CN103344248A - Optimal path calculation method for vehicle navigation system - Google Patents
Optimal path calculation method for vehicle navigation system Download PDFInfo
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- CN103344248A CN103344248A CN2013102976235A CN201310297623A CN103344248A CN 103344248 A CN103344248 A CN 103344248A CN 2013102976235 A CN2013102976235 A CN 2013102976235A CN 201310297623 A CN201310297623 A CN 201310297623A CN 103344248 A CN103344248 A CN 103344248A
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Abstract
The invention relates to an optimal path calculation method for a vehicle navigation system. The method refers to an optimal path algorithm for the vehicle navigation system, the turning point of a grid map is identified and selected only in the execution process, the intermediate node from one turning point to an adjacent turning point can be ignored, and the number of nodes required to be treated is greatly reduced. The provided algorithm is simple, the grid map is not required to be subjected to pretreatment and extra computer storage space overhead, the optimal path can be efficiently searched, the vehicle navigation efficiency is improved, the vehicle path can be well planned in a complex map environment, and the optimal path is rapidly searched for the vehicle.
Description
Technical field
The present invention relates to a kind of best path algorithm of Vehicular navigation system, particularly a kind of optimal path finding method based on Vehicular navigation system under the complicated map environment of TPA* algorithm.
Background technology
Most important part is to determine the algorithm of optimal path in the Vehicular navigation system, is used for determining vehicle optimal path from the current location to the destination in the road traffic net.For most of Vehicular navigation systems, the optimal path between starting point and the terminal point is normally defined estimates the shortest path of traveling time.Determine that the main thought of optimal path is in the Vehicular navigation system: calculate the vehicle current location to the fullpath of destination with shortest path first, make that its estimated travel time is the shortest, at last the path that calculates is offered vehicle driver's reference.
Optimal path is to seek in the network node to a class problem of direct shortest path, normally adopts the method for graph theory and mathematical programming to carry out search to the path.At present, the optimal path problem is in various fields widespread uses such as computer science, operational research, geography information science.Comprise intelligent transportation system, Geographic Information System, path planning problem, computer network communication etc. concrete the application.
From the fifties in last century, the scholar in each field has carried out deep research to the optimal path problem.Based on the Bellman principle of optimality, node is to the dijkstra's algorithm of every other node optimal path in the solution node network, in the solution node network arbitrarily to the Floyd algorithm of shortest path between the node, and the basis of having established the meshed network best path algorithm for the classic algorithm of representative such as intelligent search A* algorithm.
In numerous best path algorithm, the A* algorithm is the searching algorithm of at present popular a kind of optimal path, compare with the Dijkstra scheduling algorithm, the A* algorithm has adopted the heuristic search strategy, in the process of search, the node of each search is estimated and calculated, avoid the blindness of route searching, can reduce the node that travels through in the search procedure to a great extent, thereby improved the execution speed of algorithm.
Can find by the comparison to present best path algorithm performance, in the time of in being applied in large complicated meshed network, many, arithmetic speed waits problem slowly even the A* algorithm that performance is more superior also exists the traversal number of nodes, in the time of in the Vehicular navigation system under being applied to complicated map environment, can not satisfy Vehicular navigation system well to the requirement of real-time, therefore be necessary to propose the problem that improved algorithm solves automobile navigation under the complicated map environment in fact.
Summary of the invention
The present invention proposes a kind of optimum path calculation method of Vehicular navigation system, to solve the problem of automobile navigation under the complicated map environment, by identification with reduce with the reach home node of required traversal of the path of the best and improve the speed of algorithm, having algorithm realizes simple, do not take the extra storage space of computing machine, do not need the advantages such as pre-service to map, can under complicated map environment, search out optimal path rapidly, vehicle is navigated.
The technical scheme that the present invention takes is may further comprise the steps:
Step 1: set up the network node grating map that two dimension is directionless, weight is identical, wherein, include 8 nodes among the neighborhood node set neighbors (n) of each network node n, according to the vehicle different geographic entitys of map of travelling, each node has and can pass through and the impassability two states, a node moves with oblique line by straight line and moves the adjacent node of dual mode arrival another one, and the distance between adjacent node is defaulted as 1;
Step 2: the adjacent node set neighbors (n) to node n deletes, purpose is the incoherent node x of optimal path that will determine with arriving target, to the different two kinds of situations of consideration that need of the direction of node n, be respectively that straight line moves with oblique line and moves according to father node p (n); In addition, if node n is starting point, because its father node is empty, so can't carry out deleting of adjacent node;
(1), straight line moves
In this case, to satisfying any node x(x ∈ neighbors (n) of constraint condition in the formula (1)) delete:
len(<p(n),…,x>\n)≤len(<p(n),n,x>) (1)
(2), oblique line moves
Delete that with above-mentioned straight line rule is similar, but under the situation that oblique line moves, to node x delete that restrictive condition is more strict, need satisfy the constraint condition in the formula (2):
len(<p(n),…,x>\n)<len(<p(n),n,x>) (2)
In two kinds of above-mentioned situations, all do not comprise obstacle nodes among the neighbors (n), be called the common adjacent node (Normal Neighbor) of node n this moment through the node that obtains after deleting; And when containing obstacle nodes among the neighbors (n), situation about can not delete non-common adjacent node fully can appear, claim that at this moment these nodes of not deleted are special joint (Special Neighbor); If be special joint a node x(x ∈ neighbors (n)), it should satisfy so: node x is not the ordinary node of node n, and satisfies the constraint condition in the formula (3).
len(<p(n),n,x>)<len(<p(n),…,x>\n) (3)
Step 3: carry out the search work to the path turning point, node n is to the moving direction of node x ∈ neighbor (n)
Be a key factor, turning point be defined as follows:
Node m is the descendant node of node n, and n to the direction of m is
Minimum k the unit of process moves back arrival m if n is in that this side up, namely
And satisfy one of following constraint condition, claim that then node m is the turning point of node n;
1). node m is terminal point;
2). having one in the adjacent node of node m at least is special joint;
3).
When being oblique line directions, there is a node
On the direction apart from m node k
iIndividual unit distance, and node p is a turning point that satisfies above-mentioned condition 1 or condition 2;
Step 4: will be stored among the array ProcessList according to definition turning point that obtain, that belong to node n in the step 3, arbitrary node x ∈ ProcessList is pending node, when inserting node in the ProcessList each time, all need to keep the order of ProcessList, it is the path cost value of first node among the ProcessList: i.e. travel distance minimum from starting point to this node, the path cost value maximum of last node, in algorithm circulation next time, first node that takes out among the ProcessList is handled;
Step 5: circulation is carried out above-mentioned steps two to step 4, as terminal point n
GoalWhen being inserted among the ProcessList, finish the search to optimal path, finish; From terminal point n
GoalBeginning is that father node adds among the array PathList of path successively with the node that continues before it, up to starting point n
StartAdd among the PathList, that preserves among the array PathList of path is all path nodes on the optimal path that searches out, and Vehicular navigation system can carry out real-time navigation work to the vehicle that travels on map according to this optimal path.
Compare with existing algorithm, the best path algorithm of a kind of Vehicular navigation system of the present invention is only identified and is chosen the turning point in the grating map in the process of carrying out, intermediate node from a turning point to its adjacent next turning point can be left in the basket, and then has reduced the number of nodes that needs processing in large quantities.The algorithm that the present invention proposes is simple, does not need grating map is carried out any pre-service and extra Computer Storage space expense, can high efficiencyly search out optimal path, improves the efficient of automobile navigation.Adopt the present invention, can well under complicated map environment, carry out the planning to vehicle route, seek optimal path for vehicle rapidly.
Description of drawings
Fig. 1 is the synoptic diagram in the isometric path that relates in the algorithm of the present invention;
Fig. 2 is the synoptic diagram of under different situations the neighborhood node being deleted in the algorithm of the present invention;
Fig. 3 is to the search synoptic diagram of turning point in the algorithm of the present invention.
Embodiment:
Below by specific instantiation and accompanying drawings embodiments of the present invention, those skilled in the art can understand other advantage of the present invention and effect easily by the content that this instructions discloses.The present invention also can be implemented or be used by other different instantiation, and the every details in this instructions also can be based on different viewpoints and application, carries out various modifications and change under the spirit of the present invention not deviating from.
Before specifically introducing the present invention, explanation earlier is the main central idea of the best path algorithm of a kind of Vehicular navigation system of the present invention down: by finding that to the A* Algorithm Analysis A* algorithm exists a large amount of isometric paths in the process of search optimal path.Definition to isometric path among the present invention is: if two paths have identical starting point and terminal point, and can obtain another paths by the composition subpath of a paths wherein being replaced reorganization, claim that so this two paths is isometric path.Several paths shown in Fig. 1 are isometric path each other, can obtain by observing, and each paths all is made up of the subpath of 9 vertical directions and 9 horizontal directions.
In order to reduce in the A* algorithm unnecessary search and the traversal in isometric path, further improve efficient and the travelling speed of algorithm, the present invention proposes a kind of TPA*(Turning Point) algorithm.The central idea of TPA* algorithm is to delete anyly can avoid a large amount of isometric paths in this way from the father node of present node with the adjacent node that the mode of the best arrives.In addition, in the TPA* algorithm, all pending nodes all are those nodes that direction turnover may take place on the working direction of path, and the part of nodes between two turnover nodes is not handled, and this number of nodes that just means the needs traversal is compared and can significantly be reduced with the A* algorithm.
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is explained in detail.
Step 1: in order to seek the optimal path of Vehicular navigation system, at first need to set up the concrete enforcement environment of algorithm of the present invention.The enforcement of the optimal algorithm of a kind of Vehicular navigation system of the present invention is to carry out in the identical network node grating map of the directionless weight of two dimension.Wherein, the neighborhood node set neighbors (n) of each network node n contains 8 nodes, and according to the vehicle different geographic entitys of map of travelling, each node can have and can pass through and the obstacle two states.Node can move by straight line and move dual mode with oblique line and arrive another node, and the distance between adjacent node is defaulted as 1.
Step 2: the adjacent node set neighbors (n) to node n deletes that purpose is the incoherent node x of optimal path that will determine with arriving target.In order to reach above-mentioned requirements, need the length of two class.paths be compared: π, this path is from the father node p (n) of node n, via node n and arrive node x; π ', this path is the father node p (n) from node n equally, but arrives node x without node n.It should be noted that the node that comprises in above-mentioned two paths is included among the set neighbors (n).To the different two kinds of situations of consideration that need of the direction of node n, be respectively that straight line moves with oblique line and moves according to father node p (n).In addition, if node n is starting point, because its father node is empty, so can't carry out deleting of adjacent node.
1, straight line moves
In this case, to satisfying any node x(x ∈ neighbors (n) of constraint condition in the formula (1)) delete:
len(<p(n),…,x>\n)≤len(<p(n),n,x>) (1)
Situation as shown in Fig. 2 (a), p (n)=7, all nodes except node x=2 all will be deleted.
2, oblique line moves
Delete that with above-mentioned straight line rule is similar, but under the situation that oblique line moves, to node x delete that restrictive condition is more strict, need satisfy the constraint condition in the formula (2):
len(<p(n),…,x>\n)<len(<p(n),n,x>) (2)
Situation as shown in Fig. 2 (c), p (n)=1, except node x=5, x=7, all nodes outside the x=8 all will be deleted.
The algorithm that relates among the present invention does not all comprise obstacle nodes among the neighbors (n) in two kinds of above-mentioned situations, be called the common adjacent node (Normal Neighbor) of node n this moment through the node that obtains after deleting.And when containing obstacle nodes among the neighbors (n), situation about can not delete non-common adjacent node fully can appear, claim that at this moment these nodes are special joint (Special Neighbor).If be special joint a node x(x ∈ neighbors (n)), should satisfy so: node x is not the ordinary node of node n, and satisfies the constraint condition in the formula (3).
len(<p(n),n,x>)<len(<p(n),…,x>\n) (3)
X=3 node among x=1 node among Fig. 2 (b) and Fig. 2 (d) all is the special joint that satisfies above-mentioned condition.
Algorithm involved in the present invention can obtain the neighborhood node set neighbor (n) of a node n after the work of having finished 8 neighborhood nodes around the node n of deleting.Consideration is under worst situation, and namely node n is the starting point n in path
StartThe time, the interstitial content among the set neighbor (n) is 8.Consider generalized case, and in the neighborhood of node n, do not have under the situation of special adjacent node (Special Neighbor) that the maximum node quantity among the set neighbor (n) is 1, and is 3 when oblique line moves when straight line moves; Exist under the situation of special joint, the maximum node quantity among the set neighbor (n) is 3 when straight line moves, and is 5 when oblique line moves.Through the neighborhood number of nodes after deleting significant decline has been arranged.
Step 3: in the follow-up work of algorithm of the present invention, not directly with the neighborhood node that obtains in the step 2 as next step pending node, but carry out search work to the path turning point.In the search of this step, node n is to the moving direction of node x ∈ neighbor (n)
It is the key factor that needs are considered.Algorithm involved in the present invention is as follows to definition and the search example of turning point:
Node m is the descendant node of node n, and n to the direction of m is
Minimum k the unit of process moves back arrival m if n is in that this side up, namely
And satisfy one of following constraint condition, claim that then node m is the turning point of node n.
1. node m is terminal point.
2. having one in the adjacent node of node m at least is special joint.
3.
When being oblique line directions, there is a node
On the direction apart from m node k
iIndividual unit distance, and node p is a turning point that satisfies above-mentioned condition 1 or condition 2.
Node m among Fig. 3 (a) is the turning point of node n, satisfies above-mentioned condition 2.Node m shown in Fig. 3 (b) is 3 the turning point of satisfying condition.Begin to move along oblique line directions from node n, up to running into node m, begin through k from m
i=2 sub-levels move and arrive node p, and the p point turning point (satisfying condition 2) that to be m order, therefore, node m is the turning point of node n.
Step 4: will obtain according to definition in the step 3, the turning point that belongs to node n is stored among the array ProcessList, and arbitrary node x ∈ ProcessList is pending node.When inserting node in the ProcessList each time, all need to keep the order of ProcessList, be path cost value (travel distance from starting point to this node) minimum of first node among the ProcessList, the path cost value maximum of last node.In algorithm circulation next time, first node that takes out among the ProcessList is handled.
Step 5: circulation is carried out above-mentioned steps two to step 4, as terminal point n
GoalWhen being inserted among the ProcessList, finish the search to optimal path, algorithm finishes.From terminal point n
GoalBeginning is that father node adds among the array PathList of path successively with the node that continues before it, up to starting point n
StartAdd among the PathList.That preserves among the array PathList of path is all path nodes on the optimal path that searches out.Vehicular navigation system can carry out real-time navigation work to the vehicle that travels on map according to this optimal path.
In sum, the best path algorithm of a kind of Vehicular navigation system of the present invention is only identified and is chosen the path turning point in the map in the process of carrying out, intermediate node from a turning point to its adjacent next turning point can be left in the basket, and then has reduced the number of nodes that needs processing in large quantities.The algorithm that the present invention proposes is simple, does not need map is carried out any pre-service and extra Computer Storage space expense, can high efficiencyly search out optimal path, improves the efficient of automobile navigation.Adopt the present invention, can well under complicated map environment, carry out the planning to vehicle route, seek optimal path for vehicle rapidly.
The above only is preferred implementation of the present invention; protection scope of the present invention is not limited in above-mentioned embodiment; every technical scheme that belongs to principle of the present invention all belongs to the protection domain of this aspect; for a person skilled in the art; some improvements and modifications of carrying out under the premise of not departing from the present invention, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (1)
1. the optimum path calculation method of a Vehicular navigation system is characterized in that comprising the following steps:
Step 1: set up the network node grating map that two dimension is directionless, weight is identical, wherein, include 8 nodes among the neighborhood node set neighbors (n) of each network node n, according to the vehicle different geographic entitys of map of travelling, each node has and can pass through and the impassability two states, a node moves with oblique line by straight line and moves the adjacent node of dual mode arrival another one, and the distance between adjacent node is defaulted as 1;
Step 2: the adjacent node set neighbors (n) to node n deletes, purpose is the incoherent node x of optimal path that will determine with arriving target, to the different two kinds of situations of consideration that need of the direction of node n, be respectively that straight line moves with oblique line and moves according to father node p (n); In addition, if node n is starting point, because its father node is empty, so can't carry out deleting of adjacent node;
(1), straight line moves
In this case, to satisfying any node x(x ∈ neighbors (n) of constraint condition in the formula (1)) delete:
len(<p(n),…,x>\n)≤len(<p(n),n,x>) (1)
(2), oblique line moves
Delete that with above-mentioned straight line rule is similar, but under the situation that oblique line moves, to node x delete that restrictive condition is more strict, need satisfy the constraint condition in the formula (2):
len(<p(n),…,x>\n)<len(<p(n),n,x>) (2)
In two kinds of above-mentioned situations, all do not comprise obstacle nodes among the neighbors (n), be called the common adjacent node (Normal Neighbor) of node n this moment through the node that obtains after deleting; And when containing obstacle nodes among the neighbors (n), situation about can not delete non-common adjacent node fully can appear, claim that at this moment these nodes of not deleted are special joint (Special Neighbor); If be special joint a node x(x ∈ neighbors (n)), it should satisfy so: node x is not the ordinary node of node n, and satisfies the constraint condition in the formula (3).
len(<p(n),n,x>)<len(<p(n),…,x>\n) (3)
Step 3: carry out the search work to the path turning point, node n is to the moving direction of node x ∈ neighbor (n)
Be a key factor, turning point be defined as follows:
Node m is the descendant node of node n, and n to the direction of m is
Minimum k the unit of process moves back arrival m if n is in that this side up, namely
And satisfy one of following constraint condition, claim that then node m is the turning point of node n;
1). node m is terminal point;
2). having one in the adjacent node of node m at least is special joint;
3).
When being oblique line directions, there is a node
Apart from ki unit distance of m node, and node p is a turning point that satisfies above-mentioned condition 1 or condition 2 on the direction;
Step 4: will be stored among the array ProcessList according to definition turning point that obtain, that belong to node n in the step 3, arbitrary node x ∈ ProcessList is pending node, when inserting node in the ProcessList each time, all need to keep the order of ProcessList, it is the path cost value of first node among the ProcessList: i.e. travel distance minimum from starting point to this node, the path cost value maximum of last node, in algorithm circulation next time, first node that takes out among the ProcessList is handled;
Step 5: circulation is carried out above-mentioned steps two to step 4, as terminal point n
GoalWhen being inserted among the ProcessList, finish the search to optimal path, finish; From terminal point n
GoalBeginning is that father node adds among the array PathList of path successively with the node that continues before it, up to starting point n
StartAdd among the PathList, that preserves among the array PathList of path is all path nodes on the optimal path that searches out, and Vehicular navigation system can carry out real-time navigation work to the vehicle that travels on map according to this optimal path.
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| CN104717278A (en) * | 2014-12-04 | 2015-06-17 | 广西蕴藏科技有限公司 | Mark position guiding method and system |
| CN104917835A (en) * | 2015-06-10 | 2015-09-16 | 广西蕴藏科技有限公司 | Mark position guidance system of small network traffic and guidance method therefor |
| CN105606113A (en) * | 2016-01-28 | 2016-05-25 | 福州华鹰重工机械有限公司 | Method and device for rapidly planning optimal path |
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