CN110954118A - Service recommendation method and system for vehicle machine - Google Patents
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- CN110954118A CN110954118A CN201811146391.2A CN201811146391A CN110954118A CN 110954118 A CN110954118 A CN 110954118A CN 201811146391 A CN201811146391 A CN 201811146391A CN 110954118 A CN110954118 A CN 110954118A
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- 230000015572 biosynthetic process Effects 0.000 claims description 3
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3626—Details of the output of route guidance instructions
- G01C21/3641—Personalized guidance, e.g. limited guidance on previously travelled routes
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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
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3679—Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities
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Abstract
The invention provides a service recommendation method and system for a vehicle machine. The method includes step S1: comparing the driving history data with the current position and the current departure time, and if the driving history data is matched with the current position and the current departure time, turning to the step S3; step S2: acquiring the travel information of a user; step S3: recommending a navigation route; step S4: and recommending personalized service information based on the destination, the arrival time and the personal preference information of the navigation route. The invention also provides a vehicle machine for predicting the road condition ahead, which can plan the navigation route of the user and recommend corresponding personalized services, thereby improving the user experience and the travel efficiency.
Description
Technical Field
The invention relates to the field of vehicle machines, in particular to a service recommendation method and system for a vehicle machine.
Background
With the development of social economy, the number of motor vehicles is increasing day by day, and with the popularization of intelligent equipment and developed internet technology, the functions of vehicle equipment applied to motor vehicles are becoming perfect, and the traditional navigation function is an auxiliary tool which cannot be used by vehicle owners when going out. Although the current navigation equipment applied to the car machine has more intelligent functions such as navigation planning and real-time display, generally, the navigation equipment lacks personalized recommendation service, is not associated with the area where the destination is located, and is poor in user experience.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
In order to achieve the above object, the present invention provides a better service recommendation method for locomotive users, and the service recommendation method for a locomotive machine, including: step S1: comparing the driving history data with the current position and the current departure time, and if the driving history data is matched with the current position and the current departure time, turning to the step S3; step S2: acquiring the travel information of a user; step S3: recommending a navigation route; step S4: and recommending personalized service information based on the destination, the arrival time and the personal preference information of the navigation route.
In one embodiment of the method, after a set period of time elapses and the locomotive navigation information is accumulated, the driving history data is formed regularly, and includes a starting point, a departure time and a destination.
In an embodiment of the method as described above, in step S3, recommending the navigation route includes recommending an optimal navigation route or recommending a plurality of navigation routes for the user to select.
In an embodiment of the above method, the personal preference information is obtained through a big data platform and/or the driving history data.
In an embodiment of the above method, the personalized service information includes dining information, parking lot reservation service or movie ticket reservation service.
The invention also provides a vehicle machine for predicting the road condition ahead, which comprises:
the acquisition module is used for acquiring the travel information of the user;
the historical navigation data module is used for extracting regular driving historical data from the historical travel information, and the regular driving historical data comprises an initial place, a departure time and a destination;
the navigation module recommends a navigation route according to the driving history data of the history navigation data module or the travel information of the acquisition module;
the personal preference module is used for collecting personal preference information from a big data platform and/or the historical navigation data module;
and the service recommendation module is used for recommending personalized service information according to the navigation route and the personal preference information.
In an embodiment of the foregoing vehicle device, the vehicle device further includes a map storage module that stores map data, and the navigation module generates a plurality of navigation routes according to the map data and based on the driving history data or the formation information.
In an embodiment of the aforementioned vehicle device, the navigation module includes a comparing unit, which compares the travel times of the plurality of navigation routes to determine an optimal navigation route according to the shortest travel time.
In an embodiment of the foregoing car machine, the car machine further includes a communication module, which communicates with an external server, the personal preference module can be connected to the big data platform through the communication module, and the service recommendation module can be connected to a third party service platform through the communication module.
In an embodiment of the foregoing vehicle device, the obtaining module includes:
a receiving unit for receiving a voice input of a user; and
a voice recognition unit for performing voice recognition on the voice input to recognize the trip information.
The invention also provides the in-vehicle equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the steps of the method provided by the invention are realized when the processor executes the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method as provided by the invention.
According to the method, the vehicle machine equipment and the computer readable storage medium provided by the invention, a more intelligent and humanized service recommendation function is realized, the navigation route of the user can be planned, and the corresponding personalized service can be recommended, so that the user experience is improved, and the travel efficiency is improved.
It is to be understood that both the foregoing general description and the following detailed description of the present invention are exemplary and explanatory and are intended to provide further explanation of the invention as claimed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principle of the invention. In the drawings:
fig. 1 shows a schematic flow diagram of a method according to the invention.
Fig. 2 shows a schematic block diagram of a vehicle machine according to the present invention.
Wherein the figures include the following reference numerals:
in-vehicle machine 200 acquisition module 201
Historical navigation data Module 202 navigation Module 203
Personal preference Module 204 service recommendation Module 205
Map storage module 206 communication module 207
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the application, its application, or uses. 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 application.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As described above, in order to predict the vehicle speed of the road ahead in the navigation route of the user, and recommend a preferred navigation route in time during the car navigation process, so as to facilitate the user and the user to conveniently and quickly change the car navigation route to the optimal navigation route, the present invention provides a service recommendation method for a car machine, fig. 1 shows a flow diagram of the method provided by the present invention, and as shown in fig. 1, the method provided by the present invention includes step S1: comparing the driving history data with the current position and the current departure time, and if the driving history data is matched with the current position and the current departure time, turning to the step S3; step S2: acquiring the travel information of a user; step S3: recommending a navigation route; step S4: and recommending personalized service information based on the destination, the arrival time and the personal preference information of the navigation route.
Further, the driving history data is data that forms regularity after a set period of time, for example, 3 months, has elapsed since the accumulation of the locomotive navigation information. The driving history data includes a start point, a departure time, and a destination. For example, during 3 months, around 8 am each day of the work day, the user navigation data is from point a to point B, and around 18 pm, the locomotive returns from point B to point a. So after a period of 3 months, the car navigation system considers point a to be the address of the user's "home" and point B to be the "company" address. It is easy to understand that not every day of the working day, the navigation data between the points a and B must be satisfied to satisfy the conditions of "home" and "company", as long as the fit degree of the related data reaches 80%. Of course, the user may also directly enter the geographic locations of "home" and "company". Thus, the regular driving history data is formed. And when the vehicle-mounted device of the user is ignited before and after 8 am on a working day, comparing the driving history data with the current position and the current departure time, and if the driving history data is matched with the current position and the current departure time, actively pushing a navigation route to a company to the user by taking the destination in the driving history data as the navigation end position. Similarly, before and after 18 pm, after the vehicle-mounted device of the user is ignited, the driving history data is compared with the current position and the current departure time, and if the driving history data is matched with the current position and the current departure time, the destination in the driving history data is taken as the navigation end position, and the navigation route returned to the home is actively pushed to the user. It should be understood by those skilled in the art that the foregoing examples are merely illustrative of the concept of the method provided by the present invention, and may be set or selected according to different conditions, for example, the historical driving data may also include a weekend period, such as regular driving historical data formed by sending a child to a training class within a specific time period.
When the driving history data cannot be matched with the current position and the current departure time, the user is required to provide the end position, that is, the formation information of the user is acquired through step S2.
In step S3, the recommended navigation route may include 1 optimal navigation route or recommend several navigation routes for the user to select. Once the user determines the navigation route, the destination of the navigation is determined, and the arrival time can be estimated.
In step S4, personalized service information is recommended based on the destination, arrival time, and personal preference information of the navigation route. For example, dining information around the destination, a parking lot reservation service, or a movie ticket reservation service may be recommended to the user according to the destination. The personal preference information can be acquired through a big data platform and/or the driving history data. The big data platform is a platform with huge data, and the user preference can be determined from the record statistics of the daily habits of the user through the platform, wherein the platform has a new processing mode and has high decision power, insight and flow optimization capacity, and the platform has massive, high growth rate and diversified information assets.
In one embodiment, a user starts 8 am on Tuesday, and after the vehicle-mounted device of the user is ignited, the driving history data is compared with the current position and the current starting time, the current position and the current starting time are matched, and the optimal navigation route of the company is actively pushed to the user. And the user selects the optimal navigation route for navigation. Then, the car machine system recommends a predetermined service for a parking lot around the "company" to the user based on the destination being the "company". And when the user determines the parking reservation service, the vehicle-mounted machine system directly navigates to a specific parking space.
In another embodiment, the user starts 17 pm on saturday afternoon, after the vehicle-mounted device of the user is ignited, the driving history data is compared with the current position and the current starting time, and if the driving history data is not matched with the current position and the current starting time, the travel information of the user is obtained. And selecting a plurality of navigation routes for navigation according to the destination position provided by the user, such as a shopping mall. And the vehicle-mounted machine system recommends the parking lot reservation service of the mall and the reservation service of the catering in the mall to the user based on the fact that the destination is the mall and the estimated arrival time is 17: 45. The reservation services for the restaurant may include recommending a restaurant, and recommending a reservation service per restaurant. And after the user determines the parking reservation service, the car machine system directly navigates to a specific parking space, if the user determines the reservation service of the restaurant, the restaurant reserves the position, and the user can directly go to the restaurant for dining after arriving. If the personal preference information includes restaurant types that the user visits on average, the in-vehicle system may recommend to the user a restaurant reservation service within the mall that resembles a grade and taste.
In another embodiment, the user starts at 12 pm on a sunday, and after the vehicle-mounted device of the user is ignited, the driving history data is compared with the current position and the current starting time, and if the driving history data is not matched with the current position and the current starting time, the travel information of the user is obtained. And selecting a plurality of navigation routes for navigation according to the destination position provided by the user, such as a shopping mall. And the vehicle-mounted machine system recommends the parking lot reservation service of the mall to the user based on the fact that the destination is the mall and the estimated arrival time is 12: 45. According to the personal preference information, if the user is found to have a large amount of ticket booking information, the movie booking service of the cinema in the city of the merchant is recommended. If the personal preference information also includes the movie genre preferred by the user, a predetermined service of the relevant movie genre is pushed.
The invention also provides a vehicle machine, and fig. 2 shows a module schematic diagram of the vehicle machine provided by the invention. As shown in fig. 2, the car machine 200 provided by the present invention includes an obtaining module 201, configured to obtain travel information of a user; the historical navigation data module 202 is used for extracting regular driving historical data from the historical travel information, wherein the regular driving historical data comprises an initial place, a departure time and a destination; the navigation module 203 recommends a navigation route according to the driving history data of the historical navigation data module or the travel information of the acquisition module; the personal preference module is used for collecting personal preference information from a big data platform and/or the historical navigation data module; and the service recommendation module is used for recommending personalized service information according to the navigation route and the personal preference information.
In one embodiment, the obtaining module 201 may include a receiving unit for receiving a voice input of a user, and a voice recognition unit for performing voice recognition on the voice input to recognize the trip information. In the above embodiment, the trip information of the user may be the trip information that is pre-stored in the vehicle machine in a voice input manner during the current or previous vehicle using process of the user, and after receiving the voice input of the user and recognizing the voice input, the vehicle machine provided by the invention automatically stores the trip information about the user, so as to intelligently provide a navigation route for the user.
In another embodiment, the car machine 200 further comprises a map storage module 206 for storing map data. The navigation module 203 generates several navigation routes based on the current position and the end position from the map data stored on the map storage module 206.
In another embodiment, the car machine 200 further includes a communication module 207 capable of communicating with an external server. The personal preference module 204 can be connected to the big data platform through the communication module 207 to obtain the consumption habits of the user, etc. The service recommendation module 205 can be connected to a third party service platform, such as a parking lot service platform at a destination location, via the communication module 207. And inquiring and reserving the parking space, and finishing the reservation service after the user confirms. When the vehicle machine arrives at the parking lot, the vehicle machine can enter the parking lot by taking the license plate of the vehicle as the only mark and navigate to a specific parking space. Further, the navigation module can be connected to an external server through the communication module 207 to obtain real-time traffic information for adjusting the navigation route. In addition, the car machine 200 can update the map data stored on the map storage module 206 through the communication module 207.
In another embodiment, the route calculation module 204 includes a comparison unit capable of comparing the travel times of several navigation routes to determine the optimal navigation route for pushing with the shortest travel time.
The invention also provides the in-vehicle equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the steps of the method.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
Specific implementation manners and technical effects of the in-vehicle device and the computer-readable storage medium can be found in the above embodiments of the service recommendation method provided by the present invention, and are not described herein again.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a 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, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
It will be apparent to those skilled in the art that various modifications and variations can be made to the above-described exemplary embodiments of the present invention without departing from the spirit and scope of the invention. Thus, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.
Claims (12)
1. A service recommendation method for a vehicle machine comprises the following steps:
step S1: comparing the historical data with the current position and the current departure time, if the historical data is matched with the current position and the current departure time, switching to
Step S3;
step S2: acquiring the travel information of a user;
step S3: recommending a navigation route;
step S4: and recommending personalized service information based on the destination, the arrival time and the personal preference information of the navigation route.
2. The service recommendation method of claim 1, wherein the regular driving history data is formed after accumulation of locomotive navigation information for a set period of time, and the driving history data comprises a starting point, a departure time and a destination.
3. The service recommendation method of claim 1, wherein in step S3, recommending a navigation route comprises recommending an optimal navigation route or recommending a plurality of navigation routes for a user to select.
4. The service recommendation method of claim 1, wherein the personal preference information is obtained through a big data platform and/or the driving history data.
5. The service recommendation method of claim 1, wherein the personalized service information comprises dining information, parking lot reservation services, or movie ticketing reservation services.
6. A car machine for service recommendation, comprising:
the acquisition module is used for acquiring the travel information of the user;
the historical navigation data module is used for extracting regular driving historical data from the historical travel information, and the regular driving historical data comprises an initial place, a departure time and a destination;
the navigation module recommends a navigation route according to the driving history data of the history navigation data module or the travel information of the acquisition module;
the personal preference module is used for collecting personal preference information from a big data platform and/or the historical navigation data module;
and the service recommendation module is used for recommending personalized service information according to the navigation route and the personal preference information.
7. The vehicle machine of claim 6, further comprising a map storage module that stores map data, wherein the navigation module generates a plurality of navigation routes based on the driving history data or formation information according to the map data.
8. The vehicle machine of claim 7, wherein the navigation module comprises a comparison unit for comparing the travel time of a plurality of the navigation routes to determine the optimal navigation route with the shortest travel time.
9. The vehicle machine of claim 6, further comprising a communication module, wherein the communication module is in communication with an external server, the personal preference module can be connected with the big data platform through the communication module, and the service recommendation module can be connected with a third-party service platform through the communication module.
10. The vehicle machine of claim 6, wherein the obtaining module comprises:
a receiving unit for receiving a voice input of a user; and
a voice recognition unit for performing voice recognition on the voice input to recognize the trip information.
11. In-vehicle machine apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 5 when executing the computer program.
12. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
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| CN111968401A (en) * | 2020-08-11 | 2020-11-20 | 支付宝(杭州)信息技术有限公司 | Parking space recommendation method and device, and parking space prediction method and device of parking lot |
| CN112146675A (en) * | 2020-10-09 | 2020-12-29 | 上海博泰悦臻网络技术服务有限公司 | Service recommendation method, system, medium and device based on voice conversation |
| CN112507226A (en) * | 2020-12-14 | 2021-03-16 | 北京瞰瞰科技有限公司 | Vehicle-mounted information management method and system based on Internet of things |
| CN113888897A (en) * | 2021-09-30 | 2022-01-04 | 中国人民银行数字货币研究所 | Parking reservation method, device and system |
| CN113970341A (en) * | 2021-10-28 | 2022-01-25 | 芜湖雄狮汽车科技有限公司 | Navigation method and device for vehicle, cloud server and storage medium |
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