CN103033194A - Route guidance system - Google Patents

Route guidance system Download PDF

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CN103033194A
CN103033194A CN2012102988473A CN201210298847A CN103033194A CN 103033194 A CN103033194 A CN 103033194A CN 2012102988473 A CN2012102988473 A CN 2012102988473A CN 201210298847 A CN201210298847 A CN 201210298847A CN 103033194 A CN103033194 A CN 103033194A
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traffic
transport information
route
pattern
information
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CN2012102988473A
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熊谷正俊
奥出真理子
蛭田智昭
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Hitachi Ltd
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Hitachi Ltd
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Abstract

The invention provides a route guidance system which can rapidly output an approximate route subject to a route based on current traffic condition information. The route guidance system comprises: a traffic condition classification unit which classifies a plurality of traffic conditions based on traffic information at every moment into a plurality of traffic condition modes; a route database generation unit which corresponds to each mode of the plurality of traffic condition modes, performs route search calculation against all combinations among multiple places, and saves all the routes obtained by route search calculation in a route database; a traffic condition comparison unit which outputs a traffic condition mode similar to current traffic information out of the plurality of traffic condition modes; and a route information search unit which detects by reference to the route database and outputs a route from a starting place to a destination based on the traffic condition modes output by the traffic condition comparison unit.

Description

Route guidance system
Technical field
The present invention relates to the Route guiding service.
Background technology
As the background technology of the art, there is TOHKEMY 2007-192727 communique (patent documentation 1).This patent documentation 1 discloses and has utilized high-precision transport information to search for until the technology of the recommendation paths of destination.
In addition, disclose in the patent documentation 2 by carrying out principal component analysis (PCA) for the transport information vector and synthesizing to come the approximate technology that shows transport information based on the linearity of its substrate that obtains.
Patent documentation 1:JP JP 2007-192727 communique
Patent documentation 2:JP JP 2006-251941 communique
If utilize transport information, then can carry out and the corresponding dynamic optimal path guiding of traffic at that time.But, owing to have the request of Route guiding all to need to utilize up-to-date transport information executive path search at every turn, therefore in calculation process, expend time in.
On the other hand, in order to shorten the execution time of route searching, if for being set as the departure place, whole places of destination are respectively as the departure place, all combinations of destination, to search in advance whole departure places obtains the result to all the path between the destinations (full search) and is kept in the database, then when receiving the Route guiding request, from database, read and the specified corresponding departure place-destination in departure place and destination between the path, do not need to have the Route guiding request all to carry out the route searching calculation process at every turn, the path has just been obtained in search processing by database, correspondingly improves therewith the response for the Route guiding request.
But, in the method for in advance path between possible destination, departure place being searched for entirely, can't provide and the corresponding optimal path of traffic that constantly changes.In addition, if above-mentioned full search is carried out on the basis in the combination of the whole traffics that reflect prior hypothesis, then also can reflect traffic, but because that the status number of traffic exists is countless, therefore carries out in advance full search for whole traffics and can be described as unpractical scheme.
Summary of the invention
In order to solve above-mentioned problem, route guidance system of the present invention possesses: the traffic taxon, and it will be categorized as a plurality of traffic patterns based on a plurality of traffics of each transport information constantly; The routing database generation unit, each pattern of itself and a plurality of traffic patterns is carried out the route searching computing for all combinations of a plurality of intersites accordingly, will be kept in the routing database by all paths that the route searching computing obtains; The traffic comparing unit, it is exported from a plurality of traffic patterns and the similar traffic pattern of the present situation transport information; With the routing information retrieval unit, it is also exported from the departure place to the path of destination with reference to the path data library searching based on the traffic pattern by the output of traffic comparing unit.
The invention effect
Route guidance system of the present invention can response provides approximate path based on the path of the present situation transport information well by prior search.
Description of drawings
Fig. 1 is the pie graph of the route guidance system among the 1st embodiment.
Fig. 2 is the figure of the data structure of expression routing database.
Fig. 3 is the display frame at Route guiding interface.
Fig. 4 carries out the synoptic diagram that center of gravity that cluster obtains is carried out the traffic comparison according to transport information being projected to feature space.
Fig. 5 is the generation treatment scheme of the routing database in the route guidance system.
Fig. 6 is the treatment scheme of the route searching in the route guidance system.
Fig. 7 is the pie graph of the route guidance system among the 2nd embodiment.
Fig. 8 is the curve along with the error change trend of time process of the present situation transport information and statistic traffic information.
Fig. 9 is the treatment scheme of route guidance system.
Among the figure:
100 route guidance systems
101 traffic information databases
102 traffic sorters
103 traffic patterns
104,803 routing database generating apparatus
105,804 routing databases
106 the present situation transport information
107 traffic comparison devices
108 routing information indexing units
109 Route guiding interfaces
110 map data bases
150 guiders
The coordinate of 401 feature space vectors
501 groups (cluster)
The coordinate of 502 group's centers of gravity
503 coordinates apart from the nearest group's center of gravity of the coordinate of the eigenspace projection point of the present situation transport information
The coordinate of the eigenspace projection point of 601 the present situation transport information
801 statistic traffic information generating apparatus
802 statistic traffic information databases
Embodiment
Below, utilize description of drawings to use the embodiment of route search system of the present invention.
(the 1st embodiment)
Fig. 1 is the pie graph of the route guidance system 100 of present embodiment.Route guidance system 100 has: traffic information database 101, traffic sorter 102, traffic pattern 103, routing database generating apparatus 104, routing database 105, the present situation transport information 106, traffic comparison device 107, routing information indexing unit 108, map data base 110.Guider 150 is external device (ED)s of route guidance system 100, has Route guiding interface 109.Input and output between route guidance system 100 and the guider 150 are carried out via communicating by letter.
In route guidance system 100, each update cycle from the transport information of each time point of collected outside as the present situation transport information 106.This current situation transport information 106 also exists based on the transport information of having uploaded by the detection data of the running data of probe vehicles (mobile cart) instrumentation except the transport information that obtains from the sensor that is arranged at the roadside.Collected the present situation transport information 106 of each update cycle is stored in the traffic information database 101 of accumulating transport information in the past.
Preserve the transport information in the past that represents with numeric datas such as highway section hourage or highway section representation speeds in the traffic information database 101.
In traffic sorter 102, read the transport information of preserving in the traffic information database 101, generate representational a plurality of traffic patterns 103 by cluster (clustering).There are various known methods in the method for cluster.Traffic sorter 102 utilizes K-means method for example to carry out the cluster of traffic in the past.The detailed content of the processing that traffic sorter 102 carries out is narrated in the back.
Traffic pattern 103 is generated by traffic sorter 102.Because traffic pattern 103 generates by cluster, therefore do not represent the in the past traffic of instrumentation itself.The traffic in past is categorized as a plurality of traffic patterns 103, and each traffic pattern is represented as in the representative traffic in the past the each other approximate value of similar several situations.Give respectively intrinsic pattern numbering to traffic pattern 103.
In routing database generating apparatus 104, utilization is based on the map datum of preserving in the route searching cost of the transport information corresponding with traffic pattern 103, the map data base 110, path search algorithm by Di Jiesite (Dijkstra) method etc., for with traffic pattern 103 respectively all of corresponding whole intersites be combined into the computing of walking along the street path search, will be kept in the routing database 105 by all paths that this route searching computing obtains.At this, what is called is to carry out route searching for whole combinations of the node that may become departure place and destination (node) for the route searching computing of all combinations of whole intersites.Namely, all nodes from map data base 110 in the subject area of acquisition approach search, for with it as all combinations of departure place or destination (wherein, remove both and be all same node), carry out in advance route searching according to the route searching cost based on the transport information corresponding with each traffic pattern 103.
In routing database 105, as shown in Figure 2 with each traffic pattern 103 accordingly, preserve to consist of the highway section row in the path that departure place node and destination node are linked.This highway section row be from the departure place to the destination to consist of from as the node of departure place to the highway section numbering as the road section in the path of the node of destination.
In traffic comparison device 107, relatively the present situation transport information 106 and traffic pattern 103, the pattern of the traffic pattern 103 that output and the present situation transport information 106 are the most similar is numbered.The detailed content back narration of this processing.
In routing information indexing unit 108, with reference to the routing database 105 of having preserved for the route searching result of whole internodal all combinations corresponding with the traffic pattern of the pattern numbering of traffic comparison device 107 output, retrieval to the path of destination, exports the highway section row that consist of this path at the Route guiding interface 109 of guider 150 from the departure place of being inputted by the Route guiding interface 109 of guider 150.
Route guiding interface 109 at guider 150, accept the input of departure place and destination from the user, be sent to the routing information indexing unit 108 of route guidance system 100, the routing information in this departure place of connection of received path message indexing unit 108 outputs and the path 300 of destination.And, when receiving the highway section row at Route guiding interface 109 from routing information indexing unit 108, shown in the picture of Fig. 3, emphasize to show with the highway section at the map that shows departure place and destination to be listed as corresponding path.
Next, the detailed content of traffic sorter 102 is described.Traffic sorter 102 is with the object of the multi-C vector take the transport information in a plurality of highway sections as key element as cluster.If the transport information in a highway section is thought of as a value on the coordinate axis, the traffic in zone that for example then comprises 1000 highway section is expressed as the transport information vector on the transport information spaces of 1000 dimensions.1000 components that this transport information vector has represent respectively the numerical value relevant with the mobile cost in each highway section such as highway section hourage in 1000 highway sections or highway section representation speed.The numeric data of this highway section hourage or highway section representation speed etc. is kept in the traffic information database 101 based on the transport information in past as described above.Will there be one in this transport information vector in the update cycle of each transport information.That is, transport information vector representation is based on the traffic in 1000 highway sections of certain transport information constantly.102 pairs of traffic sorters upgrade these transport information vectors that generate by a plurality of transport information and carry out cluster, obtain a plurality of representational groups.In each group, expression is classified based on a plurality of transport information vectors of a plurality of traffics of a plurality of different transport information constantly.Utilizing the transport information vector corresponding with the center of gravity of these a plurality of transport information vectors is that the center of gravity vector of each group represents traffic pattern 103.
But in the more situation of highway section number, the operand of cluster becomes huge.In this case, preferably as patent documentation 2 is disclosed, carries out principal component analysis (PCA) and come approximate performance transport information by the linearity of resulting substrate is synthetic for the transport information vector.That is, at first the transport information vector is projected as the feature space vector in the feature space of the low dimension that obtains by principal component analysis (PCA), next carries out significantly to reduce operand thus with the cluster of the feature space vector in the feature space as object.Be explained among Fig. 4.The coordinate 401 of a plurality of feature space projection of vector points that will obtain by principal component analysis (PCA) for convenience of description among Fig. 4 is expressed as the two-dimentional segment space that cuts out 2 substrate W 1 and W2 from feature space.The dimension of actual feature space for example can be set as 90% the information that the accumulation contribution rate in the principal component analysis (PCA) be similar to as index that maintenance original traffic information vector has.When carrying out cluster as object, obtaining a plurality of groups 501 with this feature space vector (subpoint).From a plurality of centers of gravity vector that the feature space transverse projection obtains to the original traffic information space, be respectively in the transport information space, to carry out cluster and the approximate vector of the center of gravity vector of each group of obtaining with a plurality of groups 501 center of gravity 502 separately.Can will should be used as traffic pattern 103 by approximate vector.
Next, the detailed content of traffic comparison device 107 is described.Traffic comparison device 107 represents relatively that respectively the transport information vector sum based on the traffic of the present situation transport information 106 represents a plurality of transport information vectors of a plurality of traffic patterns 103, the a plurality of difference vectors that mutually relatively obtain based on its difference, output is by the pattern numbering of the traffic pattern 103 of the corresponding transport information vector representation of the difference vector of Norm minimum.
As described above, carry out a plurality of transport information vector projections in the situation of cluster to feature space at traffic sorter 102, traffic comparison device 107 also will represent transport information vector projection based on the traffic of the present situation transport information 106 to feature space, and traffic comparison device 107 carries out the comparison of the present situation transport information 106 and traffic pattern 103 in feature space thus.A plurality of centers of gravity 502,503 etc. are positioned at the coordinate on each characteristic of correspondence space with a plurality of traffic patterns 103.Coordinates 601 with expression based on the coordinate of transport information vector projection to feature space of the traffic of the present situation transport information 106.In this embodiment, the center of gravity that coordinate on traffic comparison device 107 search and the feature space 601 is nearest export the pattern of the traffic pattern 103 corresponding with this center of gravity and is numbered.In the example of Fig. 4, be output with pattern numbering from traffic pattern 103 corresponding to the nearest center of gravity of coordinate 601 503.
Fig. 5, Fig. 6 are with the action of flowcharting route guidance system 100.Fig. 5 represent to comprise a plurality of traffic patterns 103 generation, for a plurality of traffic patterns 103 processing sequence route searching computing, prepared in advance routing database 804 by route guidance system 100 of all combinations of corresponding whole intersites respectively.The processing sequence of being undertaken by route guidance system 100 when Fig. 6 is illustrated in and carries out from the departure place route searching to the destination for specified departure place and destination.Moreover, at this situation of carrying out as described above cluster in feature space is described.
In the step 701 of Fig. 5, by traffic sorter 102 sense data from traffic information database 101.Traffic sorter 102 obtains the transport information as the past in the zone of route searching object.In step S702, carried out the computing of the principal component analysis (PCA) of transport information vector by traffic sorter 102.Traffic sorter 102 generates and passes through for the resulting substrate characteristic of correspondence of the principal component analysis (PCA) of transport information vector space, and this transport information vector representation is based on the traffic of the transport information that is obtained by step 701.Moreover the substrate that obtain this moment is also used in step 705 described later, step 712, therefore is kept in other memory storages (not shown).In step S703, traffic sorter 102 carries out in this feature space this transport information vector being carried out the computing of projection.By to step S701 in the projection in the transport information characteristic of correspondence space that obtains, obtain feature space vector (subpoint).In step S704, carry out the computing of cluster by traffic sorter 102, form this subpoint and be classified group afterwards.Although there is the whole bag of tricks in the cluster, if use for example K-means method, then form a plurality of spherical groups, can guarantee from the subpoint that is classified to each group the shortest to the distance of group's center of gravity of this group.In step S705, carry out subpoint and group's center of gravity to transverse projection (inverse projection) computing in transport information space by traffic sorter 102.Obtained traffic pattern 103 according to group's center of gravity by the center of gravity vector that transverse projection obtains.
S706 is the circular treatment in the routing database generating apparatus 104.In routing database generating apparatus 104, utilization is based on the route searching cost of the transport information corresponding with traffic pattern difference, in the circular treatment relevant with all nodes of step S707, carry out route searching computing 708, Search Results is kept in the routing database 105.Particularly, because the transport information corresponding with the traffic pattern is information hourage in each highway section, therefore used as the highway section cost that is used for route searching or it is reflected in the path cost etc. carry out route searching.Thus, obtain and routing information corresponding to all internodal path coherences of each traffic pattern 103.
In the step S709 of Fig. 6, routing information indexing unit 108 receive users via the departure place of Route guiding interface 109 inputs of guider 150 and destination in interior Route guiding request.In step S710, carry out the present situation transport information 106 is inputed to the processing of traffic comparison device 107.In step S711, carry out computing by traffic comparison device 107, with expression based on the transport information vector projection of the traffic of the present situation transport information 106 to feature space.In traffic comparison device 107, this transport information vector projection is obtained feature space to step S702.The substrate that use this moment is used the substrate of obtaining in advance as described above in step S702.
Step S712 is the circular treatment in the traffic comparison device 107.In step S713, the expression that obtains among the traffic comparison device 107 calculation procedure S711 based on subpoint in feature space of the transport information vector of the traffic of the present situation transport information 106, with distance corresponding to group's center of gravity of each traffic pattern 103.
In step S714, traffic comparison device 107 will be corresponding with the group's center of gravity that is in the bee-line place within the distance of subpoint that calculates among the step S713 the pattern numbering of traffic pattern 103, export routing information indexing unit 108 to as the pattern numbering of the traffic pattern the most similar to the present situation transport information.In step S715, routing information indexing unit 108 sends retrieval request to routing database 105, carries out route search with reference to the path of the routing database 804 that generates in advance in the processing of Fig. 5.Namely, based on utilized by the user via among specified departure place, the Route guiding interface 109 of guider 150 and destination, the step S714 from the pattern numbering of the traffic pattern 103 of traffic comparison device 107 inputs, read with from the routing information corresponding to the path coherence of this departure place to this destination of this pattern numbering.Because the path corresponding with the routing information of reading is the path that retrieves in the traffic pattern 103 the most similar to the present situation transport information 106, therefore be with based on the present situation transport information 106 actual approximate paths that carry out the resulting path proximity of route searching.
In step S716, routing information indexing unit 108 is sent to this routing information of reading among the step S715 at the Route guiding interface 109 of guider 150.The Route guiding interface 109 of guider 150 will be presented on the picture as path 300 as shown in Figure 3 by the approximate path of routing information indexing unit 108 outputs.
The processing of carrying out among the processing of carrying out among step S701 shown in Figure 5~S708 and the step S709 shown in Figure 6~S716 is processing independent of each other.Step S701~S708 can carry out in the situation of off-line in advance.For example can implement termly this processing by a month inferior mode.With respect to this, step S709~S716 be according to from the Route guiding request of guider 150 and with update cycle of transport information be that obtaining synchronously of the present situation transport information carried out in real time.Like this, route guidance system 100 can provide rapidly from by Route guiding interface 109 input of guider 150 from the departure place to the above-mentioned approximate path of destination.Even if in the present situation transport information 106, comprise in the situation of information of traffic control etc. of burst, this approximate path also be to the path that comprises this information and in the most similar traffic pattern 103 of interior the present situation transport information 106, retrieve.Therefore, obtain based on the approximate path in the corresponding path of road conditions of reality.
Among the circular treatment in the traffic comparison device 107 of expressing as step S712, in step S713, traffic comparison device 107 calculates expression based on subpoint in feature space of the transport information vector of the traffic of the present situation transport information 106 that obtains among the step S711, and corresponding to the distance between group's center of gravity of each traffic pattern 103.But, in step S703, do not carried out by traffic sorter 102 with corresponding to the transport information vector projection of each traffic pattern 103 in the situation of the computing of feature space, also can be in step S711 be represented based on the computing to the projection of feature space of the transport information vector of the traffic of the present situation transport information 106 by traffic comparison device 107.At this moment, can be in step S713, traffic comparison device 107 calculate from expression based on the transport information of the traffic of the present situation transport information 106 that obtains the step S711 to the distance that measures till the transport information vector corresponding with the center of gravity of group (center of gravity vector), the center of gravity of this group is corresponding with each traffic pattern 103.
(the 2nd embodiment)
Method as the precision that improves Route guiding, known method as TOHKEMY 2007-192727 communique (patent documentation 1), for in the route searching cost, using the present situation transport information near the departure place, in place far away, distance departure place, within exceeding the scope of error of statistic traffic information, the error of the present situation transport information then uses statistic traffic information for the route searching cost.In the present embodiment, the method for precision that the method improves the route guidance system of embodiment 1 is used in expression.
Fig. 7 is the pie graph of the route guidance system 800 of present embodiment.Because the basic structure of route guidance system 800 is identical with the route guidance system 100 of Fig. 1, therefore narrate the inscape different from route guidance system 100 here.
The 801st, the statistic traffic information generating apparatus utilizes the transport information in the past of preserving in the traffic information database 101 to generate statistic traffic information.The information that obtains the statistical typical value of transport information in the past in time period festivals or holidays in week etc. at this so-called statistic traffic information, for example Sun. 10:00 highway section hourage, this information of highway section representation speed be kept in the statistic traffic information database 802.
Next, the processing of narration routing database generating apparatus 803.Routing database generating apparatus 104 in the route guidance system 100 only carries out route searching with the transport information of traffic pattern 103 as searching cost, but routing database generating apparatus 803 carries out route searching with the both sides' of traffic pattern 103 and statistic traffic information database 802 transport information as searching cost.As described in the patent documentation 1, take certain time point as starting point the time, the present situation transport information of this time point and the error of statistic traffic information along with the time through reversing as shown in Figure 8.Both error counter-rotating and the error of the present situation transport information elapsed time of surpassing the error of statistic traffic information are set as threshold value 901.Because traffic pattern 103 is the information that becomes the object that relatively contrasts with the present situation transport information 106 in traffic comparison device 107, therefore in routing database generating apparatus 803, threshold value 901 is used the threshold value of traffic pattern 103 and statistic traffic information database 802 as differentiation.Namely, in routing database generating apparatus 803, utilize in the situation that Di Jiesitefa searches for, calculate as searching cost in name a person for a particular job traffic pattern 103 of search start time, when determining to arrive the shortest time path of new node at every turn, arrive the time of arrival of this node and the comparison of threshold value 901, time point in time of arrival above threshold value 901 switches to statistic traffic information database 802 with searching cost from traffic pattern 103.
Among Fig. 9 with the processing of the routing database generating apparatus 803 narrated more than the flowcharting.S1001 is the circulation relevant with all nodes, and each node is processed as the search that the node that sets out carries out S1002~S1006.S1002 is the initialization of search, and the transport information with traffic pattern 103 in each highway section is set as searching cost.S1003 is the processing of determining successively the shortest time path that begins near the node the starting point.S1004 finish to judge, arrives and finishes search in the situation of the shortest time path of all nodes and process having set out node determination for this, continues search and process in undetermined situation still.In S1005, reach time of arrival and the threshold value 901 of the node of having determined the shortest time path among the comparison step S1003, when surpassed threshold value time of arrival, the transport information with statistic traffic information database 802 in S1006 was set as the searching cost of finishing each highway section that does not comprise in definite shortest path.By above processing, routing database generating apparatus 803 is distinguished and is entirely searched for traffic pattern 103 and statistic traffic information database 802.In addition, with reference to the routing database 804 that generates like this, routing information indexing unit 108 can send the routing information that has added traffic pattern 103 and statistic traffic information database 802 both sides based on the comparison result of the present situation transport information 106 and the traffic pattern 103 of traffic comparison device 107.

Claims (4)

1. route guidance system is characterized in that possessing:
The traffic taxon, it will be categorized as a plurality of traffic patterns based on a plurality of traffics of each transport information constantly;
The routing database generation unit, each pattern of itself and described a plurality of traffic patterns accordingly, carry out the route searching computing for all combinations of a plurality of intersites, will be kept in the routing database by all paths that described route searching computing obtains;
The traffic comparing unit, it is exported from described a plurality of traffic patterns and the similar traffic pattern of the present situation transport information; With
The routing information retrieval unit, it is also exported from the departure place to the path of destination with reference to described path data library searching based on the described traffic pattern by described traffic comparing unit output.
2. route guidance system according to claim 1 is characterized in that,
Described traffic taxon is categorized as a plurality of groups by cluster with described a plurality of traffics,
Each pattern of described a plurality of traffic patterns is corresponding to each group of described a plurality of groups.
3. route guidance system according to claim 2 is characterized in that,
Each traffic of described a plurality of traffics by comprise with corresponding to the relevant a plurality of compositions of a plurality of mobile cost of each interval road of a plurality of interval roads in interior transport information vector representation,
Each pattern of described a plurality of traffic patterns is by the described transport information vector representation corresponding with the center of gravity of described each group,
Described traffic comparing unit will a plurality of transport information vectors corresponding with described a plurality of groups centers of gravity separately within, be in and expression based on the represented traffic pattern of the described transport information vector of the nearest distance of the described traffic vector of the traffic of described the present situation transport information, as exporting with the similar traffic pattern of described the present situation transport information.
4. route guidance system according to claim 3 is characterized in that,
Be defined threshold when following in described nearest distance, described traffic comparing unit output and the similar described traffic pattern of described the present situation transport information,
According within described a plurality of groups, be in expression and determine described defined threshold based on the represented corresponding group of traffic pattern of the described transport information vector of the described nearest distance of the described traffic vector of the traffic of described the present situation transport information.
CN2012102988473A 2011-09-28 2012-08-21 Route guidance system Pending CN103033194A (en)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103337189A (en) * 2013-06-08 2013-10-02 北京航空航天大学 Dynamic road segment division based vehicle route guidance method
CN103968854A (en) * 2014-05-27 2014-08-06 四川汇源吉迅数码科技有限公司 Route cluster planning method
CN103838846B (en) * 2014-03-06 2017-02-01 中国科学院软件研究所 Emergency guiding method and emergency guiding system for individual on basis of big data
CN107003138A (en) * 2014-12-24 2017-08-01 爱信艾达株式会社 Route search system, method and program
CN109716067A (en) * 2016-09-27 2019-05-03 爱信艾达株式会社 Path searching apparatus, route search system and computer program
CN109760052A (en) * 2019-01-17 2019-05-17 琦星智能科技股份有限公司 A kind of method for building up in robot basic program library

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5586570B2 (en) * 2011-11-25 2014-09-10 株式会社日立製作所 Route guidance system
DE102015209575A1 (en) 2014-06-17 2015-12-17 Robert Bosch Engineering and Business Solutions Ltd. Navigation device and method

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1521483A (en) * 2003-01-17 2004-08-18 Lg������ʽ���� Device and method for traffic information guiding in navigation system
EP1614994A1 (en) * 2004-07-09 2006-01-11 Aisin Aw Co., Ltd. Navigation apparatus and method
JP2008096445A (en) * 2007-10-29 2008-04-24 Xanavi Informatics Corp Route searching method of navigation device and traffic information displaying method
CN101763730A (en) * 2009-12-30 2010-06-30 北京世纪高通科技有限公司 Traffic road condition information filling method and system
CN101809412A (en) * 2008-03-14 2010-08-18 爱信艾达株式会社 Navigation system and route search method
JP2010287251A (en) * 2003-08-07 2010-12-24 National Institute Of Advanced Industrial Science & Technology Traffic congestion prediction program, computer readable recording medium recording the same and traffic congestion prediction apparatus, and navigation program, computer readable storage medium recording the same and navigation apparatus
WO2011018143A1 (en) * 2009-08-11 2011-02-17 Bayerische Motoren Werke Aktiengesellschaft Transmission and/or processing of traffic information

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4135536B2 (en) * 2003-03-13 2008-08-20 株式会社デンソー Vehicle navigation device
JP3834017B2 (en) * 2003-06-05 2006-10-18 本田技研工業株式会社 Traffic information management system
JP4329711B2 (en) * 2005-03-09 2009-09-09 株式会社日立製作所 Traffic information system
JP4807083B2 (en) * 2006-01-20 2011-11-02 日産自動車株式会社 Route search system

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1521483A (en) * 2003-01-17 2004-08-18 Lg������ʽ���� Device and method for traffic information guiding in navigation system
JP2010287251A (en) * 2003-08-07 2010-12-24 National Institute Of Advanced Industrial Science & Technology Traffic congestion prediction program, computer readable recording medium recording the same and traffic congestion prediction apparatus, and navigation program, computer readable storage medium recording the same and navigation apparatus
EP1614994A1 (en) * 2004-07-09 2006-01-11 Aisin Aw Co., Ltd. Navigation apparatus and method
JP2008096445A (en) * 2007-10-29 2008-04-24 Xanavi Informatics Corp Route searching method of navigation device and traffic information displaying method
CN101809412A (en) * 2008-03-14 2010-08-18 爱信艾达株式会社 Navigation system and route search method
WO2011018143A1 (en) * 2009-08-11 2011-02-17 Bayerische Motoren Werke Aktiengesellschaft Transmission and/or processing of traffic information
CN101763730A (en) * 2009-12-30 2010-06-30 北京世纪高通科技有限公司 Traffic road condition information filling method and system

Cited By (8)

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