CN111289001A - Navigation method and device and electronic equipment - Google Patents
Navigation method and device and electronic equipment Download PDFInfo
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- CN111289001A CN111289001A CN201811504904.2A CN201811504904A CN111289001A CN 111289001 A CN111289001 A CN 111289001A CN 201811504904 A CN201811504904 A CN 201811504904A CN 111289001 A CN111289001 A CN 111289001A
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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
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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Abstract
The embodiment of the invention provides a navigation method and device and electronic equipment. The method comprises the following steps: the method comprises the steps of obtaining starting data and historical navigation data of a user, wherein the starting data at this time at least comprises a starting position at this time of the user, and the historical navigation data at least comprises a historical starting position and a historical terminal position of the user; estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user; and planning a navigation route from the starting position to the ending position. According to the embodiment of the invention, the terminal position of the trip of the user is estimated in real time by acquiring the starting data of the user and combining with the historical navigation data, and the navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a navigation method and apparatus, and an electronic device.
Background
With the popularization and wide application of intelligent devices, more and more people select a device with a navigation function as an auxiliary tool when going out, and can plan a more reasonable travel route through the navigation function to smoothly reach a destination under the condition that the destination cannot be found or the road condition is unfamiliar.
The existing navigation device or related application programs generally plan one or more travel routes according to information such as a starting position, an end position, a road condition and the like acquired in real time of a user, so that the user can select the travel routes.
In the process of implementing the invention, the inventor finds that the prior art has at least the following problems: in the prior art, the current position of a user is usually defaulted as a starting position by a navigation device or an application, so that before a route is planned, the user is required to manually input the end position information of the trip at least, the operation is complicated and not fast enough, and the user experience is poor under specific scenes that the user is inconvenient to input information and the like.
Disclosure of Invention
The embodiment of the invention provides a navigation method, a navigation device and electronic equipment, aiming at solving the defect of fussy navigation operation in the prior art and enabling navigation to be faster.
To achieve the above object, an embodiment of the present invention provides a navigation method, including:
the method comprises the steps of obtaining starting data and historical navigation data of a user, wherein the starting data at this time at least comprises a starting position at this time of the user, and the historical navigation data at least comprises a historical starting position and a historical terminal position of the user;
estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user;
and planning a navigation route from the starting position to the ending position.
An embodiment of the present invention further provides a navigation apparatus, including:
the data acquisition module is used for acquiring the starting data and the historical navigation data of the user, wherein the starting data at this time at least comprises the starting position of the user at this time, and the historical navigation data at least comprises the historical starting position and the historical terminal position of the user;
the estimating module is used for estimating the current end point position of the user according to the current starting data and the historical navigation data of the user;
and the route planning module is used for planning a navigation route from the starting position to the ending position.
An embodiment of the present invention further provides an electronic device, including:
a memory for storing a program;
a processor for executing the program stored in the memory for:
the method comprises the steps of obtaining starting data and historical navigation data of a user, wherein the starting data at this time at least comprises a starting position at this time of the user, and the historical navigation data at least comprises a historical starting position and a historical terminal position of the user;
estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user;
and planning a navigation route from the starting position to the ending position.
According to the navigation method, the navigation device and the electronic equipment provided by the embodiment of the invention, the terminal position of the trip of the user is estimated in real time by acquiring the starting data of the user and combining with historical navigation data, and the navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a system block diagram of a service system according to an embodiment of the present invention;
FIG. 2 is a flow chart of one embodiment of a navigation method provided by the present invention;
FIG. 3 is a flow chart of another embodiment of a navigation method provided by the present invention;
FIG. 4 is a flow chart of yet another embodiment of a navigation method provided by the present invention;
FIG. 5 is a schematic structural diagram of a navigation device according to an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of another embodiment of a navigation device provided in the present invention;
fig. 7 is a schematic structural diagram of an embodiment of an electronic device provided in the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
When a user goes out, the auxiliary terminal is used for positioning the starting position, and planning and navigating a traveling route. In the prior art, the navigation device or the navigation application usually defaults that the starting position of the user is the starting position, so before planning a route, at least the user needs to manually input the end position information of the trip, the operation is complicated, and the navigation device or the navigation application is not fast and convenient enough. Therefore, the present application proposes a navigation solution, whose main principle is: when a user starts a navigation function, the current starting data (such as the current starting position information) of the user is acquired in real time, meanwhile, the terminal position of the current trip of the user is estimated in real time by combining the historical navigation data of the user, and a navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user in a specific scene.
The method provided by the embodiment of the invention can be applied to any business system with a navigation function.
Fig. 1 is a system block diagram of a service system provided in an embodiment of the present invention, and the structure shown in fig. 1 is only one example of a service system to which the technical solution of the present invention can be applied. As shown in fig. 1, the service system includes a navigation device. The navigation device includes: the data acquisition module, the estimation module, and the route planning module may be used to perform the process flows shown in fig. 2, 3, and 4, which are described below. In the service system, a preprocessing module estimates an end point position according to the starting data and historical navigation data of a user, wherein the starting data comprises the starting position of the user; then, the calculation module plans a navigation route according to the starting position of the user and the estimated end position of the preprocessing module, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
The above embodiments are illustrations of technical principles and exemplary application frameworks of the embodiments of the present invention, and specific technical solutions of the embodiments of the present invention are further described in detail below through a plurality of embodiments.
Example one
Fig. 2 is a flowchart of an embodiment of the navigation method provided by the present invention, where an execution subject of the method may be the service system, or may be various terminal devices with a navigation function, such as a mobile phone, a car navigator, and the like, or may be a device or a chip integrated on these terminal devices. As shown in fig. 2, the navigation method includes the following steps:
s201, obtaining the current departure data and the historical navigation data of the user.
In an embodiment of the present invention, the current departure data at least includes a current departure position of the user, and the historical navigation data at least includes a historical departure position and a historical destination position of the user.
S202, estimating the current end point position of the user according to the current starting data and the historical navigation data of the user.
When a user starts a navigation function, the starting position of the user is obtained in real time, and the terminal position of the user on the trip is estimated in real time by combining historical navigation data.
And S203, planning a navigation route from the current departure position to the current destination position.
After the starting position (default is the starting position of the user) and the ending position of the user are obtained, a navigation route from the starting position to the ending position of the user is planned according to the existing navigation algorithm by combining the current real-time road condition information, and automatic navigation is carried out. When the position of the current terminal point is estimated, a prompt box can be popped up, and the user confirms whether to navigate to XXXXXX or not, for example, is displayed; the dialog box may be cancelled after a countdown (e.g., 3 seconds) to automatically enter the navigation mode to avoid impacting the user.
According to the navigation method provided by the embodiment of the invention, the terminal position of the trip of the user is estimated in real time by acquiring the starting data of the user and combining with the historical navigation data, and the navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
Example two
FIG. 3 is a flowchart of another embodiment of a navigation method provided by the present invention. As shown in fig. 3, on the basis of the embodiment shown in fig. 2, the navigation method provided in this embodiment may further include the following steps:
s301, obtaining the current departure data and the historical navigation data of the user.
S302, the longitude value and the latitude value of the starting position in the starting data are obtained.
And S303, forming the longitude value and the latitude value in the starting data into the starting feature vector.
In the embodiment of the present invention, the present departure position included in the present departure data is composed of the longitude value and the latitude value, and therefore, the longitude value and the latitude value of the present departure position of the user are composed of the present departure feature vector.
And S304, forming a historical navigation feature vector set by the longitude value and the latitude value of the starting position in the historical navigation data.
In the embodiment of the present invention, steps S303 and S304 are not sequential, a historical navigation feature vector set may be formed in advance, and the starting feature vector is formed when navigation is started; the starting feature vector and the historical navigation feature vector set can be formed sequentially when navigation is started, or the starting feature vector and the historical navigation feature vector set can be formed simultaneously.
S305, calculating the Euclidean distance between the starting feature vector and each historical navigation feature vector in the historical navigation feature vector set.
And S306, selecting the historical navigation data corresponding to the historical navigation feature vector with the minimum Euclidean distance as reference historical navigation data.
In the embodiment of the invention, when the current end point position is estimated, historical navigation data can be used as a historical navigation feature vector set, and the current starting data is classified and calculated, so that the current end point position is obtained. Specifically, a K-Nearest Neighbor (KNN) algorithm can be adopted for classification calculation. For example, the euclidean distance between the current departure feature vector and each historical navigation feature vector is calculated, and when K is 1, the historical navigation data corresponding to the historical navigation feature vector with the smallest euclidean distance is obtained, that is, the reference historical data for the user to obtain the current end point position. Of course, different values of K may be selected according to different situations. In addition, in the embodiment of the present invention, a decision tree algorithm or a neural network algorithm, etc. may also be used for the classification calculation.
And S307, acquiring the end point position in the reference historical data as the estimated current end point position of the user.
And after the reference historical data is determined, acquiring the end point position in the reference historical data as the estimated end point position of the travel route.
And S308, sending the estimated current end point position of the user to the user side.
S309, when the confirmation information of the user side is received, planning a navigation route from the starting position to the ending position.
And after the starting point position (default is the starting position of the user at this time) and the estimated end point position at this time are obtained, the estimated end point position of the user at this time is sent to the user side. If the confirmation information of the user side is received, planning a navigation route from the starting position to the destination position, and performing automatic navigation; and if a new end position input by the user terminal is received, planning a navigation route from the starting position to the new end position.
According to the navigation method provided by the embodiment of the invention, the historical navigation data is used as the historical navigation feature vector set for modeling, the new navigation data input by the user is used as the learning object, and the model parameters are continuously adjusted, so that the classification and identification are more accurate; during navigation, the longitude value and the latitude value of the starting position of the user are obtained, classification calculation is carried out by combining historical navigation data, the end position of the user during traveling is estimated in real time, and a navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
EXAMPLE III
FIG. 4 is a flowchart of another embodiment of a navigation method provided by the present invention. As shown in fig. 4, on the basis of the embodiment shown in fig. 2 or fig. 3, the navigation method provided in the embodiment of the present invention may further include the following steps:
s401, obtaining the current departure data and the historical navigation data of the user.
In this embodiment of the present invention, the current departure data may further include a current departure time point, and the historical navigation data may further include a historical departure time point of the user.
S402, counting the historical navigation times of the user.
And S403, when the counted historical navigation times are greater than a preset time threshold, starting an automatic navigation mode.
In the embodiment of the invention, a preset time threshold value can be set firstly, and only when the historical data of the user exceeds the preset time threshold value, the stored historical navigation data can be used for the system to learn, the system has the automatic navigation condition, and the automatic navigation mode is started. Therefore, it is necessary to collect historical data of each navigation of the user, and the historical navigation data may include, but is not limited to, a starting point position (longitude value and latitude value), a historical starting time point, an end point position (longitude value and latitude value), and the like of the user's navigation. When the counted historical navigation times is greater than a preset time threshold (for example, the preset time threshold may be set to 10 times), the automatic navigation mode is turned on, and the following step S404 is performed.
And S404, forming the longitude value, the latitude value and the time value in the starting data into the starting feature vector.
In the embodiment of the present invention, the present departure data that can be used may include the present departure time point in addition to the present departure position. And classification calculation is carried out through three dimensions of the longitude value, the latitude value and the time point, so that the classification result is more accurate. Therefore, after the automatic navigation mode is started, the longitude value, the latitude value and the departure time point of the user at the departure position at this time need to be firstly combined into the departure feature vector at this time.
S405, forming a historical navigation feature vector set by the longitude value, the latitude value and the historical departure time point of the departure position in the historical navigation data.
In the embodiment of the present invention, steps S404 and S405 are not consecutive, a historical feature vector set may be formed in advance, and the starting feature vector of this time is formed when navigation is started; the starting feature vector and the historical navigation feature vector set can be formed sequentially when navigation is started, or the starting feature vector and the historical navigation feature vector set can be formed simultaneously.
And S406, calculating the Euclidean distance between the starting feature vector and each historical navigation feature vector in the historical navigation feature vector set.
S407, selecting historical navigation data corresponding to the historical navigation feature vector with the minimum Euclidean distance as reference historical navigation data.
In the embodiment of the invention, when the current end point position is estimated, historical navigation data can be used as a historical navigation feature vector set, and the current starting data is classified and calculated, so that the current end point position is obtained. In particular, a K-nearest neighbor algorithm may be used for the classification calculation. For example, the euclidean distance between the current departure feature vector and each historical navigation feature vector is calculated, and when K is 1, the historical navigation data corresponding to the historical navigation feature vector with the smallest euclidean distance is obtained, that is, the reference historical data for the user to obtain the current end point position. Of course, different values of K may be selected according to different situations. In addition, in the embodiment of the present invention, a decision tree algorithm or a neural network algorithm, etc. may also be used for the classification calculation.
And S408, acquiring the end point position in the reference historical data as the estimated current end point position of the user.
And after the reference historical data is determined, acquiring the end point position in the reference historical data as the estimated end point position of the travel route.
In the embodiment of the present invention, after the starting point position (default is the starting position of the user this time) and the estimated end point position of the user this time are obtained, the estimated end point position of the user this time may be sent to the user side. If the confirmation information of the user side is received, planning a navigation route from the starting position to the destination position, and performing automatic navigation; and if a new end position input by the user terminal is received, planning a navigation route from the starting position to the new end position.
And S409, planning a navigation route from the starting position to the final position.
After the starting point position (default is the starting position of the user) and the ending point position of the user are obtained, the navigation route is planned according to the existing navigation algorithm by combining the current real-time road condition information, and automatic navigation is carried out.
According to the navigation method provided by the embodiment of the invention, the historical navigation data is used as the historical navigation feature vector set for modeling, the new navigation data input by the user is used as the learning object, and the model parameters are continuously adjusted, so that the classification and identification are more accurate; during navigation, the longitude value, the latitude value and the departure time point of the departure position of the user are obtained, classification calculation is carried out by combining historical navigation data, the end point position of the user on the trip is estimated in real time, and a navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
Example four
FIG. 5 is a schematic structural diagram of a navigation device according to an embodiment of the present invention, which can be used to execute the method steps shown in FIG. 2. As shown in fig. 5, the apparatus may include: a data acquisition module 51, a prediction module 52 and a route planning module 53.
The data obtaining module 51 is configured to obtain current departure data and historical navigation data of a user, where the current departure data at least includes a current departure position of the user, and the historical navigation data at least includes a historical departure position and a historical destination position of the user; the estimation module 52 is configured to estimate the current destination position of the user according to the current departure data and the historical navigation data of the user; the route planning module 53 is configured to plan a navigation route from the current departure location to the current destination location.
In the embodiment of the present invention, when the user starts the navigation function, the data obtaining module 51 obtains the current departure position of the user in real time, and the estimating module 52 estimates the end point position of the current trip of the user in real time by combining the historical navigation data. After the starting position (default is the current starting position of the user) and the ending position are obtained, the route planning module 53 plans the navigation route from the current starting position to the current ending position according to the existing navigation algorithm by combining the current real-time road condition information, and performs automatic navigation. When the estimation module 52 estimates the current end point position, a prompt box can be popped up, and the user confirms whether to navigate to XXXX or not, for example; the dialog box may be cancelled after a countdown (e.g., 3 seconds) to automatically enter the navigation mode to avoid impacting the user.
According to the navigation device provided by the embodiment of the invention, the terminal position of the trip of the user is estimated in real time by acquiring the starting data of the user and combining with the historical navigation data, and the navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
EXAMPLE five
Fig. 6 is a schematic structural diagram of another embodiment of a navigation device provided by the present invention, which can be used for executing the method steps shown in fig. 3 and fig. 4. As shown in fig. 6, on the basis of the embodiment shown in fig. 5, the estimation module 52 may be further configured to use historical navigation data as a historical navigation feature vector set, perform classification calculation on the current departure data, and obtain the current end point position.
Specifically, the estimation module 52 may perform classification calculation by using a K-nearest neighbor algorithm, and may also perform classification calculation by using a decision tree algorithm or a neural network algorithm.
When the K-nearest neighbor algorithm is used for the classification calculation, the estimation module 52 may include: a first acquisition unit 521, a first processing unit 522, a second processing unit 523, a calculation unit 524, a selection unit 525, and a second acquisition unit 526.
The first obtaining unit 521 is configured to obtain a longitude value and a latitude value of the starting position in the starting data; the first processing unit 522 is configured to combine the longitude value and the latitude value in the current departure data into a current departure feature vector; the second processing unit 523 is configured to combine the longitude value and the latitude value of the departure position in the historical navigation data into a historical navigation feature vector set; the calculating unit 524 is configured to calculate an euclidean distance between the current departure feature vector and each historical navigation feature vector in the historical navigation feature vector set; the selecting unit 525 is configured to select historical navigation data corresponding to the historical navigation feature vector with the minimum euclidean distance as reference historical navigation data; the second obtaining unit 526 is configured to obtain an end point position in the reference historical navigation data as an estimated user end point position this time.
In the embodiment of the present invention, the first obtaining unit 521 obtains the longitude value and the latitude value of the departure position in the departure data this time, and the first processing unit 522 combines the longitude value and the latitude value of the departure of the user this time into the departure feature vector this time. The second processing unit 523 composes the longitude value and the latitude value of the departure position in the historical navigation data into a historical navigation feature vector set. The processing order of the first processing unit 522 and the second processing unit 523 is not sequential. The calculating unit 524 calculates the euclidean distance between the current departure feature vector formed by the first processing unit 522 and each historical navigation feature vector formed by the second processing unit 523, and obtains the historical navigation data corresponding to the historical navigation feature vector with the smallest euclidean distance, that is, the reference historical data of the destination position acquired by the user, when K is 1. Therefore, the selecting unit 525 selects the historical navigation data corresponding to the historical navigation feature vector with the minimum euclidean distance as the reference historical data; the second obtaining unit 526 obtains the end point position in the reference history navigation data as the estimated user current end point position. Of course, different values of K may be selected according to different situations.
Further, in the embodiment of the present invention, the current departure data may further include a current departure time point, and the historical navigation data may further include a historical departure time point of the user. Prediction module 52 may further include: a third acquiring unit 527, a third processing unit 528 and a fourth processing unit 529.
The third obtaining unit 527 is configured to obtain a longitude value, a latitude value, and a departure time point of the departure position in the departure data of this time; the third processing unit 528 is configured to combine the longitude value and the latitude value in the current departure data and the current departure time point into a current departure feature vector; the fourth processing unit 529 is configured to combine the longitude value, the latitude value, and the historical departure time point of the departure position in the historical navigation data into a historical navigation feature vector set.
In the embodiment of the present invention, the present departure data that can be used may include the present departure time point in addition to the present departure position. And classification calculation is carried out through three dimensions of the longitude value, the latitude value and the time point, so that the classification result is more accurate. Therefore, the third acquiring unit 527 needs to acquire the longitude value, the latitude value, and the departure time point of the departure position in the departure data of this time. The third processing unit 528 composes the longitude value, the latitude value and the time value in the present departure data into the present departure feature vector, and the fourth processing unit 529 composes the longitude value, the latitude value and the historical departure time point in the historical navigation data into the historical navigation feature vector set. The processing order of the third processing unit 528 and the fourth processing unit 529 is not sequential. The calculating unit 524 calculates the euclidean distance between the current departure feature vector formed by the third processing unit 528 and each historical navigation feature vector formed by the fourth processing unit 529, and obtains the historical navigation data corresponding to the historical navigation feature vector with the smallest euclidean distance, that is, the reference historical data of the destination position obtained by the user, when K is 1.
In addition, the navigation device provided by the embodiment of the present invention may further include: a statistics module 61 and a triggering module 62.
Wherein, the statistical module 61 is used for counting the historical navigation times of the user; the triggering module 62 is configured to trigger the estimating module 52 to perform an operation of estimating the current end point position of the user according to the current departure data and the historical navigation data of the user when the historical navigation frequency is greater than the preset frequency threshold.
In the embodiment of the invention, a preset time threshold value can be set firstly, and only when the historical data of the user exceeds the preset time threshold value, the stored historical navigation data can be used for the system to learn, the system has the automatic navigation condition, and the automatic navigation mode is started. Therefore, it is necessary to collect historical data of each navigation of the user, and the historical navigation data may include, but is not limited to, a starting point position (longitude value and latitude value), a historical starting time point, an end point position (longitude value and latitude value), and the like of the user's navigation. When the historical navigation times counted by the counting module 61 is greater than a preset time threshold (for example, the preset time threshold may be set to 10 times), the triggering module 62 triggers the pre-estimation module 52 to start the automatic navigation mode, and perform the subsequent operations.
Furthermore, the navigation device provided by the embodiment of the present invention may further include: a sending module 63, where the sending module 63 may be configured to send the estimated current end point position of the user to the user side.
When receiving the confirmation information of the user terminal, the route planning module 53 performs an operation of planning a navigation route from the current departure position to the current destination position; when a new end position input by the user terminal is received, the route planning module 53 plans a navigation route from the current departure position to the new end position.
The navigation device provided by the embodiment of the invention models by taking historical navigation data as a historical navigation feature vector set, uses new navigation data input of a user as a learning object, and continuously adjusts model parameters, so that the classification and identification are more accurate; during navigation, the longitude value, the latitude value and the departure time point of the departure position of the user are obtained, classification calculation is carried out by combining historical navigation data, the end point position of the user on the trip is estimated in real time, and a navigation route is automatically planned, so that more intelligent and convenient navigation is automatically provided for the user, and especially under a specific scene, the user experience is improved.
EXAMPLE six
The internal functions and structure of the navigation apparatus, which can be implemented as an electronic device, are described above. Fig. 7 is a schematic structural diagram of an embodiment of an electronic device provided in the present invention. As shown in fig. 7, the electronic device includes a memory 71 and a processor 72.
The memory 71 stores programs. In addition to the above-described programs, the memory 71 may also be configured to store other various data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on the electronic device, contact data, phonebook data, messages, pictures, videos, and so forth.
The memory 71 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
A processor 72, coupled to the memory 71, that executes programs stored by the memory 71 to:
obtaining the starting data and historical navigation data of a user, wherein the starting data at this time at least comprises the starting position of the user at this time, and the historical navigation data at least comprises the historical starting position and the historical terminal position of the user;
estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user;
and planning a navigation route from the starting position to the ending position.
Further, as shown in fig. 7, the electronic device may further include: communication components 73, power components 74, audio components 75, a display 76, and the like. Only some of the components are schematically shown in fig. 7, and the electronic device is not meant to include only the components shown in fig. 7.
The communication component 73 is configured to facilitate wired or wireless communication between the electronic device and other devices. The electronic device may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 73 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 73 further includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
A power supply component 74 provides power to the various components of the electronic device. The power components 74 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for an electronic device.
The audio component 75 is configured to output and/or input audio signals. For example, the audio component 75 includes a Microphone (MIC) configured to receive external audio signals when the electronic device is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in a memory 71 or transmitted via a communication component 73. In some embodiments, audio assembly 75 also includes a speaker for outputting audio signals.
The display 76 includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (11)
1. A navigation method, comprising:
the method comprises the steps of obtaining starting data and historical navigation data of a user, wherein the starting data at this time at least comprises a starting position at this time of the user, and the historical navigation data at least comprises a historical starting position and a historical terminal position of the user;
estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user;
and planning a navigation route from the starting position to the ending position.
2. The navigation method according to claim 1, wherein the estimating the current end point position of the user according to the current departure data and the historical navigation data of the user comprises:
obtaining a longitude value and a latitude value of the starting position in the starting data;
forming the longitude value and the latitude value in the starting data into a starting feature vector;
forming a historical navigation feature vector set by the longitude value and the latitude value of the starting position in the historical navigation data;
calculating Euclidean distances between the starting feature vector and each historical navigation feature vector in the historical navigation feature vector set;
selecting historical navigation data corresponding to the historical navigation feature vector with the minimum Euclidean distance as reference historical navigation data;
and acquiring the end point position in the reference historical navigation data as the estimated current end point position of the user.
3. The navigation method according to claim 1, wherein the current departure data further includes a current departure time point, the historical navigation data further includes a historical departure time point of the user, and estimating the current destination position of the user based on the current departure data and the historical navigation data of the user includes:
obtaining a longitude value, a latitude value and a departure time point of the departure position in the departure data;
forming the longitude value, the latitude value and the departure time point in the departure data into a departure characteristic vector;
forming a historical navigation feature vector set by the longitude value, the latitude value and the historical departure time point of the departure position in the historical navigation data;
calculating Euclidean distances between the starting feature vector and each historical navigation feature vector in the historical navigation feature vector set;
selecting historical navigation data corresponding to the historical navigation feature vector with the minimum Euclidean distance as reference historical navigation data;
and acquiring the end point position in the reference historical navigation data as the estimated current end point position of the user.
4. The navigation method according to any one of claims 1 to 3, further comprising, before estimating the current end position of the user based on the current departure data and the historical navigation data of the user:
counting the historical navigation times of the user;
and when the historical navigation times are larger than a preset time threshold value, the step of estimating the current end point position of the user according to the current starting data and the historical navigation data of the user is executed.
5. The navigation method according to any one of claims 1 to 3, further comprising, before the planning of the navigation route from the present departure position to the present destination position:
sending the estimated current end point position of the user to a user side;
when receiving the confirmation information of the user terminal, executing the step of planning the navigation route from the starting position to the destination position;
and when a new terminal position input by the user terminal is received, planning a navigation route from the starting position to the new terminal position.
6. A navigation device, comprising:
the data acquisition module is used for acquiring the starting data and the historical navigation data of the user, wherein the starting data at this time at least comprises the starting position of the user at this time, and the historical navigation data at least comprises the historical starting position and the historical terminal position of the user;
the estimating module is used for estimating the current end point position of the user according to the current starting data and the historical navigation data of the user;
and the route planning module is used for planning a navigation route from the starting position to the ending position.
7. The navigation device of claim 6, wherein the prediction module comprises:
a first obtaining unit, configured to obtain a longitude value and a latitude value of the starting position in the starting data;
the first processing unit is used for forming the longitude value and the latitude value in the starting data into a starting feature vector;
the second processing unit is used for forming a historical navigation feature vector set by the longitude value and the latitude value of the starting position in the historical navigation data;
the calculation unit is used for calculating Euclidean distances between the starting feature vector and each historical navigation feature vector in the historical navigation feature vector set;
the selection unit is used for selecting historical navigation data corresponding to the historical navigation feature vector with the minimum Euclidean distance as reference historical navigation data;
and the second acquisition unit is used for acquiring the end point position in the reference historical navigation data as the estimated current end point position of the user.
8. The navigation device of claim 7, wherein the current departure data further includes a current departure time point, the historical navigation data further includes a historical departure time point of the user, and the estimation module further includes:
a third obtaining unit, configured to obtain a longitude value, a latitude value, and a departure time point of the departure position in the departure data;
the third processing unit is used for forming the longitude value, the latitude value and the departure time point in the departure data into a departure characteristic vector;
and the fourth processing unit is used for forming a historical navigation feature vector set by the longitude value, the latitude value and the historical departure time point of the departure position in the historical navigation data.
9. The navigation device according to any one of claims 6 to 8, further comprising:
the statistical module is used for counting the historical navigation times of the user;
and the triggering module is used for triggering the estimating module to execute the operation of estimating the current end point position of the user according to the current starting data and the historical navigation data of the user when the historical navigation times are larger than a preset time threshold value.
10. The navigation device according to any one of claims 6 to 8, further comprising:
the sending module is used for sending the estimated current end point position of the user to a user side;
the route planning module is used for executing the operation of planning the navigation route from the starting position to the destination position when receiving the confirmation information of the user side; and when a new terminal position input by a user terminal is received, planning a navigation route from the starting position to the new terminal position.
11. An electronic device, comprising:
a memory for storing a program;
a processor for executing the program stored in the memory for:
the method comprises the steps of obtaining starting data and historical navigation data of a user, wherein the starting data at this time at least comprises a starting position at this time of the user, and the historical navigation data at least comprises a historical starting position and a historical terminal position of the user;
estimating the current terminal position of the user according to the current starting data and the historical navigation data of the user;
and planning a navigation route from the starting position to the ending position.
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