CN111382370B - Line recommendation method, device, vehicle-mounted equipment and storage medium - Google Patents
Line recommendation method, device, vehicle-mounted equipment and storage medium Download PDFInfo
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- CN111382370B CN111382370B CN201811642967.4A CN201811642967A CN111382370B CN 111382370 B CN111382370 B CN 111382370B CN 201811642967 A CN201811642967 A CN 201811642967A CN 111382370 B CN111382370 B CN 111382370B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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Abstract
The application relates to a line recommendation method, a line recommendation device, vehicle-mounted equipment and a storage medium, wherein a prediction destination is determined according to current position information and current time information; determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value; when the starting point information and the current position information of the acquaintance road do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track; supplementing the target acquaintance path track according to the current position information to obtain a supplementing track; and determining a recommended line according to the target acquaintance path and the complement path. Therefore, the driving time can be reduced, and the navigation efficiency can be improved.
Description
Technical Field
The present disclosure relates to the field of navigation technologies, and in particular, to a method and apparatus for recommending a route, a vehicle-mounted device, and a storage medium.
Background
The navigation technology is a technology for realizing the positioning of a moving body and guiding the moving body to a destination safely, accurately and economically along a preset route from a departure point by measuring parameters related to the position of the moving body at any moment by utilizing scientific principles and methods such as electricity, magnetism, light, mechanics and the like, and measuring parameters related to the position of the moving body at any moment such as an air plane, a marine ship, a submarine in the ocean, a vehicle on the land, a people stream and the like.
In the conventional route recommendation method, after receiving the starting place and the destination by the way of inputting the instruction by the user, the route recommendation is performed according to the estimated time information and the cost information, and the user may need to bypass a large section of route to reach the destination once missing an intersection because the route user for navigation recommendation may not be familiar, so that the conventional route recommendation method has low navigation efficiency.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a route recommendation method, apparatus, in-vehicle device, and storage medium with high navigation efficiency.
A line recommendation method, the method comprising:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
Supplementing the target acquaintance path according to the current position information to obtain a supplementing path;
and determining a recommended line according to the target acquaintance path and the complement path.
In one embodiment, the determining a recommended route according to the target acquaintance track and the complement track includes:
searching current traffic condition information of the target acquaintance road track;
and when the current traffic condition information of the target acquaintance road track meets a preset condition, determining a recommended line according to the target acquaintance road track and the complement track.
In one embodiment, after determining the preset acquaintance track in the target acquaintance track group as the target acquaintance track when the starting point information of the acquaintance track and the current location information do not belong to the same road section, the method further includes:
and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
Filtering the acquaintance path tracks in the target acquaintance path group according to the current time information to obtain a acquaintance path track to be selected;
and determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
determining similarity of the acquaintance path tracks in the target acquaintance path group in pairs;
determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road;
determining a score value of the acquaintance path track in the acquaintance path according to the similarity;
and sorting the acquaintance path tracks according to the score value and the track times, and determining the first sort acquaintance path track as a target acquaintance path.
In one embodiment, after determining the recommended route according to the target acquaintance track and the complement track, the method further includes:
and before the vehicle runs, carrying out navigation prompt according to the recommended route.
In one embodiment, the determining the target acquaintance group according to the current location information and the predicted destination includes:
Determining a first range and a second range according to the current position information and the predicted destination respectively;
and determining the acquaintance road groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance road groups.
A line recommendation device, comprising:
the destination prediction module is used for determining a predicted destination according to the current position information and the current time information;
the system comprises a acquaintance road group determining module, a prediction destination determining module and a prediction destination determining module, wherein the acquaintance road group determining module is used for determining a target acquaintance road group according to the current position information and the prediction destination, the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road group comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
the system comprises a acquaintance path determining module, a target acquaintance path determining module and a target acquaintance path determining module, wherein the acquaintance path determining module is used for determining a preset acquaintance path in the target acquaintance path group as a target acquaintance path when the starting point information of the acquaintance path and the current position information do not belong to the same road section;
the acquaintance path track complement module is used for complementing the target acquaintance path track according to the current position information to obtain a complement track;
and the recommended line determining module is used for determining a recommended line according to the target acquaintance path and the complement path.
An in-vehicle apparatus comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
supplementing the target acquaintance path according to the current position information to obtain a supplementing path;
and determining a recommended line according to the target acquaintance path and the complement path.
A readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
When the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
supplementing the target acquaintance path according to the current position information to obtain a supplementing path;
and determining a recommended line according to the target acquaintance path and the complement path.
Based on the line recommendation method, the line recommendation device, the vehicle-mounted equipment and the storage medium of the embodiment, a prediction destination is determined according to the current position information and the current time information; determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value; when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track; supplementing the target acquaintance path according to the current position information to obtain a supplementing path; and determining a recommended line according to the target acquaintance path and the complement path. After the predicted destination is determined, a target acquaintance road group is determined according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks. In this way, on the one hand, the probability of a user driving by navigation is reduced, and on the other hand, for the same road, a familiar user can often take less time to reach the destination than an unfamiliar user. Therefore, the driving time can be reduced, and the navigation efficiency can be improved.
It should be noted that, because the current position information and the current time information can be automatically obtained without inputting an instruction by the user, and the predicted destination is determined according to the current position information and the current time information, without inputting an instruction by the user, the time spent by the user can be further reduced, and the navigation efficiency is further improved.
Drawings
FIG. 1 is an application environment diagram of a circuit recommendation method in one embodiment;
FIG. 2 is a flow diagram of a circuit recommendation method according to one embodiment;
FIG. 3 is a flowchart illustrating a circuit recommendation method according to an embodiment;
FIG. 4 is a block diagram of a circuit recommender in accordance with one embodiment;
fig. 5 is a block diagram showing the structure of the in-vehicle apparatus in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
FIG. 1 is an application environment diagram of a circuit recommendation method in one embodiment. The line recommendation method provided by the application can be applied to an application environment shown in fig. 1, and the line recommendation method provided by the application can be applied to a line recommendation system. The line recommendation system includes a terminal 102, a server 104, and a third party server 106. The terminal 102 is connected to the server 104 and the third party server 106 via network communication. The server 104 gathers information on each travel track on the terminal 102 and determines the user's acquaintance road groups. The terminal 102 determines a prediction destination according to the current position information and the current time information; determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value; when the starting point information and the current position information of the acquaintance road do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track; supplementing the target acquaintance path track according to the current position information to obtain a supplementing track; and determining a recommended line according to the target acquaintance path and the complement path. When determining the recommended route according to the target acquaintance track and the complement track, the terminal 102 may first obtain corresponding current traffic condition information from the third server 103 according to the target acquaintance track, and determine the recommended route according to the target acquaintance track and the complement track when the current traffic condition information meets a preset condition. The terminal 102 may be, but is not limited to, a personal computer, a notebook computer, a smart phone, a tablet computer, and a portable wearable device. The server 104 and the third party server 106 may be implemented as separate servers or as a server cluster comprising a plurality of servers.
As shown in fig. 2, in one embodiment, a line recommendation method is provided. The present embodiment is mainly illustrated by the application of the method to the terminal 102 in fig. 1. The line recommendation method comprises the following steps:
s202, determining a prediction destination according to the current position information and the current time information.
The terminal may be a vehicle-mounted device or an intelligent device having a navigation function. The current position information and the current time information are automatically acquired after the terminal is started, and the user does not need to send an acquired instruction. For example, the vehicle-mounted device may be turned on after the ignition of the vehicle is started, and the position information and the time information after the vehicle-mounted device is turned on are obtained and used as the current position information and the current time information. For another example, the intelligent terminal may acquire the current geographic location information and time information as the current location information and time information when the navigation function is turned on.
The location information may be that the map is divided into different area modules according to a preset manner, for example, a square area with a width of every 500 meters is used as an area, and for example, the area division may be performed according to two or more roads. Different areas can be distinguished by area identification, which can be area number, area name. The location information may further include latitude and longitude information, and a location name of the predicted destination may be further determined according to the latitude and longitude information of the predicted destination.
The corresponding prediction destination can be searched locally according to the current position information and the current time information. The predicted destination can be requested from the server according to the current position information, the current time information and the user identification, and the request result returned by the server is received, so that the predicted destination is obtained. The user identifier is an identifier that performs unique identification on the user, for example, the user identifier may be a user ID, and the user ID may be an identity identifier, an account number, a unique code, and the like. The user identification may be acquired after the vehicle-mounted device is started.
The predicted destination may be a constant standing point corresponding to the current time information, the constant standing point is a place where the vehicle often stays, and the place where the frequent stay is a place where the stay times is greater than a preset value and the stay time of each time is greater than the preset time. The vehicle is a vehicle to which the in-vehicle apparatus belongs.
S204, determining a target acquaintance road group according to the current position information and the prediction destination. The target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks.
The target acquaintance road group may be a combination of lines satisfying the acquaintance road condition, i.e., a combination of acquaintance roads. The acquaintance road condition may be a combination of lines whose number of trajectories is greater than a preset value. That is, the acquaintance road is a line with the track number greater than a preset value, that is, the track number corresponding to the acquaintance road is greater than the preset value. The tracks with the similarity larger than the similarity threshold value can be used as the tracks of the same line, namely the tracks similar to the same line. For example, tracks with similarity greater than a threshold value can be used as tracks of the same line. For another example, the tracks with the number of similarity greater than the similarity threshold value between every two tracks not less than the preset number may be used as the tracks of the same line. The preset number can be 2/3, 3/4, 4/5, etc. of the total number of tracks in the same line. Thus, the acquaintance road includes not less than the preset number of acquaintance road trajectories. Because the acquaintance road group comprises at least one acquaintance road, the acquaintance road group also comprises not less than the preset number of acquaintance road tracks.
The acquaintance trail may be represented by a GPS (Global Positioning System ) point sequence or by a road segment sequence. The start point information and the end point information may include area identification.
The target acquaintance road group is an acquaintance road group with the start point information and the end point information respectively corresponding to the current position information and the prediction destination. For example, the set of acquaintances may be set in which the start point and the current position are within a first predetermined distance, and the end point and the predicted destination are within a second predetermined distance. For another example, the set of acquaintance roads may be set in which the area distance between the start point information and the current position information is within a third preset distance and the area distance between the end point information and the prediction destination is within a fourth preset distance. For another example, the similarity between the start point information and the end point information, the current position information, and the prediction destination may be set to a acquaintance road group satisfying the target acquaintance road condition. The target acquaintance road condition can be that the similarity between the starting point information and the end point information and the current position information and the predicted destination respectively is not smaller than a preset value.
The target acquaintance road group can be found locally according to the current position information and the predicted destination. And the target acquaintance road group can be requested to the server according to the current position information, the predicted destination and the user identification, and a request result returned by the server is received, so that the target acquaintance road group is obtained.
S206, when the starting point information and the current position information of the acquaintance road do not belong to the same road section, determining the preset acquaintance road track in the target acquaintance road group as the target acquaintance road track.
When the starting point information of the acquaintance road and the current position information belong to different road sections, the current position is far from the starting point position of the acquaintance road, and the preset acquaintance road track in the target acquaintance road group can be determined to be a recommended line.
A road segment may be the smallest unit of storage for a road. For example, a path with a length of a preset value may be provided. Road segment also refers to a road between two intersections, which refers to the junction of at least two roads. The road segments may be represented by links, which may include road ids (which may be represented by LinkId), lengths (which may be represented by length), speed limits (which may be represented by speed limit), and GPS sequence points, which may be represented by an array.
The preset acquaintance path track may be a acquaintance path track obtained by screening the acquaintance path tracks in the target acquaintance path group. For example, the preset acquaintance path tracks may be random or ordered according to a preset rule, the acquaintance path track arranged in the preset position before may be used as the target acquaintance path, and further, the recommended line may be determined according to the target acquaintance path. For another example, similarity is determined for the acquaintance road tracks in the target acquaintance road group in pairs; determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road; determining a score value of the acquaintance path track in the acquaintance path according to the similarity; and sorting the acquaintance road tracks according to the score value and the track times, and determining the first acquaintance road track as a preset acquaintance road track.
S208, complementing the target acquaintance path track according to the current position information to obtain an complementing path.
When the starting point information of the acquaintance road and the current position information belong to different road sections, the current position is far away from the starting point position of the acquaintance road, so that the target acquaintance road track needs to be complemented.
The supplementing method may be to determine the supplementing track based on the supplementing start point and the supplementing end point by using the position point of the current position information as the supplementing start point and the most recently navigated position in the target acquaintance track as the supplementing end point. The method may further include determining a complement track based on the complement start point and the complement end point by using the position point of the current position information as the complement start point and a preset point in the target acquaintance track as the complement end point. The preset point may be an sink point of a main trunk closest to the current position in the target acquaintance path. The main road can be a lane above a preset number of lanes, such as four lanes and more than six lanes. The main trunk road can also be a pre-marked lane, and whether the main trunk road is the main trunk road can be marked by a preset mark.
S210, determining a recommended line according to the target acquaintance path and the complement path.
The recommended route can be determined by extracting starting point information, end point information, and intermediate GPS sequence points or sequences of intermediate road sections according to the target acquaintance track and the complement track. The recommendation line is used for application scenes such as navigation, recommendation to friends, automatic driving and the like.
When the starting point information and the current position information of the acquaintance road belong to the same road section, a preset acquaintance road track in the target acquaintance road group can be determined as a target acquaintance road track, and then a recommended line is determined according to the target acquaintance road track.
Based on the line recommendation method of the embodiment, a prediction destination is determined according to the current position information and the current time information; determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value; when the starting point information and the current position information of the acquaintance road do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track; supplementing the target acquaintance path track according to the current position information to obtain a supplementing track; and determining a recommended line according to the target acquaintance path and the complement path. After the predicted destination is determined, a target acquaintance road group is determined according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks. In this way, on the one hand, the probability of a user driving by navigation is reduced, and on the other hand, for the same road, a familiar user can often take less time to reach the destination than an unfamiliar user. Therefore, the driving time can be reduced, and the navigation efficiency can be improved.
It should be noted that, because the current position information and the current time information can be automatically obtained without inputting an instruction by the user, and the predicted destination is determined according to the current position information and the current time information, without inputting an instruction by the user, the time spent by the user can be further reduced, and the navigation efficiency is further improved.
In one embodiment, after determining the recommended route according to the target acquaintance track and the complement track, the method further includes: before the vehicle runs, navigation prompt is carried out according to the recommended route. After receiving the vehicle start signal, navigation prompt can be performed according to the recommended route before the vehicle runs. For example, the navigation prompt may be performed according to a recommended route before the vehicle steering wheel rotation signal is received. Therefore, the vehicle is ensured not to be prompted when the vehicle runs, and the danger of distraction operation of the user during running is avoided. The navigation prompt can be in the form of voice broadcasting or in the form of displaying recommended navigation lines on a screen.
In one embodiment, in order to ensure navigation efficiency, determining a recommended route according to a target acquaintance route and a complement route includes: searching current traffic condition information of the target acquaintance road track; and when the current traffic condition information of the target acquaintance road track meets the preset condition, determining a recommended line according to the target acquaintance road track and the complement track.
The preset condition may be that no traffic accident or/and congestion condition of a preset level exists in the current traffic condition information of the target acquaintance path. The preset condition may be that the total length of the congestion status road section of the preset level is smaller than a preset value in the current traffic status information of the target acquaintance road track. For example, the total length of the highest level of congestion status road segments is less than 1/4, 1/5, etc. of the total navigation length, or less than 500 meters, 1000 meters, etc. The preset condition may be that the duration of the target acquaintance track is not greater than the sum of the shortest required length of other routes and a preset value, where the other routes are navigation routes determined according to the current location information and the predicted destination. The duration of the target acquaintance road track may be the duration of the target acquaintance road track when running, or may be the predicted running duration when the target acquaintance road track is used as the current running route.
The current traffic condition information of the target acquaintance road track can be searched in a local searching mode by downloading the traffic condition information to the local in advance. The current traffic condition information of the target acquaintance road track can also be searched by sending a search request to a third party server and returning a search result according to the search request. The third party server is a server of a third party service, which may be TMC (Traffic Message Channel, traffic information channel). For example, the search request may be sent to the third party server at intervals of a preset time, so that the traffic status information is downloaded to the local at intervals of the preset time. The preset time may be 1 minute, 2 minutes, etc.
When the current traffic condition information of the target acquaintance road track meets the preset condition, the current traffic condition information of the target acquaintance road track is better. According to the wire line recommending method, the recommended line is determined according to the target acquaintance line track and the complement track only when the current traffic condition of the target acquaintance line track meets the preset condition, so that the situation that the target acquaintance line track is still collected as most of the recommended line when the current traffic condition of the target acquaintance line track is poor is avoided, and the navigation efficiency is guaranteed.
In one embodiment, in order to further ensure the navigation efficiency, when the starting point information of the acquaintance road and the current location information do not belong to the same road section, after determining the preset acquaintance road track in the target acquaintance road group as the target acquaintance road track, the method further includes: and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
When the current traffic condition information of the target acquaintance road track does not meet the preset condition, the current traffic condition information of the target acquaintance road track is poor. In this case, in order to ensure the navigation efficiency, the target travel route may be avoided, the route recommendation may be performed using the position corresponding to the current position information as a start point and the prediction destination as an end point, and at least one navigation route may be determined.
Based on the wire line recommendation method of the embodiment, when the current traffic condition of the target acquaintance path does not meet the preset condition, at least one recommended line is determined according to the current position information and the predicted destination. Therefore, the recommended route determined based on the target acquaintance route track is prevented from taking a long time, and therefore the navigation efficiency is further ensured.
In one embodiment, determining the preset acquaintance path track in the target acquaintance path group as the target acquaintance path track includes: according to the current time information, filtering the acquaintance path tracks in the target acquaintance path group to obtain a acquaintance path track to be selected; and determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track.
In this embodiment, before determining the preset acquaintance path in the target acquaintance path group as the target acquaintance path, the acquaintance path in the target acquaintance path group is filtered according to the current time information. And filtering out the acquaintance path tracks with time deviation larger than a preset value to obtain the acquaintance path track to be selected. And then determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track. Therefore, the acquaintance path with large deviation from the current time information can be filtered in advance, and the accuracy of line recommendation is improved.
As shown in fig. 3, in one embodiment, determining a preset acquaintance trail in the target acquaintance trail set as the target acquaintance trail includes:
s302, determining similarity of the acquaintance path tracks in the target acquaintance path group in pairs;
s304, determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road;
s306, determining the score value of the acquaintance path in the acquaintance path according to the similarity;
s308, sorting the acquaintance path tracks according to the score value and the track times, and determining the first acquaintance path as a target acquaintance path. That is, the preset acquaintance trail is the first acquaintance trail of the order.
The tracks with the similarity larger than the similarity threshold value are taken as the tracks of the same line. It should be noted that the number of times of the track corresponding to each of the acquaintance roads in the acquaintance road group is greater than a preset value. In this embodiment, after determining the same acquaintance road, the number of tracks corresponding to the acquaintance road is extracted. The determining of the score value of the acquaintance path in the acquaintance path according to the similarity may be determining the relative similarity of each second acquaintance path with respect to each first acquaintance path in one acquaintance path. Summing the relative similarity of the first acquaintance tracks to obtain a summation result. The first acquaintance path is a acquaintance path based on which the similarity is determined, and the second acquaintance path is a acquaintance path belonging to the same acquaintance path as the first acquaintance path, and may include the first acquaintance path. The similarity of the acquaintance path with respect to the self may be 100, wherein the value range of the similarity may be 0 to 100. A score value for the first acquaintance track may be determined based on the summation result. For example, the sum result may be divided by the number of tracks of the second acquaintance, that is, the number of tracks corresponding to the acquaintance, and the obtained result is used as a score value. As another example, the summation result may be taken as a score value.
The track number is the number of the acquaintance tracks when the number of the acquaintance tracks larger than the similarity threshold is maximum in one acquaintance track with reference to any one acquaintance track. When sorting, sorting can be performed according to the value of the score, the higher the score is, the more the score is, and then sorting is performed according to the track times, namely when the scores are the same, the track times are arranged in the front. Because the track number corresponding to each acquaintance road in the acquaintance road group is larger than a preset value and is a familiar line, more reasonable target acquaintance road tracks can be determined according to the score sorting. For example, assuming that four acquaintance path tracks of one acquaintance path in the target acquaintance path group are a, B, C, and D respectively, when calculating the score of the acquaintance path track a, the similarity between B, C, D, and a is obtained, if the similarity percentage is 90%,80%, and 70%, the calculation formula is: (100+90+80+70)/4=85, where the similarity threshold is 60% and the number of tracks is 4. When the score of B is calculated, the similarity of A, C, D is obtained respectively, and if the percentages are respectively 90%,90% and 90%, the calculation formula is as follows: (100+90+90)/4=97.5, wherein the similarity threshold is 60% and the number of tracks is 4. Track B is arranged in front of track a. In other embodiments, the number of tracks may also be ordered by ranking the number of tracks, with the number of tracks being ranked higher the higher. It is also possible to order according to navigation time, the shorter the time the earlier.
In this embodiment, a navigation route is recommended with the first-ordered route track as the target acquaintance track. Thus, for familiar lines, the navigation efficiency can be improved without the need for selection by a user. It will be appreciated that in other embodiments, a plurality of navigation routes may be recommended for the user to select with the target acquaintance track of the pre-set bit before the ranking.
In one embodiment, the determining the target acquaintance group according to the current location information and the predicted destination includes: determining a first range and a second range according to the current position information and the predicted destination respectively; and determining the acquaintance road groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance road groups.
The first range is a preset range corresponding to the current position information, and the second range is a preset range corresponding to the predicted destination. The preset range corresponding to the current location information may be a range within a first preset distance of the current location information, and the preset range corresponding to the predicted destination may be a range within a second preset distance corresponding to the predicted destination. The first preset distance and the second preset distance may be the same or different.
The start point information and the end point information respectively falling within the first range and the second range means that the start point corresponding to the start point information falls within the first range and the end point corresponding to the end point information falls within the second range.
Thus, a more accurate target acquaintance road group can be determined, and a more accurate recommended line can be obtained.
In one embodiment, the line recommendation method includes:
determining a prediction destination according to the current position information and the current time information;
determining a first range and a second range according to the current position information and the predicted destination respectively; determining a cooked road group in which the starting point information and the end point information respectively fall in the first range and the second range as a target cooked road group, wherein the target cooked road group comprises at least one cooked road, and the cooked road comprises the starting point information, the end point information and a cooked road track; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
according to the current time information, filtering the acquaintance path tracks in the target acquaintance path group to obtain a acquaintance path track to be selected;
when the starting point information and the current position information of the acquaintance road do not belong to the same road section, determining similarity for the acquaintance road tracks in the target acquaintance road group in pairs; determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road; determining the score value of the acquaintance path track in the acquaintance path according to the similarity; sorting the acquaintance path tracks according to the score value and the track times, and determining the first acquaintance path as a target acquaintance path;
Supplementing the target acquaintance path track according to the current position information to obtain a supplementing track;
searching current traffic condition information of the target acquaintance road track;
when the current traffic condition information of the target acquaintance road track meets the preset condition, determining a recommended line according to the target acquaintance road track and the complement track;
and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
It should be understood that, although the steps in the flowcharts of fig. 2 and 3 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2, 3 may comprise a plurality of sub-steps or phases, which are not necessarily performed at the same time, but may be performed at different times, nor does the order of execution of the sub-steps or phases necessarily follow one another, but may be performed alternately or alternately with at least a portion of the sub-steps or phases of other steps or other steps.
In one embodiment, as shown in fig. 4, a line recommending apparatus is provided, which may correspond to the above line recommending method, and includes:
a destination prediction module 402, configured to determine a predicted destination according to the current location information and the current time information;
a acquaintance road set determining module 404, configured to determine a target acquaintance road set according to the current location information and the prediction destination, where the target acquaintance road set includes at least one acquaintance road, and the acquaintance road includes start information, end information, and an acquaintance road track; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
a acquaintance track determining module 406, configured to determine a preset acquaintance track in the target acquaintance track group as a target acquaintance track when the starting point information of the acquaintance track and the current location information do not belong to the same road section;
a acquaintance track complement module 408, configured to complement the target acquaintance track according to the current location information, so as to obtain a complement track;
the recommended route determining module 410 is configured to determine a recommended route according to the target acquaintance route track and the complement track.
Based on the line recommending device of the embodiment, a prediction destination is determined according to the current position information and the current time information; determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value; when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track; supplementing the target acquaintance path according to the current position information to obtain a supplementing path; and determining a recommended line according to the target acquaintance path and the complement path. After the predicted destination is determined, a target acquaintance road group is determined according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks. In this way, on the one hand, the probability of a user driving by navigation is reduced, and on the other hand, for the same road, a familiar user can often take less time to reach the destination than an unfamiliar user. Therefore, the driving time can be reduced, and the navigation efficiency can be improved.
It should be noted that, because the current position information and the current time information can be automatically obtained without inputting an instruction by the user, and the predicted destination is determined according to the current position information and the current time information, without inputting an instruction by the user, the time spent by the user can be further reduced, and the navigation efficiency is further improved.
In one embodiment, the method further comprises: a traffic condition searching module;
the traffic condition searching module is used for searching current traffic condition information of the target acquaintance path track;
the recommended route determining module is used for determining a recommended route according to the target acquaintance route and the complement route when the current traffic condition information of the target acquaintance route meets the preset condition.
In one embodiment, the recommended route determining module is further configured to avoid the target acquaintance route when the current traffic condition information of the target acquaintance route does not meet a preset condition, and determine at least one recommended route according to the current location information and the predicted destination.
In one embodiment, the system further comprises a acquaintance filtering module; the acquaintance path filtering module is used for filtering acquaintance path tracks in the target acquaintance path group according to the current time information to obtain a acquaintance path track to be selected;
And the acquaintance path determining module is used for determining a preset acquaintance path in the acquaintance path to be selected as a target acquaintance path.
In one embodiment, the acquaintance trail determination module includes: the similarity determining unit is used for determining similarity for the acquaintance path tracks in the target acquaintance path group in pairs;
the track number determining unit is used for determining the same acquaintance road according to the similarity and the similarity threshold value and extracting track number corresponding to the acquaintance road;
a ranking score determining unit, configured to determine a score value of the acquaintance road track in the acquaintance road according to the similarity;
and the target track determining unit is used for sequencing the acquaintance track according to the score value and the track times, and determining the first acquaintance track as a target acquaintance track.
In one embodiment, the method further comprises: a range determination module;
the range determining module is used for determining a first range and a second range according to the current position information and the prediction destination respectively;
and the acquaintance path determining module is used for determining the acquaintance path groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance path groups.
In one embodiment, an in-vehicle apparatus is provided, an internal structure of which may be as shown in fig. 5. The vehicle-mounted equipment comprises a processor, a memory, a network interface, a display screen and an input device which are connected through a system bus. Wherein the processor of the in-vehicle device is configured to provide computing and control capabilities. The memory of the in-vehicle apparatus includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the vehicle-mounted device is used for communicating with an external terminal through network connection. The computer program is executed by a processor to implement a line recommendation method. The in-vehicle apparatus may be an in-vehicle terminal. The display screen of the vehicle-mounted equipment can be a liquid crystal display screen, an electronic ink display screen or a touch display screen, and the input device of the vehicle-mounted equipment can be keys arranged on the shell of the vehicle-mounted equipment, and can also be an external keyboard, a touch pad, a mouse or the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of a part of the structure related to the present application and does not constitute a limitation of the vehicle-mounted device to which the present application is applied, and that a specific vehicle-mounted device may include more or less components than those shown in the drawings, or may combine some components, or may have a different arrangement of components.
In one embodiment, an in-vehicle apparatus is provided, and an internal structure diagram of the in-vehicle apparatus may be as shown in fig. 5. The vehicle-mounted device comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the line recommendation method when executing the computer program.
For example, in one embodiment, the vehicle-mounted device includes a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the following steps:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
supplementing the target acquaintance path according to the current position information to obtain a supplementing path;
and determining a recommended line according to the target acquaintance path and the complement path.
In one embodiment, the determining a recommended route according to the target acquaintance track and the complement track includes:
searching current traffic condition information of the target acquaintance road track;
and when the current traffic condition information of the target acquaintance road track meets a preset condition, determining a recommended line according to the target acquaintance road track and the complement track.
In one embodiment, after determining the preset acquaintance track in the target acquaintance track group as the target acquaintance track when the starting point information of the acquaintance track and the current location information do not belong to the same road section, the method further includes:
and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
filtering the acquaintance path tracks in the target acquaintance path group according to the current time information to obtain a acquaintance path track to be selected;
and determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
determining similarity of the acquaintance path tracks in the target acquaintance path group in pairs;
determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road;
determining a score value of the acquaintance path track in the acquaintance path according to the similarity;
and sorting the acquaintance path tracks according to the score value and the track times, and determining the first sort acquaintance path track as a target acquaintance path.
In one embodiment, after determining the recommended route according to the target acquaintance track and the complement track, the method further includes:
and before the vehicle runs, carrying out navigation prompt according to the recommended route.
In one embodiment, the determining the target acquaintance group according to the current location information and the predicted destination includes:
determining a first range and a second range according to the current position information and the predicted destination respectively;
and determining the acquaintance road groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance road groups.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the line recommendation method described above.
For example, in one embodiment, a computer readable storage medium having a computer program stored thereon, the computer program when executed by a processor performing the steps of:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
when the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
supplementing the target acquaintance path according to the current position information to obtain a supplementing path;
and determining a recommended line according to the target acquaintance path and the complement path.
In one embodiment, the determining a recommended route according to the target acquaintance track and the complement track includes:
Searching current traffic condition information of the target acquaintance road track;
and when the current traffic condition information of the target acquaintance road track meets a preset condition, determining a recommended line according to the target acquaintance road track and the complement track.
In one embodiment, after determining the preset acquaintance track in the target acquaintance track group as the target acquaintance track when the starting point information of the acquaintance track and the current location information do not belong to the same road section, the method further includes:
and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
filtering the acquaintance path tracks in the target acquaintance path group according to the current time information to obtain a acquaintance path track to be selected;
and determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track.
In one embodiment, the determining the preset acquaintance road track in the target acquaintance road set as the target acquaintance road track includes:
Determining similarity of the acquaintance path tracks in the target acquaintance path group in pairs;
determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road;
determining a score value of the acquaintance path track in the acquaintance path according to the similarity;
and sorting the acquaintance path tracks according to the score value and the track times, and determining the first sort acquaintance path track as a target acquaintance path.
In one embodiment, after determining the recommended route according to the target acquaintance track and the complement track, the method further includes:
and before the vehicle runs, carrying out navigation prompt according to the recommended route.
In one embodiment, the determining the target acquaintance group according to the current location information and the predicted destination includes:
determining a first range and a second range according to the current position information and the predicted destination respectively;
and determining the acquaintance road groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance road groups.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. A line recommendation method, the method comprising:
determining a prediction destination according to the current position information and the current time information;
determining a target acquaintance road group according to the current position information and the predicted destination, wherein the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
When the starting point information of the acquaintance road and the current position information do not belong to the same road section, determining a preset acquaintance road track in the target acquaintance road group as a target acquaintance road track;
taking the position point of the current position information as a complement starting point, taking the most-recently navigated position in the target acquaintance path track as a complement end point, and determining a complement path according to the complement starting point and the complement end point;
determining a recommended line according to the target acquaintance path and the complement path;
the determining the preset acquaintance path track in the target acquaintance path group as the target acquaintance path includes:
determining similarity of the acquaintance path tracks in the target acquaintance path group in pairs;
determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road;
determining a score value of the acquaintance path track in the acquaintance path according to the similarity;
and sorting the acquaintance path tracks according to the score value and the track times, and determining the first sort acquaintance path track as a target acquaintance path.
2. The method of claim 1, wherein the determining a recommended route from the target acquaintance trail and the complement trail comprises:
Searching current traffic condition information of the target acquaintance road track;
and when the current traffic condition information of the target acquaintance road track meets a preset condition, determining a recommended line according to the target acquaintance road track and the complement track.
3. The method of claim 2, wherein after determining a preset acquaintance track in the target acquaintance track group as a target acquaintance track when the start information of the acquaintance track and the current location information do not belong to the same road section, further comprising:
and when the current traffic condition information of the target acquaintance path does not meet the preset condition, avoiding the target acquaintance path, and determining at least one recommended line according to the current position information and the predicted destination.
4. The method of claim 1, wherein the determining the preset acquaintance trail in the target acquaintance trail set as a target acquaintance trail further comprises:
filtering the acquaintance path tracks in the target acquaintance path group according to the current time information to obtain a acquaintance path track to be selected;
and determining a preset acquaintance path track in the acquaintance path tracks to be selected as a target acquaintance path track.
5. The method of claim 1, wherein after determining a recommended route from the target acquaintance trail and the complement trail, further comprising:
And before the vehicle runs, carrying out navigation prompt according to the recommended route.
6. The method of claim 1, wherein the determining a target acquaintance group according to the current location information and the predicted destination comprises:
determining a first range and a second range according to the current position information and the predicted destination respectively;
and determining the acquaintance road groups of which the starting point information and the end point information respectively fall in the first range and the second range as target acquaintance road groups.
7. A line recommendation device, comprising:
the destination prediction module is used for determining a predicted destination according to the current position information and the current time information;
the system comprises a acquaintance road group determining module, a prediction destination determining module and a prediction destination determining module, wherein the acquaintance road group determining module is used for determining a target acquaintance road group according to the current position information and the prediction destination, the target acquaintance road group comprises at least one acquaintance road, and the acquaintance road group comprises starting point information, end point information and acquaintance road tracks; the number of times of the tracks corresponding to the acquaintance road is larger than a preset value;
the system comprises a acquaintance path determining module, a target acquaintance path determining module and a target acquaintance path determining module, wherein the acquaintance path determining module is used for determining a preset acquaintance path in the target acquaintance path group as a target acquaintance path when the starting point information of the acquaintance path and the current position information do not belong to the same road section;
The acquaintance path supplementing module is used for taking the position point of the current position information as a supplementing starting point, taking the position which is the most recently navigated in the target acquaintance path as a supplementing end point, and determining a supplementing path according to the supplementing starting point and the supplementing end point;
the recommended line determining module is used for determining a recommended line according to the target acquaintance path and the complement path;
the acquaintance road filtering module is used for determining similarity of the acquaintance road tracks in the target acquaintance road group in pairs; determining the same acquaintance road according to the similarity and the similarity threshold value, and extracting the track times corresponding to the acquaintance road; determining a score value of the acquaintance path track in the acquaintance path according to the similarity; and sorting the acquaintance path tracks according to the score value and the track times, and determining the first sort acquaintance path track as a target acquaintance path.
8. The apparatus of claim 7, further comprising a traffic condition lookup module to: searching current traffic condition information of the target acquaintance road track; the recommended route determining module is used for determining a recommended route according to the target acquaintance route and the complement route when the current traffic condition information of the target acquaintance route meets the preset condition.
9. An in-vehicle device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 6 when the computer program is executed.
10. A readable storage medium having stored thereon a computer program, which when executed by a processor realizes the steps of the method according to any of claims 1 to 6.
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| CN116821266B (en) * | 2022-12-30 | 2024-03-29 | 北京易航远智科技有限公司 | Semantic map construction method and automatic driving system with acquaintance road mode |
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