CN106403976A - Dijkstra optimal traffic path planning method and system based on impedance matching - Google Patents
Dijkstra optimal traffic path planning method and system based on impedance matching Download PDFInfo
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Abstract
The invention discloses a Dijkstra optimal traffic path planning method and system based on impedance matching. The method comprises the following steps: obtaining sets of all directed segmental arcs within a preset scope; acquiring a time cost of all directed segmental arcs by a Dijkstra optimal path algorithm blended with traffic impedance; and taking a set of directed segmental arcs which has a shortest time cost from an original point to a terminal point as a final result, namely an optimal path set, to output. The invention can solve the technical problem that the shortest path obtained through a conventional Dijkstra algorithm lacks practical values and meanings.
Description
Technical field
The invention belongs to Dijkstra optimized algorithm technical field is and in particular to a kind of Dijkstra based on impedance matching
Optimum traffic route method and system for planning.
Background technology
When traditional dijkstra's algorithm is used for huge traffic networking, amount of calculation is very huge, and time complexity is very big,
Search efficiency is very low.For complicated traffic networking, it is not necessarily using the shortest path that dijkstra's algorithm calculates
Shortest path, because road quality, jam situation etc. lead to traffic route to there is certain traffic impedance, and then leads to this algorithm to be asked
The shortest path taking lacks real value and meaning；How to work out a kind of method and system that can solve the problem that the problems referred to above becomes
Those skilled in the art problem demanding prompt solutions.
Content of the invention
In view of this, embodiments provide a kind of optimum traffic route planning of the Dijkstra based on impedance matching
Method and system, for solving, the shortest path that traditional dijkstra's algorithm is tried to achieve lacks real value and the technology of meaning is asked
Topic.
The invention provides a kind of Dijkstra optimum traffic route planing method based on impedance matching, including step：
Ask for the set of all oriented segmental arcs in preset range；
The time obtaining all oriented segmental arcs by merging the Dijkstra optimal path algorithm of traffic impedance spends；
In taking from source point to terminal, the time spends oriented segmental arc set the shortest to export as final result, i.e. optimal path
Set.
Further, the described Dijkstra optimal path algorithm by merging traffic impedance obtains all oriented segmental arcs
The step that time spends includes：
If S is the set of the segmental arc having tried to achieve optimal path, A is the section collection in urban road network in preset range
Close；The initial optimal path time is made to spend k (r0)=0；By segmental arc r0Put in S；Make k (ri)=+ ∞, ri∈A-S；
Calculate all oriented arc-segment time with source point s as starting point to spend, obtain k (ri)=k (r0)+tsi, wherein tsi
Represent the traffic time resistance value from s to i, obtain k (r*)=min { k (ri)},ri=<s,i>；Then by arc r*Put in S；As
This, obtain first node h (r*)=s, end-node f (r*)=i, optimal path sequence node Pi=(s, f (r*))；
Calculate with segmental arc r*The time that all oriented segmental arc for starting point is put at end spends；First according to segmental arc r*With each
Bar segmental arc r to be accessedjDirection of travel carry out the judgement of steering direction, and consider intersection delay；Then obtain k (rj)=
min{k(r*)+tij；k(rj), wherein tijRepresent the traffic time resistance value from i to j；Last k (r*)=min { k (rj), will
Segmental arc r*Put in S, obtain this segmental arc front nodal point h (r*)=i, posterior nodal point f (r*)=j, optimal path sequence node Pj=Pi+f
(r*)；
Judge whether A is equal to S, that is, judge whether the section set A in urban road network in preset range all comprises
In the set S of the segmental arc trying to achieve optimal path；
If A=S, proceed to the step exporting final result；If A ≠ S, proceed to calculating with segmental arc r*End is put as starting point
All oriented segmental arc time spend step be further continued for；
Output final result；If k is (r*)<+ ∞, then k (r*) for optimal path required cost time, PjFor optimum
Set of paths.In this programme, S is the set of the oriented segmental arc to obtain optimal path, from the beginning of source point, initially only comprises in S
Source point s, is spent the time to be 0, is outwards extended layer by layer, the oriented segmental arc in A is calculated and being added progressively centered on source point s
Enter in S, when oriented segmental arc all of from source point to terminal is all obtained optimal path, the optimal path collection from source point to terminal
Close and also just obtained；Wherein, the calculating of the optimal path main time considering to spend in segmental arc and crossing, the time spends
The shortest as optimal path, rather than shortest path.
Further, described traffic time resistance value includes section time impedance value and intersection time impedance value；
Wherein, traffic time resistance value tijIncluding section time impedance value yijWith intersection time impedance value dij；
Described yijTime required for vehicle travels between any two-way section i and j；dijRepresent that intersection is spent
Time.Certainly, this tsiTry to achieve and tijSimilar；Many times, shortest path is not optimal path, particularly, for example
Exist in the case of no through traffic in short path, we pass through this shortest path and reach home to need the time spending to be infinity
, be at this time accomplished by considering traffic time resistance value, and traffic time resistance value include sections of road required spend when
Between, and by the crossedpath required time spending.
Further, try to achieve described section time impedance value yijFunction expression be referred to as：
In formula
ta(0)：The average time that vehicle on a of section travels in the case of without hindrance；
ea：The traffic capacity of section a；
qa：Traffic flow on a of section；
α、β：Parameter to be calibrated.In vehicle in the case of not having traffic to hinder, running time is into operating range
The relation of direct ratio, but in actual traffic route, the traveling that vehicle can not possibly be without hindrance.So running time and row on road
Sail distance can not simply be represented with direct ratio function, the relation between its running time and distance and flow is a kind of load
Relation function；In this programme, using most widely used be BPR function, this function is sent out by American roads office；Sections of road needs
The time wanted is to seek the key factor that optimal path needs to consider, and correctly tries to achieve section time impedance value and need by handing over
The support of the various observation data of passway, time of trying to achieve that so could be more accurate spends.
Further, try to achieve described intersection time impedance value dijFunction expression be referred to as：
In formula
d：Delay impedance；
Tc：Signal lamp cycle is long；
μ：Split；
q：The traffic flow that import track is actually reached；
x：Saturation.Although under normal circumstances, link proportion value is the main force that the time spends, in some cases, special
It is not that crossing is intensive for metropolitan road network, the time that vehicle expends in crossedpath is also can not be ignored,
The factors such as the traffic flow being actually reached in intersection, signal lamp cycle length, split and import track are all to need to consider
, the calculating so solving the time cost of optimal path is just more reasonable and practical.
Further, the described step asking for the set of all oriented segmental arcs in preset range includes：
Using existing node coordinate information, preset range is set as with source point and terminal line for cornerwise rectangle
In the range of.Under normal conditions, the optimal path between source point and terminal substantially include with source point and terminal line be diagonal
In the rectangular extent of line, in this programme, using restricted searching area, greatly reduce the quantity of traverse node, improve computing
Time.
Further, the described step asking for the set of all oriented segmental arcs in preset range includes：
Using existing node coordinate information, the region of search is set as with source point and terminal line for cornerwise square
In the range of shape, and after this rectangular extent is expanded two range of nodes, as preset range.Under normal conditions, source
Optimal path between point and terminal is included substantially in source point and terminal line for cornerwise rectangular extent, considers further that
Sometimes for the node path first detouring to beyond rectangular extent from source point, thus rectangular extent is expanded two range of nodes and makees
For preset range, in this programme, using restricted searching area, greatly reduce the quantity of traverse node, improve operation time.
Further, ask for also including step before the step of the set of all oriented segmental arcs in preset range described：
Set up traffic network design, by abstract for whole road network for " { node set }+{ segmental arc set }+{ right of way set } "
Weighted Directed Diagram；
Wherein, node refers to the point in the place of crossing, dead end street or road attribute change of road；And segmental arc then represents
Section between two neighboring crossing in road network.By abstract for traffic network design for Weighted Directed Diagram, be conducive to follow-up
The calculating of dijkstra's algorithm, improves computational efficiency.
Further, described Weighted Directed Diagram is used adjacency list to obtain road network figure as storage mode；
Adjacency list is n single-track link table representing the neighbouring relations between node, is made up of sequence list and chained list；Sequence list
Element representation road-net node, each node corresponds to the node elements in a chained list, the element representation in chained list and linked list head
Adjacent road-net node mouth.Using adjacency list storage mode, save substantial amounts of memory space, and improve the search speed of algorithm
Degree.
The invention also discloses a kind of Dijkstra optimum traffic route planning system based on impedance matching, including：
Oriented segmental arc asks for module, for asking for the set of all oriented segmental arcs in preset range；
Time spends computing module, is coupled in described oriented segmental arc and asks for module, for calculating by merging traffic impedance
Dijkstra optimal path algorithm obtain all oriented segmental arcs time spend；
Final result output module, is coupled in described time cost computing module, for exporting optimal path set, this is
Source point time cost oriented segmental arc set the shortest in terminal is taken from shortest path set.
Further, the described time spends computing module to include Dijkstra optimal path algorithm unit, is coupled in described
The section time impedance value computing unit of Dijkstra optimal path algorithm unit and intersection time impedance value computing unit.
Many times, shortest path is not optimal path, particularly, such as exists in the case of no through traffic in shortest path, we
Being reached home by this shortest path needs the time spending to be infinitely-great, is at this time accomplished by considering traffic time resistance value
, and traffic time resistance value includes the sections of road required time spending, and by the crossedpath required time spending；
Relative, when spending the time of calculating, then need Dijkstra optimal path algorithm unit, section time impedance value computing unit
Jointly coordinate calculating with intersection time impedance value computing unit.
Using technique scheme, the present invention at least can obtain following technique effects：In the present invention, due to seeking optimum
The factor of traffic impedance is considered, it is to avoid the optimal path tried to achieve by traditional dijkstra's algorithm cannot lead to during path
Row and the infinitely-great situation of delay cost that spends occurs, but certain consider truly feasible optimum friendship after traffic impedance
Path, reduces traffic trip cost, so that optimum traffic route is calculated and has more using value and meaning；For user, permissible
Reduce trip energy consumption and the time spends, particularly can solve the cognition for unfamiliar city load conditions for the traveler, and for
For whole city, then can reduce vehicle energy consumption and pollution, and can coordinate and control the path of city vehicle to advise
Draw, and then realize improving the service efficiency of urban traffic situation, reduce urban transportation blocking；In the present invention, optimal path consider master
Consider that the time spends factor, certainly, in a practical situation also can be using factor mainly the examining as optimal path such as shortest path
Amount factor, particularly in the case of traffic impedance is almost negligible；In addition, this preset range can be whole road network
Road network in the range of network or a restriction, according to the actual requirements depending on difference.
Brief description
For the technical scheme being illustrated more clearly that in the embodiment of the present invention, below will be to institute in embodiment of the present invention description
Need use accompanying drawing be briefly described it should be apparent that, drawings in the following description be only the present invention some enforcement
Example, for those of ordinary skill in the art, on the premise of not paying creative work, can also be implemented according to the present invention
The content of example and these accompanying drawings obtain other accompanying drawings.
Fig. 1 is a kind of flow chart of the Dijkstra optimum traffic route planing method based on impedance matching of the present invention；
Fig. 2 is the localized road network in certain city；
Fig. 3 is the result of calculation schematic diagram of traditional dijkstra's algorithm；
Fig. 4 is the result of calculation of the optimal path algorithm based on traffic impedance；
Fig. 5 is a kind of schematic diagram of the Dijkstra optimum traffic route planning system based on impedance matching of the present invention.
Specific embodiment
For make present invention solves the technical problem that, the technical scheme that adopts and the technique effect that reaches clearer, below
By combine accompanying drawing the technical scheme of the embodiment of the present invention is described in further detail it is clear that described embodiment only
It is a part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those skilled in the art exist
The every other embodiment being obtained under the premise of not making creative work, broadly falls into the scope of protection of the invention.
Further illustrate technical scheme below in conjunction with the accompanying drawings and by specific embodiment.Need explanation
It is as a example embodiments of the invention XXX, technical scheme to be illustrated, but not in this, as restriction.This area
Technical staff can understand, XXX proposed by the invention, in addition to for XXX, can also be widely used in other identical or phases
In nearly field, and obtain similar technique effect.
Embodiment one：
Fig. 1 is a kind of flow chart of the Dijkstra optimum traffic route planing method based on impedance matching of the present invention, ginseng
Examine Fig. 1, the invention discloses a kind of Dijkstra optimum traffic route planing method based on impedance matching, including：
S1:Ask for the set of all oriented segmental arcs in preset range；
S2:The time obtaining all oriented segmental arcs by merging the Dijkstra optimal path algorithm of traffic impedance spends；
S3:In taking from source point to terminal, the time spends oriented segmental arc set the shortest to export as final result, that is, optimum
Set of paths.
Using technique scheme, the present invention at least can obtain following technique effects：In the present invention, due to seeking optimum
The factor of traffic impedance is considered, it is to avoid the optimal path tried to achieve by traditional dijkstra's algorithm cannot lead to during path
Row and the infinitely-great situation of delay cost that spends occurs, but certain consider truly feasible optimum friendship after traffic impedance
Path, reduces traffic trip cost, so that optimum traffic route is calculated and has more using value and meaning；For user, permissible
Reduce trip energy consumption and the time spends, particularly can solve the cognition for unfamiliar city load conditions for the traveler, and for
For whole city, then can reduce vehicle energy consumption and pollution, and can coordinate and control the path of city vehicle to advise
Draw, and then realize improving the service efficiency of urban traffic situation, reduce urban transportation blocking；In the present invention, optimal path consider master
Consider that the time spends factor, certainly, in a practical situation also can be using factor mainly the examining as optimal path such as shortest path
Amount factor, particularly in the case of traffic impedance is almost negligible；In addition, this preset range can be whole road network
Road network in the range of network or a restriction, according to the actual requirements depending on difference.
Wherein, when traffic impedance is that vehicle operates on traffic route, according to the distance run, time, comfort level, congestion
The composite factors such as the comfort level of situation, transport cost and people, need to consider i.e. people, car, road, environmental interaction, to traffic
The drag effect value of trip.
The present embodiment preferably, obtains all oriented segmental arcs by merging the Dijkstra optimal path algorithm of traffic impedance
Time spend step include：
If S is the set of the segmental arc having tried to achieve optimal path, A is the section collection in urban road network in preset range
Close；The initial optimal path time is made to spend k (r0)=0；By segmental arc r0Put in S；Make k (ri)=+ ∞, ri∈A-S；
Calculate all oriented arc-segment time with source point s as starting point to spend, obtain k (ri)=k (r0)+tsi, wherein tsi
Represent the traffic time resistance value from s to i, obtain k (r*)=min { k (ri)},ri=<s,i>；Then by arc r*Put in S；As
This, obtain first node h (r*)=s, end-node f (r*)=i, optimal path sequence node Pi=(s, f (r*))；
Calculate with segmental arc r*The time that all oriented segmental arc for starting point is put at end spends；First according to segmental arc r*With each
Bar segmental arc r to be accessedjDirection of travel carry out the judgement of steering direction, and consider intersection delay；Then obtain k (rj)=
min{k(r*)+tij；k(rj), wherein tijRepresent the traffic time resistance value from i to j；Last k (r*)=min { k (rj), will
Segmental arc r*Put in S, obtain this segmental arc front nodal point h (r*)=i, posterior nodal point f (r*)=j, optimal path sequence node Pj=Pi+f
(r*)；
Judge whether A is equal to S, that is, judge whether the section set A in urban road network in preset range all comprises
In the set S of the segmental arc trying to achieve optimal path；
If A=S, proceed to the step exporting final result；If A ≠ S, proceed to calculating with segmental arc r*End is put as starting point
All oriented segmental arc time spend step be further continued for；
Output final result；If k is (r*)<+ ∞, then k (r*) for optimal path required cost time, PjFor optimum
Set of paths.In this programme, S is the set of the oriented segmental arc to obtain optimal path, from the beginning of source point, initially only comprises in S
Source point s, is spent the time to be 0, is outwards extended layer by layer, the oriented segmental arc in A is calculated and being added progressively centered on source point s
Enter in S, when oriented segmental arc all of from source point to terminal is all obtained optimal path, the optimal path collection from source point to terminal
Close and also just obtained；Wherein, the calculating of the optimal path main time considering to spend in segmental arc and crossing, the time spends
The shortest as optimal path, rather than shortest path.
Preferably, traffic time resistance value includes section time impedance value and intersection time impedance value to the present embodiment；
Wherein, traffic time resistance value tijIncluding section time impedance value yijWith intersection time impedance value dij；yij?
Time required for vehicle travels between any two section i and j；dijRepresent the time that intersection is spent.Certainly, this tsi
Try to achieve and tijSimilar；Many times, shortest path is not optimal path, particularly, such as exists in shortest path and forbids
Under passage situation, we are reached home by this shortest path needs the time spending to be infinitely-great, is at this time accomplished by examining
Consider traffic time resistance value, and the traffic impedance of traffic time resistance value, particularly Traffic Systems be broadly divided into two classes,
Including the sections of road required time spending, and by the crossedpath required time spending.
The present embodiment preferably, tries to achieve section time impedance value yijFunction expression be referred to as：
In formula
ta(0)：The average time that vehicle on a of section travels in the case of without hindrance；
ea：The traffic capacity of section a；
qa：Traffic flow on a of section；
α、β：Parameter to be calibrated.In vehicle in the case of not having traffic to hinder, running time is into operating range
The relation of direct ratio, but in actual traffic route, the traveling that vehicle can not possibly be without hindrance.So running time and row on road
Sail distance can not simply be represented with direct ratio function, the relation between its running time and distance and flow is a kind of load
Relation function；In this programme, using most widely used be BPR function, this function is sent out by American roads office；Sections of road needs
The time wanted is to seek the key factor that optimal path needs to consider, and correctly tries to achieve section time impedance value needs.
The present embodiment preferably, tries to achieve intersection time impedance value dijFunction expression be referred to as：
In formula
d：Delay impedance；
Tc：Signal lamp cycle is long；
μ：Split；
q：The traffic flow that import track is actually reached；
x：Saturation.Although under normal circumstances, link proportion value is the main force that the time spends, in some cases, special
It is not that crossing is intensive for metropolitan road network, the time that vehicle expends in crossedpath is also can not be ignored,
The factors such as the traffic flow being actually reached in intersection, signal lamp cycle length, split and import track are all to need to consider
, the calculating so solving the time cost of optimal path is just more reasonable and practical.
Preferably, the step asking for the set of all oriented segmental arcs in preset range includes the present embodiment：
Using existing node coordinate information, preset range is set as with source point and terminal line for cornerwise rectangle
In the range of.Under normal conditions, the optimal path between source point and terminal substantially include with source point and terminal line be diagonal
In the rectangular extent of line, in this programme, using restricted searching area, greatly reduce the quantity of traverse node, improve computing
Time.
Preferably, the step asking for the set of all oriented segmental arcs in preset range includes the present embodiment：
Using existing node coordinate information, the region of search is set as with source point and terminal line for cornerwise square
In the range of shape, and after this rectangular extent is expanded two range of nodes, as preset range.Under normal conditions, source
Optimal path between point and terminal is included substantially in source point and terminal line for cornerwise rectangular extent, considers further that
Sometimes for the node path first detouring to beyond rectangular extent from source point, thus rectangular extent is expanded two range of nodes and makees
For preset range, in this programme, using restricted searching area, greatly reduce the quantity of traverse node, improve operation time.
The present embodiment preferably, also included walking before asking for the step of the set of all oriented segmental arcs in preset range
Suddenly：
Set up traffic network design, by abstract for whole road network for " { node set }+{ segmental arc set }+{ right of way set } "
Weighted Directed Diagram；
Wherein, node refers to the point in the place of crossing, dead end street or road attribute change of road；And segmental arc then represents
Section between two neighboring crossing in road network.By abstract for traffic network design for Weighted Directed Diagram, be conducive to follow-up
The calculating of dijkstra's algorithm, improves computational efficiency.
Preferably, Weighted Directed Diagram is used adjacency list to obtain road network figure as storage mode to the present embodiment；
Adjacency list is n single-track link table representing the neighbouring relations between node, is made up of sequence list and chained list；Sequence list
Element representation road-net node, each node corresponds to the node elements in a chained list, the element representation in chained list and linked list head
Adjacent road-net node mouth.Using adjacency list storage mode, save substantial amounts of memory space, and improve the search speed of algorithm
Degree.
In order to preferably explain the planing method of the present invention, the example of an optimal path algorithm is shown below
Fig. 2 is the localized road network in certain city, and section is two-way section it is contemplated that actual traffic road conditions, by car
Running time on section marks in the side of in figure segmental arc, the right-hand rotation in each crossing, straight and turning left mean delay
It is respectively 0,30s, 60s.The vehicle that crossing 6 is prohibited from travelling eastwards from west turns left.Assume 30 kilometers of a certain vehicle speed/little
When, 1-3 link length is 1.5 kilometers, every section of road delay time at stop specifically such as Fig. 2, the dijkstra's algorithm based on impedance for the application,
Calculate the optimal path between crossing 1 and crossing 9.
Fig. 3 is the result of calculation schematic diagram of traditional dijkstra's algorithm, and Fig. 4 is that the optimal path based on traffic impedance is calculated
The result of calculation of method；
As table 1, it is 1-3-6- using the optimal path (as shown in heavy line in Fig. 3) that traditional dijkstra's algorithm obtains
7-9, because crossing 6 is no left turn, therefore the delay cost of required cost is infinity.Using fusion traffic impedance
Dijkstra optimal path algorithm, the optimal path (as shown in heavy line in Fig. 4) of acquisition is 1-3-5-8-9.Required cost
Delay cost be 16min, this is only truly feasible optimal path.
Table 1：The contrast of the dijkstra's algorithm of traditional Dijistra algorithm and fusion traffic impedance
As seen from the above analysis, improved dijkstra's algorithm is to be solved in traffic network using mathematical algorithm
The problem of shortest path, does not carry out any modification to traffic network structure itself, not only decreases workload, and understand earth's surface
The Connectivity Characteristics of transportation network are shown, effectively describe the intersection turning delay in road network and limit, embody city
The directivity of city's road traffic and intersection delay, thus more effectively find truly feasible city optimum traffic route.
Embodiment two：
Fig. 2 is a kind of schematic diagram of the Dijkstra optimum traffic route planning system based on impedance matching of the present invention, this
The system of invention has been suitable for optimum traffic route planing method disclosed by the invention, understands with reference to Fig. 2, this system, including：
Oriented segmental arc asks for module 10, for asking for the set of all oriented segmental arcs in preset range；
Time spends computing module 20, is coupled in oriented segmental arc and asks for module 10, for calculating by merging traffic impedance
Dijkstra optimal path algorithm obtain all oriented segmental arcs time spend；
Final result output module 30, the time that is coupled in spends computing module 30, and for exporting optimal path set, this is
Source point time cost oriented segmental arc set the shortest in terminal is taken from shortest path set.
Using technique scheme, the present invention at least can obtain following technique effects：In the present invention, due to by the time
Module is spent during seeking optimal path, to consider the factor of traffic impedance, it is to avoid to try to achieve by traditional dijkstra's algorithm
Optimal path impassable and the infinitely-great situation of delay cost that spend occurs, but certain consider traffic impedance after
Truly feasible optimum traffic route, reduces traffic trip cost, so that optimum traffic route is calculated and has more using value and meaning
Justice；For user, it is possible to reduce trip energy consumption and time spend, and particularly can solve traveler for unfamiliar city road conditions feelings
The cognition of condition, and for whole city, then can reduce vehicle energy consumption and pollution, and can coordinate and control city
The path planning of city's vehicle, and then realize improving the service efficiency of urban traffic situation, reduce urban transportation blocking；In the present invention,
The main consideration time of considering of shortest path spends factor, certainly, in a practical situation also can be using factors such as shortest paths as
The primary concern factor of shortest path, particularly in the case of traffic impedance is almost negligible；In addition, this preset range is permissible
It is the road network in the range of whole road network or a restriction, according to the actual requirements depending on difference.
Preferably, the time spends computing module 20 to include Dijkstra optimal path algorithm unit 21 to the present embodiment, coupling
Section time impedance value computing unit 22 and intersection time impedance value meter in Dijkstra optimal path algorithm unit 21
Calculate unit 23.Many times, shortest path is not optimal path, particularly, such as there are no through traffic feelings in shortest path
Under condition, we are reached home by this shortest path needs the time spending to be infinitely-great, is at this time accomplished by considering traffic
Time impedance value, and traffic time resistance value includes the sections of road required time spending, and by needed for crossedpath
The time spending；Relative, when spending the time of calculating, then need Dijkstra optimal path algorithm unit, the resistance of section time
Anti- value computing unit and intersection time impedance value computing unit coordinate calculating jointly.
All or part of content in the technical scheme that above example provides can pass through software programming or specialized hardware
Equipment is realized, and wherein software program is stored in the storage medium that can read, and storage medium is for example：Hard disk in computer, light
Disk or floppy disk；Special hardware can be ASIC, FPGA, SoC or the IP Core with related circuit.
Note, above are only presently preferred embodiments of the present invention and institute's application technology principle.It will be appreciated by those skilled in the art that
The invention is not restricted to specific embodiment described here, can carry out for a person skilled in the art various obvious changes,
Readjust and substitute without departing from protection scope of the present invention.Therefore although being carried out to the present invention by above example
It is described in further detail, but the present invention is not limited only to above example, without departing from the inventive concept, also
Other Equivalent embodiments more can be included, and the scope of the present invention is determined by scope of the appended claims.
Claims (11)
1. a kind of Dijkstra optimum traffic route planing method based on impedance matching is it is characterised in that include step：
Ask for the set of all oriented segmental arcs in preset range；
The time obtaining all oriented segmental arcs by merging the Dijkstra optimal path algorithm of traffic impedance spends；
In taking from source point to terminal, the time spends oriented segmental arc set the shortest to export as final result, i.e. optimal path collection
Close.
2. method as claimed in claim 1 is it is characterised in that the described Dijkstra optimal path by merging traffic impedance is calculated
The step that method obtains the time cost of all oriented segmental arcs includes：
If S is the set of the segmental arc having tried to achieve optimal path, A is the section set in urban road network in preset range；Order
The initial optimal path time spends k (r0)=0；By segmental arc r0Put in S；Make k (ri)=+ ∞, ri∈A-S；
Calculate all oriented arc-segment time with source point s as starting point to spend, obtain k (ri)=k (r0)+tsi, wherein tsiRepresent
Traffic time resistance value from s to i, obtains k (r*)=min { k (ri)},ri=<s,i>；Then by arc r*Put in S；So, obtain
To first node h (r*)=s, end-node f (r*)=i, optimal path sequence node Pi=(s, f (r*))；
Calculate with segmental arc r*The time that all oriented segmental arc for starting point is put at end spends；First according to segmental arc r*Will with each
Segmental arc r accessingjDirection of travel carry out the judgement of steering direction, and consider intersection delay；Then obtain k (rj)=min
{k(r*)+tij；k(rj), wherein tijRepresent the traffic time resistance value from i to j；Last k (r*)=min { k (rj), by segmental arc
r*Put in S, obtain this segmental arc front nodal point h (r*)=i, posterior nodal point f (r*)=j, optimal path sequence node Pj=Pi+f(r*)；
Judge whether A is equal to S, that is, judge whether the section set A in urban road network in preset range has all been included in
In the set S of the segmental arc trying to achieve optimal path；
If A=S, proceed to the step exporting final result；If A ≠ S, proceed to calculating with segmental arc r*The institute for starting point is put at end
The step that the time of oriented segmental arc spends is further continued for；
Output final result；If k is (r*)<+ ∞, then k (r*) for optimal path required cost time, PjFor optimal path
Set.
3. device as claimed in claim 2 is it is characterised in that described traffic time resistance value includes section time impedance value and friendship
Cross road mouth time impedance value；
Wherein, traffic time resistance value tijIncluding section time impedance value yijWith intersection time impedance value dij；
Described yijTime required for vehicle travels between any two-way section i and j；dijRepresent intersection spent when
Between.
4. device as claimed in claim 3 is it is characterised in that try to achieve described section time impedance value yijFunction expression claim
For：
In formula
ta(0)：The average time that vehicle on a of section travels in the case of without hindrance；
ea：The traffic capacity of section a；
qa：Traffic flow on a of section；
α、β：Parameter to be calibrated.
5. device as claimed in claim 3 is it is characterised in that try to achieve described intersection time impedance value dijFunction expression
Referred to as：
In formula
d：Delay impedance；
Tc：Signal lamp cycle is long；
μ：Split；
q：The traffic flow that import track is actually reached；
x：Saturation.
6. device as claimed in claim 1 is it is characterised in that the described step asking for the set of all oriented segmental arcs in preset range
Rapid inclusion：
Using existing node coordinate information, preset range is set as with source point and terminal line for cornerwise rectangular extent
Interior.
7. device as claimed in claim 1 is it is characterised in that the described step asking for the set of all oriented segmental arcs in preset range
Rapid inclusion：
Using existing node coordinate information, the region of search is set as with source point and terminal line for cornerwise rectangle model
In enclosing, and after this rectangular extent is expanded two range of nodes, as preset range.
8. device as claimed in claim 1 is it is characterised in that ask for the set of all oriented segmental arcs in preset range described
Step is also included before step：
Set up traffic network design, will be abstract for whole road network oriented for " { node set }+{ segmental arc set }+{ right of way set } "
Weighted graph；
Wherein, node refers to the point in the place of crossing, dead end street or road attribute change of road；And segmental arc then represents road network
In section between two neighboring crossing.
9. device as claimed in claim 8 is it is characterised in that described Weighted Directed Diagram is used adjacency list to obtain as storage mode
Road network figure；
Adjacency list is n single-track link table representing the neighbouring relations between node, is made up of sequence list and chained list；The unit of sequence list
Element represents road-net node, and each node corresponds to a chained list, and the element representation in chained list is adjacent with the node elements in linked list head
The road-net node mouth connecing.
10. a kind of Dijkstra optimum traffic route planning system based on impedance matching is it is characterised in that include：
Oriented segmental arc asks for module, for asking for the set of all oriented segmental arcs in preset range；
Time spends computing module, is coupled in described oriented segmental arc and asks for module, for calculating by merging traffic impedance
The time that Dijkstra optimal path algorithm obtains all oriented segmental arcs spends；
Final result output module, is coupled in described time cost computing module, for exporting optimal path set, this optimum road
Source point time cost oriented segmental arc set the shortest in terminal is taken from footpath set.
11. devices as claimed in claim 10 are it is characterised in that cost of described time computing module includes Dijkstra optimum road
Footpath algorithm unit, is coupled in section time impedance value computing unit and the crossroad of described Dijkstra optimal path algorithm unit
Mouth time impedance value computing unit.
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|---|---|---|---|---|
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-
2016
- 2016-08-30 CN CN201610781472.4A patent/CN106403976A/en active Pending
Non-Patent Citations (2)
| Title |
|---|
| 姜凤辉 等: "基于GIS的Dijkstra改进算法及其在交通导航系统中的应用", 《测绘与空间地理信息》 * |
| 潘杰: "智能交通系统中最优路径选择的设计与实现", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
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