CN117824687A - Path planning method and device, electronic equipment and computer readable storage medium - Google Patents
Path planning method and device, electronic equipment and computer readable storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3476—Special cost functions, i.e. other than distance or default speed limit of road segments using point of interest [POI] information, e.g. a route passing visible POIs
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Abstract
The disclosure provides a path planning method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of computers, in particular to the technical fields of path planning, map navigation and the like. The specific implementation scheme is as follows: acquiring position information of a path starting point and position information of a path ending point; generating a target path from the path starting point to the path ending point according to the position information of the path starting point, the position information of the path ending point and the street information of a plurality of associated streets; wherein the street information of the associated street includes point of interest information of points of interest of the street.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to the technical field of path planning, map navigation, and the like. In particular, the disclosure relates to a path planning method and apparatus, an electronic device, and a computer-readable storage medium.
Background
With the improvement of living standard, travel modes are more and more various, and autonomous travel of people is more and more.
With the development of map technology, an electronic map installed in a terminal device can provide convenient navigation service for a user to travel.
Disclosure of Invention
The disclosure provides a path planning method and device, electronic equipment and a computer readable storage medium.
According to a first aspect of the present disclosure, there is provided a path planning method comprising:
acquiring position information of a path starting point and position information of a path ending point;
generating a target path from the path starting point to the path ending point according to the position information of the path starting point, the position information of the path ending point and the street information of a plurality of associated streets;
wherein the street information of the associated street includes point of interest information of points of interest of the associated street.
According to a second aspect of the present disclosure, there is provided a path planning apparatus comprising:
the information module is used for acquiring the position information of the path starting point and the position information of the path ending point;
a path planning module, configured to generate a target path from the path start point to the path end point according to the position information of the path start point, the position information of the path end point, and street information of a plurality of associated streets;
Wherein the street information of the associated street includes point of interest information of points of interest of the associated street.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the path planning method.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the above-described path planning method.
According to a fifth aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the above-described path planning method.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flow chart of a path planning method according to an embodiment of the disclosure;
FIG. 2 is a flow chart illustrating partial steps of another path planning method provided by an embodiment of the present disclosure;
FIG. 3 is a flow chart illustrating partial steps of another path planning method provided by an embodiment of the present disclosure;
FIG. 4 is a flow chart illustrating partial steps of another path planning method provided by an embodiment of the present disclosure;
FIG. 5 is a process schematic of one embodiment of a path planning method provided by embodiments of the present disclosure;
fig. 6 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present disclosure;
fig. 7 is a block diagram of an electronic device for implementing a path planning method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In some related art, a path planning scheme may be provided to a user based on real-time road conditions, traffic light volumes, or specific vehicle preferences.
The generation of path planning schemes is mostly considered from the speed aspect, and the satisfaction of personalized requirements is lacking, namely, the special path planning requirements existing in some specific scenes cannot be satisfied.
If the user is shopping, the user should pay attention to selecting a path which meets the shopping requirement along the street shop classification; the user rides the street lamp by walking at night, and the route with more street lamps is selected; these are not available in existing navigation methods.
The embodiment of the disclosure provides a path planning method and device, electronic equipment and a computer readable storage medium, which aim to solve at least one of the technical problems in the prior art.
The path planning method provided by the embodiment of the present disclosure may be performed by an electronic device such as a terminal device or a server, where the terminal device may be a vehicle-mounted device, a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor invoking computer readable program instructions stored in a memory. Alternatively, the method may be performed by a server.
Fig. 1 shows a flow chart of a path planning method provided by an embodiment of the present disclosure. As shown in fig. 1, the path planning method provided by the embodiment of the present disclosure may include step S110 and step S120.
In step S110, position information of a route start point and position information of a route end point are acquired;
in step S120, a target path from the path start point to the path end point is generated according to the position information of the path start point, the position information of the path end point, and the street information of the plurality of associated streets;
wherein the street information associated with the street includes point of interest information associated with the point of interest of the street.
For example, in step S110, the position information of the route start point may be obtained based on text information or selection information of the route start point input by the user, the position information of the route start point may be determined according to a map, the current position of the user may be determined according to GPS (Global Positioning System ) information of a device carried by the user, the position of the user is taken as the route start point, and the position information of the position is taken as the position information of the route start point.
In some possible implementations, the obtaining the location information of the path end point may be based on text information or selection information of the path end point input by the user, and determining the location information of the path end point according to the map.
In some possible implementations, in step S120, generating the target path according to the position information of the start point of the path, the position information of the end point of the path, and the street information of the plurality of associated streets may be determining feature information corresponding to each of the plurality of paths of the start point of the path and the end point of the path according to the street information of the associated street included in each of the plurality of paths, and determining one path from the plurality of paths as the target path according to the feature information corresponding to each of the paths.
In some possible implementations, user demand information may be acquired, street information of a plurality of associated streets is processed based on the user demand information, and a target path is determined according to position information of a path start point and position information of a path end point based on a processing result.
In some possible implementations, the associated streets may include a plurality of streets within a predetermined range between the path start point and the path end point, a plurality of streets within a predetermined range of the path start point, a plurality of streets within a predetermined range of the path end point.
In some possible implementations, the street information of the associated street may be based on POI information of a POI (Point of interest) included in the associated street.
Where POI refers to a meaningful point in geographic location, such as a store, restaurant, park, art gallery, etc. The POI information may include various information such as names, addresses, longitude and latitude of POI.
In some possible implementations, after step S120, i.e. after determining the target path, the target path is pushed to the client for the user to travel according to the target path.
In the path planning method provided by the embodiment of the disclosure, the street information of the street is mined through the POI information of the POI of the street, so that richer information is provided for path planning, and the richer information can provide planning basis for personalized path planning requirements to help generate a path planning result meeting the personalized path planning requirements.
The following describes a path planning method provided by an embodiment of the present disclosure in detail.
As described above, in some possible implementations, user demand information may be acquired, street information of a plurality of associated streets may be processed based on the user demand information, and a target path may be determined according to position information of a path start point and position information of a path end point based on a processing result.
The user demand information may be determined according to path planning information of the user.
The route planning information of the user can comprise at least one of information of route end points, travel time and travel modes.
The travel time may be a departure time input by the user, that is, a time when the user intends to execute the target path. In some specific implementations, the departure time may not be obtained due to forgetting input of the user, and the travel time is determined according to the time of inputting the path starting point and the path ending point by the user, for example, the completion time of inputting the path starting point and the path ending point by the user may be used as the time of path planning.
The information of the path end point may be determined according to information corresponding to the path end point input by the user. In some specific implementation manners, determining a route end point according to information input by a user, and if the route end point is a POI, directly acquiring POI information of the POI corresponding to the route end point as information of the route end point; if the route end point is not a POI, the POI information of the POI closest to the periphery of the route end point may be obtained as the information of the route end point.
Similarly, the information of the path start point may be determined according to the information corresponding to the path start point inputted by the user. In some specific implementation manners, determining a path starting point according to information input by a user, and if the path starting point is a POI, directly acquiring POI information corresponding to the path starting point as information of the path starting point; if the route start point is not a POI, the POI information of the POI closest to the route start point may be acquired as the information of the route start point.
In some possible implementations, the travel mode may be determined according to a travel mode corresponding to the route plan selected by the user, such as self-driving, riding, walking, and the like.
In some specific implementations, determining the user demand information based on the travel time may be determining a security level demand of the user on the target path based on the travel time.
If the travel time belongs to the late night time period, the safety registration requirement of the user on the target path is higher; if the travel time belongs to the working period, the user may not have excessive demands on the security level of the target path.
In some specific implementations, determining the user demand information according to the travel mode may be determining that the user demand information is a path suitable for riding or walking, such as a path with a higher comfort level, in the case that the travel mode is riding or walking.
In some specific implementations, determining the user demand information according to the information of the route end point may be determining a user trip target according to POI information around the route end point, and taking the user trip target as the user demand information.
If the POI corresponding to the route end point is determined to be a mall according to the POI information around the route end point, the user can be determined that the travel target of the user is likely to be shopping; if the POI corresponding to the route end point is determined to be a park according to the POI information around the route end point, the user can be determined to travel or walk.
In some specific implementations, the user requirement information may also be determined according to the information of the path end point and combined with the information of the path start point.
If the POI corresponding to the route end point is determined to be a park according to the POI information around the route end point, if the POI corresponding to the route start point is determined to be a hotel according to the POI information around the route start point, the travel target of the user can be determined to be travel; if the POI corresponding to the route starting point is determined to be the cell according to the POI information around the route starting point, the user trip target can be determined to be the walk.
In some specific implementation manners, the user demand information can be determined by combining the POI information corresponding to the travel mode, the travel time and the route end point.
In some specific implementations, the user demand information is determined according to a travel mode and travel time, and whether the user demand information determines the safety level of the target path or the comfort level of the target path according to the travel time and travel mode is higher in priority is determined according to the travel mode and travel time.
If the travel time belongs to the late night time period, the security level priority is higher; and if the travel time belongs to the working time period, the comfort level priority is higher.
In some specific implementations, determining the user demand information according to the travel mode and the POI information around the route end point may be when determining the user travel target according to the POI information around the route end point under the condition that the travel mode is self-driving, and the road with more pedestrians should be considered.
In some possible implementations, the user demand information may also be determined from user history information.
The user history information includes history path planning information corresponding to the user.
For example, the user demand information can be determined according to the travel mode, travel time and path end point which are commonly used by the user according to the user history path planning information.
The specific manner of determining the user demand information according to the travel mode, travel time and path end point commonly used by the user is as shown above, and will not be described in detail here.
In some possible implementations, determining the user demand information according to the user history information may further include selecting to determine whether the user is a driving novice according to the user history travel mode, and if the user is the driving novice, determining that the user demand information is a path with wider lanes and less traffic.
In some possible implementations, after confirming the user demand information, generating the target path according to the position information of the path start point, the position information of the path end point, and the street information of the plurality of associated streets based on the user demand information may be to process the street information of the plurality of associated streets, and determine the target path according to the position information of the path start point and the position information of the path end point based on the processing result.
In some specific implementations, the satisfaction degree of the plurality of related streets to the user demand information can be determined according to the user demand information and the street information of the plurality of related streets, and the path with the highest satisfaction degree to the user demand information in the path starting point and the path ending point is determined as the target path according to the position information of the path starting point and the position information of the path ending point.
Fig. 2 is a flow chart of an implementation manner of processing street information of a plurality of streets based on user demand information and determining a target path according to position information of a start point of the path and position information of an end point of the path based on processing results, and as shown in fig. 2, may include step S210, step S220 and step S230.
In step S210, a plurality of candidate paths from the path start point to the path end point are generated based on the position information of the path start point and the position information of the path end point;
in step S220, based on the user demand information, demand street information related to the user demand information is acquired from street information of the associated street included in each candidate route;
in step S230, a target path is determined from the plurality of candidate paths according to the required street information of the associated street included in each candidate path.
In some possible implementations, in step S210, generating the plurality of candidate paths according to the position information of the path start point and the position information of the path end point may be generating the plurality of candidate paths according to the position information of the path start point and the position information of the path end point based on whether the road segment between the path start point and the path end point is congested, jammed, or not passable. The streets traversed by the plurality of candidate paths are at least partially different.
The method for generating the candidate paths according to the embodiments of the present disclosure is not limited, and any method capable of generating the candidate paths according to the position information of the path start point and the position information of the path end point is within the scope of the embodiments of the present disclosure.
In some possible implementations, in step S220, based on the user requirement information, the required street information related to the user requirement information is obtained from the street information of the associated street included in the candidate path, and the required street information related to the user requirement information may be determined based on the user requirement information according to the preset information correspondence.
In some specific implementations, where the user demand information includes security rating information, the demand street information associated with the user demand information may include business hours of the POI, POI location, POI area.
In some specific implementations, where the user demand information includes comfort level information, the demand street information related to the user demand information may include classification information for POIs, vegetation coverage information for POIs.
In some specific implementations, where the user demand information includes a user travel goal, the demand street information related to the user demand information may include POI classification information, business hours of the POI.
In some possible implementations, in step S230, a satisfaction degree of each candidate path to the user demand information may be determined according to the demand street information, and the target path may be determined from the plurality of candidate paths according to the satisfaction degree.
In some possible implementations, where the user demand information includes security level information, determining satisfaction of the candidate path with the user demand information based on the demand street information may be determining satisfaction of the candidate path with the user demand information based on street security of an associated street included by the candidate path.
In some specific implementations, determining the satisfaction of the candidate path to the user demand information according to the street security of the associated streets included in the candidate path may be determining the satisfaction of the candidate path to the user demand information according to the number of associated streets whose security included in the candidate path satisfies a preset threshold and the distribution of the associated streets in the candidate path.
In some possible implementations, the street security of the associated street may be determined based on the business hours of the POIs included in the associated street and the aggregate degree of the multiple POIs of the associated street. The aggregation degree of the POIs is determined according to the street distance between the adjacent POIs, and the shorter the street distance between the adjacent POIs is, the higher the aggregation degree of the POIs is.
In some specific implementations, the later the business hours of the POIs associated with the street, the higher the security of the associated street; the higher the POI aggregation degree on the associated street, the higher the security degree of the associated street; the wider the POI face width on the associated street, the higher the security of the associated street.
In some possible implementations, where the user demand information includes comfort level information, determining satisfaction of the candidate path with the user demand information from the demand street information may be determining satisfaction of the candidate path with the user demand information from street comfort of an associated street included by the candidate path.
In some specific implementations, determining the satisfaction of the candidate path with the user demand information based on the street comfort level of the streets included in the candidate path may be determining the satisfaction of the candidate path with the user demand information based on the number of associated streets whose comfort level included in the candidate path meets a preset threshold and the distribution of the associated streets in the target path.
In some specific implementations, the greater the number of more comfortable POIs on the associated street that are categorized as parks, gardens, etc., the greater the comfort of the associated street; the higher the vegetation coverage of the POIs on the associated street, the higher the comfort of the associated street.
In some possible implementations, where the user demand information includes a travel target, determining the satisfaction of the candidate path to the user demand information based on the demand street information may be determining the satisfaction of the candidate path to the user demand information based on the match of the associated street included by the candidate path to the travel target.
In some specific implementations, determining the satisfaction of the candidate path to the user demand information according to the matching degree of the associated streets included in the candidate path and the travel target may be determining the satisfaction of the candidate path to the user demand information according to the number of the associated streets included in the candidate path and the distribution condition of the associated streets in the target path, wherein the matching degree of the associated streets included in the candidate path and the travel target meets a preset threshold.
In some specific implementations, in the case where the travel target is entertainment, the matching degree of the associated street and the travel target may be determined according to classification information of the POI included in the associated street. The classification information of the POI can be determined according to the function of the POI, and if the function of the POI is meal, the POI is classified as a restaurant; the POI has the function of purchasing clothes, and is classified as a store; the POI can either eat or purchase clothing, and the classification of the POI can be a mall.
In some specific implementation manners, under the condition that the travel target is shopping, the more POIs classified as shops and shops on the associated street, the higher the matching degree of the associated street and the travel target; under the condition that the travel target is travel, the more the number of POIs classified as scenic spots on the associated streets, the higher the matching degree of the associated streets and the travel target; under the condition that the travel targets are walking, the more the number of POIs with higher comfortableness, such as parks, gardens and the like, on the associated streets are, the higher the matching degree between the associated streets and the travel targets is; under the condition that the travel targets are learned, the more the number of POIs with higher science and technology degrees, such as science and technology museums, cultural museums and the like, on the associated streets, the higher the matching degree of the associated streets and the travel targets is.
In some specific implementation manners, under the condition that the travel target is a path with wider lanes and less people flow, the fewer the number of POIs classified as shops, shops and scenic spots on the associated street, the higher the matching degree of the associated street and the travel target; the more distant the positions of the POIs on both sides of the associated street are, the fewer the number of POIs classified as shops and shops, the higher the matching degree of the associated street and the travel target is.
In some possible ways, the user demand information may include a plurality of information, and thus, the target path may be determined by a weighted calculation, and the number of target paths may be plural.
In some possible implementations, after confirming the user demand information, generating the target path according to the position information of the path start point, the position information of the path end point, and the street information of the plurality of associated streets based on the user demand information may be generating a plurality of candidate paths from the path start point to the path end point according to the position information of the path start point, the position information of the path end point, and determining the target path from the candidate paths based on the user demand information.
In some specific implementations, a plurality of candidate paths from the path start point to the path end point can be determined according to the position information of the path start point and the position information of the path end point, the satisfaction degree of the plurality of candidate paths to the user demand information is determined based on the user demand information, and the candidate path with the highest satisfaction degree to the user demand information is determined to be the target path.
Fig. 3 shows a flow chart of an implementation manner of generating a plurality of candidate paths from the path start point to the path end point according to the position information of the path start point and the position information of the path end point, and determining a target path from the candidate paths based on the user demand information, as shown in fig. 3, may include step S310, step S320, and step S330.
In step S310, a plurality of candidate paths from the path start point to the path end point are generated based on the position information of the path start point and the position information of the path end point;
in step S320, feature information of the candidate paths is determined according to street information of the associated streets included in each candidate path;
in step S330, a target path is determined from the plurality of candidate paths according to the feature information of each candidate path based on the user demand information.
In some possible implementations, in step S310, generating the plurality of candidate paths according to the position information of the path start point and the position information of the path end point may be generating the plurality of candidate paths according to the position information of the path start point and the position information of the path end point based on whether the road segment between the path start point and the path end point is congested, jammed, or not passable. The streets traversed by the plurality of candidate paths are at least partially different.
The method for generating the candidate paths according to the embodiments of the present disclosure is not limited, and any method capable of generating the candidate paths according to the position information of the path start point and the position information of the path end point is within the scope of the embodiments of the present disclosure.
In some possible implementations, in step S320, determining the feature information of the candidate path according to the street information of the associated street included in the candidate path may be determining the feature information of the candidate path according to the street feature information of the associated street included in the candidate path, and the street feature information may be determined in advance according to the associated street information.
In some possible implementations, the street characteristic information may include at least one of a security level of a street, a comfort level of a street, an entertainment level of a street, a science level of a street.
In some specific implementations, the later the business hours of the POIs associated with the street, the higher the security of the associated street; the higher the POI aggregation degree on the associated street, the higher the security degree of the associated street; the wider the POI face width on the associated street, the higher the security of the associated street.
In some specific implementations, the greater the number of more comfortable POIs on the associated street that are categorized as parks, gardens, etc., the greater the comfort of the associated street; the higher the vegetation coverage of the POIs on the associated street, the higher the comfort of the associated street.
In some specific implementations, the greater the number of POIs categorized as shops, attractions on the associated street, the higher the entertainment of the associated street.
In some specific implementations, the greater the number of POIs categorized as a museum, a cultural museum on an associated street, the greater the science and technology of the associated street.
In some possible implementations, the characteristic information of the candidate path includes at least one of security level information, comfort level information, entertainment level information, and technology level information.
In some possible implementations, the security level information of the candidate path may be determined according to the security level of the associated street included in the candidate path; the comfort level information of the candidate path may be determined according to the comfort level of the associated street included in the candidate path; entertainment level information of the candidate path can be determined according to entertainment level of the associated street included in the candidate path; the skill level information for the candidate path may be determined based on the skill level of the associated street included in the candidate path.
In some possible implementations, in step S330, determining the target path from the plurality of candidate paths according to the feature information of the candidate paths may be based on the user demand information, selecting feature information related to the user demand information from the feature information of the candidate paths, and determining the target path from the plurality of candidate paths according to the related feature information.
In some possible implementations, the method further includes a step of binding the POI to the street before generating the target path from the path start point to the path end point according to the position information of the path start point, the position information of the path end point and the street information of the plurality of streets.
Fig. 4 shows a flow diagram of one implementation of binding POIs to streets, as shown in fig. 4, which may include step S410, step S420, step S430.
In step S410, point of interest information of a plurality of points of interest is acquired;
in step S420, a binding relationship is established between the points of interest and the streets according to the location information of the plurality of points of interest and the plurality of associated streets;
in step S430, for any one of the plurality of associated streets, street information of the associated street is determined according to the point of interest information of at least one point of interest with which the associated street is in a binding relationship.
In some possible implementations, in step S410, the POI information may include various information such as name, address, latitude and longitude of the POI.
In some possible implementations, POI information of the POI may be obtained by a feature extraction method.
In some possible implementations, in step S420, a binding relationship is established between the POI located within a preset range of the location of the associated street and the associated street according to the location information of the POI and the location information of the associated street.
In some possible implementations, in step S430, for any one of the associated streets, POI information of POIs that establish a binding relationship with the associated street is taken as the street information of the associated street.
POI information of a POI can be converted into street information by binding the associated street with the POI.
The following describes a path planning method provided by an embodiment of the present disclosure in detail.
FIG. 5 illustrates a schematic diagram of a path planning process for one embodiment, as shown in FIG. 5, requiring pre-processing of map modeling prior to path planning.
The preprocessing process may include extracting POI features from the map to obtain POI information of the POI, binding the POI with the street, and generating the map containing the street information by using the POI information of the POI which has a binding relationship with the street as the street information of the street to realize information transition from the POI information to the street information.
When a path planning demand is received, user demand information is acquired, path planning is performed according to the user demand information by using the path planning method provided by the embodiment of the disclosure, and a target path is pushed to a client as a personalized path planning result for the user to acquire.
The dimensions of map data are enriched through POI attribute information, and navigation route planning can be adapted to more scenes.
Based on the same principle as the method shown in fig. 1, fig. 6 shows a schematic structural diagram of a path planning apparatus provided by an embodiment of the present disclosure, and as shown in fig. 6, the path planning apparatus 60 may include:
an information module 610, configured to obtain position information of a path start point and position information of a path end point;
a path planning module 620, configured to generate a target path from a path start point to a path end point according to the position information of the path start point, the position information of the path end point, and the street information of a plurality of associated streets;
wherein the street information associated with the street includes point of interest information associated with the point of interest of the street.
In the path planning device provided by the embodiment of the disclosure, the street information of the street is mined through the POI information of the POI of the street, so that richer information is provided for path planning, and the richer information can provide planning basis for personalized path planning requirements to help generate a path planning result meeting the personalized path planning requirements.
It will be appreciated that the above-described modules of the path planning apparatus in the embodiments of the present disclosure have functions to implement the respective steps of the path planning method in the embodiment shown in fig. 1. The functions can be realized by hardware, and can also be realized by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the functions described above. The modules may be software and/or hardware, and each module may be implemented separately or may be implemented by integrating multiple modules. For the functional description of each module of the path planning apparatus, reference may be specifically made to the corresponding description of the path planning method in the embodiment shown in fig. 1, which is not repeated herein.
In some possible implementations, the path planning module 620 is further configured to: based on the user demand information, a target path is generated from the position information of the path start point, the position information of the path end point, and the street information of the plurality of associated streets.
In some possible implementations, the path planning module 620 includes: a candidate path generation unit for generating a plurality of candidate paths from the path start point to the path end point according to the position information of the path start point and the position information of the path end point; an information processing unit, configured to acquire, based on the user demand information, demand street information related to the user demand information from street information of the associated street included in each candidate route; and the target path determining unit is used for determining the target path from the plurality of candidate paths according to the required street information of the associated street included in each candidate path.
In some possible implementations, the path planning module 620 includes: a candidate path generation unit for generating a plurality of candidate paths from the path start point to the path end point according to the position information of the path start point and the position information of the path end point; the information processing unit is used for determining the characteristic information of each candidate path according to the street information of the associated street included in each candidate path; and a target path determining unit for determining a target path from the plurality of candidate paths according to the characteristic information of each candidate path based on the user demand information.
In some possible implementations, the characteristic information of the candidate path includes at least one of security level information, comfort level information, entertainment level information.
In some possible implementations, in a case where the feature information of the candidate path includes security level information, the point of interest information of the point of interest includes at least one of business hours of the point of interest, a degree of aggregation of the point of interest with other points of interest, and a relative area of the point of interest with a corresponding associated street; or in the case that the feature information of the candidate path includes comfort level information, the interest point information of the interest point includes vegetation coverage information of the interest point; or in case the feature information of the candidate path comprises entertainment class information, the point of interest information of the point of interest comprises classification information of the point of interest.
In some possible implementations, the user demand information is determined from the path planning information; the route planning information comprises at least one of trip mode, POI information around a route end point and trip time.
In some possible implementations, the user demand information is determined from user history information; the user history information includes history path planning information corresponding to the user.
In some possible implementations, the path planning apparatus further includes a preprocessing module; the preprocessing module comprises: the information extraction unit is used for acquiring the interest point information of the plurality of interest points; the binding unit is used for establishing a binding relationship between the interest points and the streets according to the position information of the interest points and the streets; and the information integration unit is used for determining the street information of the street according to the interest point information of at least one interest point which is in binding relation with the street.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the related user personal information all conform to the regulations of related laws and regulations, and the public sequence is not violated.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
The electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a path planning method as provided by embodiments of the present disclosure.
Compared with the prior art, the electronic equipment has the advantages that the street information of the street is mined through the POI information of the POI of the street, more abundant information is provided for path planning, planning basis can be provided for personalized path planning requirements by the abundant information, and the generation of the path planning result meeting the personalized path planning requirements is facilitated.
The readable storage medium is a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a path planning method as provided by embodiments of the present disclosure.
Compared with the prior art, the readable storage medium is used for mining street information of the street through POI information of the street, providing richer information for path planning, providing planning basis for personalized path planning requirements by the rich information, and helping to generate path planning results meeting the personalized path planning requirements.
The computer program product comprises a computer program which, when executed by a processor, implements a path planning method as provided by embodiments of the present disclosure.
Compared with the prior art, the computer program product has the advantages that the street information of the street is mined through the POI information of the POI of the street, more abundant information is provided for path planning, the abundant information can provide planning basis for personalized path planning requirements, and the generation of the path planning result meeting the personalized path planning requirements is facilitated.
Fig. 7 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the apparatus 700 includes a computing unit 701 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 may also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in device 700 are connected to I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, etc.; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, an optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 701 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 701 performs the respective methods and processes described above, for example, a path planning method. For example, in some embodiments, the path planning method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 700 via ROM 702 and/or communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the path planning method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform the path planning method by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on 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.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server incorporating a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (21)
1. A path planning method, comprising:
acquiring position information of a path starting point and position information of a path ending point;
generating a target path from the path starting point to the path ending point according to the position information of the path starting point, the position information of the path ending point and the street information of a plurality of associated streets;
wherein the street information of the associated street includes point of interest information of points of interest of the associated street.
2. The method of claim 1, wherein the generating a target path from the path start point to the path end point based on the position information of the path start point, the position information of the path end point, and the street information of a plurality of associated streets comprises:
and generating the target path according to the position information of the path starting point, the position information of the path ending point and the street information of a plurality of associated streets based on the user demand information.
3. The method of claim 2, wherein the generating the target path based on the user demand information from the location information of the path start point, the location information of the path end point, and the street information of the plurality of associated streets comprises:
generating a plurality of candidate paths from the path starting point to the path ending point according to the position information of the path starting point and the position information of the path ending point;
acquiring required street information related to the user requirement information from street information of associated streets included in each candidate path based on the user requirement information;
the target path is determined from a plurality of the candidate paths according to the required street information of the associated street included in each candidate path.
4. The method of claim 2, wherein the generating the target path based on the user demand information from the location information of the path start point, the location information of the path end point, and the street information of the plurality of associated streets comprises:
generating a plurality of candidate paths from the path starting point to the path ending point according to the position information of the path starting point and the position information of the path ending point;
determining characteristic information of each candidate path according to street information of the associated street included in each candidate path;
and determining the target path from a plurality of candidate paths according to the characteristic information of each candidate path based on the user demand information.
5. The method of claim 4, wherein the characteristic information of the candidate path includes at least one of security level information, comfort level information, entertainment level information.
6. The method of claim 5, wherein, in the case where the feature information of the candidate path includes the security level information, the point of interest information of the point of interest includes at least one of business hours of the point of interest, a degree of aggregation of the point of interest with other points of interest, a relative area of the point of interest with the corresponding associated street; or (b)
In the case that the feature information of the candidate path includes the comfort level information, the interest point information of the interest point includes vegetation coverage information of the interest point; or (b)
In the case where the feature information of the candidate path includes the entertainment class information, the point of interest information of the point of interest includes classification information of the point of interest.
7. The method of claim 2, wherein the user demand information is determined from path planning information; the path planning information comprises at least one of trip mode, trip time and interest point information around the path end point.
8. The method of claim 2, wherein the user demand information is determined from user history information; the user history information comprises history path planning information corresponding to the user.
9. The method of claim 1, wherein before generating the target path from the path start point to the path end point based on the position information of the path start point, the position information of the path end point, and the street information of the plurality of associated streets, further comprising:
acquiring interest point information of a plurality of interest points;
Establishing a binding relation between the interest points and the streets according to the position information of the interest points and the associated streets;
for any one of a plurality of associated streets, determining the street information of the associated street according to the interest point information of at least one interest point which is in binding relation with the associated street.
10. A path planning apparatus comprising:
the information module is used for acquiring the position information of the path starting point and the position information of the path ending point;
a path planning module, configured to generate a target path from the path start point to the path end point according to the position information of the path start point, the position information of the path end point, and street information of a plurality of associated streets;
wherein the street information of the associated street includes point of interest information of points of interest of the associated street.
11. The apparatus of claim 10, wherein the path planning module is further to:
and generating the target path according to the position information of the path starting point, the position information of the path ending point and the street information of a plurality of associated streets based on the user demand information.
12. The apparatus of claim 11, wherein the path planning module comprises:
A candidate path generation unit configured to generate a plurality of candidate paths from the path start point to the path end point based on the position information of the path start point and the position information of the path end point;
an information processing unit, configured to obtain, based on the user demand information, demand street information related to the user demand information from street information of associated streets included in each of the candidate paths;
and the target path determining unit is used for determining the target path from a plurality of candidate paths according to the required street information of the associated street included in each candidate path.
13. The apparatus of claim 11, wherein the path planning module comprises:
a candidate path generation unit configured to generate a plurality of candidate paths from the path start point to the path end point based on the position information of the path start point and the position information of the path end point;
the information processing unit is used for determining the characteristic information of each candidate path according to the street information of the associated street included in each candidate path;
and a target path determining unit configured to determine the target path from a plurality of candidate paths according to the feature information of each of the candidate paths based on the user demand information.
14. The apparatus of claim 13, wherein the characteristic information of the candidate path comprises at least one of security level information, comfort level information, entertainment level information.
15. The apparatus of claim 14, wherein, in a case where the feature information of the candidate path includes the security level information, the point of interest information of the point of interest includes at least one of business hours of the point of interest, a degree of aggregation of the point of interest with other points of interest, a relative area of the point of interest with the corresponding associated street; or (b)
In the case that the feature information of the candidate path includes the comfort level information, the interest point information of the interest point includes vegetation coverage information of the interest point; or (b)
In the case where the feature information of the candidate path includes the entertainment class information, the point of interest information of the point of interest includes classification information of the point of interest.
16. The apparatus of claim 11, wherein the user demand information is determined from path planning information; the path planning information comprises at least one of trip mode, trip time and interest point information around the path end point.
17. The apparatus of claim 11, wherein the user demand information is determined from user history information; the user history information comprises history path planning information corresponding to the user.
18. The apparatus of claim 10, wherein the path planning apparatus further comprises a preprocessing module; the preprocessing module comprises:
the information extraction unit is used for obtaining the interest point information of a plurality of interest points;
the binding unit is used for establishing a binding relation between the interest points and the streets according to the position information of the interest points and the associated streets;
and the information integration unit is used for determining the street information of the associated street according to the interest point information of at least one interest point which establishes a binding relation with the associated street aiming at any one of a plurality of associated streets.
19. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.
20. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-9.
21. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-9.
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