CN106931986A - Personalized method for path navigation and system - Google Patents
Personalized method for path navigation and system Download PDFInfo
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- CN106931986A CN106931986A CN201710282460.1A CN201710282460A CN106931986A CN 106931986 A CN106931986 A CN 106931986A CN 201710282460 A CN201710282460 A CN 201710282460A CN 106931986 A CN106931986 A CN 106931986A
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3484—Personalized, e.g. from learned user behaviour or user-defined profiles
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Abstract
The invention discloses a kind of personalized method for path navigation and system.Method includes that from track data extract the routing information that user often accesses, the routing information that the user based on extraction often accesses finds path familiar to user, and on path familiar to user, generation meets the personalized path navigation of user；System includes data preprocessing module, path division module and navigation information generation module, data preprocessing module is used for from the historical trajectory data of user, extract the routing information that user often accesses, path division module is used to find optimal path division, navigation information generation module is based on the routing information that user often accesses for extracting, and personalized path navigation is generated on path familiar to user.One aspect of the present invention makes navigation information become easier to be easily absorbed on a cognitive level by the user, another this invention simplifies navigation instruction, to significantly reduce demand of the navigation application to resource face to face, reduces the development cost of Navigator and the operation cost of navigation application.
Description
Technical field
The present invention relates to field of navigation technology, specifically a kind of personalized method for path navigation and system.
Background technology
Navigation application is a kind of application that best route and corresponding turn direction are found in road network.Existing navigation application
The navigation Service being made up of turn direction (turn-by-turn) for providing, is specially to extract information from the road network of bottom and get
's.So, the information that it can be easily translated into physical world goes to tell about (how far/how long turn direction).But this translation, suddenly
Cognition of the mankind to geographical space has been omited, it is often very tediously long for understanding the driver of geographic area.On most of roads
Driver has good city knowledge and is familiar with some of road network part, the route that they take, (for example, route from
Family can in short be summarized to neighbouring highway：From the home to XXX highways；Rather than：Above XX meters of left-hand rotation ... ...).Therefore,
If to part road familiar to driver, also navigated using the turn direction of existing navigation application, then actually navigation system
To be very redundancy and complexity, corresponding Navigator is also high to the demand of resource, cause the development cost of navigation application and
Operation cost is also high.Also, if used always by direction navigation is turned, typically " front XX meters left for the information that user receives
Turn, front XX meters of right-hand rotation, front keep straight on XX meters ... ... ", the navigation information that user receives is single, it is difficult to meet individual character
The navigation needs of change.Especially with the development of development of Mobile Internet technology, the navigation application of mobile device and onboard navigation system
Ground constantly increases, and have accumulated the track data of substantial amounts of user generation, using these big datas produce more effectively, be easier quilt
The navigation information that people understands is highly useful.
The content of the invention
It is an object of the invention to overcome the deficiencies in the prior art, there is provided a kind of personalized method for path navigation and system,
On the one hand, historical trajectory data based on user produce more customizations and intuitively navigation information, navigation information is become more
Easily understood by driver；On the other hand, navigation instruction is simplified, navigation redundancy is reduced, navigation algorithm is significantly reduced to money
The demand in source.
The purpose of the present invention is achieved through the following technical solutions：A kind of personalized method for path navigation, including：
From track data, extract user knowledge, based on extract user knowledge, find path familiar to user, with
On path familiar to family, generation meets the personalized path navigation of user；
The user knowledge includes the routing information and landmark information that user often accesses, what described user often accessed
Routing information includes avenue name information；The source of the track data, including track data recording equipment, mobile terminal
Navigation application and vehicle terminal navigation application.
Further, in the route or a plurality of route including route familiar to user and the unfamiliar route of user,
For route familiar to user, user is instructed using the personalized route guidance；For the unfamiliar route of user, using turning
Curved direction navigation instruction user.
Further, user is weighed by calculating familiarity fraction f (R) to be in the push route, it is described
Familiarity fraction f (R) is calculated according to the pass by meaning of the frequency in the path and the terrestrial reference in the path of user；Wherein,
The size interval range of f (R) includes：f(R)∈[0,1].
Further, to the familiarity of path segments R (i, j), using equation below calculate familiarity fraction f (R (i,
j))：
Wherein,It is the length ratio of path segments, g () is a monotonic function, g (0)=0, g (1)=1, R
(i, j) is a path segments of R, is terminated to R (j) since R (i), and R (i) is i-th terrestrial reference of path R, and R (j) is path
J-th terrestrial reference of R.
Further, in a kind of travel navigation scene, to route known to user, using passenger as authority, terrestrial reference conduct
Center, registration office carries out the calculating of the meaning of terrestrial reference using HITS algorithms as hyperlink, and then user passes by the path
Frequency is normalized weighted sum with the result of calculation of the meaning of terrestrial reference, using the result of the normalization weighted sum as
Know familiarity fraction f (R) in path；For natural route, then its familiarity fraction f (R) is set to a steady state value.
Further, described method, including step：
S1：From the historical trajectory data of user, path known to extraction user makes user have phase to known path
That answers is familiar with value；
S2：Based on road network information architecture natural route；
S3：Optimal path is found using Dynamic Programming to divide, or, first make path proximity using path candidate condition is relaxed
Matching, then find optimal path division；
S4：Path segments after being divided based on path, the personalized path of generation is summarized, and instructs user.
Including sub-step further, in step sl,：
S101：Calibrated with the track based on anchor using map match, initial trace T is converted into a rail based on terrestrial reference
Mark, anchor point is used as by processing terrestrial reference；After calibration, on the basis of track alignedly target, the track of calibration is used as a ground
Target sequence, as path；
S102：After trajectory path has been demarcated, paired similar of the trajectory path demarcated is calculated using EDR distance algorithms
Property, and path cluster is constituted using similar path；
S103：Using equation below, most representative path R in each path cluster is selected*As known paths；
Wherein, R is path,It is path cluster, DEDRIt is the EDR distances of two paths；
S104：User is weighed using path familiarity fraction f (R) and path segments familiarity fraction f (R (i, j))
To the familiarity in path.
Including sub-step further, in step s 2,：
S201：Input road network, and initialization path clusterMakeIt is empty set；
S202：According to the Name ＆ Location of path segments in road network, it is ranked up using comparator, and from road network
According to the Rule Extraction a line of agreement in network, a line extracted is assigned to setting variable e1；
S203：The side extracted in removing step S202 in road network, then, path is deposited into by this side for removing
In R；
S204：In remaining road network, searched using path R and belong to same section, be joined directly together and turn
Angle and completes the link between the path that finds less than remaining path of setting value, finally links these paths and constitutes
Path candidate cluster；
S205：The Name ＆ Location of the path segments in path candidate cluster is sorted using comparator, and from step
According to the Rule Extraction a line of agreement in path candidate cluster in S204, a line extracted is assigned to setting and is become
Amount e2；
S206：The side extracted in step S205 is removed from road network；
S207：By path R and setting variable e find, satisfactory2In path connection, constitute new path；
S208：When path R can not again find remaining path candidate cluster, terminate to set variable e1Headed by path
Link process, the new path that will be found is deposited into path clusterIn；
S209：Circulation performs step S202~S208, and traversal searches all paths in road network, until road network
In there is no manageable road segment segment untill, then, return path cluster
Further, in step s3, including：
(1) the use Dynamic Programming described in is found optimal path and is divided, including sub-step：
S3012：Whole path R is traveled through, path candidate cluster of the retrieval comprising path link has retrieved all path candidates
Afterwards, the condition optimal dividing of the subpath in whole path R is calculated one by one；
S3013：Path link and current path are divided and merges the new path division of generation, use equation below increment meter
The quality score that newly-generated path divides：
Wherein, Q (i, R'(j, k)) is the quality score that newly-generated path divides；It is path segments R
(i-1, path candidate cluster i)；(R'(j k) is path segments R'(j, familiarity fraction k) to f；λ is specified for user
One nonnegative constant；(i-1 i) is the path segments of R (i-1) to R (i) to R；R " (l, m) is R " (l) arrives R " the path pieces of (m)
Section；R'(j, k) is R'(j) to R'(k) path segments；L-th terrestrial reference of R " (l) is path R "；The of R " (m) be path R "
M terrestrial reference；R'(j) it is j-th terrestrial reference of path R'；R'(k) it is k-th terrestrial reference of path R'；
Then, selection quality score highest one is divided as optimal path；
S3014：Circulation performs step S3012~S3014, calculating is constantly iterated, until finding whole path R most
Shortest path is divided, and then, is returned to the whole path R optimal paths and is divided.
(2) use described in is relaxed path candidate condition and first makees path proximity matching, then finds optimal path division, including
Sub-step：
S3021：Define route matching relation and define path similarity relation, including：
A () defines route matching relation：Two paths R and R` are given, each path is represented by a series of terrestrial reference, one
Route matching M (R, R`) is a terrestrial reference arranged properly to set, and first terrestrial reference of each terrestrial reference centering comes from R, second
Terrestrial reference comes from R2；
B () defines path similarity relation：Given two paths R and R`, and if only if, and R and R` has common terminal, and
M (R, R`) is matched in the presence of an optimal path, then R is similar to R`；Described optimal path matches M (R, R`) and meets：
Each terrestrial reference in R and R` of I occurs at least one times in M (R, R`)；
Each terrestrial reference of II in M (R, R`) is to (li, li`), their network space DN(li,li`)≤ε；
III is in M (R, R`) in the absence of the terrestrial reference pair for intersecting；
Wherein, ε is the maximum road network spacing between the terrestrial reference pair of matching；
S3022：Setting Q (i, R'(j, k)) be last path segments be R'(j, k) R (1, i) relax it is optimal
The quality score that path divides, when R (i) is a terminal of R, it is stipulated that R (i)=R` (k), then the optimal path for relaxing is divided
Meet following recurrence formula：
The condition optimal path that calculating is relaxed is dividedIncluding following two situations：
If 1. k-j>1, then the condition optimal path for relaxing is divided intoWith
Last path segments come from same paths, enumerate when R (i-1) match R` (k), R (i-1) match R` (k-1), R (i)
Matching R` (k-1) when three kinds of situations, then incrementally calculated using equation below path division quality score Q (i, R'(j,
k))：
Q(i,R'(j,k))←max{Q(i-1,R'(j,k)),Q(i-1,R'(j,k-1))+f(R'(j,k))-f(R'(j,
k-1)),
Q(i,R'(j,k-1))+f(R'(j,k))-f(R'(j,k-1))}
If 2. k-j=1, that is, terminate the search procedure of path candidate, new route segment R` (j, k) is opened, now
Path candidate clusterR` (j) is contained, also, R`` isIn arbitrary path, for a paths
There are two kinds of situations in section R`` (l, m), wherein R`` (m)=R` (j)：R`` (m) and R (i-1) is matched or R`` (m) and R (i)
Match somebody with somebody, enumerate both of these case, the quality score Q (i, R'(j, k)) of path division is then incrementally calculated using equation below：
Then, selection quality score highest one is divided as optimal path.
Further, in step s 4, including：
(1) for natural route section, it is described using multiple key features；Described multiple key features include street
Name, distance and shift strategy, described shift strategy represent the action taken at the end of natural route section, it includes turning to,
Continue to travel, leave and reach；
(2) for known paths section, it is described by describing its initial terrestrial reference and terminal terrestrial reference, in starting point terrestrial reference and
In the case that terminal ground terrestrial reference is not enough to describe it, the turnpike road travelled along this paths is also included within description；According to
Actual conditions, can omit one or more features, and the feature of omission includes starting point, street name.
A kind of personalized path guiding system, including：The generation of data preprocessing module, path division module and navigation information
Module, described data preprocessing module, for from the historical trajectory data of user, extracting the path letter that user often accesses
Breath；Described path division module, divides for finding optimal path；Described navigation information generation module, based on what is extracted
The routing information that user often accesses, generates personalized path navigation on path familiar to user.
The beneficial effects of the invention are as follows：
(1) using the historical trajectory data of abundant user's generation, terrestrial reference is extracted from road network, terrestrial reference is (for example, profit
Beneficial point or crosspoint) and the frequent route for accessing of user, and it is utilized for each user customization route plan using the information extracted
Slightly；
(2) as the navigation application ground of mobile device and onboard navigation system constantly increases, have accumulated substantial amounts of user's life
Into track data, the present invention using these data can produce more effectively, be easier the navigation information that is more readily understood；
(3) it is of the invention to become easier to navigation information to be understood by driver, meanwhile, the simplification of instruction can also significantly reduce money
The demand (space of such as bandwidth and screen) in source, additionally, such path framework may also be used for, and guidance is emerging to drive automatically
Automobile is sailed, they need not follow detailed turn direction, and go to pay close attention to those higher level information；
(4) present invention replaces those redundancies, the portion known to driver using content that is specific, being readily appreciated that
Point, and the unfamiliar place of driver, still guide them using detailed steering；
(5) present invention finds terrestrial reference and known track, and uses them to generation navigation direction succinctly, but transmission foot
Enough information come be user explain route, simplify navigation instruction, reduce navigation redundancy；
(6) using known route, these routes are probably sparse to the present invention, and are possible to comprising significantly
Uncertainty, is to be adjusted to " approximate match " from " matching completely " by the requirement of alternative route, is ensureing the enough information of transmission
On the premise of to explain route, so as to summarize path using route known to more users, it is considered to actual driving row
For, algorithm redundancy is not only significantly reduced, and cause that navigation information is easier to be easily absorbed on a cognitive level by the user, individual character can be provided to driver
The navigation information of change；
(7) present invention has carried out substantial amounts of experiment on true and synthesis track data collection, as a result shows, extracts appropriate
The known route of quantity, it is possible to reduce the quantity of redundancy navigation, more than 60%, is user while enough information still can be provided
Guiding route；
(8) one aspect of the present invention makes navigation information become easier to be easily absorbed on a cognitive level by the user, it is another face to face, this invention simplifies leading
Boat instruction, significantly reduces demand of the navigation application to resource, reduces the development cost of Navigator and the fortune of navigation application
Battalion's cost；
(9) navigation Service being made up of turn direction that existing navigation application is provided, is the special extraction from the road network of bottom
Information and get, by comparison, the present invention from user accumulation track data or other track data sources in, extract user
Known paths information, and based on the Given information for extracting, generation meets the navigation information of user, facilitates user, improves use
Family navigation experience.
Brief description of the drawings
The step of Fig. 1 is the inventive method flow chart；
Fig. 2 is flow chart the step of the present invention extracts user's known paths；
Fig. 3 is the step of present invention builds the natural route based on road network information flow chart；
Fig. 4 directly finds flow chart the step of optimal path is divided for the present invention using Dynamic Programming；
Fig. 5 first makees path proximity matching for the present invention using path candidate condition is relaxed, then finds optimal path division
Flow chart of steps；
Fig. 6 is the functional module structure figure of present system.
Specific embodiment
Technical scheme is described in further detail below in conjunction with the accompanying drawings, but protection scope of the present invention is not limited to
It is as described below.
Embodiment
Basic variable is defined first, including：
Define terrestrial reference l, terrestrial reference l is a geographic point in space, and it is stable, independently of user trajectory
Outside, it can be a node on a point of interest or road network.
Define path R, the paths R in road network is defined as the sequence of the composition of terrestrial reference one by one, R=l1,
L2 ... ln, R i represent i-th terrestrial reference in the path, and the adjacent ground of each two is joined directly together in being marked on road network.
Define path segmentsConsider paths a R=l1, l2 ..., ln, its path segments A terrestrial reference sequence subset in R is defined as, wherein, R (i, i+1) represents connection R (i)
With the route segment of R (i+1), R (1, n) represent path R in itself.
It is i-th terrestrial reference in the R of path to define R (i).
It is a path segments to define R (i, j), is terminated to R (j) since R (i).
It is the quality score that a path divides P to define Q (P).
In road network, adjacent link generally has some common features, such as street name, direction.Based on this
Road network, can be divided into multiple disjoint routes, i.e. each link fully belongs to a route, same by a little features
All adjacent links have identical feature in one route.Because such route is independently of specific user,
It is defined as natural route (natural route, NR), and natural route is navigated software with the mode that turn direction is navigated to retouch
State stretch.Path R=l1, l2 ... the ln given for one, can be represented with a sequence for natural route fragment,
Can be expressed as：[NR1(,),NR2(,),…,NRm(,)](m<=n), it is called the navigation strategy of system optimal.
But, also there is another type of route, it varies with each individual.In real world, the commuter in city
(user) some terrestrial references and route can be especially familiar with, such as from the home to job site or from job site to shopping in
The heart, we call this path for known paths (known route, KR), and a known paths are often comprising multiple nature roads
Footpath section, such as KR=[NRi (), NRi+1 () ..., NRj ()].Therefore, if this natural route section sequence is of R
Subsequence, we can replace this subsequence with using a single known paths section, be the optimal navigation of user
Strategy.Because multiple naturally route segments are generalized a known route segment, the optimal navigation strategy of user can make navigation
Become more succinct, i.e. used less path hop count than the navigation strategy of system optimal, user can be cooked up and be more familiar with
Route.
A kind of personalized method for path navigation, including：
From track data, extract user knowledge, based on extract user knowledge, find path familiar to user, with
On path familiar to family, generation meets the personalized path navigation of user；
The user knowledge includes the routing information and landmark information that user often accesses, what described user often accessed
Routing information includes avenue name information；The source of the track data, including track data recording equipment, mobile terminal
Navigation application and vehicle terminal navigation application.
Further, in the route or a plurality of route including route familiar to user and the unfamiliar route of user,
For route familiar to user, user is instructed using the personalized route guidance；For the unfamiliar route of user, using turning
Curved direction navigation instruction user.
Further, as shown in figure 1, described method includes step：
S1：From the historical trajectory data of user, path known to extraction user makes user have phase to known path
That answers is familiar with value；
S2：Based on road network information architecture natural route；
S3：Optimal path is found using Dynamic Programming to divide, or, first make path proximity using path candidate condition is relaxed
Matching, then find optimal path division；
S4：Path segments after being divided based on path, the personalized path of generation is summarized, and instructs user.
Further, as shown in Fig. 2 in step sl, including sub-step：
S101：Calibrated with the track based on anchor using map match, initial trace T is converted into a rail based on terrestrial reference
Mark, anchor point is used as by processing terrestrial reference；After calibration, on the basis of track alignedly target, the track of calibration is used as a ground
Target sequence, as path；
One original track T is a sequence for limited position, from an original path for mobile object and its phase
The timestamp sampling of pass, i.e. T=(P1, T1), (P2, T2) ... ... (PN, TN), wherein Pi is the position specified by latitude and longitude
Put, Ti is corresponding timestamp.In order to preferably analyze track, our tracks using map match and based on anchor are calibrated, will
Initial trace T is converted into a track based on terrestrial reference, and anchor point is used as by processing terrestrial reference.After calibration, in these tracks pair
On the basis of quasi- terrestrial reference, the track of calibration can be considered as a sequence for terrestrial reference, i.e. path.
S102：After path is demarcated, paired similar of the path demarcated is calculated using EDR distance algorithms
Property, path cluster is constituted using similar path；
S103：Using equation below, most representative path is used as known paths R in selecting each cluster*；
Wherein, R is path,It is path cluster, DEDRIt is the EDR distances of two paths；Most representative path is
The path minimum with other all path distance sums；
In these known routes, route familiar to driver may be different.For example, for from the home to yard
Route, driver knows the change in track and common traffic.Conversely, only having walked route several times for user, take charge of
Machine may not know to want Zou Zhetiao roads.Therefore, to each known route, calculate a fraction f (R) ∈ [0,1] and weigh
User's is in the push.F (R) is called familiarity fraction, generally, the influence of f (R) comes from the following aspects：
(1) pass by the frequency in the path；(2) meaning of beginning and end terrestrial reference.Calculating to f (R), as a kind of embodiment, one
In kind travel navigation application scenarios, it is possible to use HITS algorithms, using passenger as authority, terrestrial reference is used as center, registration for the algorithm
Place first carries out the calculating of the meaning of terrestrial reference as hyperlink, then using the normalization weighted sum of the two factors as known road
The familiarity score in footpath.For a natural path, its familiarity score is set to steady state value.Further, it is possible to use
The method of stationary point detection carrys out point of interest familiar to identifying user.
It is contemplated that to the familiarity of a paths R, familiarity fraction f is also adopted by its path segments R (i, j)
(R (i, j)) carries out calculating scoring：
To the familiarity of path segments R (i, j), familiarity fraction f (R (i, j)) is calculated using equation below：
Wherein,It is the length ratio of path segments, g () is a monotonic function, g (0)=0, g (1)=1, R
(i, j) is a path segments of R, is terminated to R (j) since R (i), and R (i) is i-th terrestrial reference of path R, and R (j) is path
J-th terrestrial reference of R.With length than reduction, be familiar with that score g () decrease speed is faster than linear function, this is with human cognitive more
For consistent.
S104：User is weighed using path familiarity fraction f (R) and path segments familiarity fraction f (R (i, j))
To the familiarity in path, for natural route, then its familiarity fraction is set to a steady state value.
Natural route is generally made up of route segment of the multiple with same characteristic features, such as street name, direction.For convenience
Path is collected, and connects adjacent road segment segment, forms new natural route, and first Xuan Yitiao roads are set out, and connect out a big nature
Path, if connection can not be continued, just selects a new road to continue to repeat above-mentioned connection procedure, until no road can be elected as
Only, specifically used step S2 is calculated, as shown in Figure 3：
S201：Input road network, and initialization path clusterMakeIt is empty set；
S202：According to the Name ＆ Location of path segments in road network, it is ranked up using comparator, and from road network
According to the Rule Extraction a line of agreement in network, a line extracted is assigned to setting variable e1；
S203：The side extracted in removing step S202 in road network, then, path is deposited into by this side for removing
In R；
S204：In remaining road network, searched using path R and belong to same section, be joined directly together and turn
Angle and completes the link between the path that finds less than remaining path of setting value, finally links these paths and constitutes
Path candidate cluster；
S205：The Name ＆ Location of the path segments in path candidate cluster is sorted using comparator, and from step
According to the Rule Extraction a line of agreement in path candidate cluster in S204, a line extracted is assigned to setting and is become
Amount e2；
S206：The side extracted in step S205 is removed from road network；
S207：By path R and setting variable e find, satisfactory2In path connection, constitute new path；
S208：When path R can not again find remaining path candidate cluster, terminate to set variable e1Headed by path
Link process, the new path that will be found is deposited into path clusterIn；
S209：Circulation performs step S202~S208, and traversal searches all paths in road network, until road network
In there is no manageable road segment segment untill, then, return path cluster
Further, also include, S210：Outgoing route cluster
Up to the present, we just extract known path from the historical track of user, and construct and be based on
The natural route of road network information.
When we describe a route, it is generally divided into logical segment by we, for example, go ahead until stop flag,
Then each section is described again, the present invention is divided, in step S3 based on user knowledge based on subregion conclusion to path
In：
A path R is given, a path for R is defined and is divided intoCan have
Following conclusion：
It is total path R, the part that any two paths are not overlapped each other, per path segments that all route segments are added up
RSi can be known route segment, or natural route section.Although any subregion of path R can produce one always
Knot, but not every is all a good summary.In general, it is intended that the navigation direction of generation has：(1) it is directly perceived
Understand with user is easy to, i.e. using known route, produce familiar path navigation；(2) succinct, the quantity of route segment will be most
Smallization.
The mass equation Q (P (R)) of subregion is defined, optimal path is calculated and is divided P*(R)：
Wherein, f () is the fractional function for weighing user to path familiarity, is the quantity of route segment in this subregion,
λ is the nonnegative constant that user specifies, and it is used for the quantity of the route segment for punishing generation, makes the quantity of route segment will not be too
Greatly, can so cause that formula is chosen those users and is familiar with, but be unlikely to allow the segmentation become excessive again, finally reach a kind of folding
In effect；" all partition " is all of path splitting scheme, and finally selection causes quality Q (P (R)), and score is most
It is optimal splitting scheme P that path high divides P (R)*(R)。
As shown in figure 4, optimal path is found in the use Dynamic Programming described in (1) divide, including sub-step：
Optionally, also including an initialization step, S3011：Input path R, initializes two-dimensional array D [i] [R
`], for storage state information, described status information is last including what is be used for during the parent pointer p of backtracking, current path are divided
One path segmentsThe quality score divided with current path, also, the storage all conditions in two-dimensional array D [i] [R`]
The information that optimal path is divided；
S3012：Whole path R is traveled through, path candidate cluster of the retrieval comprising path link has retrieved all path candidates
Afterwards, the condition optimal dividing of the subpath in whole path R is calculated one by one；
S3013：Path link and current path are divided and merges the new path division of generation, use equation below increment meter
The quality score that newly-generated path divides：
Wherein, Q (i, R'(j, k)) is the quality score that newly-generated path divides；It is path segments R (i-
1, path candidate cluster i)；(R'(j k) is path segments R'(j, familiarity fraction k) to f；Specify for user one of λ
Nonnegative constant；(i-1 i) is the path segments of R (i-1) to R (i) to R；R " (l, m) is R " (l) arrives the R " path segments of (m)；R'
(j, k) is R'(j) to R'(k) path segments；L-th terrestrial reference of R " (l) is path R "；M-th ground of R " (m) is path R "
Mark；R'(j) it is j-th terrestrial reference of path R'；R'(k) it is k-th terrestrial reference of path R'；
Then, selection quality score highest one is divided as optimal path；
S3014：Circulation performs step S3012~S3014, calculating is constantly iterated, until finding whole path R most
Shortest path is divided, and then, is returned to the whole path R optimal paths and is divided.
Also include, S3015：The optimal path of outgoing route R divides P*(R)。
One simple searching P*(R) method is that being possible to of dividing of the exhaustive path is combined, and then finds one
Quality highest solution.However, the time complexity of this method and number of paths exponentially other elevational relationship, work as path
In number of links it is larger when, obtain optimal path will become to hang back.So, our method is to use Dynamic Programming,
Optimal path can be found in polynomial time complexity to divide.
As shown in figure 5, path candidate condition is relaxed in the use described in (2) first makees path proximity matching, then find optimal road
Footpath divides, including sub-step：
Define conditional optimal path to divide, path R=l1, the l2 given for one, ln, its condition is optimal
Path divides P*(R | R` (j, k)) be defined as R in final stage for the optimal path of R` (j, k) is divided.Particularly, P*(R|R`
()) represent R in final stage be all optimal dividings from R`.
The optimal dividing on (1) road is that one kind optimal during all path candidates are divided.
Wherein,Be comprising path link R (i-1, the set in all paths i), we investigate it is all can
The situation of energy, then therefrom selects that optimal one kind.
Primarily look at a given path R, using Q (i, R'(j, k)) represent subpath (R (and 1, i) in final stage be
R'(j, the quality of optimal dividing k).
(2) subpath (R (and 1, condition optimal path i) divide quality can (condition of R (1, i-1) be most from subpath
Shortest path is divided and derived：
In formula (6), R'(k-1)=R (i-1), R'(j) ∈ R；
In formula (7),It is all comprising path R (i-1, natural route and the collection of known paths i)
Close, to R``, meet following restrictive condition：R`` (i) ∈ R and R`` (m)=R (i-1)；
Prove the derivation formula in (2)：
(1, optimal path i) divides P to subpath R*(R (1, i)), can be from P*(R (1, i-1)) build, comprising with
Lower two kinds of situations：
1. P is extended*Last path segments of (R (1, i-1)) obtain P*(R(1,i))；
2. a new path segments are created, optimal path is then added it to and is divided P*In (R (1, i-1)),
As k-j>When 1, P*(R (1, i) | ()) and P*Last path segments of (R (1, i-1) | ()) are all from same
What individual path obtained, so building P*(R (1, i) | ()) only need to a P*(R (1, i-1) | (R'(j, k-1))) extend just
Can be with.Therefore, the quality in newly-generated path can just be calculated with formula (6).
As k-j=1, P*(R (1, i) | ()) and P*Last path segments of (R (1, i-1) | ()) come from not
Same path, we represent their own last path segments with R` and R``.
According to formula：Understand, P*(R (1, i) | (R'(j, k))) can lead to
Cross addition the last item path and divide P to optimal path*(R (1, i-1) | R`` ()), quality then is divided to new path,
Calculated using formula (7).
From this recurrence formula, the optimal path that can calculate R with Dynamic Programming is divided, and idiographic flow includes：
First, a two-dimensional array D [i] [R`] is initialized, for storage state information, these status informations include being used for
The parent pointer p of backtracking, last route segment in current divisionThe quality score that current path is divided, D [i] [R`] is deposited
Store up all conditions optimal path and divide P*The information of (R (1, i+1) | R` ())；
Whole path is traveled through, the condition optimal dividing of subpath is calculated step by step, algorithm is retrieved comprising R (i, i+ respectively
1) and R (i-1, path candidate i) can (key be terrestrial reference, and value is the road comprising the terrestrial reference with inverted index or key-value pair
Footpath) effectively complete；
After retrieval path candidate, design conditions optimal path is divided.New link R (i, i+1) is drawn with existing path
Division simultaneously, and with formula (6) and the quality score of the newly-generated division of (7) incremental computations.Then, quality score highest is selected
One division.After completing iteration, the optimal path for finding whole route is divided, and can find whole division by backtracking
Route.
In real life, due to a variety of causes, such as personal like, mistake of noise and track data etc., it is known that
Path tends not to completely overlapped given path.Such as one selected route segmentWith a known paths KR1 very phases
Seemingly, R is described with KR1 can seem more succinct, intuitively, based on our previous definition relations, due to there is subtle difference,
It can not be described with KR1.So in order to overcome this problem, it would be desirable to soften terms, that is, relax and path candidate is wanted
Ask, from identical to approximately the same, realize the matching to path, including：
S3021：Route matching and similarity relation are defined, including：
A () defines route matching：Two paths R and R` are given, each path is represented by a series of terrestrial reference, a path
Matching M (R, R`) is a terrestrial reference arranged properly to set, and first terrestrial reference of each centering comes from R, and second terrestrial reference comes from
In R`；
B () defines similarity relation：Given two paths R and R`, and if only if, and R and R` has common terminal, and exists
One optimal path matches M (R, R`), then R is similar to R`；Described optimal path matches M (R, R`) and meets：
Each terrestrial reference in R and R` of I occurs at least one times in M (R, R`)；
To (li, li`), their road network is smaller than ε to each terrestrial reference of II in M (R, R`)；
III is in M (R, R`) in the absence of the terrestrial reference pair for intersecting.
Wherein, ε is the maximum road network spacing between the terrestrial reference pair of matching, it is considered to two kinds of extreme situations：
If ε is arranged to 0, this has reformed into the problem for most having path to divide；
If ε is arranged to a sufficiently large value, then arbitrary path can all be considered as similar.
Therefore the setting to ε values has reformed into a personalized path recommendation problem based on historical information, and this value is got over
Greatly, it is more with the more user knowledges of utilization.After completing the definition of similarity relation, then discussed by following manner and put
Optimal path partition problem wide：A path R is given, the high-quality path for finding the R` similar to R divides P*(R`)。P*
(R`) optimal path for relaxing for being also referred to as R is divided, and is expressed asIn order to the optimal path for relaxing for finding R is divided, lead to
Cross and enumerate all R situations similar to R`, the optimal path for then calculating R` using optimal path partitioning algorithm divides.Tool
It is what we to be found that the path for having first water divides.However, the quantity in this kind of potential path will be adjusted in index rank
With optimal path partitioning algorithm index so that the solution is very poorly efficient.
For to result what is observed in following lemma 3, it has been found that can be used to effectively solve using Dynamic Programming
Certainly this problem.On path R, R*Quality highest path divides in the expression path similar to R.M*(R,R*) represent them
Between a good route matching, (i, k) ∈ M* (R, R*), it is meant that R (i) is matched with R* (k).
Lemma 3：The route matching M* (R, R`) good for one, if (i, k) ∈ M* (R, R`), then three below ground
Mark is to ((i-1, k), (i-1, k-1), (i, k-1)) at least has one and be present in M* (R, R`).
To the proof of lemma 3：Assuming that these three terrestrial references are present in M* (R, R`) to neither one, for a good road
For the matching of footpath, each terrestrial reference must occur at least one times, we can assume that R (i-1) is matched with R` (l), R` (k-1)
It is to be matched with R (m), because can not there is situation about intersecting in them, therefore i-1 can be released>M, l<k-1.This means M*
The terrestrial reference of intersection is there is in (R, R`) to (i-1, l) with (m, k-1).
In order to solve this problem with Dynamic Programming, we first define the structure of its subproblem.
S3022：For a paths R, with Q (i, R'(j, k)) be last path segments for R` (j, k) R (1, i)
The quality that divides of the optimal path that relaxes, when R (i) is a terminal of R, it is stipulated that R (i)=R` (k), the road then relaxed
The quality of footpath optimal dividing, meets following recurrence Relation：
The optimal path for then relaxing is dividedIncluding following two situations：
If 1. k-j>1, then the optimal path that path segments are relaxed is divided intoWithLast path segments come from same paths, enumerate when R (i-1) match R` (k), R (i-1)
With R` (k-1), three kinds of situations during R (i) matching R` (k-1) then incrementally calculate path quality Q using formula equation below
(i,R'(j,k))：
Q(i,R'(j,k))←max{Q(i-1,R'(j,k)),Q(i-1,R'(j,k-1))+f(R'(j,k))-f(R'(j,
k-1)),
Q(i,R'(j,k-1))+f(R'(j,k))-f(R'(j,k-1))}
If 2. k-j=1, the route segment before terminating, open new route segment R` (j, k), this is comprising R` (j)
The set in path, R`` isIn arbitrary path, for path segments R`` (l, m), wherein R`` (m)=R` (j),
Here there are two kinds of possible situations：R`` (m) and R (i-1) is matched, and R`` (m) and R (i) is matched, and enumerates both of these case, so
Path quality score Q (i, R'(j, k)) is incrementally calculated using equation below afterwards：
Further, user is weighed by calculating familiarity fraction f (R) to be in the push route, it is described
Familiarity fraction f (R) is calculated according to the pass by meaning of the frequency in the path and the terrestrial reference in the path of user；Wherein,
f(R)∈[0,1]。
Further, to the familiarity of path segments R (i, j), using equation below calculate familiarity fraction f (R (i,
j))：
Wherein,It is the length ratio of path segments, g () is a monotonic function, g (0)=0, g (1)=1, R
(i, j) is a path segments of R, is terminated to R (j) since R (i), and R (i) is i-th terrestrial reference of path R, and R (j) is path
J-th terrestrial reference of R.
Further, in a kind of travel navigation scene, to route known to user, using passenger as authority, terrestrial reference conduct
Center, registration office carries out the calculating of the meaning of terrestrial reference using HITS algorithms as hyperlink, and then user passes by the path
The result of calculation of the meaning of frequency and terrestrial reference is normalized weighted sum, using summed result as known route familiarity
Fraction f (R)；For natural route, then its familiarity fraction f (R) is set to a steady state value.
After path is divided into section, described per path segments by order, generation path is summarized.
(1) for natural route section, it is described using several crucial features, for example, street name, distance and mobile plan
Slightly (shift strategy is used to indicate that in route segment, at the end of the action to be taken, for example, " steerings ", " continuing traveling ", " from
Open ", " arrival ".This can the relation of route segment based on neighbour calculate.There are these information, one can be generated by turning
The navigation that direction represents.For example：" 3 kilometers of rear lefts of traveling are rotated into Olympics main road ", 3 kilometers is distance, and right-hand rotation is mobile
Strategy, Olympics main road is street name.
(2) for known route segment, it is important that how to generate simplicity, it is easy to the description of understanding.Passed through for a user
The known path often passed through, we describe this section of way by describing its initial terrestrial reference and terminal terrestrial reference, remove centre
Some details, for example, from the home to the route of workspace.If in the case that starting point and destination are not enough to description route, along this
The main roads of bar route running are also included within description.In order that path summarizes more smooth, we define several sentences
Subtemplate describes a known route segment.For example " travelled towards destination from starting point, be designated as until XX by XXX streets
Only ... " starting point and destination are starting point and the destination of known paths, and street name is the arterial street name in known paths, ground
Mark represents the terminal of this known paths section.Note, according to feelings actual conditions, it is convenient to omit one or more characteristics, such as starting point
And street name.
Known paths are more, and the route segment produced after being divided to path is fewer, describe also more save resources, and
Traditional turn direction (turn-by-turn) navigation will not produce change according to this information.
As shown in fig. 6, a kind of personalized path guiding system, including：Data preprocessing module, path division module and lead
Boat information generating module, described data preprocessing module, for from the historical trajectory data of user, extracting user through frequentation
The routing information asked；Described path division module, divides for finding optimal path；Described navigation information generation module,
Based on the routing information that the user for extracting often accesses, personalized path navigation is generated on path familiar to user.
The present invention can be used to give user one general introduction on route, is generally so short that than the tediously long navigation being made up of turning
It is many.For example, from the home to job site, description can since " being driven to workplace ", this will to user one intuitively build
View goes to determine the driving of next step.When driver is near the position for deviateing the known route specified, a prompting will be provided, and
Suggestion is provided in the way of turn direction is navigated.
Application scenarios of the invention：
Application scenarios 1：Known route is used to generate more succinct navigation.Assuming that user plan drive to dining room and by
The corresponding route RB that general navigation system is produced.By analysis of history track data, the present invention it can be found that driver is through frequentation
Ask that supermarket A and the subpath of corresponding path RA, RA and RB have overlapped greatly.Using the present invention it is last as a result,
Direct driver instructor is driven to supermarket A, rather than the navigation that detailedization is provided by rotation direction.For the unfamiliar road of driver
Line, still there is provided detailed by turning direction.
Application scenarios 2：Driver comes a new city, can be found without known route, is given birth to according to natural route
Navigation into turn direction is supplied to him.
In the present invention, by extracting the historical trajectory data of user, it is considered to which user's goes out row mode so that navigation instruction
More brief introduction, it is more personalized.In this process, the framework summarized is divided and made a summary we have proposed a new path, first
Based on user to the access frequency in path, the optimum division of route is found, then generate a summary to describe each route segment.
Finally, on real and synthesis track data collection, extensive experiment and subjective research have been carried out.Test result indicate that,
In most cases, compared with traditional navigation being made up of rotation direction, the framework can be provided the user based on historical track
Navigation, more intuitively, and can be in Mobile solution, the resource needed for substantially reducing be (for example, reducing sentence number reduces navigation
With the resource needed for bandwidth).
Conventional algorithm, input is generally made up of starting point and destination, and output is based on some standards (such as conventional, safety)
Best route.And be a route in input of the invention, output is a route summary.Personalization tourism recommendation is one
Individual special navigation system, target is to find a route, best suits the preference of user.Our work is the navigation system of bottom
System, therefore can be integrated with any navigation system.That is, the present invention can take any road produced by navigation system
Line, and be mapped in a pattern based on user's history travelling.
The invention allows for a two stage framework (subregion and summary).Particularly, framework of the invention school first
Accurate and cluster historical trajectory data, extracts the knowledge and familiar road network of user.Next step, for the path for giving, profit
Path is divided into multistage with the feature in the first step.The step is formally to find the route of optimal segmentation, to greatest extent
Its quality is improved to lay the foundation.
It will be appreciated by those of skill in the art that the method step of each example described with reference to the embodiments described herein
Rapid and module, can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually with hard
Part or software mode are performed, depending on the application-specific and design constraint of technical scheme.Professional and technical personnel can be with
Distinct methods are used each specific application to realize described function, but this realization should not exceed model of the invention
Enclose.
It is apparent to those skilled in the art that, for convenience of description and succinctly, foregoing description is
The specific work process of system, device and module, may be referred to the corresponding process in preceding method embodiment, will not be repeated here.
Disclosed herein method, system and module, can realize by another way.For example, described above
Device embodiment be only illustrative, it is actual for example, the division of the module, can be only a kind of division of logic function
There can be other dividing mode when realizing, such as multiple module or components can be combined or be desirably integrated into another and be
System, or some features can be ignored, or not perform.It is another, shown or discussed coupling or direct-coupling each other
Or communication connection is it may be said that by some interfaces, the INDIRECT COUPLING or communication connection of device or module, can be it is electrical, machinery or
Other forms.
The module of discrete parts explanation can be or may not be physically separate, be shown as module
Part can be or can not be physical module, you can with positioned at a place, or can also be distributed to multiple network moulds
On block.Some or all of module therein can be according to the actual needs selected to realize the scheme purpose of the present embodiment.
In addition, during each functional module in each embodiment of the invention can be integrated in a processing module, it is also possible to
It is that modules are individually physically present, it is also possible to which two or more modules are integrated in a module.
If the function is to realize in the form of software function module and as independent production marketing or when using, can be with
Storage is in a computer-readable recording medium.Based on such understanding, technical scheme is substantially right in other words
The part or the part of the technical scheme that prior art contributes can be embodied in the form of software product, the calculating
Machine software product is stored in a storage medium, including some instructions are used to so that a computer equipment (can be personal
Computer, server, or network equipment etc.) perform all or part of step of each embodiment methods described of the invention.And
Foregoing storage medium includes：USB flash disk, mobile hard disk, system memory (Read-Only Memory, ROM), random access memory
Device (Random Access Memory, RAM), magnetic disc or CD etc. are various can be with the medium of store program codes.
The above is only the preferred embodiment of the present invention, it should be understood that the present invention is not limited to described herein
Form, is not to be taken as the exclusion to other embodiment, and can be used for various other combinations, modification and environment, and can be at this
In the text contemplated scope, it is modified by the technology or knowledge of above-mentioned teaching or association area.And those skilled in the art are entered
Capable change and change does not depart from the spirit and scope of the present invention, then all should be in the protection domain of appended claims of the present invention
It is interior.
Claims (11)
1. a kind of personalized method for path navigation, it is characterised in that including：
From track data, user knowledge is extracted, based on the user knowledge extracted, find path familiar to user, it is ripe in user
On the path known, generation meets the personalized path navigation of user；
The user knowledge includes the routing information and landmark information that user often accesses, the path that described user often accesses
Information includes avenue name information；The source of the track data, including the navigation of track data recording equipment, mobile terminal
Using with vehicle terminal navigation application.
2. method according to claim 1, it is characterised in that：Including route familiar to user and the unfamiliar road of user
In one route of line or a plurality of route, for route familiar to user, user is instructed using the personalized route guidance；It is right
In the unfamiliar route of user, turn direction navigation instruction user is used.
3. method according to claim 1, it is characterised in that：Use is weighed by calculating familiarity fraction f (R)
Family is in the push to route, described familiarity fraction f (R) according to user pass by the path frequency and the path
The meaning of terrestrial reference be calculated；Wherein, the size interval range of f (R) includes：f(R)∈[0,1].
4. method according to claim 3, it is characterised in that：To the familiarity of path segments R (i, j), using as follows
Equation calculates familiarity fraction f (R (i, j))：
Wherein,It is the length ratio of path segments, g () is a monotonic function, g (0)=0, g (1)=1, R (i,
J) it is a path segments of R, terminates to R (j) since R (i), R (i) is i-th terrestrial reference of path R, R (j) is path R's
J-th terrestrial reference.
5. method according to claim 3, it is characterised in that：In a kind of travel navigation scene, to road known to user
Line, using passenger as authority, terrestrial reference carries out the meaning of terrestrial reference using HITS algorithms as center, registration office as hyperlink
Calculate, the pass by result of calculation of the frequency in the path and the meaning of terrestrial reference of user is then normalized weighted sum, by institute
The result of normalization weighted sum is stated as familiarity fraction f (R) of known paths；For natural route, then it is familiar with
Degree fraction f (R) is set to a steady state value.
6. the method according to claim 1,2,3 or 4 any one, it is characterised in that including step：
S1：From the historical trajectory data of user, path known to extraction user makes user have known path corresponding
It is familiar with value；
S2：Based on road network information architecture natural route；
S3：Optimal path is found using Dynamic Programming to divide, or, first make path proximity using path candidate condition is relaxed
Match somebody with somebody, then find optimal path division；
S4：Path segments after being divided based on path, the personalized path of generation is summarized, and instructs user.
7. method according to claim 6, it is characterised in that in step sl, including sub-step：
S101：Calibrated with the track based on anchor using map match, initial trace T be converted into a track based on terrestrial reference,
It is used as anchor point by processing terrestrial reference；After calibration, on the basis of track alignedly target, the track of calibration is used as terrestrial reference
Sequence, as path；
S102：After trajectory path has been demarcated, the paired similitude of the trajectory path demarcated is calculated using EDR distance algorithms,
And path cluster is constituted using similar path；
S103：Using equation below, most representative path R in each path cluster is selected*As known paths；
Wherein, R is path,It is path cluster, DEDRIt is the EDR distances of two paths；
S104：User is weighed using path familiarity fraction f (R) and path segments familiarity fraction f (R (i, j)) to satisfy the need
The familiarity in footpath.
8. method according to claim 6, it is characterised in that in step s 2, including sub-step：
S201：Input road network, and initialization path clusterMakeIt is empty set；
S202：According to the Name ＆ Location of path segments in road network, it is ranked up using comparator, and from road network
According to the Rule Extraction a line of agreement, a line extracted is assigned to setting variable e1；
S203：The side extracted in removing step S202 in road network, then, this side for removing is deposited into the R of path；
S204：In remaining road network, searched using path R and belong to same section, be joined directly together and angle of turn
Less than remaining path of setting value, and the link between the path that finds is completed, finally by these paths link composition candidate
Path cluster；
S205：The Name ＆ Location of the path segments in path candidate cluster is sorted using comparator, and from step S204
In path candidate cluster according to agreement Rule Extraction a line, by extract a line be assigned to set variable
e2；
S206：The side extracted in step S205 is removed from road network；
S207：By path R and setting variable e find, satisfactory2In path connection, constitute new path；
S208：When path R can not again find remaining path candidate cluster, terminate to set variable e1Headed by path link
Process, the new path that will be found is deposited into path clusterIn；
S209：Circulation performs step S202~S208, and traversal searches all paths in road network, until not having in road network
Untill having manageable road segment segment, then, return path cluster
9. method according to claim 6, it is characterised in that in step s3, including：
(1) the use Dynamic Programming described in is found optimal path and is divided, including sub-step：
S3012：Whole path R is traveled through, retrieval includes the path candidate cluster of path link, after having retrieved all path candidates,
The condition optimal dividing of the subpath in whole path R is calculated one by one；
S3013：Path link and current path are divided and merges the new path division of generation, it is new using equation below incremental computations
The quality score that the path of generation divides：
Wherein, Q (i, R'(j, k)) is the quality score that newly-generated path divides；For path segments R (i-1, i)
Path candidate cluster；(R'(j k) is path segments R'(j, familiarity fraction k) to f；The non-negative that λ is specified for user
Constant；(i-1 i) is the path segments of R (i-1) to R (i) to R；R " (l, m) be R " (l) arrive R " (m) path segments；R'(j,k)
Be R'(j) to R'(k) path segments；R " (l) be path R " l-th terrestrial reference；R " (m) be path R " m-th terrestrial reference；R'
J () is j-th terrestrial reference of path R'；R'(k) it is k-th terrestrial reference of path R'；
Then, selection quality score highest one is divided as optimal path；
S3014：Circulation performs step S3012~S3014, is constantly iterated calculating, the optimal road until finding whole path R
Footpath divides, and then, returns to the whole path R optimal paths and divides.
(2) use described in is relaxed path candidate condition and first makees path proximity matching, then finds optimal path division, including sub-step
Suddenly：
S3021：Define route matching relation and define path similarity relation, including：
A () defines route matching relation：Two paths R and R` are given, each path is represented by a series of terrestrial reference, a path
Matching M (R, R`) is a terrestrial reference arranged properly to set, and first terrestrial reference of each terrestrial reference centering comes from R, second terrestrial reference
Come from R2；
B () defines path similarity relation：Given two paths R and R`, and if only if, and R and R` has common terminal, and exists
One optimal path matches M (R, R`), then R is similar to R`；Described optimal path matches M (R, R`) and meets：
Each terrestrial reference in R and R` of I occurs at least one times in M (R, R`)；
Each terrestrial reference of II in M (R, R`) is to (li, li`), their network space DN(li,li`)≤ε；
III is in M (R, R`) in the absence of the terrestrial reference pair for intersecting；
Wherein, ε is the maximum road network spacing between the terrestrial reference pair of matching；
S3022：Setting Q (i, R'(j, k)) is that last path segments is R'(j, R (1, the optimal path for relaxing i) k)
The quality score of division, when R (i) is a terminal of R, it is stipulated that R (i)=R` (k), then the optimal path for relaxing is divided and met
Following recurrence formula：
The condition optimal path that calculating is relaxed is dividedIncluding following two situations：
If 1. k-j>1, then the condition optimal path for relaxing is divided intoWithIt is last
One path segments comes from same paths, enumerates when R (i-1) matches R` (k), and R (i-1) matches R` (k-1), R (i) matchings R`
(k-1) three kinds of situations when, then incrementally calculate the quality score Q (i, R'(j, k)) of path division using equation below：
Q(i,R'(j,k))←max{Q(i-1,R'(j,k)),Q(i-1,R'(j,k-1))+f(R'(j,k))-f(R'(j,k-
1)),
Q(i,R'(j,k-1))+f(R'(j,k))-f(R'(j,k-1))}
If 2. k-j=1, that is, terminate the search procedure of path candidate, new route segment R` (j, k), time now are opened
Routing footpath clusterR` (j) is contained, also, R`` isIn arbitrary path, for a path segments R``
, there are two kinds of situations in (l, m), wherein R`` (m)=R` (j)：R`` (m) and R (i-1) is matched or R`` (m) and R (i) is matched, piece
Both of these case is lifted, the quality score Q (i, R'(j, k)) of path division is then incrementally calculated using equation below：
Then, selection quality score highest one is divided as optimal path.
10. method according to claim 6, it is characterised in that in step s 4, including：
(1) for natural route section, it is described using multiple key features；Described multiple key features include street name,
Distance and shift strategy, described shift strategy represent the action taken at the end of natural route section, and it includes turning to, continues
Travel, leave and reach；
(2) for known paths section, it is described by describing its initial terrestrial reference and terminal terrestrial reference, in starting point terrestrial reference and terminal
In the case that ground terrestrial reference is not enough to describe it, the turnpike road travelled along this paths is also included within description；According to reality
Situation, can omit one or more features, and the feature of omission includes starting point, street name.
A kind of 11. personalized path guiding systems, it is characterised in that including：Data preprocessing module, path division module and lead
Boat information generating module, described data preprocessing module, for from the historical trajectory data of user, extracting user through frequentation
The routing information asked；Described path division module, divides for finding optimal path；Described navigation information generation module,
Based on the routing information that the user for extracting often accesses, personalized path navigation is generated on path familiar to user.
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| CN107270914A (en) * | 2017-07-17 | 2017-10-20 | 广州地理研究所 | Indoor paths planning method based on major trunk roads |
| CN107289961A (en) * | 2017-07-18 | 2017-10-24 | 电子科技大学 | A kind of method for the navigation information for being easy to user to understand based on subregion and summary generation |
| CN107993441A (en) * | 2017-12-18 | 2018-05-04 | 北京中交兴路信息科技有限公司 | A kind of lorry often runs away the Forecasting Methodology and device of line |
| CN108225356A (en) * | 2017-12-04 | 2018-06-29 | 北京中交兴路信息科技有限公司 | A kind of shipping air navigation aid and device based on lorry historical track |
| CN108573429A (en) * | 2018-03-07 | 2018-09-25 | 北京嘀嘀无限科技发展有限公司 | Order processing method, apparatus, server, terminal and readable storage medium storing program for executing |
| CN109255085A (en) * | 2018-04-28 | 2019-01-22 | 云天弈（北京）信息技术有限公司 | A kind of search result shows system and method |
| CN110083149A (en) * | 2018-01-26 | 2019-08-02 | 百度（美国）有限责任公司 | For infeed mechanism after the path of automatic driving vehicle and speed-optimization |
| CN110542425A (en) * | 2018-05-28 | 2019-12-06 | 百度在线网络技术（北京）有限公司 | navigation path selection method, navigation device, computer equipment and readable medium |
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| CN111060102A (en) * | 2018-10-16 | 2020-04-24 | 中兴通讯股份有限公司 | Indoor navigation method, system and computer readable storage medium |
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| CN113240816A (en) * | 2021-03-29 | 2021-08-10 | 泰瑞数创科技(北京)有限公司 | AR and semantic model based city accurate navigation method and device |
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| CN115406443A (en) * | 2021-05-27 | 2022-11-29 | 中国科学院沈阳自动化研究所 | Two-stage multi-AGV path planning method based on driving line |
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| CN107270914A (en) * | 2017-07-17 | 2017-10-20 | 广州地理研究所 | Indoor paths planning method based on major trunk roads |
| CN107289961A (en) * | 2017-07-18 | 2017-10-24 | 电子科技大学 | A kind of method for the navigation information for being easy to user to understand based on subregion and summary generation |
| CN108225356A (en) * | 2017-12-04 | 2018-06-29 | 北京中交兴路信息科技有限公司 | A kind of shipping air navigation aid and device based on lorry historical track |
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| CN110083149B (en) * | 2018-01-26 | 2022-05-13 | 百度（美国）有限责任公司 | Path and speed optimized feedback mechanism for autonomous vehicles |
| CN110083149A (en) * | 2018-01-26 | 2019-08-02 | 百度（美国）有限责任公司 | For infeed mechanism after the path of automatic driving vehicle and speed-optimization |
| CN108573429A (en) * | 2018-03-07 | 2018-09-25 | 北京嘀嘀无限科技发展有限公司 | Order processing method, apparatus, server, terminal and readable storage medium storing program for executing |
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| CN109255085B (en) * | 2018-04-28 | 2021-09-21 | 云天弈（北京）信息技术有限公司 | Search result display system and method |
| CN110542425A (en) * | 2018-05-28 | 2019-12-06 | 百度在线网络技术（北京）有限公司 | navigation path selection method, navigation device, computer equipment and readable medium |
| CN110654372A (en) * | 2018-06-29 | 2020-01-07 | 比亚迪股份有限公司 | Vehicle driving control method and device, vehicle and storage medium |
| CN110654372B (en) * | 2018-06-29 | 2021-09-03 | 比亚迪股份有限公司 | Vehicle driving control method and device, vehicle and storage medium |
| CN111060102A (en) * | 2018-10-16 | 2020-04-24 | 中兴通讯股份有限公司 | Indoor navigation method, system and computer readable storage medium |
| CN111060102B (en) * | 2018-10-16 | 2024-03-08 | 中兴通讯股份有限公司 | Indoor navigation method, system and computer readable storage medium |
| CN110647693A (en) * | 2019-09-23 | 2020-01-03 | 京东城市(北京)数字科技有限公司 | Path recommendation method and device |
| CN111207764A (en) * | 2019-10-31 | 2020-05-29 | 浙江中测新图地理信息技术有限公司 | Self-service route planning method for mountaineering |
| CN113240816B (en) * | 2021-03-29 | 2022-01-25 | 泰瑞数创科技(北京)有限公司 | AR and semantic model based city accurate navigation method and device |
| CN113240816A (en) * | 2021-03-29 | 2021-08-10 | 泰瑞数创科技(北京)有限公司 | AR and semantic model based city accurate navigation method and device |
| CN115406443A (en) * | 2021-05-27 | 2022-11-29 | 中国科学院沈阳自动化研究所 | Two-stage multi-AGV path planning method based on driving line |
| CN115406443B (en) * | 2021-05-27 | 2024-04-26 | 中国科学院沈阳自动化研究所 | Two-stage multi-AGV path planning method based on driving line |
| CN113701778A (en) * | 2021-09-02 | 2021-11-26 | 广州宸祺出行科技有限公司 | Network appointment route planning method and device based on passenger route preference |
| CN113701778B (en) * | 2021-09-02 | 2024-04-19 | 广州宸祺出行科技有限公司 | Network taxi route planning method and device based on passenger route preference |
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