CN112284407A - Driving information recommendation method and device - Google Patents
Driving information recommendation method and device Download PDFInfo
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- CN112284407A CN112284407A CN202011614152.2A CN202011614152A CN112284407A CN 112284407 A CN112284407 A CN 112284407A CN 202011614152 A CN202011614152 A CN 202011614152A CN 112284407 A CN112284407 A CN 112284407A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3484—Personalized, e.g. from learned user behaviour or user-defined profiles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
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Abstract
The embodiment of the invention provides a driving information recommendation method and a driving information recommendation device, which relate to the technical field of intelligent traffic, and the driving information recommendation method comprises the following steps: acquiring a first information point of a target vehicle passing by; and analyzing the first information points through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises passing information points, the occurrence time periods of the information points and the vehicle states passing the information points. By applying the driving recommendation method provided by the embodiment of the invention, the current recommendation information can be generated according to the historical driving record of the target vehicle, so that the target vehicle is recommended in an individualized way, and the driving is more intelligent.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to a driving information recommendation method and device.
Background
With the continuous development of the internet technology and the navigation technology, the intelligent degree of vehicle running is higher and higher, and the vehicle can also receive the running information recommended by vehicle-mounted navigation in the running process. The vehicle navigation is performed by using a vehicle-mounted GPS (Global Positioning System) in cooperation with an electronic map, and can conveniently and accurately tell a driver the shortest or fastest route to a destination, which is a good helper for the driver.
Generally, vehicle navigation needs to set a starting point and a destination and generate a driving route, so that in the driving process of a vehicle, when approaching a key mark point where the driving route passes, the vehicle navigation can recommend driving information to a user in a voice broadcast mode. However, the recommendation method of the driving information does not distinguish the vehicles, and the contents of the driving information passing through each key mark point are the same, that is, the personalized recommendation cannot be performed for each vehicle.
Disclosure of Invention
The embodiment of the invention provides a method and a device for recommending driving information, which can be used for carrying out personalized recommendation on different vehicles.
In order to achieve the above object, an embodiment of the present invention discloses a method for recommending driving information, including:
acquiring a first information point of a target vehicle passing by;
and analyzing the first information points through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises passing information points, the occurrence time periods of the information points and the vehicle states passing the information points.
Optionally, acquiring a target occurrence time period corresponding to the first information point;
the analyzing the first information point through the driving information recommendation model, and the generating recommendation information for the target vehicle includes: and analyzing the first information point and the target occurrence time period through the driving information recommendation model to generate recommendation information for the target vehicle.
Optionally, the analyzing the first information point and the target occurrence period through the driving information recommendation model, and generating recommendation information for the target vehicle includes:
when the target vehicle runs to the first information point, if the target occurrence time period of the first information point is matched with the habit time period corresponding to the historical driving behavior of the target vehicle, recommending corresponding driving habit information to the target vehicle.
Optionally, when the target vehicle travels to the first information point, if the target appearance time period of the first information point matches a habit time period corresponding to the historical driving behavior of the target vehicle, recommending corresponding driving habit information to the target vehicle includes:
and when the target vehicle runs to the first information point, recommending corresponding refueling or parking information to the target vehicle if the appearance time period of the first information point is matched with the historical refueling or parking habit time period of the target vehicle.
Optionally, acquiring a second information point of the passing of the target vehicle;
the analyzing the first information point through the driving information recommendation model, and the generating recommendation information for the target vehicle includes:
generating a target driving path according to the first information point and the second information point;
and analyzing the target driving path through a driving information recommendation model to generate recommendation information for the target vehicle.
Optionally, the analyzing the target driving path through the driving information recommendation model, and generating recommendation information for the target vehicle includes:
and if the target driving path is matched with the historical navigation path of the target vehicle, recommending navigation information to the target vehicle according to the historical navigation path.
Optionally, the method further includes updating training data of the driving information recommendation model by using a historical driving record generated by the target vehicle in real time.
In order to achieve the above object, an embodiment of the present invention discloses a device for recommending driving information, including:
the information point acquisition module is used for acquiring a first information point of a target vehicle passing by;
and the recommendation information generation module is used for analyzing the first information points through a driving information recommendation model and generating recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training multiple groups of historical driving records of the target vehicle, and each group of historical driving records comprises information points passing by, the occurrence time period of the information points and the vehicle state passing by the information points.
Optionally, the system further comprises a time obtaining module, configured to obtain a target occurrence time period corresponding to the first information point;
the recommendation information generation module is further configured to analyze the first information point and the target occurrence time period through the driving information recommendation model to generate recommendation information for the target vehicle.
Optionally, the recommendation information generating module is configured to recommend the corresponding driving habit information to the target vehicle when the target vehicle drives to the first information point, if a target occurrence time period of the first information point matches a habit time period corresponding to the historical driving behavior of the target vehicle.
Optionally, the recommendation information generating module is specifically configured to recommend the corresponding refueling or parking information to the target vehicle when the target vehicle travels to the first information point, if an appearance time period of the first information point matches a habit time period of the historical refueling or parking of the target vehicle.
Optionally, the information point obtaining module is further configured to obtain a second information point where the target vehicle passes;
the driving information recommendation module is used for generating a target driving path according to the first information point and the second information point; and analyzing the target driving path through a driving information recommendation model to generate recommendation information for the target vehicle.
Optionally, the driving information recommending module is specifically configured to recommend navigation information to the target vehicle according to a historical navigation path if the target driving path matches the historical navigation path of the target vehicle.
Optionally, the vehicle information recommendation system further includes a model updating module, configured to update training data of the driving information recommendation model by using a historical driving record generated by the target vehicle in real time.
In order to achieve the above object, an embodiment of the present invention discloses a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the method for recommending driving information as described above.
To achieve the above object, an embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the method for recommending driving information as described above.
The method and the device for recommending the driving information provided by the embodiment of the invention can acquire the historical driving record of the target vehicle, establish the driving information recommendation model aiming at the target vehicle according to the historical driving record and acquire the current recommendation information aiming at the target vehicle. By applying the driving information recommendation scheme provided by the embodiment of the invention, the current recommendation information can be generated according to the historical driving record of the target vehicle, so that the target vehicle is recommended in an individualized way, the same content is recommended for different vehicles, and the driving is obviously more intelligent.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for recommending driving information according to an embodiment of the present invention;
fig. 2 is another flowchart of a method for recommending driving information according to an embodiment of the present invention;
fig. 3 is another flowchart of a method for recommending driving information according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for recommending driving information according to an embodiment of the present invention
Fig. 5 is a structural diagram of an apparatus for recommending driving information according to an embodiment of the present invention;
fig. 6 is another structural diagram of an apparatus for recommending driving information according to an embodiment of the present invention;
fig. 7 is another structural diagram of an apparatus for recommending driving information according to an embodiment of the present invention;
fig. 8 is a block diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Although the current vehicle-mounted navigation technology is relatively intelligent, the content of the prompted driving information is the same for different vehicles, that is, personalized information recommendation cannot be performed for different vehicles. In order to solve the problem, the embodiment of the invention provides a driving information recommendation method and device.
As shown in fig. 1, a flowchart of recommended driving information provided in an embodiment of the present invention may include the following steps:
s101: and acquiring a first information point of the passing of the target vehicle.
In the geographic Information system, a POI (Point of Information) may be a house, a shop, a mailbox, a bus station, etc., but the present invention is not limited thereto.
It will be appreciated that the historical driving history typically reflects the driving habits of the vehicle, such as what time periods the vehicle is typically filled, the mileage of the day, whether high speed is preferred, etc.
S102: and analyzing the first information points through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises passing information points, the occurrence time periods of the information points and the vehicle states passing the information points.
The driving information recommendation model is used for analyzing and processing the historical driving record of the target vehicle and generating recommendation information of the target vehicle.
Specifically, a machine learning algorithm may be used to train a historical driving record, and specific contents in the historical driving record are associated, so as to generate a model capable of recommending information to a target vehicle.
Wherein the historical driving record at least comprises: the passing information point, the appearance time period of the passing information point and the vehicle state when passing the information point.
In one implementation, the vehicle state when passing the information point at least includes: driving state, mileage, refueling and parking information. Of course, the vehicle states listed here are only some specific states, and the embodiment of the present invention does not limit this.
As can be seen from the above, the method for recommending driving information according to the embodiment of the present invention can obtain the historical driving record of the target vehicle, establish the driving information recommendation model for the target vehicle according to the historical driving record, and obtain the current recommendation information for the target vehicle. By applying the driving information recommendation scheme provided by the embodiment of the invention, the current recommendation information can be generated according to the historical driving record of the target vehicle, so that the target vehicle is recommended in an individualized way, the same content is recommended for different vehicles, and the driving is obviously more intelligent.
After the driving information recommendation model is established, when the target vehicle passes through the current information point, the most probable driving behavior of the target vehicle, namely the current recommendation information, can be determined by combining the current time interval, and the current recommendation information is broadcasted to the target vehicle.
As shown in fig. 2, another flowchart of recommending driving information provided in the embodiment of the present invention includes the following steps:
s201: and acquiring a first information point of the passing of the target vehicle.
S202: and acquiring the target occurrence time period corresponding to the first information point.
S203: and analyzing the first information point and the target occurrence time period through the driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training multiple groups of historical driving records of the target vehicle, and each group of historical driving records comprises information points passing by, the occurrence time periods of the information points and the vehicle states passing by the information points.
It should be noted that steps S201 and S203 in the embodiment shown in fig. 2 are similar to steps S101 and S102 in the embodiment shown in fig. 1, and related points can refer to the embodiment shown in fig. 1, which is not described herein again.
As can be seen from the above, the driving information recommendation scheme provided in the embodiment of the present invention inputs the obtained first information point and the target occurrence time period into the driving information recommendation model, and can generate the driving information of the target vehicle when the target vehicle is located at the first information point and is located at the target occurrence time period according to the historical driving record of the target vehicle, so that personalized recommendation of the target vehicle is realized, and the same content is recommended for different vehicles, so that it is obvious that driving is more intelligent.
In an embodiment of the present invention, when the target vehicle travels to the first information point, if a target occurrence time period of the first information point matches a habit time period corresponding to the historical driving behavior of the target vehicle, the corresponding driving habit information is recommended to the target vehicle.
For example, when the target vehicle travels to the first information point, if the appearance time period of the first information point matches the habit time period of the target vehicle for historical refueling or parking, the corresponding refueling or parking information is recommended to the target vehicle.
As shown in fig. 3, a flowchart of recommended driving information provided in an embodiment of the present invention includes the following steps:
s301: and acquiring a first information point and a second information point of the passing of the target vehicle.
S302: and generating a target driving path according to the first information point and the second information point.
S303: and analyzing the target driving path through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises information points passing by, the occurrence time period of the information points and the vehicle state passing by the information points.
For example, if the target driving path matches the historical navigation path of the target vehicle, the navigation information is recommended to the target vehicle according to the historical navigation path.
It should be noted that steps S301 and S303 in the embodiment shown in fig. 3 are similar to steps S101 and S102 in the embodiment shown in fig. 1, and related points can refer to the embodiment shown in fig. 1, which is not described herein again.
As can be seen from the above, according to the driving information recommendation scheme provided in the embodiment of the present invention, the first information and the second information point are obtained to generate the target driving path, and the target driving path is input into the driving information recommendation model, so that recommendation information when the target vehicle drives on the target driving path can be generated according to the historical driving record of the target vehicle, thereby realizing personalized recommendation of the target vehicle, instead of recommending the same content for different vehicles, and obviously making driving more intelligent.
As shown in fig. 4, a further flowchart of the recommended driving information provided in the embodiment of the present invention may include the following steps:
s401: and updating the training data of the driving information recommendation model by using the historical driving record generated by the target vehicle in real time.
S402: and acquiring a first information point of the passing of the target vehicle.
S403: and analyzing the first information points through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises passing information points, the occurrence time periods of the information points and the vehicle states passing the information points.
It should be noted that steps S402 and S403 in the embodiment shown in fig. 4 are similar to steps S101 and S102 in the embodiment shown in fig. 1, and related points can refer to the embodiment shown in fig. 1, which is not described herein again.
As can be seen from the above, the driving information recommendation scheme provided in the embodiment of the present invention can update the training data of the driving recommendation model by using the historical driving record generated in real time, and then establish the driving information recommendation model for the target vehicle according to the updated historical driving record, which is beneficial to improving the accuracy of the driving information recommendation model, so as to obtain the current recommendation information for the target vehicle, implement personalized recommendation for the target vehicle, instead of recommending the same content for different vehicles, and obviously make driving more intelligent.
The following describes a driving information recommendation device provided in an embodiment of the present invention.
As shown in fig. 5, a structural diagram of a driving information recommendation device according to an embodiment of the present invention is shown, where the device includes: an information point acquisition module 510 and a recommendation information generation module 520.
The information point obtaining module 510 is configured to obtain a first information point where the target vehicle passes;
and a recommendation information generating module 520, configured to analyze the first information point through a driving information recommendation model, and generate recommendation information for the target vehicle, where the driving information recommendation model is obtained by training multiple sets of historical driving records of the target vehicle, and each set of historical driving records includes information points passing by, appearance time periods of the information points, and vehicle states passing by the information points.
In the geographic Information system, a POI (Point of Information) may be a house, a shop, a mailbox, a bus station, etc., which is not limited in the present invention.
It will be appreciated that the historical driving history typically reflects the driving habits of the vehicle, such as what time periods the vehicle is typically filled, the mileage of the day, whether high speed is preferred, etc.
As can be seen from the above, in the driving information recommendation scheme provided in the embodiment of the present invention, the model building module generates the driving information recommendation model by using the historical driving record of the vehicle obtained by the historical record obtaining module, so that the information recommendation module can generate the current recommendation information according to the historical driving record of the target vehicle, thereby realizing personalized recommendation of the target vehicle, not recommending the same content for different vehicles, and obviously making driving more intelligent.
In an embodiment of the present invention, as shown in fig. 6, the apparatus further includes a time obtaining module 530, configured to obtain a target occurrence time period corresponding to the first information point;
the recommendation information generating module 520 is further configured to analyze the first information point and the target occurrence time period through the driving information recommendation model, and generate recommendation information for the target vehicle.
As can be seen from the above, the driving information recommendation scheme provided in the embodiment of the present invention inputs the obtained first information point and the target occurrence time period into the driving information recommendation model, and can generate the driving information of the target vehicle when the target vehicle is located at the first information point and is located at the target occurrence time period according to the historical driving record of the target vehicle, so that personalized recommendation of the target vehicle is realized, and the same content is recommended for different vehicles, so that it is obvious that driving is more intelligent.
In an embodiment of the present invention, the recommended information generating module 520 is configured to recommend driving habit information to the target vehicle if a target occurrence time period of the first information point matches a habit time period corresponding to the historical driving behavior of the target vehicle when the target vehicle drives to the first information point.
For example, the recommended information generating module 520 is specifically configured to recommend the fueling or parking information to the target vehicle if the appearance time period of the first information point matches the habit time period of the historical fueling or parking of the target vehicle when the target vehicle travels to the first information point.
In another embodiment of the present invention, the information point obtaining module 510 is further configured to obtain a second information point where the target vehicle passes;
the driving information recommending module 520 is configured to generate a target driving path according to the first information point and the second information point; and analyzing the target driving path through a driving information recommendation model to generate recommendation information for the target vehicle.
For example, the driving information recommending module 520 is specifically configured to recommend navigation information to the target vehicle according to a historical navigation path if the target driving path matches the historical navigation path of the target vehicle.
As can be seen from the above, according to the driving information recommendation scheme provided in the embodiment of the present invention, the first information and the second information point are obtained to generate the target driving path, and the target driving path is input into the driving information recommendation model, so that recommendation information when the target vehicle drives on the target driving path can be generated according to the historical driving record of the target vehicle, thereby realizing personalized recommendation of the target vehicle, instead of recommending the same content for different vehicles, and obviously making driving more intelligent.
In another embodiment of the present invention, as shown in fig. 7, the present invention further includes a model updating module 540, configured to update the training data of the driving information recommendation model by using the historical driving record generated by the target vehicle in real time.
As can be seen from the above, the driving information recommendation scheme provided in the embodiment of the present invention can update the training data of the driving recommendation model by using the historical driving record generated in real time, and then establish the driving information recommendation model for the target vehicle according to the updated historical driving record, which is beneficial to improving the accuracy of the driving information recommendation model, so as to obtain the current recommendation information for the target vehicle, implement personalized recommendation for the target vehicle, instead of recommending the same content for different vehicles, and obviously make driving more intelligent.
As shown in fig. 8, a structure diagram of a computer device provided for an embodiment of the present invention includes a memory 610, a processor 620, and a computer program stored on the memory 610 and executable on the processor 620, where the processor 620 implements the method for recommending driving information as described above when executing the computer program.
The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer device may include, but is not limited to, a processor 620, a memory 610. Those skilled in the art will appreciate that fig. 8 is merely an example of a computing device and is not intended to be limiting and may include more or fewer components than those shown, or some of the components may be combined, or different components, e.g., the computing device may also include input output devices, network access devices, buses, etc.
The Processor 620 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 610 may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. The memory 610 may also be an external storage device of a computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer device. Further, the memory 610 may also include both an internal storage unit and an external storage device of the computer device. The memory 610 is used for storing the computer program and other programs and data required by the computer device. The memory 610 may also be used to temporarily store data that has been output or is to be output.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory 610, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for recommending driving information as described above.
Note that the computer-readable storage medium may be a computer-readable storage medium contained in the memory in the above-described embodiment; or it may be a computer-readable storage medium that exists separately and is not incorporated into a computer device. The computer readable storage medium stores one or more computer programs.
For the apparatus embodiment, since it is substantially similar to the method embodiment, it is described relatively simply, and reference may be made to some descriptions of the method embodiment for relevant points.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Those skilled in the art will appreciate that all or part of the steps in the above method embodiments may be implemented by a program to instruct relevant hardware to perform the steps, and the program may be stored in a computer-readable storage medium, referred to herein as a storage medium, such as: ROM/RAM, magnetic disk, optical disk, etc.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A method for recommending driving information is characterized by comprising the following steps:
acquiring a first information point of a target vehicle passing by;
and analyzing the first information points through a driving information recommendation model to generate recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training a plurality of groups of historical driving records of the target vehicle, and each group of historical driving records comprises passing information points, the occurrence time periods of the information points and the vehicle states passing the information points.
2. The method for recommending driving information according to claim 1, further comprising:
acquiring a target occurrence time period corresponding to the first information point;
the analyzing the first information point through the driving information recommendation model, and the generating recommendation information for the target vehicle includes:
and analyzing the first information point and the target occurrence time period through the driving information recommendation model to generate recommendation information for the target vehicle.
3. The method for recommending traffic information according to claim 2, wherein the analyzing the first information point and the target occurrence period through the traffic information recommendation model, and the generating of the recommendation information for the target vehicle comprises:
when the target vehicle runs to the first information point, if the target occurrence time period of the first information point is matched with the habit time period corresponding to the historical driving behavior of the target vehicle, recommending corresponding driving habit information to the target vehicle.
4. The method for recommending driving information according to claim 3, wherein when the target vehicle travels to the first information point, if the target occurrence period of the first information point matches a habit period corresponding to the historical driving behavior of the target vehicle, recommending corresponding driving habit information to the target vehicle comprises:
and when the target vehicle runs to the first information point, recommending corresponding refueling or parking information to the target vehicle if the appearance time period of the first information point is matched with the historical refueling or parking habit time period of the target vehicle.
5. The method for recommending driving information according to claim 1, further comprising:
acquiring a second information point of the passing of the target vehicle;
the analyzing the first information point through the driving information recommendation model, and the generating recommendation information for the target vehicle includes:
generating a target driving path according to the first information point and the second information point;
and analyzing the target driving path through a driving information recommendation model to generate recommendation information for the target vehicle.
6. The method for recommending driving information according to claim 5, wherein the analyzing the target driving path through a driving information recommendation model, and generating recommendation information for the target vehicle comprises:
and if the target driving path is matched with the historical navigation path of the target vehicle, recommending navigation information to the target vehicle according to the historical navigation path.
7. The method of recommending driving information of claim 1, further comprising:
and updating the training data of the driving information recommendation model by using the historical driving record generated by the target vehicle in real time.
8. An apparatus for recommending traffic information, wherein the method for recommending traffic information according to any one of claims 1-7 is applied, and comprises:
the information point acquisition module is used for acquiring a first information point of a target vehicle passing by;
and the recommendation information generation module is used for analyzing the first information points through a driving information recommendation model and generating recommendation information for the target vehicle, wherein the driving information recommendation model is obtained by training multiple groups of historical driving records of the target vehicle, and each group of historical driving records comprises information points passing by, the occurrence time period of the information points and the vehicle state passing by the information points.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of recommending driving information according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium on which a computer program is stored, the program, when being executed by a processor, implementing a method of recommending driving information according to any one of claims 1 to 7.
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