CN101256083A - Method for selecting urban traffic network path based on dynamic information - Google Patents
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Abstract
The invention relates to a city traffic network path selecting method which is based on dynamic information. The invention includes the following steps: (1) using the ground sensing coil, GPS and other existing information collecting methods to collect real-time traffic information, and establishing real-time information database; (2) using electronic map information to establish city traffic network topological structure map; (3) using Djkstra labeling method to find the optimal path between the commencement and termination dynamically in time. The invention has the merits of easy achievement, high reliability, high immediacy, a few parameters and so on, which can provide real-time and reliable navigation information for modern city traffic inducement.
Description
Technical field
The present invention relates to a kind of method of traffic communication technical field, specifically is a kind of method for selecting urban traffic network path based on multidate information.
Background technology
In existing auto-navigation system, the selection of optimal path mostly is as the basis with static information, seldom utilize the real-time information of urban transportation to navigate, the optimal path that provides in the case is the traffic flow modes that can't reflect city road network, also just make traveler can't know the jam situation on the urban road, make people's the unusual blindness of trip.Therefore, become today of modern city malignant tumor, sought and effectively utilize multidate information to carry out automobile navigation just to seem particularly important in traffic congestion.
Find through retrieval: Wu Bijun, Li Lixin, Lei Xiaoping " based on the Shortest Path Searching of City Road Database " Southwest Jiaotong University's journal 2003.38 (1): 80-83 prior art; Severe cold ice, Liu Yingchun " the urban road network's shortest path first based on GIS is inquired into " Chinese journal of computers 2000.23 (2): 210-215; Liu Canqi, Yang Peikun " urban road network's traffic characteristics realistic model and shortest path first " Communication and Transportation Engineering journal 2002.2 (3): 60-62; Zhou Peide " in the traffic road net between any 2 fast algorithm of shortest path " 2002.24 (4): 35-37.Above-mentioned prior art all is to carry out according to static transport information about the search of shortest path, does not consider and utilize Real-time Traffic Information to determine optimal path that can not reflect the traffic of the road of urban traffic network, method is relatively backward.Therefore, be dynamic information characteristics of the present invention as the reference of seeking optimal path.
Summary of the invention
The objective of the invention is to overcome static optimal route selection method in the prior art and multidate information can not be included in the shortcoming and defect of path Choice Model, a kind of method for selecting urban traffic network path based on multidate information is provided.It is at the Geographic Information System of the actual needs and the existing electronic chart of traffic engineering, by gathering the traffic state information of each bar road of city, foundation is based on the transportation network topology diagram of multidate information, and the dynamic information according to real road is determined optimal path in real time on this model based, for traveler provides real-time accurate dynamic optimal path.
The present invention is achieved through the following technical solutions, and may further comprise the steps:
1. utilize ground induction coil, the existing information acquisition means of GPS, gather real-time road condition information, and set up the real-time information database;
2. utilize existing electronic map information of authorizing, set up the urban traffic network topology diagram;
3. use the Djkstra labeling method dynamically to seek optimal path between the origin and destination immediately.
Step 1., concrete grammar is: the GPS device that the ground inductive coil that has laid according to modern city and each taxi company are equipped with, gather the actual traffic information on the urban road in real time, comprise: the dutycycle of average stroke time, average overall travel speed, vehicle flowrate, vehicle density, coil, the information fusion algorithm of uses advanced obtains traffic flow modes information accurately,, the branch time other these information classifications leaves database one by one in, thereby sets up the real-time information database.
Actual traffic information on the described real-time collection urban road, be meant: according to the existing information acquisition means of modern city, coming in the information search of multiple foreign peoples's sensor, be input to the nonlinear Intelligent Fusion model of having set up, merge the real-time traffic flow state information that on the road, these information are put in the dynamic data base, in order to the transport information issue.
Described information database mainly comprises following content; The road section information table, the highway section node table, summit, highway section table, the highway section is communicated with table.
Table 1 road section information table:
| Field name | Field type | Field width | Explanation of field |
| Road code | Character type | 5 | The highway section code |
| Road name | Character type | 100 | The highway section title |
| Road dir | Character type | 2 | Garage's direction |
| Road time | Character type | 8 | Constantly |
| Road trav-time | Double | 16 | The average stroke time |
| Road length | Double | 16 | The physical length in highway section |
Highway section in the table 1 represents that an intersection is to the road between another adjacent intersection in the urban network.The multidate information feature of the road of description that back 5 fields in the table 1 are complete comprises the highway section name, the physical length in highway section, the car that the highway section is represented (traffic) flow path direction, the highway section sometime, vehicle is by this approaches of average link travel time etc.Road code is the field that is associated with table 2.
Table 2 highway section node table:
| Field name | Field type | Field width | Explanation of field |
| Node ID | Long | 6 | Highway section node sequence identifier |
| Road code | Character type | 5 | The highway section code |
| Road name | Character type | 100 | The highway section title |
| Ncord.X | Long | 4 | The nodes X coordinate |
| Ncord.Y | Long | 4 | Node Y coordinate |
Five field descriptions in the table 2 the space topological characteristic in highway section, Node ID, Ncord.X, Ncord.X field are represented the acquisition order and the locus of road collection point, Road code is the field that is associated with table 1.
Summit, table 3 highway section table:
| Field name | Field type | Field width | Explanation of field |
| TopNode ID | Integer | 2 | Summit, highway section sequence identifier |
| Road nodeID | Character type | 5 | Summit, highway section sign |
| Ncord.X | Long | 4 | The nodes X coordinate |
| Ncord.Y | Long | 4 | Node Y coordinate |
| Road number | Integer | 2 | The road way that the summit connects |
The numbering that 5 fields of table 3 have been represented the intersection and locus and the road way that is connected with the intersection.
Table 4 highway section is communicated with table:
| Field name | Field type | Field width | Explanation of field |
| Road Num ID | Long | 4 | The highway section bar is counted sequence identifier |
| Road start | Character type | 5 | Summit, highway section sign |
| Road end | Character type | 5 | Summit, highway section sign |
| Road code | Character type | 5 | The highway section code |
| Road name | Character type | 100 | The highway section title |
| Ncord start.X | Long | 4 | Summit Road start X coordinate |
| Ncord start.Y | Long | 4 | Summit Road start Y coordinate |
| Ncord end.X | Long | 4 | Summit Road end X coordinate |
| Ncord end.Y | Long | 4 | Summit Road end Y coordinate |
| Road number | Integer | 2 | The road way that the summit connects |
| Road length | Double | 16 | The physical length in highway section |
Table 4 has been represented the communication information of an intersection to another intersection, the highway section that is communicated with and the information such as link length of connection, wherein Road start is the sign of an intersection, Road end is attached thereto another logical intersection, Ncord start.X, Ncord start.Y and Ncord end.X, Ncordend.Y represents the geographical position coordinates of these two intersections respectively.
Described road section information table and highway section node table are essential informations, have described locus attribute, topological property and the multidate information characteristic etc. in highway section.According to the information of table 1-4, can finish at a time, obtaining seeking a shortest road warp of time between arbitrary terminal point from arbitrary starting point in the urban traffic network, as the tutorial message of traveler.
Step 2. in, the electronic map information of described utilization mandate, set up the urban traffic network topology diagram, be meant: the dynamic model of setting up urban traffic network, determine the dynamic weights on every limit of model, these weights represent that with a function about road traffic density this density function changes with real-time dynamic information, and therefore reflection is the real-time traffic stream mode.The electronic map information of described utilization mandate is meant: the geography information in city must be as the criterion with the geographical communication system of authoritative institution.
Step 2. in, the described urban traffic network topology diagram of setting up, be meant: the static traffic network topology of setting up the city, each the bar limit in the topological structure, tax is the weights of function with the dynamic information, then this topological structure has become the structural drawing of dynamic urban traffic network, and the weights on every limit can reflect that traveling vehicle passes through the needed average stroke time of road of this limit representative, the economic target that is spent etc.
The weights on described every limit, available concrete model is represented:
(V E) represents the model of transportation network, wherein V={v with two tuple G=
1, v
2, v
nBe called set of node,
Be called the limit collection, for a limit (v among the G
i, v
j), claim v
iBe starting point, claim v
jBe destination node, also claim limit (v sometimes
i, v
j) be from v
iTo v
jThe limit, node also can be described as the summit.
L
i，j(t)＝f(ρ
i，j(t)) (1)
Wherein, L
I, j(t) be the weights on limit, ρ
I, j(t) be illustrated in t constantly, (v
i, v
j) on traffic density.
This traffic density is a real-time change, the dynamic information on its reflection road, and it is obtained by various foreign peoples's sensor real time fusion.
Described step in 3. the instant Djkstra labeling method that uses dynamically seek optimal path between the origin and destination, be meant: going on a journey vehicle after starting point, whenever before entering a crossing, all to calculate current optimal path with DJKSTRA according to real-time dynamic information, also do not take place when avoiding setting out block up, accident etc., thereby save time effectively, use the shortest time to reach home.
Described Djkstra labeling method is dynamically sought the optimal path between the origin and destination, is meant; Dynamically use traditional Dijkstra labeling method in the process that vehicle is advanced, utilize existing dynamic information, when vehicle whenever enters a new node, come again all to determine that present node is to the optimal path under present traffic behavior between the terminal point.Objective function at a time is as follows:
Described Dijkstra labeling method, concrete steps are as follows: from the off, at each node two-dimentional label (L that all annotates
i, p
i), wherein, L
iThe shortest path of expression vehicle from starting point s to node i, p
iThen represent the previous node number from starting point s to node i, the label of destination county is (L so
T-1, p
T-1), last, oppositely write outbound path from destination county according to the label of each node, can obtain optimal path.The advantage of this Dijkstra labeling method is that complexity is low and effective, can determine in the short period of time that starting point is to the shortest path between the interior arbitrary node of network.
The present invention obtains optimal path from determining a rectangle plane figure between the origin-to-destination with the Dijkstra labeling method, and this paths necessarily is included in this rectangular area.In order to guarantee convergence, during vehicle launch, between origin-to-destination, determine a rectangular area, in this zone, adopt the Dijkstra labeling method to obtain one optimal path, along this path, arrive second node place, at this moment, with second node is ground zero, terminal point originally is settled point, redefines the rectangular area according to above-mentioned rule, adopts the Dijkstra labeling method to obtain optimal path once more, by that analogy, up to reaching home.Thus, finally must access the dynamic optimal path of a connection source and terminal point by the inventive method.
The invention has the beneficial effects as follows: the function that can realize seeking in real time optimal path to the trip vehicle has practical significance to the pressure that alleviates present urban transportation, for the modern city traffic trip provides the favorable service function; With modern city transportation network topology is background, based on the optimal path of multidate information is constantly to change along with the variation of time and advancing of vehicle, before reaching home from starting point, the optimal path of trip vehicle is a path that is traveled through in continuing to optimize the process of selection.
Description of drawings
Fig. 1 is the schematic flow sheet of the present invention's dynamic optimal routing of a certain moment.
Embodiment
Below in conjunction with accompanying drawing embodiments of the invention are elaborated:
Present embodiment has provided detailed embodiment and process being to implement under the prerequisite with the technical solution of the present invention, but protection scope of the present invention is not limited to following embodiment.
Present embodiment, the Yanshan Mountain viaduct of choosing the Jinan City is as starting point, the zoo, Jinan is as settled point, time is selected between the 8:00-10:00 in the morning, utilize two cars to test, a route of walking apart from shortest path, another is walked guider and economizes the path most in the time that each calculates constantly.
As shown in Figure 1, the realization of present embodiment is a target with the testing vehicle that has guider, and concrete steps are as follows:
1. at a time, gather the real-time traffic stream mode-average vehicle density that utilizes information fusion model to merge to obtain each bar highway section from the real time data of GPS device and ground inductive coil, with the real-time update of SQL statement fulfillment database information.
2. state of traffic flow is presented on the electronic chart of guider in real time, and 2. calculates the average stroke time with formula, thereby obtain the average stroke time on each bar road according to real-time traffic stream mode-average vehicle density.
3. with 5 minutes as cycle update time, with the optimal path between Djkstra algorithm computation trip vehicle is from the current location to the terminal point.
Compare with existing routing resource in the prior art, present embodiment makes full use of the real-time dynamic information on the urban road, instructs the requirement of traveler according to oneself, the optimum trip of Dynamic Selection path.As required, traveler can be selected the path etc. of saving time most.And existing routing is with the shortest path of chosen distance basically, has significant limitation, and particularly when traffic congestion occurs, original routing resource can not satisfy the needs of people's trip.Present embodiment is tested on Jinan City's road, in the time period that traffic congestion takes place, the result of test is: two test carriages have carried out ten tests from same starting point to same terminal point, through finding that relatively the former will improve more than 30% than the time that the latter on average reaches home.This explanation present embodiment carries out routing with multidate information method has clearly superiority than existing method, and it can make the vehicle of going on a journey effectively avoid the highway section of traffic congestion, reaches home with the minimum time, has improved line efficiency.
Claims (10)
1. the method for selecting urban traffic network path based on multidate information is characterized in that, comprises the steps:
1. utilize ground induction coil, the existing information acquisition means of GPS, gather real-time road condition information, and set up the real-time information database;
2. utilize electronic map information, set up the urban traffic network topology diagram;
3. use the Djkstra labeling method dynamically to seek optimal path between the origin and destination immediately.
2. the method for selecting urban traffic network path based on multidate information as claimed in claim 1, it is characterized in that, described step 1., concrete grammar is: the GPS device that the ground inductive coil that has laid according to modern city and each taxi company are equipped with, gather the actual traffic information on the urban road in real time, comprise: the average stroke time, average overall travel speed, vehicle flowrate, vehicle density, the dutycycle of coil, the exploit information blending algorithm obtains traffic flow modes information accurately, other these information classifications, divide the time to leave database one by one in, thereby set up the real-time information database.
3. the method for selecting urban traffic network path based on multidate information as claimed in claim 1 or 2, it is characterized in that, actual traffic information on the described real-time collection urban road, be meant: according to the existing information acquisition means of modern city, coming in the information search of multiple foreign peoples's sensor, be input to the nonlinear Intelligent Fusion model of having set up, merge the real-time traffic flow state information that on the road, these information are put in the dynamic data base, in order to the transport information issue.
4 method for selecting urban traffic network path based on multidate information as claimed in claim 1 or 2 is characterized in that described information database comprises: road section information table, highway section node table, summit, highway section table, highway section are communicated with table.
5. the method for selecting urban traffic network path based on multidate information as claimed in claim 1, it is characterized in that, step 2. in, the described electronic map information of utilizing, set up the urban traffic network topology diagram, be meant: set up the dynamic model of urban traffic network, determine the dynamic weights on every limit of model, these weights represent that with a function about road traffic density described density function is to change with real-time dynamic information.
6. as claim 1 or 5 described method for selecting urban traffic network path based on multidate information, it is characterized in that, the described urban traffic network topology diagram of setting up, be meant: the static traffic network topology of setting up the city, each the bar limit in the topological structure, tax is the weights of function with the dynamic information, then this topological structure has become the structural drawing of dynamic urban traffic network, and the weights reflection traveling vehicle on every limit is by the needed average stroke of the road time of this limit representative, the economic target that is spent.
7. the method for selecting urban traffic network path based on multidate information as claimed in claim 6 is characterized in that, the weights on described every limit are represented with concrete model:
(V E) represents the model of transportation network, wherein V={v with two tuple G=
1, v
2, v
nBe called set of node,
Be called the limit collection, for a limit (v among the G
i, v
j), claim v
iBe starting point, claim v
jBe destination node, also claim limit (v
i, v
j) be from v
iTo v
jThe limit, node is also referred to as the summit;
L
i，j(t)＝f(ρ
i，j(t))
Wherein, L
I, j(t) be the weights on limit, ρ
I, j(t) be illustrated in t constantly, (v
i, v
j) on traffic density;
8. the method for selecting urban traffic network path based on multidate information as claimed in claim 1, it is characterized in that, step 3. in, described instant use Djkstra labeling method is dynamically sought the optimal path between the origin and destination, be meant: going on a journey vehicle after starting point, whenever before entering a crossing, all to calculate current optimal path with Djkstra according to real-time dynamic information.
9. as claim 1 or 8 described method for selecting urban traffic network path, it is characterized in that described Djkstra labeling method is dynamically sought, and is meant based on multidate information; In the process that vehicle is advanced, utilize existing dynamic information, when vehicle whenever enters a new node, all come to determine present node again to the optimal path under traffic behavior at present between the terminal point, objective function at a time is as follows:
10. the method for selecting urban traffic network path based on multidate information as claimed in claim 9 is characterized in that, described Dijkstra labeling method, and concrete grammar is as follows: from the off, at each node two-dimentional label (L that all annotates
i, p
i), wherein, L
iThe shortest path of expression vehicle from starting point s to node i, p
iThen represent the previous node number from starting point s to node i, the label of destination county is (L
T-1, p
T-1), last, oppositely write outbound path from destination county according to the label of each node, can obtain optimal path.
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