CN110689804A - Method and apparatus for outputting information - Google Patents
Method and apparatus for outputting information Download PDFInfo
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- CN110689804A CN110689804A CN201910956672.2A CN201910956672A CN110689804A CN 110689804 A CN110689804 A CN 110689804A CN 201910956672 A CN201910956672 A CN 201910956672A CN 110689804 A CN110689804 A CN 110689804A
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- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
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- G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
- G09B29/003—Maps
- G09B29/006—Representation of non-cartographic information on maps, e.g. population distribution, wind direction, radiation levels, air and sea routes
- G09B29/007—Representation of non-cartographic information on maps, e.g. population distribution, wind direction, radiation levels, air and sea routes using computer methods
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- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
- G09B29/10—Map spot or coordinate position indicators; Map reading aids
- G09B29/106—Map spot or coordinate position indicators; Map reading aids using electronic means
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Abstract
The embodiment of the disclosure discloses a method and a device for outputting information. One embodiment of the method comprises: acquiring a track data set of a driving user; determining a parking lot boundary and a parking lot peripheral area according to the trajectory data set; clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot; determining whether the central point of the cluster is an entrance or an exit of the parking lot according to the weighted sum of the number and the distance; and if the parking lot is at the entrance, the entrance of the parking lot is marked on the map. According to the embodiment, the entrance and exit of the parking lot can be excavated according to the information of the parking point extracted from the user track, on one hand, wrong entrance and exit information of the parking lot can be effectively corrected, and on the other hand, a correct guide point for driving is provided for the parking lot without the entrance and exit information.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of electronic maps, in particular to a method and a device for outputting information.
Background
The map has a large amount of parking lot data, and a large number of driving users navigate to the parking lot every day, so that the map is very important for digging an entrance and an exit (navigation guide point) of the parking lot. If the parking lot has no corresponding entrance and exit identification, the user is difficult to feed back when encountering the problem of entrance and exit errors, so that the problem is not found timely.
At present, data of an entrance and an exit of a parking lot are reported by users, and are contributed by crowdsourcing of users, and a scheme for excavating the entrance and the exit of the parking lot through a stop point on a user track is not provided.
The main problems of the prior art solutions are two major:
firstly, the current entrance and exit of the parking lot are missing or wrong, and the user has poor experience after encountering the missing or wrong entrance and exit;
and secondly, the data of the entrance and the exit of the parking lot is not updated timely through user reporting or crowdsourcing collection.
Disclosure of Invention
Embodiments of the present disclosure propose methods and apparatuses for outputting information.
In a first aspect, an embodiment of the present disclosure provides a method for outputting information, including: acquiring a track data set of a driving user; determining a parking lot boundary and a parking lot peripheral area according to the trajectory data set; clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot; determining whether the central point of the cluster is an entrance or an exit of the parking lot according to the weighted sum of the number and the distance; and if the parking lot is at the entrance, the entrance of the parking lot is marked on the map.
In some embodiments, the method further comprises: and determining the type of the entrance and the exit corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
In some embodiments, obtaining a set of trajectory data for a driving user comprises: and determining a track data set of the driving user from the historical user track data according to the driving speed.
In some embodiments, determining parking lot boundaries and parking lot peripheral areas from the set of trajectory data comprises: screening at least one piece of target track data comprising a parking lot from the track data set; determining a stopping point and stopping time in at least one piece of target track data; determining a target parking lot according to the parking point with the parking time length exceeding a first preset value; determining a parking lot boundary according to a parking point of a target parking lot, wherein the parking point has a parking time length exceeding a second preset value, and the second preset value is larger than the first preset value; and determining the peripheral area of the parking lot from the target parking lot according to the parking boundary.
In some embodiments, the target trajectory data includes at least one parking lot; and determining the boundary of the parking lot according to the stopping point of the target parking lot, wherein the stopping time of the stopping point exceeds a second preset value, and the method comprises the following steps: intercepting track data comprising target parking lots from at least one piece of target track data and grouping the track data according to the parking lots; and for each target parking lot, determining the boundary of the parking lot according to the position of a parking point with the stay time exceeding a second preset value in the intercepted track data.
In some embodiments, determining whether the center point of the cluster is an entrance of the parking lot based on the weighted sum of the number and the distance includes: calculating the probability that each cluster is the entrance of the parking lot according to the following formula, and determining the cluster with the probability greater than a preset probability threshold value as the entrance and the exit of the parking lot:
where p is the probability, n is the number of clusters, α is the weight of the number, β is the weight of the distance, CjIs the number of clusters in the j cluster, DiIs the distance from the center point in the j cluster to the boundary of the parking lot
In a second aspect, an embodiment of the present disclosure provides an apparatus for outputting information, including: an acquisition unit configured to acquire a set of trajectory data of a driving user; a determination unit configured to determine a parking lot boundary and a parking lot peripheral area from the set of trajectory data; the clustering unit is configured to cluster the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot; a weighting unit configured to determine whether a center point of the cluster is an entrance of the parking lot according to a weighted sum of the number and the distance; and an identification unit configured to identify the entrance and exit of the parking lot on the map if the entrance and exit is provided.
In some embodiments, the identification unit is further configured to: and determining the type of the entrance and the exit corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
In some embodiments, the obtaining unit is further configured to: and determining a track data set of the driving user from the historical user track data according to the driving speed.
In some embodiments, the determining unit is further configured to: screening at least one piece of target track data comprising a parking lot from the track data set; determining a stopping point and stopping time in at least one piece of target track data; determining a target parking lot according to the parking point with the parking time length exceeding a first preset value; determining a parking lot boundary according to a parking point of a target parking lot, wherein the parking point has a parking time length exceeding a second preset value, and the second preset value is larger than the first preset value; and determining the peripheral area of the parking lot from the target parking lot according to the parking boundary.
In some embodiments, the target trajectory data includes at least one parking lot; and the determining unit is further configured to: intercepting track data comprising target parking lots from at least one piece of target track data and grouping the track data according to the parking lots; and for each target parking lot, determining the boundary of the parking lot according to the position of a parking point with the stay time exceeding a second preset value in the intercepted track data.
In some embodiments, the weighting unit is further configured to: calculating the probability that each cluster is the entrance of the parking lot according to the following formula, and determining the cluster with the probability greater than a preset probability threshold value as the entrance and the exit of the parking lot:
where p is the probability, n is the number of clusters, α is the weight of the number, β is the weight of the distance, CjIs j polyNumber of clusters in class, DiIs the distance from the center point in the j cluster to the boundary of the parking lot
In a third aspect, an embodiment of the present disclosure provides an electronic device for outputting information, including: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement a method as in any one of the first aspects.
In a fourth aspect, embodiments of the disclosure provide a computer readable medium having a computer program stored thereon, wherein the program when executed by a processor implements a method as in any one of the first aspect.
According to the method and the device for outputting the information, the entrance and the exit of the parking lot on the line are excavated according to the information of the parking point extracted according to the user track aiming at the existing parking lot on the line, so that the wrong entrance and exit information of the parking lot on the line can be effectively corrected, and the correct guide point for driving is provided aiming at the parking lot without the entrance and exit information on the line.
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Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present disclosure may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for outputting information, according to the present disclosure;
FIG. 3 is a schematic diagram of one application scenario of a method for outputting information according to the present disclosure;
FIG. 4 is a flow diagram of yet another embodiment of a method for outputting information in accordance with the present disclosure;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for outputting information according to the present disclosure;
FIG. 6 is a schematic block diagram of a computer system suitable for use with an electronic device implementing embodiments of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the present method for outputting information or apparatus for outputting information may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as navigation applications, map applications, web browser applications, shopping applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having a display screen and supporting navigation functions, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4 players (Moving Picture Experts Group Audio Layer IV, mpeg compression standard Audio Layer 4), laptop portable computers, desktop computers, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server providing various services, such as a background map server analyzing GPS data reported by the terminal devices 101, 102, 103. The background map server can analyze the historical track received by the terminal equipment, judge the entrance and exit of the parking lot, and mark the entrance and exit of the parking lot in the map and feed back the mark to the terminal equipment.
The server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as multiple pieces of software or software modules (e.g., multiple pieces of software or software modules used to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for outputting information provided in the embodiment of the present application is generally performed by the server 105, and accordingly, the apparatus for outputting information is generally disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for outputting information in accordance with the present application is shown. The method for outputting information comprises the following steps:
step 201, acquiring a track data set of a driving user.
In the present embodiment, an executing subject (e.g., the server shown in fig. 1) of the method for outputting information may acquire a set of trajectory data of the driving user from a third-party server. When the vehicle-mounted terminal is used for navigation, the current position information (longitude and latitude) of the vehicle can be reported at regular time. The position information is recorded to form the trajectory data of the driving user. Each track starts and ends with the position of the start and end of the navigation.
In some alternative implementations of the present embodiment, a set of trajectory data for the driving user is determined from historical user trajectory data based on travel speed. The server records the time point when receiving the position information reported by the user, and can calculate the driving speed of the user, so that the track with the speed exceeding a preset value (such as 40 kilometers per hour) is screened out to be used as the track data of the driving user.
Step 202, determining parking lot boundaries and parking lot peripheral areas according to the trajectory data set.
In this embodiment, the user's stopping point may be determined based on the speed at which the user is traveling. The dwell point is the position where the user has not moved for a predetermined time (e.g., 5 seconds) without encountering a red light. The vehicle can stay in the parking lot for a long time, and can stay for a short time due to payment, license plate recognition and the like when getting in or out of the parking lot. The parking lot and the surrounding area can be identified by the parking spot. A dwell point may be identified from the trace data where the dwell time exceeds a second predetermined value (e.g., 15 minutes). From these parking points, the boundaries of the parking lot can be drawn. A parking lot peripheral area may be defined by a certain range (e.g., 100 meters) around this boundary.
In some alternative implementations of this embodiment, if the location of the parking lot is known. Screening at least one piece of target track data comprising a parking lot from the track data set; determining a stopping point and stopping time in at least one piece of target track data; determining a target parking lot according to the parking point with the parking time length exceeding a first preset value; determining a parking lot boundary according to a parking point of a target parking lot, wherein the parking point has a parking time length exceeding a second preset value, and the second preset value is larger than the first preset value; and determining the peripheral area of the parking lot from the target parking lot according to the parking boundary.
And step 203, clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot.
In this embodiment, a kmeans algorithm may be used to cluster the stop points to obtain at least one group of stop points. Each cluster has a plurality of parking points and a cluster center, and the distance from the cluster center to the parking lot boundary can be calculated. The boundary here refers to the boundary closest to the center of the cluster.
And step 204, determining whether the central point of the cluster is the entrance or the exit of the parking lot according to the weighted sum of the number and the distance.
In the present embodiment, the probability that the center point of the cluster is the entrance of the parking lot is determined according to the weighted sum of the number and the distance. Wherein the weight of the number is positively correlated with the probability and the weight of the distance is negatively correlated with the parking lot. And when the probability is higher than a preset probability threshold value, judging that the center of the cluster is the entrance and exit of the parking lot.
In some optional implementations of this embodiment, the probability that each cluster is a parking lot entrance is calculated according to the following formula, and the cluster with the probability greater than the predetermined probability threshold is determined as the parking lot entrance:
where p is the probability, n is the number of clusters, α is the weight of the number, β is the weight of the distance, CjIs the number of clusters in the j cluster, DiIs the distance from the center point in the j cluster to the parking lot boundary. The sum of alpha and beta is 1.
And step 205, if the parking lot is an entrance, marking the entrance of the parking lot on the map.
In this embodiment, if it is determined as an entrance, the entrance may be identified at a position on the map where the boundary of the parking lot is closest to the clustering center.
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the method for outputting information according to the present embodiment. In the application scenario of fig. 3, the server obtains a large amount of vehicle trajectory data reported by the vehicle-mounted terminal, and dots in the figure are stay points. And determining the approximate range of the parking lot according to the stopping point. The parking spot where the parking time exceeds a second predetermined value is then determined as the vehicle in the parking lot. Through statistical analysis, the boundary of the parking lot can be determined, and therefore the specific area range of the parking lot can be obtained. And then clustering the stopping points in the rough range without the specific area range of the parking lot to obtain the information of the stopping points around the parking lot. And determining whether the cluster is a parking lot entrance or exit according to the distance between each cluster center and the parking lot boundary and the number of the stop points in the cluster. And if the map is the entrance, the map is identified. The type of entrance and exit (exit, entrance or both) can also be determined according to the trajectory direction.
According to the method provided by the embodiment of the disclosure, the entrance and exit of the parking lot on the line are excavated through the information of the parking point extracted from the user track, so that on one hand, wrong entrance and exit information of the parking lot on the line can be effectively corrected, and on the other hand, a correct guiding point for driving is provided for the parking lot without the entrance and exit information on the line.
With further reference to fig. 4, a flow 400 of yet another embodiment of a method for outputting information is shown. The process 400 of the method for outputting information includes the steps of:
step 401, obtaining a trajectory data set of a driving user.
Step 402, determining parking lot boundaries and parking lot peripheral areas from the set of trajectory data.
And step 403, clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot.
And step 404, determining whether the central point of the cluster is the entrance or the exit of the parking lot according to the weighted sum of the number and the distance.
The steps 401 and 404 are substantially the same as the steps 201 and 204, and therefore, the description thereof is omitted.
And 405, if the cluster is an entrance, determining the entrance type corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
In this embodiment, the track direction may be determined according to the track position of the stay point and the reporting time. If the stop point of a cluster is towards a parking lot boundary, it is said that the cluster is an entry. If the stop point of a cluster is far from the boundary of the parking lot, the cluster is an exit. An entrance is bidirectional if there is a stop in a cluster both towards and away from the boundary of the parking lot.
Step 406, identifying the parking lot doorway type on the map.
In this embodiment, the type of entrance and exit, e.g., exit, entrance, bi-directional, is identified at the corresponding location of the parking lot boundary on the map.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for outputting information in the present embodiment represents a step of determining the type of the gateway. Therefore, the scheme described in the embodiment can identify the direction of the entrance and the exit, and is convenient for the vehicle to travel.
With further reference to fig. 5, as an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of an apparatus for outputting information, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable in various electronic devices.
As shown in fig. 5, the apparatus 500 for outputting information of the present embodiment includes: an acquisition unit 501, a determination unit 502, a clustering unit 503, a weighting unit 504, and an identification unit 505. Wherein, the obtaining unit 501 is configured to obtain a trajectory data set of a driving user; a determination unit 502 configured to determine a parking lot boundary and a parking lot peripheral area from the set of trajectory data; the clustering unit 503 is configured to cluster the stop points in the trajectory data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot; a weighting unit 504 configured to determine whether the center point of the cluster is an entrance of the parking lot according to the weighted sum of the number and the distance; and an identification unit 505 configured to identify the entrance and exit of the parking lot on the map if the entrance and exit is provided.
In this embodiment, specific processing of the obtaining unit 501, the determining unit 502, the clustering unit 503, the weighting unit 504 and the identifying unit 505 of the apparatus 500 for outputting information may refer to step 201, step 202, step 203, step 204 and step 205 in the corresponding embodiment of fig. 2.
In some optional implementations of this embodiment, the identifying unit 505 is further configured to: and determining the type of the entrance and the exit corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
In some optional implementations of this embodiment, the obtaining unit 501 is further configured to: and determining a track data set of the driving user from the historical user track data according to the driving speed.
In some optional implementations of the present embodiment, the determining unit 502 is further configured to: screening at least one piece of target track data comprising a parking lot from the track data set; determining a stopping point and stopping time in at least one piece of target track data; determining a target parking lot according to the parking point with the parking time length exceeding a first preset value; determining a parking lot boundary according to a parking point of a target parking lot, wherein the parking point has a parking time length exceeding a second preset value, and the second preset value is larger than the first preset value; and determining the peripheral area of the parking lot from the target parking lot according to the parking boundary.
In some optional implementations of this embodiment, the target trajectory data includes at least one parking lot; and the determining unit 502 is further configured to: intercepting track data comprising target parking lots from at least one piece of target track data and grouping the track data according to the parking lots; and for each target parking lot, determining the boundary of the parking lot according to the position of a parking point with the stay time exceeding a second preset value in the intercepted track data.
In some optional implementations of this embodiment, the weighting unit 504 is further configured to: calculating the probability that each cluster is the entrance of the parking lot according to the following formula, and determining the cluster with the probability greater than a preset probability threshold value as the entrance and the exit of the parking lot:
where p is the probability and n is the clusterNumber, α is the weight of the number, β is the weight of the distance, CjIs the number of clusters in the j cluster, DiIs the distance from the center point in the j cluster to the parking lot boundary.
Referring now to FIG. 6, a schematic diagram of an electronic device (e.g., the server of FIG. 1) 600 suitable for use in implementing embodiments of the present disclosure is shown. The server shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 6, electronic device 600 may include a processing means (e.g., central processing unit, graphics processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 609, or may be installed from the storage means 608, or may be installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the methods of embodiments of the present disclosure. It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a track data set of a driving user; determining a parking lot boundary and a parking lot peripheral area according to the trajectory data set; clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot; determining whether the central point of the cluster is an entrance or an exit of the parking lot according to the weighted sum of the number and the distance; and if the parking lot is at the entrance, the entrance of the parking lot is marked on the map.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a determination unit, a clustering unit, a weighting unit, and an identification unit. Where the names of the units do not in some cases constitute a limitation of the units themselves, for example, the acquisition unit may also be described as a "unit acquiring a set of trajectory data of a driving user".
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Claims (14)
1. A method for outputting information, comprising:
acquiring a track data set of a driving user;
determining a parking lot boundary and a parking lot peripheral area according to the track data set;
clustering the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot;
determining whether the central point of the cluster is an entrance or an exit of the parking lot according to the weighted sum of the number and the distance;
and if the parking lot is at the entrance, the entrance of the parking lot is marked on the map.
2. The method of claim 1, wherein the method further comprises:
and determining the type of the entrance and the exit corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
3. The method of claim 1, wherein said obtaining a set of trajectory data for a driving user comprises:
and determining a track data set of the driving user from the historical user track data according to the driving speed.
4. The method of claim 1, wherein said determining parking lot boundaries and parking lot peripheral areas from said set of trajectory data comprises:
screening at least one target track data including a parking lot from the track data set;
determining a stopping point and stopping time in the at least one piece of target track data;
determining a target parking lot according to the parking point with the parking time length exceeding a first preset value;
determining a parking lot boundary according to a parking point of the target parking lot, wherein the parking point has the parking time length exceeding a second preset value, and the second preset value is larger than the first preset value;
and determining a parking lot peripheral area from the target parking lot according to the parking boundary.
5. The method of claim 3, wherein the target trajectory data comprises at least one parking lot; and
the determining the boundary of the parking lot according to the stopping point of which the stopping time length in the target parking lot exceeds a second preset value comprises the following steps:
intercepting track data comprising target parking lots from the at least one piece of target track data and grouping the track data according to the parking lots;
and for each target parking lot, determining the boundary of the parking lot according to the position of a parking point with the stay time exceeding a second preset value in the intercepted track data.
6. The method of any one of claims 1-5, wherein said determining whether a center point of a cluster is an entrance to a parking lot based on a weighted sum of said number and said distance comprises:
calculating the probability that each cluster is the entrance of the parking lot according to the following formula, and determining the cluster with the probability greater than a preset probability threshold value as the entrance and the exit of the parking lot:
where p is the probability, n is the number of clusters, α is the weight of the number, β is the weight of the distance, CjIs the number of clusters in the j cluster, DiIs the distance from the center point in the j cluster to the parking lot boundary.
7. An apparatus for outputting information, comprising:
an acquisition unit configured to acquire a set of trajectory data of a driving user;
a determination unit configured to determine a parking lot boundary and a parking lot peripheral area from the set of trajectory data;
the clustering unit is configured to cluster the stop points in the track data of the peripheral area of the parking lot to obtain the number of the stop points contained in each cluster and the distance between each cluster and the boundary of the parking lot;
a weighting unit configured to determine whether a center point of a cluster is an entrance/exit of a parking lot according to a weighted sum of the number and the distance;
and an identification unit configured to identify the entrance and exit of the parking lot on the map if the entrance and exit is provided.
8. The apparatus of claim 7, wherein the identification unit is further configured to:
and determining the type of the entrance and the exit corresponding to each cluster internal stay point according to the track direction of each cluster internal stay point.
9. The apparatus of claim 7, wherein the obtaining unit is further configured to:
and determining a track data set of the driving user from the historical user track data according to the driving speed.
10. The apparatus of claim 7, wherein the determination unit is further configured to:
screening at least one target track data including a parking lot from the track data set;
determining a stopping point and stopping time in the at least one piece of target track data;
determining a target parking lot according to the parking point with the parking time length exceeding a first preset value;
determining a parking lot boundary according to a parking point of the target parking lot, wherein the parking point has the parking time length exceeding a second preset value, and the second preset value is larger than the first preset value;
and determining a parking lot peripheral area from the target parking lot according to the parking boundary.
11. The apparatus of claim 10, wherein the target trajectory data comprises at least one parking lot; and
the determination unit is further configured to:
intercepting track data comprising target parking lots from the at least one piece of target track data and grouping the track data according to the parking lots;
and for each target parking lot, determining the boundary of the parking lot according to the position of a parking point with the stay time exceeding a second preset value in the intercepted track data.
12. The apparatus according to one of claims 7-11, wherein the weighting unit is further configured to:
calculating the probability that each cluster is the entrance of the parking lot according to the following formula, and determining the cluster with the probability greater than a preset probability threshold value as the entrance and the exit of the parking lot:
where p is the probability, n is the number of clusters, α is the weight of the number, β is the weight of the distance, CjIs the number of clusters in the j cluster, DiIs the distance from the center point in the j cluster to the parking lot boundary.
13. An electronic device for outputting information, comprising:
one or more processors;
a storage device having one or more programs stored thereon,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-6.
14. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-6.
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