CN104990559A - Route recommending method based on taxi empirical data, system and client - Google Patents
Route recommending method based on taxi empirical data, system and client Download PDFInfo
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- CN104990559A CN104990559A CN201510444193.4A CN201510444193A CN104990559A CN 104990559 A CN104990559 A CN 104990559A CN 201510444193 A CN201510444193 A CN 201510444193A CN 104990559 A CN104990559 A CN 104990559A
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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
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Abstract
The invention provides a route recommending method based on taxi empirical data, a system and a client. The method comprises the following steps: presetting nodes by a node presetting module, obtaining a route between two nodes; obtaining the recommendation weight of the route in a preset time period by a second obtaining module according to the empirical data, storing the recommendation weight; obtaining the current position and the target position of a user by a third obtaining module, obtaining the primary node that is closest to the current position and the target node that is closes to the target position; selecting at least one route between the primary node and the target node; obtaining the current time of the user by a fourth obtaining module, obtaining the recommendation weights of the selected routes in the time period that the current time belongs to; and recommending the preset-number routes by the recommending module according to the recommendation weight.
Description
Technical field
The present invention relates to field of electronic navigation, particularly relate to a kind of path recommend method based on taxi empirical data, system and client.
Background technology
Along with development and the growth in the living standard of science and technology, path navigation becomes people and to go on a journey an indispensable step, application number be 200610105972.2 patent document disclose a kind of navigational system, for the route searching based on use predetermined condition, the guidance path of the stroke between starting point and terminal is provided, described navigational system comprises: display unit, for show navigator path and/or candidate's guidance path with relevant conditional name, the described predetermined condition wherein with relevant conditional name produces multiple candidate's guidance path.
Such scheme is correlated with according to title and journey navigation path between distance search starting point and terminal, but under the road conditions of city complexity, especially when often there is traffic congestion in big city, different time sections, different sections of highway road conditions are not identical, such as the go to work section of peak period concentration of enterprises and the section at place, sight spot festivals or holidays is often compared and is blocked up, it is smooth and easy that the path compared with short circuit journey adopting such scheme to obtain can not ensure that section is open to traffic, and therefore accurately can not obtain optimum guidance path.
In addition, under the road conditions of city complexity, experienced taxi driver can understand the jam situation of road conditions, and can quick and the most unobstructed path be found, if can make full use of the existing Model choices path of experience taxi driver, and be supplied to user according to the demand of user, then the trip of user has provided path comparatively smoothly, improve the comfort level of user's trip, and for the unimpeded operation of whole city road network and utilization ratio also significant.
Summary of the invention
Technical matters to be solved by this invention is: under the road conditions of city complexity, recommends best driving path to user.
In order to solve the problems of the technologies described above, the technical solution used in the present invention is:
The invention provides a kind of path recommend method based on taxi empirical data, comprising:
Preset node, obtain the path between two described nodes;
Rule of thumb data, obtain the recommendation weights of arbitrary described path in preset time period, the recommendation weights described in storage;
Obtain user's current location and target location, and obtain start node corresponding to current location, the destination node that target location is corresponding nearest; Choose more than one path between described start node and destination node;
Obtain the current time of user, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommend the described recommendation weights respective path of predetermined number.
The beneficial effect of the above-mentioned path recommend method based on taxi empirical data is: preset node, and obtain the recommendation weights of arbitrary two hops in preset time period, thus arbitrary two internodal optimal paths in different time sections can be obtained, obtain the path with user's current location and the target location corresponding nearest start node of difference and destination node, and the recommendation weights in path between start node and destination node are obtained by the current time of user, thus obtain optimum recommendation paths, therefore effectively can avoid congested link.
The present invention also provides a kind of path commending system based on taxi empirical data, comprising:
Preset node module, for default node;
First acquisition module, for obtaining the path between two described nodes;
Second acquisition module, for rule of thumb data, obtains the recommendation weights of arbitrary described path in preset time period; Memory module, for storing described recommendation weights;
3rd acquisition module, for obtaining user's current location and target location, and obtains start node corresponding to current location, the destination node that target location is corresponding nearest; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module, for recommending the described recommendation weights respective path of predetermined number.
The above-mentioned path recommend method based on taxi empirical data, its beneficial effect is: default node module presets node, and obtain the recommendation weights of arbitrary two hops in preset time period by the first acquisition module and the second acquisition module, thus arbitrary two internodal optimal paths in different time sections can be obtained, 3rd acquisition module obtains the path with user's current location and the target location corresponding nearest start node of difference and destination node, and current time and the recommendation weights in path between current time start node and destination node of user are obtained by the 4th acquisition module, thus obtain optimum recommendation paths, therefore effectively congested link can be avoided.
The present invention also provides a kind of path recommend customers end based on taxi empirical data, comprising:
3rd acquisition module, for obtaining the target location of user's current location, and obtains nearest start node corresponding to current location, the nearest destination node that target location is corresponding; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module, for recommending the described recommendation weights respective path of predetermined number.
The beneficial effect of above-mentioned client is: user obtains the path between the start node of current location and target location difference correspondence and destination node by the 3rd acquisition module, and obtain the current time by the 4th, and the recommendation weights in path between current time start node and destination node, thus the optimal path obtained between start node and destination node, efficiently solve the driving difficult problem that congestion in road causes; The recommendation weights of any two hops of above-mentioned client node data, different time sections are default in client, therefore client is logical without the need to carrying out other communication again, also effectively can avoid congested link when not having communication signal or connecting without network.
The present invention reoffers a kind of path recommend customers end based on taxi empirical data, comprising:
5th acquisition module, for obtaining the target location of user's current location;
First receiver module, for receiving nearest start node corresponding to current location, the nearest destination node that target location is corresponding; And receive described in start node and destination node between more than one path;
6th acquisition module, for obtaining active user's time;
Second receiver module, for receive described path current time residing for recommendation weights in described preset time period;
3rd receiver module, for receiving the described recommendation weights respective path of predetermined number.
The beneficial effect of above-mentioned client is: user is received respectively by the first receiver module and path between the nearest start node of current location and target location and destination node, received the recommendation weights in path between current time start node and destination node by the second receiver module, received the path of recommending weights corresponding by the 3rd receiver module; The recommendation weights of above-mentioned client node data, different time sections and recommend path corresponding to weights be client by communications reception, and do not need to be stored in client, save the storage space of client.
Accompanying drawing explanation
Fig. 1 is the path recommend method process flow diagram based on taxi empirical data of the embodiment of the present invention one;
Fig. 2 is the default node process flow diagram of the path recommend method based on taxi empirical data of the embodiment of the present invention one;
Fig. 3 is the path commending system structural representation based on taxi empirical data of the embodiment of the present invention two;
Fig. 4 is the path recommend customers end structure schematic diagram based on taxi empirical data of the embodiment of the present invention three;
Fig. 5 is the path recommend customers end structure schematic diagram 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, the 3rd acquisition module; 4, the 4th acquisition module; 5, recommending module; 6, the 7th acquisition module; 7, computing module; 8, laminating module; 9, the 5th acquisition module; 10, the first receiver module; 11, the 6th acquisition module; 12, the second receiver module; 13, the 3rd receiver module; 14, the first acquisition module.
Embodiment
By describing technology contents of the present invention in detail, realized object and effect, accompanying drawing is coordinated to be explained below in conjunction with embodiment.
The design of most critical of the present invention is: rule of thumb data, obtain the recommendation weights of arbitrary path in preset time period, and the advowson value in the path included by current location and target location and the preset time period residing for current time obtains optimal path.
Please refer to Fig. 1 to Fig. 5,
Based on a path recommend method for taxi empirical data, comprising:
S1, default node, obtain the path between two described nodes;
S2, rule of thumb data, obtain the recommendation weights of arbitrary described path in preset time period, the recommendation weights described in storage;
S3, acquisition user's current location and target location, and obtain start node corresponding to current location, the destination node that target location is corresponding nearest; Choose more than one path between described start node and destination node;
S41, obtain the current time of user, and the recommendation weights in described preset time period residing for the current time obtaining described path;
The described recommendation weights respective path of S5, recommendation predetermined number.
From foregoing description, this beneficial effect based on the path recommend method of taxi empirical data is: preset node, and obtain the recommendation weights of arbitrary two hops in preset time period, thus arbitrary two internodal optimal paths in different time sections can be obtained, obtain the path with user's current location and the target location corresponding nearest start node of difference and destination node, and the recommendation weights in path between start node and destination node are obtained by the current time of user, thus obtain optimum recommendation paths, therefore effectively can avoid congested link.
Further, described " presetting node " is specially:
S11, traversal taxi initial position or target location;
S12, initial position in preset time period or the target location taxi frequency to be sorted;
S13, according to described sequence, extract the initial position of predetermined number or target location for presetting node.
From foregoing description, by carrying out the default node extracted that sorts to initial position and the target location taxi frequency, call a taxi initial position and the target location of the overwhelming majority can be represented.
Further, described " the recommendation weights of preset time period " are specially: according to festivals or holidays, working day, weekend and ordinary period and peak period, in conjunction with a path in the taxi speed of above-mentioned period and frequency information, obtain and recommend weights.
From foregoing description, in the different time periods, this path of taxi speed and frequency message reflection is in the unimpeded situation of the bus or train route of different time sections, thus the recommendation weights that obtain effectively can avoid the section that blocks up.
Further, the path recommend method based on taxi empirical data also comprises:
S42, acquisition current location are to the path of start node, and obtain the path of target location to destination node, calculate the recommendation weights in described path, described recommendation weights are superposed with internodal recommendation weights, using the recommendation weights after superposition as recommendation weights.
From foregoing description, total path also contemplates initial position to the path of start node and target location to the position of destination node.
Based on a path commending system for taxi empirical data, comprising:
Preset node module 1, for default node; First acquisition module 14, for obtaining the path between two described nodes;
Second acquisition module 2, for rule of thumb data, obtains the recommendation weights of arbitrary described path in preset time period; Memory module, for storing described recommendation weights;
3rd acquisition module 3, for obtaining user's current location and target location, and obtains start node corresponding to current location, the destination node that target location is corresponding nearest; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module 4, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module 5, for recommending the described recommendation weights respective path of predetermined number.
Seen from the above description, this beneficial effect based on the path commending system of taxi empirical data is: preset node module 1 and preset node, and obtain the recommendation weights of arbitrary two hops in preset time period by the first acquisition module 14 and the second acquisition module 2, thus arbitrary two internodal optimal paths in different time sections can be obtained, 3rd acquisition module 3 obtains the path with user's current location and the target location corresponding nearest start node of difference and destination node, and current time and the recommendation weights in path between current time start node and destination node of user are obtained by the 4th acquisition module 4, thus obtain optimum recommendation paths, therefore effectively congested link can be avoided.
Based on a path recommend customers end for taxi empirical data, comprise;
3rd acquisition module 3, for obtaining the target location of user's current location, and obtains nearest start node corresponding to current location, the nearest destination node that target location is corresponding; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module 4, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module 5, for recommending the described recommendation weights respective path of predetermined number.
From foregoing description, this beneficial effect based on the path recommend customers end of taxi empirical data is: user obtains the path between the start node of current location and target location difference correspondence and destination node by the 3rd acquisition module 3, and obtain the current time by the 4th acquisition module 4, and the recommendation weights in path between current time start node and destination node, thus the optimal path obtained between start node and destination node, efficiently solve the driving difficult problem that congestion in road causes; The recommendation weights of any two hops of above-mentioned client node data, different time sections are default in client, therefore client is logical without the need to carrying out other communication again, also effectively can avoid congested link when not having communication signal or connecting without network.
Further, described a kind of path recommend customers end based on taxi empirical data also comprises:
7th acquisition module 6, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module 7, for calculating the recommendation weights in described path;
Laminating module 8, for superposing described recommendation weights with internodal recommendation weights.
From foregoing description, total path also contemplates initial position to the path of start node and target location to the position of destination node.
Based on a path recommend customers end for taxi empirical data, comprise;
5th acquisition module 9, for obtaining the target location of user's current location;
First receiver module 10, for receiving nearest start node corresponding to current location, the nearest destination node that target location is corresponding; And receive described in start node and destination node between more than one path;
6th acquisition module 11, for obtaining active user's time;
Second receiver module 12, for receive described path current time residing for recommendation weights in described preset time period;
3rd receiver module 13, for receiving the described recommendation weights respective path of predetermined number.
From foregoing description, this is based on beneficial effect of the path recommend customers end of taxi empirical data: user is received respectively by the first receiver module 10 and path between the nearest start node of current location and target location and destination node, received the recommendation weights in path between current time start node and destination node by the second receiver module 12, received the path of recommending weights corresponding by the 3rd receiver module 13; The recommendation weights of above-mentioned client node data, different time sections and recommend path corresponding to weights be client by communications reception, and do not need to be stored in client, save the storage space of client.
Further, described a kind of path recommend customers end based on taxi empirical data also comprises;
7th acquisition module 6, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module 7, for calculating the recommendation weights in described path;
Laminating module 8, for superposing described recommendation weights with internodal recommendation weights.
From foregoing description, total path also contemplates initial position to the path of start node and target location to the position of destination node.
Please refer to Fig. 1 and Fig. 2, embodiments of the invention one are:
Based on a path recommend method for taxi empirical data, comprising:
S1, default node, obtain the path between two described nodes; Described " presetting node " is specially: S11, traversal taxi initial position or target location; S12, initial position in preset time period or the target location taxi frequency to be sorted; S13, according to described sequence, extract the initial position of predetermined number or target location for presetting node; City is divided into multiple node by the road network based on map, the frequency of occurrence of taxi is reached a certain amount of node as default node, and such as the frequency of occurrence of park and Liang Ge place, railway station 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 the recommendation weights of arbitrary described path in preset time period, the recommendation weights described in storage; Described " the recommendation weights of preset time period " are specially: according to festivals or holidays, working day, weekend and ordinary period and peak period, in conjunction with a path in the taxi speed of above-mentioned period and frequency information, obtain and recommend weights; There are footpath, East Road, lakeside, footpath, South Road, lakeside and footpath, North Road, lakeside in railway station, peak period festivals or holidays to the path in park, and the recommendation weights in footpath, East Road, lakeside are a, and the recommendation weights in footpath, South Road, lakeside are b, and the recommendation weights in footpath, North Road, lakeside are c;
S3, acquisition user's current location and target location, and obtain start node corresponding to current location, the destination node that target location is corresponding nearest; Choose more than one path between described start node and destination node; Suppose that the nearest initial starting point of current location is railway station, the destination node park that target location is corresponding nearest, then choose the shortest footpath, East Road, lakeside of distance and the shorter South Road, lakeside of distance through being path;
S41, obtain the current time of user, and the recommendation weights in described preset time period residing for the current time obtaining described path; Suppose that current time is peak period festivals or holidays, then obtaining recommendation weights corresponding to this footpath, East Road, period lakeside and footpath, South Road, lakeside is a and b;
S42, acquisition current location are to the path of start node, and obtain the path of target location to destination node, calculate the recommendation weights in described path, described recommendation weights are superposed with internodal recommendation weights, using the recommendation weights after superposition as recommendation weights; Current location is d and e to the corresponding respectively recommendation weights in the two paths Xinghua paths in start node railway station and institution of higher learning path, target location is f to the recommendation weights that a paths Zhongshan Road in destination node park is corresponding, a, d, f superposition, a, e, f superposition, b, d, f is superposed and b, e, f are superposed the recommendation weights as current location to target location total path;
The described recommendation weights respective path of S5, recommendation predetermined number; Recommend the recommendation weights after the above-mentioned superposition of predetermined number, the recommendation weights after contrast superposition, the recommendation weights of b, d, f superposition are optimum, and Xinghua road, path-South Road-Zhongshan Road, lakeside that final b, d, f are corresponding is optimum path.
Please refer to Fig. 3, embodiments of the invention two are:
Based on a path commending system for taxi empirical data, comprising:
Preset node module 1, for default node; First acquisition module 14, for obtaining the path between two described nodes;
Second acquisition module 2, for rule of thumb data, obtains the recommendation weights of arbitrary described path in preset time period; Memory module, for storing described recommendation weights;
3rd acquisition module 3, for obtaining user's current location and target location, and obtains start node corresponding to current location, the destination node that target location is corresponding nearest; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module 4, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module 5, for recommending the described recommendation weights respective path of predetermined number.
Please refer to Fig. 4, embodiments of the invention three are:
Based on a path recommend customers end for taxi empirical data, comprising:
3rd acquisition module 3, for obtaining the target location of user's current location, and obtains nearest start node corresponding to current location, the nearest destination node that target location is corresponding; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module 4, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module 5, for recommending the described recommendation weights respective path of predetermined number;
7th acquisition module 6, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module 7, for calculating the recommendation weights in described path;
Laminating module 8, for superposing described recommendation weights with internodal recommendation weights.
Please refer to Fig. 5, embodiments of the invention four are:
Based on a path recommend customers end for taxi empirical data, comprising:
5th acquisition module 9, for obtaining the target location of user's current location;
First receiver module 10, for receiving nearest start node corresponding to current location, the nearest destination node that target location is corresponding; And receive described in start node and destination node between more than one path;
6th acquisition module 11, for obtaining active user's time;
Second receiver module 12, for receive described path current time residing for recommendation weights in described preset time period;
3rd receiver module 13, for receiving the described recommendation weights respective path of predetermined number.
7th acquisition module 6, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module 7, for calculating the recommendation weights in described path;
Laminating module 8, for superposing described recommendation weights with internodal recommendation weights.
In sum, a kind of path recommend method based on taxi empirical data provided by the invention, system and client, the inaccurate problem of navigation that section jam situation causes only is not considered according to reference position for existing navigational system, preset node by default node module and the second acquisition module and obtain the recommendation weights in path between any two nodes, and obtain user's current location by the 3rd acquisition module and the 4th acquisition module, target location and current time, recommended weights accordingly, recommending module recommends respective path, effectively can avoid section, vehicle peak, best path is provided to user.
The foregoing is only embodiments of the invention; not thereby the scope of the claims of the present invention is limited; every equivalents utilizing instructions of the present invention and accompanying drawing content to do, or be directly or indirectly used in relevant technical field, be all in like manner included in scope of patent protection of the present invention.
Claims (9)
1., based on a path recommend method for taxi empirical data, comprising:
Preset node, obtain the path between two described nodes;
Rule of thumb data, obtain the recommendation weights of arbitrary described path in preset time period, the recommendation weights described in storage;
Obtain user's current location and target location, and obtain start node corresponding to current location, the destination node that target location is corresponding nearest; Choose more than one path between described start node and destination node;
Obtain the current time of user, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommend the described recommendation weights respective path of predetermined number.
2. a kind of path recommend method based on taxi empirical data as claimed in claim 1, is characterized in that:
Described " presetting node " is specially:
Traversal taxi initial position or target location;
Initial position in preset time period or the target location taxi frequency are sorted;
According to described sequence, initial position or the target location of extracting predetermined number are default node.
3. a kind of path recommend method based on taxi empirical data as claimed in claim 1, is characterized in that:
Described " the recommendation weights of preset time period " are specially: according to festivals or holidays, working day, weekend and ordinary period and peak period, in conjunction with a path in the taxi speed of above-mentioned period and frequency information, obtain and recommend weights.
4. a kind of path recommend method based on taxi empirical data as claimed in claim 1, is characterized in that: comprise further:
Obtain the path of current location to start node, and obtain target location to the path of destination node, calculate the recommendation weights in described path, described recommendation weights are superposed with internodal recommendation weights, using the recommendation weights after superposition as recommendation weights.
5., based on a path commending system for taxi empirical data, comprising:
Preset node module, for default node; First acquisition module, for obtaining the path between two described nodes;
Second acquisition module, for rule of thumb data, obtains the recommendation weights of arbitrary described path in preset time period; Memory module, for storing described recommendation weights;
3rd acquisition module, for obtaining user's current location and target location, and obtains start node corresponding to current location, the destination node that target location is corresponding nearest; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module, for recommending the described recommendation weights respective path of predetermined number.
6., based on a path recommend customers end for taxi empirical data, it is characterized in that: comprise;
3rd acquisition module, for obtaining the target location of user's current location, and obtains nearest start node corresponding to current location, the nearest destination node that target location is corresponding; Choose module, for choosing more than one path between described start node and destination node;
4th acquisition module, for obtaining user's current time, and the recommendation weights in described preset time period residing for the current time obtaining described path;
Recommending module, for recommending the described recommendation weights respective path of predetermined number.
7. a kind of path recommend customers end based on taxi empirical data as claimed in claim 6, is characterized in that: also comprise,
7th acquisition module, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module, for calculating the recommendation weights in described path;
Laminating module, for superposing described recommendation weights with internodal recommendation weights.
8., based on a path recommend customers end for taxi empirical data, it is characterized in that: comprise,
5th acquisition module, for obtaining the target location of user's current location;
First receiver module, for receiving nearest start node corresponding to current location, the nearest destination node that target location is corresponding; And receive described in start node and destination node between more than one path;
6th acquisition module, for obtaining active user's time;
Second receiver module, for receive described path current time residing for recommendation weights in described preset time period;
3rd receiver module, for receiving the described recommendation weights respective path of predetermined number.
9. a kind of path recommend customers end based on taxi empirical data as claimed in claim 8, is characterized in that: also comprise,
7th acquisition module, for obtaining the path of current location to start node, and obtains the path of target location to destination node;
Computing module, for calculating the recommendation weights in described path;
Laminating module, for superposing described recommendation weights with internodal recommendation weights.
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