information of the candidate traffic objects, in combination with the access amount and the metric information, and the target traffic objects are determined according to the ranking result; and generating auxiliary description information of the target traffic object according to the sequencing result, the access amount, the measurement information and the measurement area of the target traffic object.
Illustratively, if the candidate traffic object is an intersection in a certain measuring area, counting the number of the intersections visited by the user according to the user track data to obtain the pedestrian flow and the vehicle flow of each intersection; determining the area of the crossroads according to the measurement information (such as the width, the length and the number of zebra crossings) of each crossroad; further, the crossroads are sorted by integrating the pedestrian flow, the vehicle flow, and the area, and for example, priorities may be set for the pedestrian flow, the vehicle flow, and the area, and the crossroads may be sorted based on the priorities. And taking the crossroads with the set number ranked at the top as target traffic objects. And then generating auxiliary description information of the target traffic objects according to the sequencing condition, the pedestrian volume, the traffic volume, the area and the measurement area of each target traffic object, for example, the auxiliary description information may include the pedestrian volume, the traffic volume, the area, the 3 rd comprehensive ranking, the measurement area and the crossroads.
Further, as an optional mode of the embodiment of the present disclosure, the candidate traffic objects may be ranked based on the access amount according to the user trajectory data and the position information in the attribute information of the candidate traffic objects, and the target traffic object may be determined according to the ranking result; and generating auxiliary description information of the target traffic object according to the sequencing condition, the access amount and the weighing area of the target traffic object.
The access amount may be a traffic flow or a pedestrian flow.
Illustratively, if the candidate traffic object is a pedestrian overpass in a certain measurement area, counting the number of visiting pedestrian overpasses in the user track according to the user track data and the position information of the pedestrian overpass to obtain the pedestrian traffic of each pedestrian overpass, and sequencing the pedestrian overpasses based on the pedestrian traffic. And taking the pedestrian overpasses with the set number ranked at the top as target traffic objects. And then generating auxiliary description information of the target traffic objects according to the ordering condition, the pedestrian volume and the measurement area of each target traffic object, for example, the auxiliary description information may include the pedestrian volume, the maximum (or ranking 3 rd), the measurement area and the pedestrian overpass.
It can be understood that the user trajectory data is introduced to determine the target traffic object and the auxiliary description information of the target traffic object, and personalized information can be formulated for the user in combination with the user daily trajectory for navigation, so as to further provide a personalized navigation experience for the user.
Further, as another optional mode of the embodiment of the present disclosure, the candidate traffic objects may be sorted based on the violation amount according to the traffic violation data and the location information in the attribute information of the candidate traffic objects, and the target traffic object may be determined according to the sorting result; and generating auxiliary description information of the target traffic object according to the sequencing condition, the violation amount and the measurement area of the target traffic object.
Illustratively, if the candidate traffic objects are all roads or intersections with electronic eyes in a certain measuring area, all the roads or intersections are ranked based on the violation amount of each road or intersection according to the traffic violation data and the position information in the attribute information of the roads or intersections, and the road or intersection with the highest violation amount which is ranked in the front is taken as the target traffic object; and then generating auxiliary description information of the target traffic object according to the sequencing condition, the violation amount and the measurement area of the target traffic object, wherein the auxiliary description information can comprise maximum violation, measurement area and road or intersection.
Compared with the existing reminding user based on the road sign, the method and the device for reminding the user based on the road sign have the advantages that the violation data are introduced to determine the target traffic object and the auxiliary description information of the target traffic object, so that the actual situation of the user can be combined more flexibly, and personalized navigation experience is provided for the user.
According to the technical scheme provided by the embodiment of the disclosure, candidate traffic objects are determined from road network data according to the measurement area and the measurement object type, then, a target traffic object is determined from the candidate traffic objects according to at least one of user track data, traffic violation data and interest point data and attribute information of the measurement area and the candidate traffic objects, and auxiliary description information of the target traffic object is generated for navigation output. According to the technical scheme, the user track data, the traffic violation data and the interest point data are introduced, the characteristics of the target traffic object can be further enriched, the auxiliary description information is used for navigation, and richer and personalized navigation experience can be provided for the user.
FIG. 4 is a flow chart of yet another data processing method provided in accordance with an embodiment of the present disclosure; this embodiment further optimizes and provides an optional implementation on the basis of the above embodiment, and as shown in fig. 4, the method for providing data processing in this embodiment may include:
s401, determining candidate traffic objects from road network data according to the measuring regions and the measuring object types.
S402, according to the attribute information of the weighing area and the candidate traffic objects, determining the target traffic objects from the candidate traffic objects, and generating auxiliary description information of the target traffic objects for navigation output.
And S403, in the navigation process, if the target traffic object is identified to be located on the navigation route, generating a voice file of the target traffic object according to the auxiliary description information of the target traffic object.
In this embodiment, in the navigation process, if it is recognized that the target traffic object is located on the road route, the auxiliary description information of the target traffic object is automatically called, and a voice file of the target traffic object is generated based on a voice generation technology.
And S404, broadcasting the voice file to the user.
In this embodiment, the voice file is broadcasted to the user.
Further, as an optional implementation manner of the present disclosure, the corresponding target traffic object may be displayed in an enlarged map while the voice file is broadcasted. For example, in the navigation process, if it is recognized that a certain X-shaped zebra crossing is located on the navigation route, the navigation program automatically recognizes the auxiliary description information of the crossing, the voice file of the crossing, and prompts "you have passed the first X-shaped zebra crossing in X city and please pay attention to safe driving" on voice navigation, and can be specially shown in cooperation with the guidance enlarged image. It can be understood that the target traffic object is displayed through the auxiliary description information of the target traffic object broadcasted through voice and the enlarged image, and richer and personalized navigation experience is provided for the user.
It should be noted that, if the execution subject of the embodiment of the present disclosure is the server, in the navigation process, if it is recognized that the target traffic object is located on the navigation route, the voice file of the target traffic object is called; and sending the voice file to the terminal so that the terminal can broadcast the voice file.
According to the technical scheme provided by the embodiment of the disclosure, candidate traffic objects are determined from road network data according to the weighing area and the type of the weighing object, then the target traffic object is determined from the candidate traffic objects according to the attribute information of the weighing area and the candidate traffic object, and the auxiliary description information of the target traffic object is generated for navigation output, so that in the navigation process, if the target traffic object is identified to be located on the navigation route, the voice file of the target traffic object is generated according to the auxiliary description information of the target traffic object, and the voice file is broadcasted to the user. According to the technical scheme, the auxiliary description information of the target traffic object is broadcasted to the user, and rich and personalized navigation experience is provided for the user.
Fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present disclosure. The embodiment of the disclosure is suitable for the situation of how to process data, and is particularly suitable for the situation of how to process road network data and the like so as to provide richer and personalized navigation experience for users. The apparatus may be implemented by software and/or hardware, and the apparatus may implement the data processing method of any embodiment of the present disclosure. As shown in fig. 5, the data processing apparatus 500 includes:
a candidate object determining module 501, configured to determine candidate traffic objects from road network data according to the measured region and the measured object type;
and the data processing module 502 is used for determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
According to the technical scheme provided by the embodiment of the disclosure, candidate traffic objects are determined from road network data according to the measurement area and the measurement object type, then the target traffic object is determined from the candidate traffic objects according to the measurement area and the attribute information of the candidate traffic objects, and auxiliary description information of the target traffic object is generated for navigation output. According to the technical scheme, the target traffic object can be found from the candidate traffic objects based on the weighing area, the type of the weighing object and the attribute information of the candidate traffic object, and the auxiliary description information, namely the personalized description information of the target traffic object is generated, so that the characteristics of the target traffic object are enriched, the auxiliary description information is used for navigation, and richer and personalized navigation experience can be provided for a user.
Further, the data processing module 502 is specifically configured to:
sorting the candidate traffic objects according to the attribute information of the candidate traffic objects;
and determining a target traffic object from the candidate traffic objects according to the sequencing result and the weighing area, and generating auxiliary description information of the target traffic object.
Further, the data processing module 502 comprises a data processing unit for:
and determining a target traffic object from the candidate traffic objects and generating auxiliary description information of the target traffic object according to at least one of the user track data, the traffic violation data and the point of interest data and the attribute information of the measurement area and the candidate traffic objects.
Further, the data processing unit is specifically configured to:
according to the user track data and the position information in the attribute information of the candidate traffic objects, sorting the candidate traffic objects based on the access amount, and determining the target traffic objects according to the sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the access amount and the weighing area of the target traffic object.
Further, the data processing unit is further specifically configured to:
sorting the candidate traffic objects based on the violation amount according to the traffic violation data and the position information in the attribute information of the candidate traffic objects, and determining the target traffic objects according to the sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the violation amount and the measurement area of the target traffic object.
Further, the apparatus further comprises:
and the time configuration module is used for configuring the effective time for the auxiliary description information of the target traffic object.
Further, the apparatus further comprises:
the storage identification determining module is used for determining the storage identification to which the target traffic object belongs;
and the data storage module is used for storing the auxiliary description information and the attribute information of the target traffic object in a correlation manner based on the storage identification.
Further, the apparatus further comprises:
the voice file generation module is used for generating a voice file of the target traffic object according to the auxiliary description information of the target traffic object if the target traffic object is identified to be positioned on the navigation route in the navigation process;
and the broadcasting module is used for broadcasting the voice file to the user.
The data processing device disclosed by the disclosure can execute the data processing method provided by the above embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method.
According to the technical scheme, the acquisition, storage, application and the like of the related road network data, the user track data, the traffic violation data, the point of interest data and the like all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Various components in the electronic device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 executes the respective methods and processes described above, such as the data processing method. For example, in some embodiments, the data processing method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the data processing method by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A method of data processing, comprising:
determining candidate traffic objects from the road network data according to the weighing area and the weighing object type;
and determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
2. The method of claim 1, wherein the determining a target traffic object from the candidate traffic objects and generating auxiliary description information of the target traffic object according to the measurement area and the attribute information of the candidate traffic objects comprises:
sorting the candidate traffic objects according to the attribute information of the candidate traffic objects;
and determining a target traffic object from the candidate traffic objects according to the sequencing result and the weighing area, and generating auxiliary description information of the target traffic object.
3. The method of claim 1, wherein the determining a target traffic object from the candidate traffic objects and generating auxiliary description information of the target traffic object according to the measurement area and the attribute information of the candidate traffic objects comprises:
and determining a target traffic object from the candidate traffic objects according to at least one of user track data, traffic violation data and interest point data and the attribute information of the measuring area and the candidate traffic objects, and generating auxiliary description information of the target traffic object.
4. The method of claim 3, wherein determining a target traffic object from the candidate traffic objects and generating auxiliary description information of the target traffic object according to user trajectory data and the attribute information of the measurement area and the candidate traffic objects comprises:
according to the user track data and position information in the attribute information of the candidate traffic objects, sorting the candidate traffic objects based on the access amount, and determining a target traffic object according to a sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the access amount and the measuring area of the target traffic object.
5. The method of claim 3, wherein the determining a target traffic object from the candidate traffic objects and generating auxiliary descriptive information for the target traffic object based on the traffic violation data and the measurement area and the attribute information for the candidate traffic objects comprises:
sorting the candidate traffic objects based on the violation amount according to the traffic violation data and the position information in the attribute information of the candidate traffic objects, and determining a target traffic object according to a sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the violation amount and the measurement area of the target traffic object.
6. The method of claim 1, after generating the auxiliary description information of the target traffic object, further comprising:
and configuring effective time for the auxiliary description information of the target traffic object.
7. The method of claim 1, after generating the auxiliary description information of the target traffic object, further comprising:
determining a storage identifier to which the target traffic object belongs;
and based on the storage identification, storing the auxiliary description information of the target traffic object in association with the attribute information.
8. The method according to any one of claims 1-7, wherein after generating the auxiliary description information of the target traffic object, the method further comprises:
in the navigation process, if the target traffic object is identified to be positioned on a navigation route, generating a voice file of the target traffic object according to the auxiliary description information of the target traffic object;
and broadcasting the voice file to a user.
9. A data processing apparatus comprising:
the candidate object determining module is used for determining candidate traffic objects from the road network data according to the weighing area and the weighing object type;
and the data processing module is used for determining a target traffic object from the candidate traffic objects according to the weighing area and the attribute information of the candidate traffic objects, and generating auxiliary description information of the target traffic object for navigation output.
10. The apparatus according to claim 9, wherein the data processing module is specifically configured to:
sorting the candidate traffic objects according to the attribute information of the candidate traffic objects;
and determining a target traffic object from the candidate traffic objects according to the sequencing result and the weighing area, and generating auxiliary description information of the target traffic object.
11. The apparatus of claim 9, wherein the data processing module comprises:
and the data processing unit is used for determining a target traffic object from the candidate traffic objects and generating auxiliary description information of the target traffic object according to at least one of user track data, traffic violation data and interest point data and the attribute information of the measuring area and the candidate traffic objects.
12. The apparatus according to claim 11, wherein the data processing unit is specifically configured to:
according to the user track data and position information in the attribute information of the candidate traffic objects, sorting the candidate traffic objects based on the access amount, and determining a target traffic object according to a sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the access amount and the measuring area of the target traffic object.
13. The apparatus of claim 11, wherein the data processing unit is further specifically configured to:
sorting the candidate traffic objects based on the violation amount according to the traffic violation data and the position information in the attribute information of the candidate traffic objects, and determining a target traffic object according to a sorting result;
and generating auxiliary description information of the target traffic object according to the sequencing condition, the violation amount and the measurement area of the target traffic object.
14. The apparatus of claim 9, further comprising:
and the time configuration module is used for configuring effective time for the auxiliary description information of the target traffic object.
15. The apparatus of claim 9, further comprising:
the storage identification determining module is used for determining the storage identification to which the target traffic object belongs;
and the data storage module is used for storing the auxiliary description information of the target traffic object and the attribute information in a correlation mode based on the storage identification.
16. The apparatus of any of claims 9-15, further comprising:
the voice file generation module is used for generating a voice file of the target traffic object according to the auxiliary description information of the target traffic object if the target traffic object is identified to be positioned on a navigation route in the navigation process;
and the broadcasting module is used for broadcasting the voice file to a user.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the data processing method of any one of claims 1-8.
18. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the data processing method according to any one of claims 1 to 8.
19. A computer program product comprising a computer program which, when executed by a processor, implements a data processing method according to any one of claims 1-8.
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