CN114279457B - Path planning method, device, equipment and readable storage medium - Google Patents
Path planning method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention provides a path planning method, a path planning device, path planning equipment and a readable storage medium. The method comprises the following steps: constructing a defined directed acyclic graph according to the starting point, the ending point, the class constraint and the ordering constraint; performing topological sorting according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point; deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set; and determining an optimal path based on the candidate path sequences and the effective interest point set. According to the invention, the optimal path is determined by comprehensively considering the starting point, the ending point, the category constraint, the ordering constraint and the preference constraint, so that the path planning problem with multiple constraint conditions is solved.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a path planning method, apparatus, device, and readable storage medium.
Background
In location-based services, shortest paths are an important issue, and in common path planning, starting and ending points are typically specified, and then the shortest paths are planned.
But in everyday life, for example, users want to find an optimal route through movie theatres, restaurants and banks; moreover, money is taken from banks before going to movie theatres and markets; in addition, the score of the restaurant must not be lower than 4.8 points, and the price per capita must not be higher than 60 yuan. The existing path planning method cannot solve the path planning problem, so a new path planning method is needed.
Disclosure of Invention
In order to solve the technical problems, the invention provides a path planning method, a path planning device, path planning equipment and a readable storage medium.
In a first aspect, the present invention provides a path planning method, including:
constructing a defined directed acyclic graph according to the starting point, the ending point, the class constraint and the ordering constraint;
performing topological sorting according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point;
deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set;
and determining an optimal path based on the candidate path sequences and the effective interest point set.
In a second aspect, the present invention also provides a path planning apparatus, including:
The building module is used for building a limited directed acyclic graph according to the starting point, the ending point, the category constraint and the ordering constraint;
the sequencing module is used for carrying out topological sequencing according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point;
the deleting module is used for deleting the interest points which do not accord with the preference constraint in the road network to obtain an effective interest point set;
and the determining module is used for determining an optimal path based on the candidate path sequences and the effective interest point set.
In a third aspect, the present invention also provides a path planning apparatus comprising a processor, a memory, and a path planning program stored on the memory and executable by the processor, wherein the path planning program, when executed by the processor, implements the steps of the path planning method as described above.
In a fourth aspect, the present invention also provides a readable storage medium having a path planning program stored thereon, wherein the path planning program, when executed by a processor, implements the steps of the path planning method as described above.
In the invention, a limited directed acyclic graph is constructed according to starting points, end points, category constraints and ordering constraints; performing topological sorting according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point; deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set; and determining an optimal path based on the candidate path sequences and the effective interest point set. According to the invention, the optimal path is determined by comprehensively considering the starting point, the ending point, the category constraint, the ordering constraint and the preference constraint, so that the path planning problem with multiple constraint conditions is solved.
Drawings
Fig. 1 is a schematic hardware structure of a path planning apparatus according to an embodiment of the present invention;
FIG. 2 is a flow chart of a first embodiment of the path planning method of the present invention;
FIG. 3 is a schematic diagram of an initialized BDAG;
FIG. 4 is a schematic diagram of a BDAG under construction;
FIG. 5 is a schematic diagram of a constructed BDAG;
FIG. 6 is a schematic diagram of a refinement flow chart of step S40 in FIG. 2;
FIG. 7 is a flow chart of a second embodiment of the path planning method of the present invention;
FIG. 8 is a schematic diagram of the refinement procedure of step S50 in FIG. 7;
fig. 9 is a schematic functional block diagram of an embodiment of a path planning apparatus.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In a first aspect, an embodiment of the present invention provides a path planning apparatus, which may be a personal computer (personal computer, PC), a notebook computer, a server, or the like, having a data processing function.
Referring to fig. 1, fig. 1 is a schematic hardware structure of a path planning apparatus according to an embodiment of the present invention. In an embodiment of the present invention, the path planning apparatus may include a processor 1001 (e.g., central processor Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein the communication bus 1002 is used to enable connected communications between these components; the user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard); the network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., WIreless-FIdelity, WI-FI interface); the memory 1005 may be a high-speed random access memory (random access memory, RAM) or a stable memory (non-volatile memory), such as a disk memory, and the memory 1005 may alternatively be a storage device independent of the processor 1001. Those skilled in the art will appreciate that the hardware configuration shown in fig. 1 is not limiting of the invention and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
With continued reference to fig. 1, an operating system, a network communication module, a user interface module, and a path planning program may be included in the memory 1005, which is one type of computer storage medium in fig. 1. The processor 1001 may call a path planning program stored in the memory 1005, and execute the path planning method provided by the embodiment of the present invention.
In a second aspect, an embodiment of the present invention provides a path planning method.
In an embodiment, referring to fig. 2, fig. 2 is a flow chart of a first embodiment of a path planning method according to the present invention. As shown in fig. 2, the path planning method includes:
s10, constructing a limited directed acyclic graph according to a starting point, an ending point, category constraints and ordering constraints;
in this embodiment, for example, the user starts from the starting point vs, goes to the bank, restaurant, movie theater, post office, and mall, and finally goes to the ending point ve. The banks, restaurants, movie theatres, post offices and shops are 5 category nodes, which are respectively represented by tag1, tag2, tag3, tag4 and tag5, and category constraint tc= (tag 1, tag2, tag3, tag4 and tag 5). The sorting constraint oc= { < tag2, tag3> and < tag2, tag4> } is that the customer needs to go to the bank before going to the restaurant and needs to go to the bank before going to the post office.
First, let the starting point vs point to all class nodes respectively, and all class nodes point to the end point ve, get the initialized defined directed acyclic graph BDAG. Referring to fig. 3, fig. 3 is a schematic diagram of an initialized BDAG.
Then, traversing all elements in the sorting constraint oc, and when the elements are not empty, taking out the elements, for example, for the elements < tag2, tag3> in the sorting constraint oc, firstly setting a parent node set of tag3 as an empty set, and traversing all child node sets in tag 2; if the sub-node set of tag2 contains the end point ve, then delete ve from the set, add tag3 to the sub-node set of tag2, and finally delete < tag2, tag3> from the ordering constraint oc, to obtain BDAG in construction. Referring to fig. 4, fig. 4 is a schematic diagram of a BDAG under construction.
Similarly, for element < tag2, tag4> in ordering constraint oc, first the parent set of nodes for tag4 is set to an empty set while traversing all child nodes in tag 2. If the sub-node set of the tag2 contains the end point ve, deleting ve from the set, adding the tag4 into the sub-node set of the tag2, deleting the < tag2, the tag4> from the ordering constraint set oc, and repeatedly executing the operations until the ordering constraint oc is empty, thus obtaining the BDAG after construction. Referring to fig. 5, fig. 5 is a schematic diagram of a BDAG constructed in the above manner.
Step S20, topological sorting is carried out according to the limited directed acyclic graph, a plurality of candidate path sequences are obtained, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point;
in this embodiment, taking fig. 5 as an example of the defined directed acyclic graph, performing topological ordering on the BDAG may obtain 16 candidate path sequences:
(vs，tag1，tag2，tag3，tag4，tag5，ve)
(vs，tag1，tag2，tag4，tag3，tag5，ve)
(vs，tag1，tag2，tag5，tag3，tag4，ve)
(vs，tag1，tag2，tag5，tag4，tag3，ve)
(vs，tag2，tag1，tag3，tag4，tag5，ve)
(vs，tag2，tag1，tag4，tag3，tag5，ve)
(vs，tag2，tag1，tag5，tag3，tag4，ve)
(vs，tag2，tag1，tag5，tag4，tag3，ve)
(vs，tag5，tag1，tag2，tag3，tag4，ve)
(vs，tag5，tag1，tag2，tag4，tag3，ve)
(vs，tag5，tag2，tag1，tag3，tag4，ve)
(vs，tag5，tag2，tag1，tag4，tag3，ve)
(vs，tag5，tag2，tag3，tag1，tag4，ve)
(vs，tag5，tag2，tag3，tag4，tag1，ve)
(vs，tag5，tag2，tag4，tag1，tag3，ve)
(vs，tag5，tag2，tag4，tag3，tag1，ve)
if the topology ordering is done with only 5 places the user wants to go, then we get 5-! =120 candidate path sequences, it can be seen that by constructing the BDAG, unnecessary candidate path sequences are greatly reduced, thereby reducing the time required to determine the optimal path.
Step S30, deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set;
in this embodiment, the preference constraint is formulated according to actual demands, for example, the preference constraint is that the restaurant score must not be lower than 4.8 points and the price per capita must not be higher than 60 yuan; the score of the cinema is not lower than 4.8 points, and the price per person is not higher than 40 yuan. Based on the preference constraint, deleting restaurant interest points with scores lower than 4.8 points or people average prices higher than 60 yuan in the road network, and deleting cinema interest points with scores lower than 4.8 points or people average prices higher than 40 yuan in the road network to obtain an effective interest point set.
Specifically, in this embodiment, a CAIR-tree index structure is provided, where each leaf node in the CAIR-tree represents each object contained in the leaf node by a triplet (pid, tag, { < A1, V1>, …, < Ai, vi > }), where pid is an id of a point of interest in the road network, tag is key information (e.g. category information) of a point of interest in the road network, < a, V > is an attribute and attribute value pair, a represents an attribute of the point of interest p corresponding to the tag, and V is a corresponding attribute value; the non-leaf nodes are represented as a triplet (ct, rect, akl), where ct is represented as a pointer to its child node, rect is the minimum bounding rectangle of that node, akl is the set of key descriptions and the set of attribute descriptions for all of its child nodes, organized in a reverse file. The inverted file is composed of two inverted lists, keyword list tag1: ({ 1}, { R1, …, ri }) and attribute list Ai: ({ tag1, …, tagi }, { V1, …, vi }). Wherein the keyword list tag1: ({ 1}, { R1, …, ri }) 1} indicates that the non-leaf node contains the key tag1; { R1, …, ri } means that the keyword tag1 is contained in each of the regions R1, …, ri. Attribute list Ai: in { tag1, tag2} in { tag1, …, tag }, { V1, …, vi }) represents that the keywords tag1 to tag contain the attribute Ai; if the attribute is a numerical attribute, vi in { V1, …, vi } is V2, which represents the minimum V1 and the maximum V2 of the numerical attribute in the node, and if the attribute is a non-numerical attribute, { V1, …, vi } is the set of all values of the non-numerical attribute in the node region.
First two priority queues U, U' and an array P are initialized cand (wherein U is used to store candidate non-leaf nodes, U' is used to store candidate leaf nodes, P cand Is an effective point of interest set. Then, the process is carried out, the root node of the CAIR-tree is added to the queue U. Next, processing is performed in the CAIR-tree from the root node, and the first element of the queue is dequeued and saved with e when the queue U is not empty. If the current node e is a non-leaf node and accords with the category constraint and preference constraint of the query Q (vs, ve, tc, oc, pc), traversing the node e, and sequentially examining each sub-node e': if e 'is a non-leaf node, it is added to queue U, otherwise it is added to queue U'. Then judging the queue U ', if the queue U ' is not empty, dequeuing the first queue element of the queue U ' in sequence, and marking the dequeued element as T Node When dequeued element T Node In the event that the preference constraint is met, add it to array P cand Is a kind of medium. Finally, return the obtained P cand And (5) completing the pruning process.
And step S40, determining an optimal path based on the candidate path sequences and the effective interest point set.
In this embodiment, a path is constructed based on a plurality of candidate path sequences and an effective interest point set, and an optimal path is selected based on the weights of the constructed paths.
Further, in an embodiment, referring to fig. 6, fig. 6 is a schematic diagram of a refinement process of step S40 in fig. 2. As shown in fig. 6, step S40 includes:
determining a shortest path corresponding to a candidate path sequence based on the effective interest point set, and taking the weight of the shortest path as a threshold value;
selecting a first interest point corresponding to a first category node in another candidate path sequence from the effective interest point set, updating the weight of the other candidate path sequence according to the distance between the first interest point and the last position point, and judging whether the updated weight is larger than a threshold value;
if the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the other candidate path sequence is completed or not;
if the plurality of category nodes in the other candidate path sequence are not traversed, taking the next category node as a first category node, and returning to the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set;
if the traversal of the plurality of category nodes in the other candidate path sequence is completed, taking the latest weight of the other candidate path sequence as a threshold value;
detecting whether the traversal of a plurality of candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
If the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
if the updated weight is greater than the threshold, detecting whether the traversal of the candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
and if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as the optimal path.
In this embodiment, for example, the several candidate path sequences include:
candidate path sequence 1: starting point-bank-restaurant-cinema-ending point;
candidate path sequence 2: starting point-bank-cinema-restaurant-ending point;
candidate path sequence 3: starting point-cinema-bank-restaurant-ending point;
the banks in the effective interest point set are bank 1, bank 2 and bank 3, the restaurants are restaurant 1 and restaurant 3, and the movie theatre is movie theatre 1.
Firstly, determining a shortest path corresponding to a candidate path sequence based on a valid interest point set, and taking the weight of the shortest path as a threshold value. The candidate path sequence may be any one of candidate path sequences 1 to 3, and taking the candidate path sequence 1 as an example here, the shortest path 1 corresponding to the candidate path sequence 1 is obtained, and the weight 1 of the shortest path 1 is taken as a threshold. Specifically, the length of the shortest path 1 may be a weight 1.
The other candidate path sequence may be any one of candidate path sequences 2 to 3, taking the candidate path sequence 2 as an example, where the first category node in the candidate path sequence 2 is a bank, the optional interest points include a bank 1, a bank 2 and a bank 3, if the distance between the bank 1 and the starting point is closest, the weight of the candidate path sequence 2 is updated by the distance between the bank 1 and the last position point (i.e. the starting point), and whether the updated weight is greater than a threshold value is determined. The updated weight at this time may be the starting point→the length of bank 1.
If the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the candidate path sequence 2 is completed;
since two category nodes of the movie theatre and the restaurant are not traversed at this time, the next category node (namely the movie theatre) is taken as the first category node, and the step of selecting the first interest point corresponding to the first category node in another candidate path sequence from the effective interest point set is returned;
when the first category node is a cinema, the optional interest point is only cinema 1, the weight of the candidate path sequence 2 is updated according to the distance between the cinema 1 and the last position point (namely, the bank 1), and whether the updated weight is larger than a threshold value is judged. The updated weight at this time may be the length of the start point → bank 1 → movie theater 1.
If the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the candidate path sequence 2 is completed;
since the class node of the restaurant is not traversed, the next class node (namely the restaurant) is taken as the first class node, and the step of selecting the first interest point corresponding to the first class node in another candidate path sequence from the effective interest point set is returned;
when the first category node is a restaurant, the selectable interest points are restaurant 1 and restaurant 3, if the distance between the restaurant 3 and the movie theater 1 is nearest, the weight of the candidate route sequence 2 is updated according to the distance between the restaurant 3 and the last location point (namely, movie theater 1), and whether the updated weight is larger than a threshold value is judged. The updated weight at this time may be the length of the start point→bank 1→movie theater 1→restaurant 3→end point.
If the updated weight is smaller than the threshold value and the traversal of the plurality of category nodes in the candidate path sequence 2 is completed, taking the latest weight of the candidate path sequence 2 as the threshold value;
detecting whether the traversal of a plurality of candidate path sequences is completed;
if the candidate path sequence 3 is not traversed, returning to the step of selecting a first interest point corresponding to a first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence 3 as the other candidate path sequence;
And if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as the optimal path.
If the weight value of the other candidate path sequence after the weight value update is greater than a threshold value, detecting whether the traversal of a plurality of candidate path sequences is completed or not;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
and if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as the optimal path.
Further, in an embodiment, the step of determining the shortest path corresponding to a candidate path sequence based on the valid interest point set includes:
determining the category of a first category node in a candidate path sequence;
selecting selectable interest points corresponding to the categories from the effective interest point set;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
If the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned.
In this embodiment, for example, the several candidate path sequences include:
candidate path sequence 1: starting point-bank-restaurant-cinema-ending point;
candidate path sequence 2: starting point-bank-cinema-restaurant-ending point;
candidate path sequence 3: starting point-cinema-bank-restaurant-ending point;
the banks in the effective interest point set are bank 1, bank 2 and bank 3, the restaurants are restaurant 1 and restaurant 3, and the movie theatre is movie theatre 1.
Taking a candidate path sequence 1 as an example, wherein the class of a first class node in the candidate path sequence 1 is a bank, and the selectable interest points corresponding to the bank selected from the effective interest point set comprise a bank 1, a bank 2 and a bank 3, wherein the bank 1 is nearest to the last position point (namely a starting point), and the bank 1 is taken as a target interest point;
at this time, if two kinds of nodes, namely a restaurant and a movie theater, are not traversed in the candidate path sequence 1, the next kind of node (namely the restaurant) is taken as the first kind of node, and the step of determining the kind of the first kind of node in the candidate path sequence is returned;
When the first category node is a restaurant, and the category of the first category node in the candidate path sequence 1 is the restaurant, the selectable interest points corresponding to the restaurant selected from the effective interest point set comprise a restaurant 1 and a restaurant 3, wherein the restaurant 3 is closest to the last position point (namely, the bank 1), and the restaurant 3 is taken as a target interest point;
at this time, if the class node of the movie theatre is not traversed in the candidate path sequence 1, the next class node (i.e. movie theatre) is taken as the first class node, and the step of determining the class of the first class node in the candidate path sequence is returned;
when the first category node is a cinema, and the category of the first category node in the candidate path sequence 1 is the cinema, only the cinema 1 is selected from the selectable interest points corresponding to the cinema selected from the effective interest point set, and the cinema 1 is taken as the target interest point;
at this time, when the traversal of the plurality of class nodes in the candidate path sequence 1 is completed, a path formed by a start point, all target interest points and an end point is taken as a shortest path, wherein the target interest point determined first in the shortest path is adjacent to the start point, the target interest point determined last is adjacent to the end point, and all the target interest points are ordered according to a determined order, namely, the shortest path corresponding to the candidate path sequence 1 is:
Start point → bank 1 → restaurant 3 → movie theater 1 → end point.
In the embodiment, a defined directed acyclic graph is constructed according to starting points, ending points, category constraints and ordering constraints; performing topological sorting according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point; deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set; and determining an optimal path based on the candidate path sequences and the effective interest point set. According to the embodiment, the optimal path is determined by comprehensively considering the starting point, the ending point, the category constraint, the ordering constraint and the preference constraint, so that the path planning problem with multiple constraint conditions is solved.
Further, in an embodiment, referring to fig. 7, fig. 7 is a flow chart of a second embodiment of the path planning method according to the present invention. As shown in fig. 7, after step S20, further includes:
step S50, obtaining the shortest path corresponding to each candidate path sequence based on preference constraint and a plurality of candidate path sequences;
in this embodiment, the shortest path corresponding to each candidate path sequence is constructed based on a plurality of candidate path sequences and preference constraint, and an optimal path is selected based on the weight of the constructed path.
Further, in an embodiment, referring to fig. 8, fig. 8 is a schematic diagram of a refinement process of step S50 in fig. 7. As shown in fig. 8, step S50 includes:
determining the category of a first category node in a candidate path sequence;
selecting interest points corresponding to the categories from a road network;
selecting selectable interest points meeting preference constraint from interest points corresponding to the categories;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned;
if the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
Detecting whether the traversal of a plurality of candidate path sequences is finished or not;
if the plurality of candidate path sequences are not traversed, taking one candidate path sequence which is not traversed as one candidate path sequence, and returning to the step of determining the category of the first category node in the candidate path sequence.
In this embodiment, for example, the several candidate path sequences include:
candidate path sequence 1: starting point-bank-restaurant-cinema-ending point;
candidate path sequence 2: starting point-bank-cinema-restaurant-ending point;
candidate path sequence 3: starting point-cinema-bank-restaurant-ending point;
banks in the road network include bank 1, bank 2, and bank 3, restaurants include restaurant 1, restaurant 2, and restaurant 3, and movie theatres include movie theatre 1 and movie theatre 2.
The preference constraints are: the bank contains no less than 20 counters, the restaurant score is no less than 4.8 points, and the cinema score is no less than 4.8 points.
Taking a candidate path sequence as any one of candidate path sequences 1-3, taking a candidate path sequence as a candidate path sequence 1 as an example, and taking the class of a first class node in the candidate path sequence 1 as a bank, selecting interest points corresponding to the bank from a road network, wherein the interest points comprise a bank 1, a bank 2 and a bank 3;
If the number of counters of the bank 1 is 15, the number of counters of the bank 2 is 25, and the number of counters of the bank 3 is 20. The selectable points of interest that meet the preference constraints include bank 2 and bank 3.
If the bank 2 is closest to the last location point (i.e. the starting point), the bank 2 is taken as the target interest point.
At this time, two kinds of nodes, namely a restaurant and a movie theatre, in the candidate path sequence 1 are not traversed, and the next kind of node restaurant is taken as a first kind of node, and the step of determining the kind of the first kind of node in the candidate path sequence is returned;
at this time, if the class of the first class node in the candidate path sequence 1 is a restaurant, selecting the interest points corresponding to the restaurant from the road network to include restaurant 1, restaurant 2 and restaurant 3;
if the score of restaurant 1 is 5.0 points, the score of restaurant 2 is 4.0 points, and the score of restaurant 3 is 3.0 points. Then the selectable points of interest that meet the preference constraints include restaurant 1. The optional point of interest closest to the last location point (i.e., bank 2) is restaurant 1, restaurant 1 is the target point of interest.
At this time, if the class node of the cinema is not traversed in the candidate path sequence 1, the next class node cinema is taken as the first class node, and the step of determining the class of the first class node in the candidate path sequence is returned;
At this time, if the class of the first class node in the candidate path sequence 1 is a movie theater, selecting a point of interest corresponding to the movie theater from the road network, wherein the point of interest comprises movie theater 1 and movie theater 2;
if the score of cinema 1 is 5.0 points, the score of cinema 2 is 4.9 points. The selectable points of interest that meet the preference constraints include movie theatre 1 and movie theatre 2.
If movie theatre 2 is closest to the last location point (i.e., restaurant 1), movie theatre 2 is targeted for the point of interest.
At this time, when the traversal of each category node in the candidate path sequence 1 is completed, taking a path formed by a starting point, all target interest points and an end point as a shortest path, wherein the target interest point which is determined first in the shortest path is adjacent to the starting point, the target interest point which is determined last is adjacent to the end point, and all target interest points are ordered according to a determined sequence; for example, the shortest path of candidate path sequence 1 is:
start point → bank 2 → restaurant 1 → movie theater 2 → end point.
At this time, there are candidate path sequences 2 and 3 that are not traversed, and a candidate path sequence (for example, candidate path sequence 2) that is not traversed is used as a candidate path sequence, and the step of determining the category of the first category node in the candidate path sequence is returned, so as to obtain the shortest path of the candidate path sequence 2.
At this time, if the candidate path sequence 3 is not traversed, a candidate path sequence (i.e. candidate path sequence 3) is used as a candidate path sequence, and the step of determining the category of the first category node in the candidate path sequence is returned, so as to obtain the shortest path of the candidate path sequence 3.
Thus, the shortest path corresponding to each candidate path sequence can be obtained.
Step S60, taking the shortest path with the smallest weight as the optimal path.
In this embodiment, the weight of each shortest path is compared, and the shortest path with the smallest weight is taken as the optimal path. The shortest path length may be the shortest path weight.
In a third aspect, an embodiment of the present invention further provides a path planning apparatus.
In an embodiment, referring to fig. 9, fig. 9 is a schematic diagram of functional modules of an embodiment of a path planning apparatus. As shown in fig. 9, the path planning apparatus includes:
a building module 10 for building a defined directed acyclic graph according to start, end, class constraints, and ordering constraints;
the sorting module 20 is configured to perform topological sorting according to the defined directed acyclic graph, so as to obtain a plurality of candidate path sequences, where a first point of each candidate path sequence is the start point, and a last point is the end point;
The deleting module 30 is configured to delete points of interest in the road network that do not conform to the preference constraint, so as to obtain an effective point of interest set;
a determining module 40, configured to determine an optimal path based on the candidate path sequences and the valid interest point set.
Further, in an embodiment, the determining module 40 is configured to:
determining a shortest path corresponding to a candidate path sequence based on the effective interest point set, and taking the weight of the shortest path as a threshold value;
selecting a first interest point corresponding to a first category node in another candidate path sequence from the effective interest point set, updating the weight of the other candidate path sequence according to the distance between the first interest point and the last position point, and judging whether the updated weight is larger than a threshold value;
if the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the other candidate path sequence is completed or not;
if the plurality of category nodes in the other candidate path sequence are not traversed, taking the next category node as a first category node, and returning to the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set;
if the traversal of the plurality of category nodes in the other candidate path sequence is completed, taking the latest weight of the other candidate path sequence as a threshold value;
Detecting whether the traversal of a plurality of candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
if the updated weight is greater than the threshold, detecting whether the traversal of the candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
and if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as the optimal path.
Further, in an embodiment, the determining module 40 is configured to:
determining the category of a first category node in a candidate path sequence;
selecting selectable interest points corresponding to the categories from the effective interest point set;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
Detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned.
Further, in an embodiment, the path planning further includes:
the shortest path construction module is used for obtaining a shortest path corresponding to each candidate path sequence based on preference constraint and a plurality of candidate path sequences;
and the selecting module is used for taking the shortest path with the smallest weight as the optimal path.
Further, in an embodiment, the shortest path building module is configured to:
determining the category of a first category node in a candidate path sequence;
selecting interest points corresponding to the categories from a road network;
Selecting selectable interest points meeting preference constraint from interest points corresponding to the categories;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned;
if the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
detecting whether the traversal of a plurality of candidate path sequences is finished or not;
if the plurality of candidate path sequences are not traversed, taking one candidate path sequence which is not traversed as one candidate path sequence, and returning to the step of determining the category of the first category node in the candidate path sequence.
The function implementation of each module in the path planning device corresponds to each step in the path planning method embodiment, and the function and implementation process of each module are not described in detail herein.
In a fourth aspect, embodiments of the present invention also provide a readable storage medium.
The readable storage medium of the present invention stores a path planning program, wherein the path planning program, when executed by a processor, implements the steps of the path planning method as described above.
The method implemented when the path planning procedure is executed may refer to various embodiments of the path planning method of the present invention, and will not be described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising several instructions for causing a terminal device to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (6)
1. A path planning method, characterized in that the path planning method comprises:
Constructing a defined directed acyclic graph according to the starting point, the ending point, the class constraint and the ordering constraint;
performing topological sorting according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point;
deleting the interest points which do not accord with preference constraint in the road network to obtain an effective interest point set;
determining an optimal path based on the candidate path sequences and the effective interest point set;
the step of determining an optimal path based on the candidate path sequences and the effective interest point set comprises the following steps:
determining a shortest path corresponding to a candidate path sequence based on the effective interest point set, and taking the weight of the shortest path as a threshold value;
selecting a first interest point corresponding to a first category node in another candidate path sequence from the effective interest point set, updating the weight of the other candidate path sequence according to the distance between the first interest point and the last position point, and judging whether the updated weight is larger than a threshold value;
if the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the other candidate path sequence is completed or not;
If the plurality of category nodes in the other candidate path sequence are not traversed, taking the next category node as a first category node, and returning to the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set;
if the traversal of the plurality of category nodes in the other candidate path sequence is completed, taking the latest weight of the other candidate path sequence as a threshold value;
detecting whether the traversal of a plurality of candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
if the updated weight is greater than the threshold, detecting whether the traversal of the candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
If the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
the step of determining the shortest path corresponding to a candidate path sequence based on the effective interest point set comprises the following steps:
determining the category of a first category node in a candidate path sequence;
selecting selectable interest points corresponding to the categories from the effective interest point set;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned.
2. The path planning method of claim 1 wherein after the step of topologically ordering according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein a first point of each candidate path sequence is the start point and a last point is the end point, further comprising:
obtaining the shortest path corresponding to each candidate path sequence based on preference constraint and a plurality of candidate path sequences;
and taking the shortest path with the smallest weight as the optimal path.
3. The path planning method of claim 2 wherein the step of deriving a shortest path for each candidate path sequence based on the preference constraint and the plurality of candidate path sequences comprises:
determining the category of a first category node in a candidate path sequence;
selecting interest points corresponding to the categories from a road network;
selecting selectable interest points meeting preference constraint from interest points corresponding to the categories;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned;
If the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
detecting whether the traversal of a plurality of candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, taking one candidate path sequence which is not traversed as one candidate path sequence, and returning to the step of determining the category of the first category node in the candidate path sequence.
4. A path planning apparatus, characterized in that the path planning apparatus comprises:
the building module is used for building a limited directed acyclic graph according to the starting point, the ending point, the category constraint and the ordering constraint;
the sequencing module is used for carrying out topological sequencing according to the defined directed acyclic graph to obtain a plurality of candidate path sequences, wherein the first point of each candidate path sequence is the starting point, and the last point is the end point;
the deleting module is used for deleting the interest points which do not accord with the preference constraint in the road network to obtain an effective interest point set;
The determining module is used for determining an optimal path based on the candidate path sequences and the effective interest point set;
the determining module is used for:
determining a shortest path corresponding to a candidate path sequence based on the effective interest point set, and taking the weight of the shortest path as a threshold value;
selecting a first interest point corresponding to a first category node in another candidate path sequence from the effective interest point set, updating the weight of the other candidate path sequence according to the distance between the first interest point and the last position point, and judging whether the updated weight is larger than a threshold value;
if the updated weight is smaller than the threshold value, detecting whether the traversal of the plurality of category nodes in the other candidate path sequence is completed or not;
if the plurality of category nodes in the other candidate path sequence are not traversed, taking the next category node as a first category node, and returning to the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set;
if the traversal of the plurality of category nodes in the other candidate path sequence is completed, taking the latest weight of the other candidate path sequence as a threshold value;
detecting whether the traversal of a plurality of candidate path sequences is completed;
If the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
if the updated weight is greater than the threshold, detecting whether the traversal of the candidate path sequences is completed;
if the plurality of candidate path sequences are not traversed, returning the step of selecting the first interest point corresponding to the first category node in the other candidate path sequence from the effective interest point set by taking the candidate path sequence which is not traversed as the other candidate path sequence;
if the traversal of the candidate path sequences is completed, taking the shortest path corresponding to the threshold value as an optimal path;
the determining module is used for:
determining the category of a first category node in a candidate path sequence;
selecting selectable interest points corresponding to the categories from the effective interest point set;
taking the selectable interest point closest to the last position point in the selectable interest points as a target interest point;
detecting whether traversing of a plurality of category nodes in a candidate path sequence is completed or not;
If the traversal of a plurality of category nodes in a candidate path sequence is completed, taking a path formed by the starting point, all target interest points and the end point as a shortest path, wherein the target interest point which is determined firstly in the shortest path is adjacent to the starting point, the target interest point which is determined finally is adjacent to the end point, and all target interest points are ordered according to a determined sequence;
if the plurality of category nodes in the candidate path sequence are not traversed, the next category node is taken as the first category node, and the step of determining the category of the first category node in the candidate path sequence is returned.
5. A path planning device comprising a processor, a memory, and a path planning program stored on the memory and executable by the processor, wherein the path planning program, when executed by the processor, implements the steps of the path planning method of any one of claims 1 to 3.
6. A readable storage medium, wherein a path planning program is stored on the readable storage medium, wherein the path planning program, when executed by a processor, implements the steps of the path planning method of any one of claims 1 to 3.
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