CN104990559B - A kind of path recommendation method, system and client based on taxi empirical data - Google Patents
A kind of path recommendation method, system and client based on taxi empirical data Download PDFInfo
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- CN104990559B CN104990559B CN201510444193.4A CN201510444193A CN104990559B CN 104990559 B CN104990559 B CN 104990559B CN 201510444193 A CN201510444193 A CN 201510444193A CN 104990559 B CN104990559 B CN 104990559B
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/343—Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
Abstract
The present invention provides a kind of path recommendation method, system and client based on taxi empirical data, including：Default node module presets node, and obtains the path between two nodes；Rule of thumb data, any path of acquisition store the recommendation weights to second acquisition module in the recommendation weights of preset time period；Third acquisition module obtains user current location and target location, and obtains current location and correspond to nearest start node, and target location corresponds to nearest destination node；Choose more than one path between the start node and destination node；4th acquisition module obtains the current time of user, and obtains the recommendation weights in the preset time period residing for the current time in the path；Recommending module recommends the recommendation weights respective path of predetermined number.
Description
Technical field
The present invention relates to field of electronic navigation more particularly to a kind of path based on taxi empirical data recommend method,
System and client.
Background technology
With the development of science and technology and improvement of living standard, path navigation become the indispensable step of people's trip,
Application No. is 200610105972.2 patent documents to disclose a kind of navigation system, for based on the path for using predetermined condition
Search, provides the guidance path of the stroke between beginning and end, the navigation system includes：Display unit is led for showing
Bit path and/or candidate guidance path with relevant conditional name, wherein described predetermined with relevant conditional name
Condition generates multiple candidate guidance paths.
Said program is according to title is related and journey navigation path between distance search starting point and terminal, however in city
Under complicated road conditions, especially big city often occurs in the case of blocking up, different time sections, different sections of highway road conditions not phases
Together, for example, working peak period concentration of enterprises section and the section where festivals or holidays sight spot often compare congestion, use is above-mentioned
It is smooth that the path for the more short-circuit journey that scheme obtains does not ensure that section is open to traffic, therefore can not accurately obtain optimal navigation road
Diameter.
In addition, under the road conditions of city complexity, experienced taxi driver most will appreciate that the jam situation of road conditions, and meeting
Most quick and unobstructed path is found, if the existing Model choices path of experience taxi driver can have been made full use of, and according to
The demand of user is supplied to user, then the trip of user provides more smoothly path, improves the comfort level of user's trip,
And it is also significant for the unimpeded operation of entire city road network and utilization ratio.
Invention content
The technical problem to be solved by the present invention is to：Under the road conditions of city complexity, recommend best traveling road to user
Diameter.
In order to solve the above-mentioned technical problem, the technical solution adopted by the present invention is：
The present invention provides a kind of path recommendation method based on taxi empirical data, including：
Default node, obtains the path between two nodes；
Rule of thumb data obtain any path in the recommendation weights of preset time period, store the advowson
Value；
User current location and target location are obtained, and obtains current location and corresponds to nearest start node, target location
Corresponding nearest destination node；Choose more than one path between the start node and destination node；
The current time of user is obtained, and obtains the recommendation in the preset time period residing for the current time in the path
Weights；
Recommend the recommendation weights respective path of predetermined number.
The advantageous effect of method is recommended to be in the above-mentioned path based on taxi empirical data：Default node, and must take office
One or two internode path preset time period recommendation weights, so as to obtain in different time sections between any two node most
Good path obtains the path for corresponding to nearest start node and destination node respectively with user current location and target location, and
The recommendation weights that path between start node and destination node is obtained by the current time of user, to obtain optimal recommendation road
Diameter, therefore can effectively avoid congested link.
The present invention also provides a kind of path commending systems based on taxi empirical data, including：
Default node module, for presetting node；
First acquisition module, for obtaining the path between two nodes；
Second acquisition module, for rule of thumb data, recommendation weights of any path of acquisition in preset time period；
Memory module, for storing the recommendation weights；
Third acquisition module for obtaining user current location and target location, and obtains current location and corresponds to recently
Start node, target location correspond to nearest destination node；Module is chosen, for choosing the start node and destination node
Between more than one path；
4th acquisition module for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module, the recommendation weights respective path for recommending predetermined number.
Method, advantage is recommended to be in the above-mentioned path based on taxi empirical data：Default node module is default
Node, and by the first acquisition module and the second acquisition module obtain any two internode path preset time period advowson
Value, so as to obtain the optimal path in different time sections between any two node, third acquisition module obtains current with user
Position and target location correspond to the path of nearest start node and destination node respectively, and are obtained and used by the 4th acquisition module
The recommendation weights in path between the current time and current time start node and destination node at family, to obtain optimal recommendation
Path, therefore can effectively avoid congested link.
The present invention also provides a kind of, and client is recommended in the path based on taxi empirical data, including：
Third acquisition module, the target location for obtaining user current location, and it is corresponding recently to obtain current location
Start node, the corresponding nearest destination node in target location；Module is chosen, for choosing the start node and target
More than one path between node；
4th acquisition module for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module, the recommendation weights respective path for recommending predetermined number.
The advantageous effect of above-mentioned client is：User obtains current location and target location point by third acquisition module
Path between not corresponding start node and destination node, and by the beginning of the 4th acquisition current time and current time
The recommendation weights in path between beginning node and destination node, to obtain the optimal path between start node and destination node, effectively
It drives a vehicle caused by solving congestion in road difficult problem；Road between arbitrary two node of above-mentioned client node data, different time sections
The recommendation weights of diameter are to default in client, therefore client is logical no longer needs to carry out other communications, in no communication signal or
Also congested link can be effectively avoided in the case of no network connection.
The present invention provides a kind of path recommendation client based on taxi empirical data again, including：
5th acquisition module, the target location for obtaining user current location；
First receiving module, for receiving the corresponding nearest start node in current location, target location is corresponding recently
Destination node；And receive more than one path between the start node and destination node；
6th acquisition module, for obtaining active user's time；
Second receiving module, for receiving the advowson in the preset time period residing for the current time in the path
Value；
Third receiving module, the recommendation weights respective path for receiving predetermined number.
The advantageous effect of above-mentioned client is：User by the first receiving module receive respectively with current location and target
Path between position nearest start node and destination node receives current time start node and mesh by the second receiving module
The recommendation weights for marking internode path are received by third receiving module and recommend the corresponding path of weights；Above-mentioned client node
Data, recommendation weights in different time periods and to recommend the corresponding path of weights be client by communications reception, without
It is stored in client, saves the memory space of client.
Description of the drawings
Fig. 1 is that method flow diagram is recommended in the path based on taxi empirical data of the embodiment of the present invention one；
Fig. 2 is that the default node flow of method is recommended in the path based on taxi empirical data of the embodiment of the present invention one
Figure；
Fig. 3 is the path commending system structural schematic diagram based on taxi empirical data of the embodiment of the present invention two；
Fig. 4 is that client terminal structure schematic diagram is recommended in the path based on taxi empirical data of the embodiment of the present invention three；
Fig. 5 is that client terminal structure schematic diagram is recommended in the path based on taxi empirical data of the embodiment of the present invention four.
Label declaration：
1, node module is preset；2, the second acquisition module；3, third acquisition module；4, the 4th acquisition module；5, recommend mould
Block；6, the 7th acquisition module；7, computing module；8, laminating module；9, the 5th acquisition module；10, the first receiving module；11,
Six acquisition modules；12, the second receiving module；13, third receiving module；14, the first acquisition module.
Specific implementation mode
To explain the technical content, the achieved purpose and the effect of the present invention in detail, below in conjunction with embodiment and coordinate attached
Figure is explained.
The design of most critical of the present invention is:Rule of thumb data, advowson of the acquisition either path in preset time period
Value, and the path included by current location and target location and the advowson in the preset time period residing for current time
It is worth to optimal path.
Fig. 1 to Fig. 5 is please referred to,
A kind of path recommendation method based on taxi empirical data, including：
S1, default node, obtain the path between two nodes；
S2, rule of thumb data obtain any path in the recommendation weights of preset time period, store the recommendation
Weights；
S3, user current location and target location are obtained, and obtains current location and corresponds to nearest start node, target position
Set corresponding nearest destination node；Choose more than one path between the start node and destination node；
S41, the current time for obtaining user, and obtain in the preset time period residing for the current time in the path
Recommend weights；
S5, the recommendation weights respective path for recommending predetermined number.
As can be seen from the above description, the advantageous effect of method is recommended to be based on the path of taxi empirical data：It is default
Node, and obtain any two internode path preset time period recommendation weights, so as to obtain in different time sections appoint
Optimal path between one or two node obtains and corresponds to nearest start node and target respectively with user current location and target location
The path of node, and by the recommendation weights in path between the current time of user acquisition start node and destination node, to obtain
To optimal recommendation paths, therefore it can effectively avoid congested link.
Further, " the default node " is specially：
S11, traversal taxi initial position or target location；
S12, initial position in preset time period or the target location taxi frequency are ranked up；
S13, according to the sequence, it is default node to extract the initial position of predetermined number or target location.
As can be seen from the above description, by being ranked up the default section of extraction to initial position and the target location taxi frequency
Point can represent call a taxi initial position and the target location of the overwhelming majority.
Further, " the recommendation weights of preset time period " are specially：According to festivals or holidays, working day, weekend with
And ordinary period and peak period, taxi vehicle speed and frequency information in conjunction with a path in the above-mentioned period obtain and recommend weights.
As can be seen from the above description, vehicle speed and the frequency message reflection path are hired out in the different periods when different
Between section the unimpeded situation of bus or train route, to which the recommendation weights obtained can effectively avoid the section of congestion.
Further, the path recommendation method based on taxi empirical data further includes：
S42, current location to the path of start node is obtained, and obtains target location to the path of destination node, meter
The recommendation weights are superimposed, by the advowson after superposition by the recommendation weights for calculating the path with the recommendation weights between node
Value is as recommendation weights.
As can be seen from the above description, total path also contemplates initial position and is arrived to the path of start node and target location
The position of destination node.
A kind of path commending system based on taxi empirical data, including：
Default node module 1, for presetting node；First acquisition module 14, between two nodes of acquisition
Path；
Second acquisition module 2, for rule of thumb data, advowson of any path of acquisition in preset time period
Value；Memory module, for storing the recommendation weights；
Third acquisition module 3 for obtaining user current location and target location, and obtains current location and corresponds to recently
Start node, target location correspond to nearest destination node；Module is chosen, for choosing the start node and destination node
Between more than one path；
4th acquisition module 4 for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module 5, the recommendation weights respective path for recommending predetermined number.
Seen from the above description, having the beneficial effect that based on the path commending system of taxi empirical data：Default section
Point module 1 presets node, and obtains any two internode path default by the first acquisition module 14 and the second acquisition module 2
The recommendation weights of period, so as to obtain the optimal path in different time sections between any two node, third acquisition module 3
It obtains and corresponds to the path of nearest start node and destination node respectively with user current location and target location, and pass through the 4th
The recommendation weights in path between the current time and current time start node and destination node of the acquisition user of acquisition module 4, from
And optimal recommendation paths are obtained, therefore can effectively avoid congested link.
A kind of path recommendation client based on taxi empirical data, including；
Third acquisition module 3, the target location for obtaining user current location, and it is corresponding recently to obtain current location
Start node, the corresponding nearest destination node in target location；Module is chosen, for choosing the start node and target
More than one path between node；
4th acquisition module 4 for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module 5, the recommendation weights respective path for recommending predetermined number.
As can be seen from the above description, the advantageous effect of client is recommended to be based on the path of taxi empirical data：With
Family obtains the road between current location and the corresponding start node in target location and destination node by third acquisition module 3
Diameter, and pushing away for path between current time and current time start node and destination node is obtained by the 4th acquisition module 4
Weights are recommended, to obtain the optimal path between start node and destination node, driving caused by efficiently solving congestion in road is tired
Difficult problem；The recommendation weights of arbitrary two internode path of above-mentioned client node data, different time sections are to default in client
It is interior, therefore client is logical no longer needs to carry out other communications, no communication signal or without network connection in the case of also can be effective
Avoid congested link.
Further, a kind of path recommendation client based on taxi empirical data further includes：
7th acquisition module 6 for obtaining current location to the path of start node, and obtains target location to target
The path of node；
Computing module 7, the recommendation weights for calculating the path；
Laminating module 8, for being superimposed the recommendation weights with the recommendation weights between node.
As can be seen from the above description, total path also contemplates initial position and is arrived to the path of start node and target location
The position of destination node.
A kind of path recommendation client based on taxi empirical data, including；
5th acquisition module 9, the target location for obtaining user current location；
First receiving module 10, for receiving the corresponding nearest start node in current location, target location is corresponding most
Close destination node；And receive more than one path between the start node and destination node；
6th acquisition module 11, for obtaining active user's time；
Second receiving module 12, for receiving the advowson in the preset time period residing for the current time in the path
Value；
Third receiving module 13, the recommendation weights respective path for receiving predetermined number.
As can be seen from the above description, the advantageous effect of client is recommended to be based on the path of taxi empirical data：With
Family is received by the first receiving module 10 between nearest with current location and target location respectively start node and destination node
Path receives the recommendation weights in path between current time start node and destination node by the second receiving module 12, by the
Three receiving modules 13, which receive, recommends the corresponding path of weights；Above-mentioned client node data, recommendation weights in different time periods with
And it is client by communications reception to recommend the corresponding path of weights, without being stored in client, saves client
Memory space.
Further, a kind of path recommendation client based on taxi empirical data further includes；
7th acquisition module 6 for obtaining current location to the path of start node, and obtains target location to target
The path of node；
Computing module 7, the recommendation weights for calculating the path；
Laminating module 8, for being superimposed the recommendation weights with the recommendation weights between node.
As can be seen from the above description, total path also contemplates initial position and is arrived to the path of start node and target location
The position of destination node.
Fig. 1 and Fig. 2 is please referred to, the embodiment of the present invention one is：
A kind of path recommendation method based on taxi empirical data, including：
S1, default node, obtain the path between two nodes；" the default node " is specially：S11, traversal
Taxi initial position or target location；S12, initial position in preset time period or the target location taxi frequency are arranged
Sequence；S13, according to the sequence, it is default node to extract the initial position of predetermined number or target location；Road based on map
City is divided into multiple nodes by net, and the frequency of occurrence of taxi is reached a certain amount of node as default node, such as public affairs
The frequency of occurrence of garden and the railway station places Liang Ge taxi is high, using park and railway station as two default nodes；
S2, rule of thumb data, the i.e. historical data of taxi obtain recommendation of any path in preset time period
Weights store the recommendation weights；" the recommendation weights of preset time period " are specially：According to festivals or holidays, working day, week
End and ordinary period and peak period, taxi vehicle speed and frequency information in conjunction with a path in the above-mentioned period obtain and recommend
Weights；There are lakeside East Road diameter, lakeside South Road diameter and lakeside North Road diameter, peak period festivals or holidays, lake in the path in railway station to park
The recommendation weights of shore East Road diameter are a, and the recommendation weights of lakeside South Road diameter are b, and the recommendation weights of lakeside North Road diameter are c；
S3, user current location and target location are obtained, and obtains current location and corresponds to nearest start node, target position
Set corresponding nearest destination node；Choose more than one path between the start node and destination node；Assuming that present bit
It is railway station to set nearest initial starting point, and target location corresponds to nearest destination node park, then chooses the shortest lakeside of distance
It is path that East Road diameter and the shorter lakeside South Road of distance, which pass through,；
S41, the current time for obtaining user, and obtain in the preset time period residing for the current time in the path
Recommend weights；Assuming that current time is peak period festivals or holidays, then obtains the period lakeside East Road diameter and lakeside South Road diameter corresponds to
Recommendation weights be a and b；
S42, current location to the path of start node is obtained, and obtains target location to the path of destination node, meter
The recommendation weights are superimposed, by the advowson after superposition by the recommendation weights for calculating the path with the recommendation weights between node
Value is as recommendation weights；Current location is corresponding to the two paths Xinghua paths in start node railway station and institution of higher learning path
Recommendation weights are d and e, and the corresponding recommendation weights in a paths Zhongshan Road of target location to destination node park are f, by a, d,
F superpositions, a, e, f superposition, b, d, f are superimposed and b, e, f are superimposed as current location to the advowson of target location total path
Value；
S5, the recommendation weights respective path for recommending predetermined number；Recommend the recommendation after the above-mentioned superposition of predetermined number
The recommendation weights of weights, the recommendation weights after comparison superposition, b, d, f superposition are optimal, final b, d, f corresponding path Xinghua road-
Lakeside South Road-Zhongshan Road is optimal path.
Fig. 3 is please referred to, the embodiment of the present invention two is：
A kind of path commending system based on taxi empirical data, including：
Default node module 1, for presetting node；First acquisition module 14, between two nodes of acquisition
Path；
Second acquisition module 2, for rule of thumb data, advowson of any path of acquisition in preset time period
Value；Memory module, for storing the recommendation weights；
Third acquisition module 3 for obtaining user current location and target location, and obtains current location and corresponds to recently
Start node, target location correspond to nearest destination node；Module is chosen, for choosing the start node and destination node
Between more than one path；
4th acquisition module 4 for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module 5, the recommendation weights respective path for recommending predetermined number.
Fig. 4 is please referred to, the embodiment of the present invention three is：
A kind of path recommendation client based on taxi empirical data, including：
Third acquisition module 3, the target location for obtaining user current location, and it is corresponding recently to obtain current location
Start node, the corresponding nearest destination node in target location；Module is chosen, for choosing the start node and target
More than one path between node；
4th acquisition module 4 for obtaining user's current time, and obtains described pre- residing for the current time in the path
If the recommendation weights in the period；
Recommending module 5, the recommendation weights respective path for recommending predetermined number；
7th acquisition module 6 for obtaining current location to the path of start node, and obtains target location to target
The path of node；
Computing module 7, the recommendation weights for calculating the path；
Laminating module 8, for being superimposed the recommendation weights with the recommendation weights between node.
Fig. 5 is please referred to, the embodiment of the present invention four is：
A kind of path recommendation client based on taxi empirical data, including：
5th acquisition module 9, the target location for obtaining user current location；
First receiving module 10, for receiving the corresponding nearest start node in current location, target location is corresponding most
Close destination node；And receive more than one path between the start node and destination node；
6th acquisition module 11, for obtaining active user's time；
Second receiving module 12, for receiving the advowson in the preset time period residing for the current time in the path
Value；
Third receiving module 13, the recommendation weights respective path for receiving predetermined number.
7th acquisition module 6 for obtaining current location to the path of start node, and obtains target location to target
The path of node；
Computing module 7, the recommendation weights for calculating the path；
Laminating module 8, for being superimposed the recommendation weights with the recommendation weights between node.
In conclusion method, system and client are recommended in a kind of path based on taxi empirical data provided by the invention
End, the inaccurate problem of navigation caused by not considering section jam situation according only to initial position for existing navigation system, leads to
It crosses default node module and the second acquisition module presets node and obtains the recommendation weights in path between arbitrary two node, and pass through the
Three acquisition modules and the 4th acquisition module obtain user current location, target location and current time, obtain corresponding advowson
Value, recommending module recommend respective path, can be effectively shielded from vehicle peak section, provide the user with best path.
Example the above is only the implementation of the present invention is not intended to limit the scope of the invention, every to utilize this hair
Equivalents made by bright specification and accompanying drawing content are applied directly or indirectly in relevant technical field, include similarly
In the scope of patent protection of the present invention.
Claims (8)
1. method is recommended in a kind of path based on taxi empirical data, including：
Default node, obtains the path between two nodes；The default node is the road network based on map by city
Multiple nodes are divided into, the frequency of occurrence of taxi is reached into a certain amount of node as default node；
Rule of thumb data obtain any path in the recommendation weights of preset time period, store the recommendation weights；Institute
" the recommendation weights of preset time period " stated are specially：When according to festivals or holidays, working day, weekend and ordinary period and peak
Section, taxi vehicle speed and frequency information in conjunction with a path in the above-mentioned period obtain and recommend weights；
User current location and target location are obtained, and obtains current location and corresponds to nearest start node, target location corresponds to
Nearest destination node；Choose more than one path between the start node and destination node；
The current time of user is obtained, and is obtained in the preset time period residing for the current time in the selected path
Recommend weights；
Recommend the recommendation weights respective path of predetermined number.
2. method is recommended in a kind of path based on taxi empirical data as described in claim 1, it is characterised in that：
" the default node " is specially：
Traverse taxi initial position or target location；
Initial position in preset time period or the target location taxi frequency are ranked up；
According to the sequence, it is default node to extract the initial position of predetermined number or target location.
3. method is recommended in a kind of path based on taxi empirical data as described in claim 1, it is characterised in that：Further
Including：
Current location to the path of start node is obtained, and obtains target location to the path of destination node, calculates the road
The recommendation weights are superimposed by the recommendation weights of diameter with the recommendation weights between node, using the recommendation weights after superposition as pushing away
Recommend weights.
4. a kind of path commending system based on taxi empirical data, including：
Default node module, for presetting node；First acquisition module, for obtaining the path between two nodes；Institute
City is divided into multiple nodes by the default node module stated based on the road network of map, and the frequency of occurrence of taxi is reached certain
The node of amount is as default node；
Second acquisition module, for rule of thumb data, recommendation weights of any path of acquisition in preset time period；It is described
" the recommendation weights of preset time period " be specially：According to festivals or holidays, working day, weekend and ordinary period and peak period,
Taxi vehicle speed and frequency information in conjunction with a path in the above-mentioned period obtain and recommend weights；
Memory module, for storing the recommendation weights；
Third acquisition module for obtaining user current location and target location, and obtains current location and corresponds to recently initial
Node, target location correspond to nearest destination node；
Module is chosen, for choosing more than one path between the start node and destination node；
4th acquisition module for obtaining user's current time, and obtains the current time institute place in the selected path
State the recommendation weights in preset time period；
Recommending module, the recommendation weights respective path for recommending predetermined number.
5. client is recommended in a kind of path based on taxi empirical data, it is characterised in that：Including；
Third acquisition module, the target location for obtaining user current location, and obtain current location it is corresponding it is nearest just
Beginning node, the corresponding nearest destination node in target location；
Module is chosen, for choosing more than one path between the start node and destination node；The start node
It it is respectively one in default node with the destination node, the default node is that the road network based on map divides city
For multiple nodes, the frequency of occurrence of taxi is reached into a certain amount of node as default node；
4th acquisition module for obtaining user's current time, and obtains pre- residing for the current time in the selected path
If the recommendation weights in the period；Recommendation weights in the preset time period, specially：According to festivals or holidays, working day, weekend
And ordinary period and peak period, taxi vehicle speed and frequency information in conjunction with a path in the above-mentioned period obtain advowson
Value；
Recommending module, the recommendation weights respective path for recommending predetermined number.
6. client is recommended in a kind of path based on taxi empirical data as claimed in claim 5, it is characterised in that：Also wrap
It includes,
7th acquisition module for obtaining current location to the path of start node, and obtains target location to destination node
Path；
Computing module, the recommendation weights for calculating the path；
Laminating module, for being superimposed the recommendation weights with the recommendation weights between node.
7. client is recommended in a kind of path based on taxi empirical data, it is characterised in that：Including,
5th acquisition module, the target location for obtaining user current location；
First receiving module, for receiving the corresponding nearest start node in current location, the corresponding nearest mesh in target location
Mark node；And receive more than one path between the start node and destination node；The start node and the mesh
It is respectively one in default node to mark node, and the default node is that city is divided into multiple knots by the road network based on map
The frequency of occurrence of taxi is reached a certain amount of node as default node by point；
6th acquisition module, for obtaining active user's time；
Second receiving module, for receiving the recommendation weights in preset time period residing for the current time in the path；It is described pre-
If the recommendation weights in the period, specially：According to festivals or holidays, working day, weekend and ordinary period and peak period, in conjunction with
Taxi vehicle speed and frequency information of one path in the above-mentioned period obtain and recommend weights；
Third receiving module, the recommendation weights respective path for receiving predetermined number.
8. client is recommended in a kind of path based on taxi empirical data as claimed in claim 7, it is characterised in that：Also wrap
It includes,
7th acquisition module for obtaining current location to the path of start node, and obtains target location to destination node
Path；
Computing module, the recommendation weights for calculating the path；
Laminating module, for being superimposed the recommendation weights with the recommendation weights between node.
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| CN105389974A (en) * | 2015-11-19 | 2016-03-09 | 深圳市赛格导航科技股份有限公司 | Vehicle tracking method and system based on vehicle historical driving data |
| CN106225793A (en) * | 2016-06-30 | 2016-12-14 | 佛山市天地行科技有限公司 | navigation algorithm based on experience |
| CN107038886B (en) * | 2017-05-11 | 2019-05-28 | 厦门大学 | A kind of taxi based on track data is cruised path recommended method and system |
| WO2018209576A1 (en) | 2017-05-16 | 2018-11-22 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for digital route planning |
| WO2019218335A1 (en) * | 2018-05-18 | 2019-11-21 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for recommending a personalized pick-up location |
| CN108775904A (en) * | 2018-08-20 | 2018-11-09 | 蔚来汽车有限公司 | For the air navigation aid of charged area in parking lot |
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| KR101467557B1 (en) * | 2007-05-02 | 2014-12-10 | 엘지전자 주식회사 | Selecting Route According To Traffic Information |
| CN102278995B (en) * | 2011-04-27 | 2013-02-13 | 中国石油大学(华东) | Bayes path planning device and method based on GPS (Global Positioning System) detection |
| KR101379846B1 (en) * | 2012-07-24 | 2014-04-17 | 이현복 | A Dispenser Vessel |
| CN103714708A (en) * | 2013-12-18 | 2014-04-09 | 福建工程学院 | Optimal path planning method based on split-time experience path of taxi |
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