CN102927990B - Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile - Google Patents
Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile Download PDFInfo
- Publication number
- CN102927990B CN102927990B CN201210419222.8A CN201210419222A CN102927990B CN 102927990 B CN102927990 B CN 102927990B CN 201210419222 A CN201210419222 A CN 201210419222A CN 102927990 B CN102927990 B CN 102927990B
- Authority
- CN
- China
- Prior art keywords
- node
- urban road
- optimal path
- next node
- automobile
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Abstract
The invention discloses the method for a kind of locomotive by Geographic Information System determination urban road optimal path of automobile, it is characterized in that said method comprising the steps of: (1) determines the starting point node location of advancing and peripheral node position by Geographic Information System on urban road electronic chart; (2) from starting point node, neighbor node is found, then according to V at urban road electronic chart
tsize select the position of next node in optimal path; Wherein V
tcalculate according to formula (I): V
t=Lcos θ V
iω/(L+CV
iω+aNV
iω) (I); (3) when the next node selected is not peripheral node, with the next node selected for starting point node carries out cyclic search according to step (2); Otherwise, terminate search, build urban road optimal path of automobile according to the node sequence determined.The method is Reality simulation road traffic condition as much as possible, and reliable results is feasible.
Description
Technical field
The invention belongs on electronic chart and travel optimal path optimisation technique field, be specifically related to the method for a kind of locomotive by Geographic Information System determination urban road optimal path of automobile.
Background technology
According to statistics, nearly 17 kinds of the algorithm of the city shortest path based on GIS proposed at present.The people such as F.Benjamin Zhan test 15 wherein kind, and it is good that result shows 3 kinds of effectiveness comparison, they respectively: TQQ, DKA and DKD.Wherein the basis of TQQ algorithm is figure growth theory, is comparatively suitable for calculating the bee-line between single source point to other all node; Latter two algorithm is the algorithm based on Dijkstra, is more suitable for the shortest route problem calculating point-to-point transmission.On the whole, space storage problem, owing to being subject to the restriction of computer hardware development level at that time, has been put into a very important position by the data structure that these algorithms adopt and its implementation, saves to exchange space for sacrifice reasonable time efficiency.At present, space storage problem has not been the subject matter that will consider, is therefore necessary to re-start existing algorithm consider and improve, and can improve the efficiency of shortest path first with space for time.
And the time of existing urban road optimal path of automobile algorithm meeting at substantial, a lot of computing times can be expended when node is a lot.And although some modified hydrothermal process is improved in time, not necessarily satisfactory in result of calculation, there is a lot of area for improvement.Simultaneously due to present algorithm a large amount of be all the calculating carried out on the basis of shortest path, might not realistic demand.Because a lot of people selects the object of shortest path to be actually the path selecting spended time minimum, but not necessarily represent spended time the shortest in the shortest path.This will consider the road conditions in the path of selection, as: category of roads, the degree of crowding, traffic lights quantity etc.The present invention therefore.
Summary of the invention
The object of the invention is a kind of method providing locomotive by Geographic Information System determination urban road optimal path of automobile, solves in prior art traffic lights, the speed of a motor vehicle of not considering urban road when obtaining urban road optimal path of automobile and the road conditions such as to block up cause the problems such as routing is unreasonable.
In order to solve these problems of the prior art, technical scheme provided by the invention is:
Locomotive, by a method for Geographic Information System determination urban road optimal path of automobile, is characterized in that said method comprising the steps of:
(1) on urban road electronic chart, the starting point node location of advancing and peripheral node position is determined by Geographic Information System;
(2) from starting point node, neighbor node is found, then according to V at urban road electronic chart
tsize select the position of next node in optimal path; Wherein V
tcalculate according to formula (I):
V
t＝LcosθV
iω/(L+CV
iω+aNV
iω) (I)；
In formula (I), L represents next node and the internodal road section length determined before, and θ represents the angle of the line segment that next node is connected with the node determined before and terminal with the internodal section determined before, V
iω represents the vehicle running speed in the section of urban road different brackets under the predetermined degree of crowding, and N represents traffic lights number, a representation unit traffic lights spended time, and C is the correction time;
(3) when the next node selected is not peripheral node, with the next node selected for starting point node carries out cyclic search according to step (2); Otherwise, terminate search, build urban road optimal path of automobile according to the node sequence determined.
Preferably, when the next node selected does not have neighbor node in described method, and the next node selected is not when being peripheral node, give up the current path determined, the node determined before turning back to carries out the determination of next node according within the scope of the neighbor node of step (2) after deleting the next node selected.
The setting of correction time is because turn inside diameter, some other impacts caused running time such as the vehicle deceleration that traffic lights cause.The present invention proposes one can take in Reality simulation situation as much as possible in put forward factor, obtains optimization simultaneously, can realize the search of optimal path fast on Algorithms T-cbmplexity.
If s and j is 2 nodes any given in network, find the optimal path of s to j, this path is made up of limit and node, or else be that between 2, line segment is the shortest obviously during consideration true path, the path namely connecting s, j 2 is shortest path, but situation so is in practical situations both little, but most convergence and the path of this straight line are the selections of optimum.Therefore can utilize the technology of GIS under this target, find a feasible solution.
The principle of technical solution of the present invention is: from the node that s point set off in search is adjacent with it, and they are coupled together.Make the angle that formed with s, j 2 lines minimum, suppose to have searched out some s1, this finds the next node minimum with s1, j angle from s1.And recurrence is gone down like this.Circulation is jumped out when searching terminal j.Owing to being the carrying out at urban road, based on the rationality (each place can reach) in path, city, such path always can be found.
According to ultimate principle of the present invention, the present inventor finds a kind of situation, as shown in Figure 1, is but obviously irrational.If searched for according to method above, obviously can obtain separating the such solution of s → k → j, but this solution obviously do not have s → l → m → j to come good, analyze reason and can find it is due to the long reason of path s, k.Therefore need to consider the size of angle and the length in path to the impact of routing.
Technical scheme provided by the invention adopts the section model shown in Fig. 2, and wherein L represents road section length, and θ represents the angle of section and useful direction, V
iω represents the travel speed in the section of different brackets under certain degree of crowding, and N represents traffic lights number, a representation unit traffic lights spended time.Then consider these factors, obtain judging factor Ⅴ
t, V
trepresent effective velocity.
V
t＝LcosθV
iω/(L+CV
iω+aNV
iω)；
By judging factor Ⅴ
tcarry out the reliability judging section in path; C is the correction time.
The present invention compared with prior art, has following beneficial effect:
Technical solution of the present invention can Reality simulation road traffic condition as much as possible, when ensureing to obtain optimum solution as much as possible, can realize the search of optimal path fast; Technical solution of the present invention can utilize the advantage of GIS technology, system is realized to the optimization of a nearly step.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the invention will be further described:
Fig. 1 is the Method And Principle figure carrying out optimal path in prior art;
Fig. 2 be in technical solution of the present invention locomotive by the Method And Principle figure of Geographic Information System determination urban road optimal path of automobile.
Fig. 3 is the workflow diagram of technical solution of the present invention when specifically implementing;
Fig. 4 is process flow diagram when utilizing technical solution of the present invention to carry out route searching.
Embodiment
Below in conjunction with specific embodiment, such scheme is described further.Should be understood that these embodiments are not limited to for illustration of the present invention limit the scope of the invention.The implementation condition adopted in embodiment can do further adjustment according to the condition of concrete producer, and not marked implementation condition is generally the condition in normal experiment.
Embodiment
As shown in Figure 3, the present embodiment locomotive, by the method for Geographic Information System determination urban road optimal path of automobile, comprises the following steps:
(1) on urban road electronic chart, the starting point node location of advancing and peripheral node position is determined by Geographic Information System;
(2) from starting point node, neighbor node is found, then according to V at urban road electronic chart
tsize select the position of next node in optimal path; Wherein V
tcalculate according to formula (I):
V
t＝LcosθV
iω/(L+CV
iω+aNV
iω) (I)；
In formula (I), L represents next node and the internodal road section length determined before, and θ represents the angle of the line segment that next node is connected with the node determined before and terminal with the internodal section determined before, V
iω represents the vehicle running speed in the section of urban road different brackets under the predetermined degree of crowding, N represents traffic lights number, a representation unit traffic lights spended time, C (revises because turn inside diameter, some other impacts caused running time such as the vehicle deceleration that traffic lights cause the correction time.
(3) when the next node selected is not peripheral node, with the next node selected for starting point node carries out cyclic search according to step (2); Otherwise, terminate search, build urban road optimal path of automobile according to the node sequence determined.
Specifically as shown in Figure 3, first will to the region image data chosen, ArcGIS is adopted to set up Coverage data model, then modify again after on-the-spot investigation, obtain final operable database, then determine solving model and method, solve, and solving result is verified.
As shown in Figure 4, concrete solution procedure is as follows, if s and j is 2 nodes any given in network, the optimal path algorithm step finding s to j is:
The first step: initialization parameters, determines each rank section motor vehicle speedometer (table 1)
Second step: search for from node s, and according to V
tsize select the next search node i (V of i in the neighbor node of s
tmaximum)
3rd step: terminate search if i is terminal j, be not, returns second step and continues search.If i node does not have neighbor node and is not terminal, then cast out this paths and return second step and continue search.
4th step: the finish node of search is terminal, terminates to return results.
Result verification:
The present embodiment is tested in Suzhou, starts the intersection that place is set to Nan Shi Jie Yulvxiang village, terminates place and is set to Fang Qian village and crossing, Xing Long street.The beginning place that input will be inquired about, and terminate place, the present embodiment system can take forward lookup and reverse search two kinds of modes automatically.Search for.Finally return with traveling road is long estimating the time travelling cost.
Finally determine two travel routes: scheme 1 and scheme 2.From Lv Xiang village eastwards, the Shen Hu Lu that turns right to Xing Tang street continues eastbound scheme 1, turns right curved to Xie Yu street, turn left curved to modern main road, turn right to Fengli street and curvedly turn left to Zhong Yuanlu curved, turn right curved to Chang Yang street, turn right to Su Shenglu and be bent to Xing Longjie, keep straight on Fang Qian village and crossing, Xing Long street.Scheme 2 from Nan Shi street southwards to modern main road eastwards, Cui Yuan road continuation of turning left to Xing Tang street is eastbound, turns right southwards to coloured glaze street, and turning left to Fang Zhoulu bends towards east craspedodrome, turn right and be bent to Chang Yangjie, curved rear craspedodrome of turning left to Fang Qian village is to Fang Qian village and crossing, Xing Long street.
Long 10541.0 meters of the whole process of scheme 1, spended time 901.3667 milliseconds; Long 9832.0 meters of the whole process of scheme 2, spended time 837.73334 milliseconds.Namely be approximately 0.901 second according to program option 1 time used above system-computed, scheme 2 is approximately 0.837 second.And the time that the present embodiment expends when adopting traditional Dijstra algorithm to calculate same problem under identical hardware condition is approximately 1.4 seconds.The system that the embodiment of the present invention obtains thus has superiority; And from map path, scheme 1 and scheme 2 significantly can find out that returning results of systematic search is credible, and therefore the confidence level of native system is very high simultaneously.
Above-mentioned example, only for technical conceive of the present invention and feature are described, its object is to person skilled in the art can be understood content of the present invention and implement according to this, can not limit the scope of the invention with this.All equivalent transformations of doing according to Spirit Essence of the present invention or modification, all should be encompassed within protection scope of the present invention.
Claims (2)
1. locomotive is by a method for Geographic Information System determination urban road optimal path of automobile, it is characterized in that said method comprising the steps of:
(1) on urban road electronic chart, the starting point node location of advancing and peripheral node position is determined by Geographic Information System;
(2) from starting point node, neighbor node is found, then according to V at urban road electronic chart
tsize select the position of next node in optimal path; Wherein V
tcalculate according to formula (I):
V
t＝LcosθV
iω/(L+CV
iω+aNV
iω) (I)；
In formula (I), L represents next node and the internodal road section length determined before, and θ represents the angle of the line segment that next node is connected with the node determined before and terminal with the internodal section determined before, V
iω represents the vehicle running speed in the section of urban road different brackets under the predetermined degree of crowding, and N represents traffic lights number, a representation unit traffic lights spended time, and C is the correction time;
(3) when the next node selected is not peripheral node, with the next node selected for starting point node carries out cyclic search according to step (2); Otherwise, terminate search, build urban road optimal path of automobile according to the node sequence determined.
2. method according to claim 1, it is characterized in that in described method when the next node selected does not have neighbor node, and the next node selected is not when being peripheral node, give up the current path determined, the node determined before turning back to carries out the determination of next node according within the scope of the neighbor node of step (2) after deleting the next node selected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210419222.8A CN102927990B (en) | 2012-10-29 | 2012-10-29 | Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210419222.8A CN102927990B (en) | 2012-10-29 | 2012-10-29 | Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102927990A CN102927990A (en) | 2013-02-13 |
| CN102927990B true CN102927990B (en) | 2015-10-21 |
Family
ID=47642848
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210419222.8A Expired - Fee Related CN102927990B (en) | 2012-10-29 | 2012-10-29 | Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102927990B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105651276A (en) * | 2015-12-30 | 2016-06-08 | 天津盛购科技发展有限公司 | System for planning warehouse path based on dynamic line |
| CN105743783B (en) * | 2016-04-12 | 2019-05-14 | 同济大学 | Car networking network node screening technique based on BS-TS and autoencoder network |
| US10115305B2 (en) * | 2016-09-30 | 2018-10-30 | Nissan North America, Inc. | Optimizing autonomous car's driving time and user experience using traffic signal information |
| EP3759560B8 (en) | 2018-02-28 | 2022-03-30 | Nissan North America, Inc. | Transportation network infrastructure for autonomous vehicle decision making |
| CN111968369B (en) * | 2020-08-14 | 2021-07-20 | 山东师范大学 | Traffic route guidance method and system |
| CN113494926A (en) * | 2021-09-06 | 2021-10-12 | 深圳慧拓无限科技有限公司 | Path finding method, device and equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5523765A (en) * | 1993-06-10 | 1996-06-04 | Alpine Electronics, Inc. | Method and apparatus for detecting vehicle location for a vehicle navigation system |
| CN101777257A (en) * | 2009-12-29 | 2010-07-14 | 北京世纪高通科技有限公司 | Method and system for obtaining traffic report |
| CN102128629A (en) * | 2010-01-13 | 2011-07-20 | 华为技术有限公司 | Path planning method, navigation system and geographical information system |
| CN102252687A (en) * | 2011-07-06 | 2011-11-23 | 广东威创视讯科技股份有限公司 | Method and device for acquiring fastest running path of vehicle |
| CN102506885A (en) * | 2011-10-31 | 2012-06-20 | 武汉光庭科技有限公司 | Method for planning paths according to habit data of users |
| CN102741654A (en) * | 2010-03-08 | 2012-10-17 | 三菱电机株式会社 | Path search device |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3154571B2 (en) * | 1992-10-27 | 2001-04-09 | 松下電器産業株式会社 | Travel position display device provided with voice guidance device |
| JPH06301893A (en) * | 1993-04-15 | 1994-10-28 | Toshiba Corp | Route searching device and car navigation device |
| JP5669593B2 (en) * | 2011-01-24 | 2015-02-12 | 株式会社ナビタイムジャパン | Information processing system, information processing server, information processing apparatus, information processing method, and program |
-
2012
- 2012-10-29 CN CN201210419222.8A patent/CN102927990B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5523765A (en) * | 1993-06-10 | 1996-06-04 | Alpine Electronics, Inc. | Method and apparatus for detecting vehicle location for a vehicle navigation system |
| CN101777257A (en) * | 2009-12-29 | 2010-07-14 | 北京世纪高通科技有限公司 | Method and system for obtaining traffic report |
| CN102128629A (en) * | 2010-01-13 | 2011-07-20 | 华为技术有限公司 | Path planning method, navigation system and geographical information system |
| CN102741654A (en) * | 2010-03-08 | 2012-10-17 | 三菱电机株式会社 | Path search device |
| CN102252687A (en) * | 2011-07-06 | 2011-11-23 | 广东威创视讯科技股份有限公司 | Method and device for acquiring fastest running path of vehicle |
| CN102506885A (en) * | 2011-10-31 | 2012-06-20 | 武汉光庭科技有限公司 | Method for planning paths according to habit data of users |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102927990A (en) | 2013-02-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102927990B (en) | Locomotive is by the method for Geographic Information System determination urban road optimal path of automobile | |
| CN102147260B (en) | Electronic map matching method and device | |
| CN104677374B (en) | Multi-mode route planning | |
| CN102538806B (en) | A kind of paths planning method and relevant device | |
| CN102788584B (en) | The energy consumption prediction unit of road grade data generating device and generation method, vehicle console device and vehicle | |
| CN101694749B (en) | Method and device for speculating routes | |
| US10139245B2 (en) | Device for providing electric-moving-body information and method for providing electric-moving-body information | |
| CN106323321A (en) | Vehicle navigation real-time correction method and vehicle navigation real-time correction system | |
| CN102081658A (en) | Hierarchical road network-based path search method and device | |
| CN104931063A (en) | Route planning method | |
| CN104197948A (en) | Navigation system and method based on traffic information prediction | |
| CN103149577B (en) | The Combinated navigation method that " Big Dipper " navigation, GPS navigation and historical data merge | |
| JP6081806B2 (en) | Electric vehicle information providing apparatus, electric vehicle information providing method, program, and EV management system | |
| CN103903468B (en) | Congestion in road time method for early warning and device | |
| CN104266656A (en) | Method and device for searching shortest path of road network | |
| CN112765753B (en) | Public transport super network construction method | |
| CN106767857A (en) | Vehicle mounted guidance driftage path recalculation method and device | |
| CN106225800A (en) | Environmentally friendly automobile navigation path construction method based on real-time road condition information | |
| CN104394568A (en) | Geographic position routing method based on artificial cobweb in vehicle self-organizing network | |
| JP6647172B2 (en) | Route identification device, route identification system, and route identification method | |
| CN112381472A (en) | Subway connection bus route optimization method and device and storage medium | |
| CN112991743A (en) | Real-time traffic risk AI prediction method based on driving path and system thereof | |
| CN103245350B (en) | A kind of method and device judging point of interest getatability | |
| CN105160429B (en) | It is a kind of that there is the multi-mode Public Transport Transfer method for virtually changing to micro- hinge | |
| CN111337047A (en) | Unstructured road macroscopic path planning method based on multi-task point constraint |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20151021 Termination date: 20161029 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |