Tourist attraction random recommendation method based on voice navigation

Abstract

The application discloses a kind of tourism scenic spot random recommendation methods based on voice navigation, in determining the driving scene of not providing clear destination, based on demand instruction trigger vehicle positioning and predict driving state, broadcast scenic type for user selection, and based on the selected scenic type and driving state prediction result, obtain and broadcast multiple matched candidate scenic spots for user selection again, in getting user target demand to carry out optimal path planning and generate voice navigation scheme.Better, through in-depth combination specific scene to the to-be-broadcast candidate scenic spot is optimized to provide more reliable suitable scenic options.The application greatly saves the time and effort of user, especially for the specific demand population of random intention during driving, based on the random tour recommendation of voice navigation, can let user carry out temporary tour planning in driving, can significantly improve the use experience of intelligent and personalized, realize the effect of just want to go.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, and particularly to a scenic spot random recommendation method based on voice navigation. BACKGROUND

[0002] With the development of voice technology, the voice control system of the car is also gradually mature, and the voice navigation is one of the popular ones. The voice control operation in the car can change the existing man-machine information exchange mode of the car, liberate the hands and eyes of the driver, and make the car more humanized and personalized.

[0003] Voice navigation is an intelligent voice application technology represented by voice recognition, voice coding and decoding, and voice synthesis. In the voice process, full voice interaction can be realized, and real-time broadcasting can be realized by the vehicle-mounted navigation. There is no need to check the screen of the navigator during driving. As long as the destination is provided at the start, the driving route can be broadcasted in real time during the journey through voice, so that the driver can focus more on driving operation.

[0004] The function that can be realized by the current voice navigation is to navigate to the explicit destination provided by the user in advance. However, for random requirements in the driving graph, for example, in the application scenario without fixed destination, the current navigation system cannot actively and intelligently provide real-time navigation recommendation of the scenic spot, that is, the voice navigation function is designed to meet the user's regular navigation requirements, and it is difficult to adapt to the more sudden random play requirements. SUMMARY

[0005] In view of the above, the present application aims to provide a scenic spot random recommendation method based on voice navigation to solve the technical problems mentioned above.

[0006] The technical solution adopted by the present application is as follows:

[0007] The present application provides a scenic spot random recommendation method based on voice navigation, which comprises:

[0008] After the voice navigation system is turned on, it is judged whether there is a fixed destination in the driving process;

[0009] After determining that there is no fixed destination, the random travel demand instruction is listened to;

[0010] After receiving the random travel demand instruction, the current vehicle is positioned and the driving state is predicted;

[0011] The preset multiple scenic types are broadcasted by voice, and the user is prompted to select;

[0012] According to the selected scenic type of the user and the driving state, a plurality of corresponding candidate scenic spots are obtained and broadcasted;

[0013] The target scenic spot selected by the user from the candidate scenic spots is taken as a destination for optimal path planning, and a voice navigation scheme is generated.

[0014] In at least one possible implementation manner, the predicted driving state comprises: predicting an area in which the vehicle will drive in a future predetermined period according to the current positioning, the driving road, the direction, and the real-time vehicle speed.

[0015] In at least one possible implementation manner, the obtaining and broadcasting of the plurality of corresponding candidate scenic spots comprises: determining a scenic spot type according to a keyword input by the user, and matching a plurality of candidate scenic spots from a vehicle networking platform and constructing a broadcasting list in combination with a prediction result of the driving state.

[0016] In at least one possible implementation manner, the candidate scenic spots in the broadcasting list are sorted before the candidate scenic spots are broadcasted.

[0017] In at least one possible implementation manner, the recommendation method further comprises: before the sorting, refining the broadcasting list according to a vehicle attribute, a driver and passenger attribute, and an environmental attribute of the candidate scenic spots in the broadcasting list.

[0018] In at least one possible implementation manner, the sorting of the candidate scenic spots in the broadcasting list comprises:

[0019] Based on the predicted driving state, a distance between the vehicle and each candidate scenic spot is calculated;

[0020] In combination with a current endurance mileage of the vehicle, the broadcasting list is refined in a first round;

[0021] The candidate scenic spots remaining in the broadcasting list after the first round of refinement are sorted according to the distance from near to far.

[0022] In at least one possible implementation manner, after the first round of refinement, weather prediction information and / or traffic notification information and / or scenic spot early warning information of the candidate scenic spots remaining in the broadcasting list are obtained;

[0023] According to the weather prediction information and / or the traffic notification information and / or the scenic spot early warning information, the current broadcasting list is refined in a second round.

[0024] In at least one possible implementation manner, the weather prediction information comprises weather information of a location of the scenic spot and a surrounding area at a time when the vehicle arrives.

[0025] Compared with the prior art, the main design concept of the present application is that, in the driving scene where no clear destination is provided, the vehicle positioning is triggered based on the demand instruction, the driving state is predicted, the scenic area type is broadcast for the user to select, and based on the selected scenic area type and the driving state prediction result, a plurality of matched candidate scenic spots are obtained and broadcast for the user to select again, and the optimal path planning is performed and the voice navigation scheme is generated according to the user target demand. More preferably, the to-be-broadcast candidate scenic spots are optimized in a targeted manner by deep integration with specific scenes to provide more reliable and suitable scenic spot options. The present application greatly saves the time and effort of the user, especially for the specific demand population who generates random intentions during driving. The random tour recommendation based on voice navigation can allow the user to plan a temporary tour during driving, which can significantly improve the intelligent and personalized user experience and achieve the effect of going wherever you want. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described below with reference to the drawings, in which:

[0027] Figure 1 The flowchart of the random tour recommendation method based on voice navigation provided by the embodiment of the present application is shown. DETAILED DESCRIPTION

[0028] The embodiments of the present application will be described in detail below, and the examples of the embodiments are shown in the drawings, in which the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present application, but cannot be interpreted as a limitation on the present application.

[0029] The present application proposes an embodiment of a random tour recommendation method based on voice navigation, specifically as shown in Figure 1 , which includes:

[0030] Step S1, after the voice navigation system is started, it is determined whether there is a fixed destination during driving;

[0031] Step S2, after determining that there is no fixed destination, a random tour demand instruction is listened to;

[0032] It can be pointed out here that the random tour demand instruction can come from the user's active voice input or be obtained through an inquiry mechanism, for example, after determining that there is no fixed destination, the voice navigation system inquires whether the user has the intention to go to a tourist attraction in a voice broadcast manner.

[0033] Step S3, after receiving the random tour demand instruction, the current vehicle is positioned and the driving state is predicted;

[0034] As to the predicted driving state, in actual operation, it can refer to predicting the area where the vehicle will drive in a future predetermined period (which can be set according to experience, such as 5 minutes later) according to the current positioning, driving road, direction (which can be positioned by GPS after the system is started on the car machine MP5, the vehicle networking platform can real-time position the vehicle position, road and driving mode, and refresh the display on the system map) and real-time vehicle speed. This is because the application scenario of the present application is during driving, so in the process of subsequently performing random tourist attraction recommendation and finally determining the target attraction, the vehicle has already driven a certain distance, that is, it is no longer in the place at the current time when the demand instruction is given. Based on the prediction result, the tourist attraction that is convenient to reach can be more accurately recommended, and it can be understood that this preferred embodiment is particularly suitable for use in high-speed driving.

[0035] Step S4, voice broadcast a plurality of preset attraction types, and prompt the user to activate selection;

[0036] The system can broadcast the preset attraction types, such as but not limited to: lake scenic spot, mountain scenic spot, landscape scenic spot, forest scenic spot, seaside scenic spot, leisure summer resort, cultural scenic spot, etc. Of course, in actual operation, the attraction classification mechanism can also use other dimensions such as attraction level for pre-classification.

[0037] Step S5, according to the user-selected attraction type and in combination with the driving state, a plurality of corresponding candidate attractions are obtained and broadcasted;

[0038] Specifically, after the user speaks the selected attraction type keyword, the system automatically corresponds to the attraction type and combines the driving state prediction result mentioned in the foregoing, matches in the database pre-stored in the vehicle networking platform, obtains a plurality of candidate attractions and constructs a broadcast list. The database mentioned here can be obtained from the official website of the tourism bureau and the statistical bureau of each place, and in addition to the attraction name, the database can also include the address of each attraction and the introduction of the attraction related to the attraction.

[0039] Based on this concept, the candidate attractions in the broadcast list can also be sorted before the candidate attractions are broadcasted. For example, in some embodiments, the distance between the vehicle and each candidate attraction is calculated based on the predicted driving state, and the current range of the vehicle (not limited to the battery capacity, but also based on the fuel remaining amount and the average fuel consumption) is combined to perform the first round of refinement on the broadcast list, and then the remaining candidate attractions in the first round of refined list are sorted from near to far.

[0040] In some preferred embodiments of the present application, the weather forecast information (specifically, the weather information at the location of the vehicle and the surrounding area when the vehicle arrives) and / or the traffic report information and / or the scenic spot warning information related to the remaining candidate scenic spots are also preferably obtained in the first round of the refined list of the broadcast, and the current broadcast list is refined for a second round according to the above information, so as to ensure that the candidate scenic spots finally broadcast to the user are more suitable for touring, for example, a mountainous scenic spot is expected to have severe weather when the vehicle arrives, or the road to a forest scenic spot is limited, or a certain cultural scenic spot is temporarily closed due to flow limitation, etc. These scenic spots that are not suitable for touring at the moment are filtered out from the first round of the refined list, and then sorted from near to far, thereby obtaining a better broadcast list.

[0041] In other embodiments of the present application, the refinement and screening strategy is mainly safety, for example, the vehicle attributes (off-road, load, power, etc.), the driver attributes (children, the elderly, pregnant women, etc.) and the environmental attributes (altitude, air pressure, temperature and humidity, terrain and road conditions, etc.) of the candidate scenic spots in the broadcast list are obtained by using existing mature technologies to refine the current broadcast list.

[0042] As can be understood by those skilled in the art, the multi-round refinement strategy mentioned above can be combined as needed, and the present application does not limit this.

[0043] Step S6, the target scenic spot selected by the user from the candidate scenic spots is taken as the destination for optimal path planning, and a voice navigation scheme is generated.

[0044] After that, voice broadcast navigation can be performed according to the existing voice navigation system function, and in addition, real-time path updating can be performed during driving according to the navigation path, and the current best path is recommended for the user to select and switch. For this, mature navigation technology can be referred to, and the present application does not repeat it.

[0045] From the above description, it can be seen that the present application solves the pain points of specific groups of people, i.e. for drivers who have random touring and viewing needs and do not want to plan the itinerary, they no longer need to stop and search for information about tourist attractions and then plan the itinerary, i.e. they can realize on-the-go touring, so that the voice navigation is more intelligent and flexible, and can solve specific problems in specific scenarios in a humanized manner.

[0046] To sum up, the main design idea of the present application is that, in the driving scene where no clear destination is provided, the vehicle positioning is triggered based on the demand instruction and the driving state is predicted, the type of scenic area is broadcast for the user to select, and based on the selected scenic area type and the driving state prediction result, a plurality of matched candidate scenic spots are obtained and broadcast for the user to select again, and the optimal path planning is performed based on the target demand of the user and the voice navigation scheme is generated. More preferably, the selected candidate scenic spots to be broadcast are optimized in a targeted manner by deep integration with specific scenarios, so as to provide more reliable and suitable scenic spot options. The present application greatly saves the time and effort of the user, especially for the specific demand population who generates random intentions during driving, and the random tour recommendation based on voice navigation can allow the user to simultaneously plan a temporary tour during driving, which can significantly improve the intelligent and personalized use experience and achieve the effect of wanting to go immediately.

[0047] In the embodiments of the present application, "at least one" refers to one or more, and "multiple" refers to two or more. The "and / or" describes the association relationship of the associated objects, which means that there can be three kinds of relationships, for example, A and / or B, which can represent the cases of A alone, A and B together, and B alone. Wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the front and rear associated objects. "At least one of the following" and the like means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, wherein a, b, and c can be single or multiple.

[0048] The above embodiments according to the drawings illustrate the structure, features and effects of the present application, but the above are only preferred embodiments of the present application, and it should be noted that the technical features involved in the above embodiments and preferred modes can be reasonably combined and matched into a plurality of equivalent schemes by those skilled in the art without departing from or changing the design idea and technical effects of the present application. Therefore, the present application is not limited by the drawings shown in the drawings, and any changes or modifications made in accordance with the idea of the present application, or equivalent embodiments with equivalent changes, shall be within the scope of protection of the present application.

Claims

1.A method for random recommendation of a tourist attraction based on voice navigation, characterized in that, The method comprises: After the voice navigation system is turned on, it is determined whether there is a fixed destination during driving; After determining that no fixed destination is provided, a random travel demand instruction is listened to, including: after determining that there is no fixed destination set, the voice navigation system inquires whether the user has the intention to go to a scenic spot in a voice broadcast manner; After receiving the random travel demand instruction, the current vehicle is positioned and the driving state is predicted, including: predicting the area where the vehicle will travel in the future within a certain period of time; The voice broadcast pre-set multiple types of scenic spots and prompts the user to select, including: broadcasting the types of scenic spots that the user can select from, rather than directly providing the target scenic spot by the user; According to the user's selected scenic spot type and the predicted future vehicle driving area, multiple corresponding candidate scenic spots are obtained and broadcasted; The target scenic spot selected by the user from the candidate scenic spots is used as the destination for optimal path planning, and a voice navigation scheme is generated. 2.The voice navigation-based random recommendation method for a tourist attraction according to claim 1, characterized in that, The prediction of the driving state includes: according to the current positioning, driving road, direction and real-time speed, the area where the vehicle will travel in the future within a certain period of time is predicted. 3.The voice navigation based random recommendation method of a tourist attraction according to claim 1, characterized in that, The method of obtaining and broadcasting multiple corresponding candidate scenic spots includes: determining the type of scenic spot according to the user input keyword, and combining the prediction result of the driving state, matching multiple candidate scenic spots from the Internet of Vehicles platform and constructing a broadcast list. 4.The voice navigation-based random recommendation method of a tourist attraction according to claim 3, characterized in that, Before broadcasting the candidate scenic spots, the candidate scenic spots in the broadcast list are sorted. 5.The voice navigation-based random recommendation method of a tourist attraction according to claim 4, characterized in that, The recommendation method further comprises: before sorting, according to the vehicle attributes, the driver and passenger attributes, and the environmental attributes of the candidate scenic spots in the broadcast list, the broadcast list is refined. 6.The voice navigation based random recommendation method of a tourist attraction according to claim 4, characterized in that, The method of sorting the candidate scenic spots in the broadcast list comprises: Based on the predicted driving state, the distance between the vehicle and each candidate scenic spot is calculated; Combined with the current range of the vehicle, the broadcast list is refined in the first round; The remaining candidate scenic spots in the broadcast list after the first round of refinement are sorted from near to far according to the distance. 7.The voice navigation-based random recommendation method of a tourist attraction according to claim 6, characterized in that, After the first round of refinement, the weather forecast information and / or traffic information and / or scenic spot warning information of the remaining candidate scenic spots in the broadcast list are obtained; According to the weather forecast information and / or traffic information and / or scenic spot warning information, the current broadcast list is refined in the second round. 8.The voice navigation based random recommendation method of a tourist attraction according to claim 7, characterized in that, The weather forecast information includes the weather information of the scenic spot location and the surrounding area when the vehicle arrives.

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