CN108051011B - Reliable navigation path setting method based on taxi experience data - Google Patents
Reliable navigation path setting method based on taxi experience data Download PDFInfo
- Publication number
- CN108051011B CN108051011B CN201711069146.1A CN201711069146A CN108051011B CN 108051011 B CN108051011 B CN 108051011B CN 201711069146 A CN201711069146 A CN 201711069146A CN 108051011 B CN108051011 B CN 108051011B
- Authority
- CN
- China
- Prior art keywords
- node
- grids
- taxi
- preset
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
A route setting method and system based on taxi experience data comprises the following steps: the method comprises the steps that a first obtaining module obtains preset nodes and all taxi data; the classification module classifies the taxi data according to the time period; the second acquisition module acquires the path information of the taxi passing through the preset node in a time period; the first statistical module counts a path information set of all taxis passing through paths between two adjacent nodes in a time period; the second statistical module is used for counting the path information sets of all taxis passing through the paths between two adjacent nodes in all time periods; the calculation module calculates the corresponding weight of the path according to the path information set; and the first storage module stores the paths and the weights corresponding to the paths according to time period classification.
Description
The application is a divisional application of a parent application named 'route setting method and system based on taxi experience data' with the application date of 2015-07-27 and the application number of 2015104441915.
Technical Field
The invention relates to the field of electronic navigation, in particular to a route setting method and system based on taxi experience data.
Background
With the development of science and technology and the improvement of living standard, path navigation becomes an indispensable step for people going out, the traditional navigation method generally adopts the steps of obtaining an initial position and a target position, and selecting a route with the closest distance between the initial position and the target position as a navigation route according to a map, however, under the complex road conditions of a large city, the distance is not a simple navigation consideration any more.
The patent document with the application number of 201010566504.1 discloses a road condition navigation method, a mobile terminal and a road condition navigation server, which perform grouping fusion calculation according to positioning data of more than one mobile terminal and road condition request information of a target mobile terminal, acquire position data, direction data and speed identification information of more than one mobile terminal group to be displayed and send the position data, the direction data and the speed identification information to the target mobile terminal; the method subdivides the whole road into a set of a plurality of road sections, and respectively collects the specific road conditions of all the road sections in the road.
However, the scheme just subdivides the same road into a plurality of road sections, does not provide more navigation route selection, and the road conditions of a plurality of road sections of the same road are similar, so that the subdivision of the plurality of road sections and the calculation and analysis of each road section increase unnecessary workload.
In addition, under the complex road conditions in cities, people mostly travel in a taxi mode, experienced taxi drivers can know the congestion conditions of the road conditions most and can find the fastest and unobstructed paths, and if the experience of the taxi drivers can be fully utilized to set the navigation paths, the method has important significance for helping users such as private cars to quickly arrive at destinations and improving the road conditions of urban roads.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: under the complex road conditions of the city, a comprehensive and reasonable path is set, and reliable data is provided for navigation.
In order to solve the technical problems, the invention adopts the technical scheme that:
a route setting method based on taxi experience data comprises the following steps:
acquiring preset nodes and all taxi data;
classifying the taxi data according to time periods;
acquiring path information of the taxi passing through the preset node in a time period;
counting a path information set of all taxis passing through paths between two adjacent nodes in a time period;
counting path information sets of all taxis passing through paths between two adjacent nodes in all time periods;
calculating the corresponding weight of the path according to the path information set;
and storing the paths and the weights corresponding to the paths according to time period classification.
The route setting method based on taxi experience data has the beneficial effects that: classifying taxi data according to time periods, respectively obtaining path information sets of taxis passing through two adjacent preset nodes in each time period, counting the path information sets in each time period to enable the finally obtained path information to be representative and to represent road conditions in different time periods, calculating corresponding weights according to the counted path information sets to enable each weight to reflect one type of path information, calculating each path to obtain the road condition through the weight, and finally classifying and storing the paths and the weights corresponding to the paths to provide reliable data for navigation route selection.
A route setting system based on taxi experience data comprises:
the first acquisition module is used for acquiring preset nodes and all taxi data;
the classification module is used for classifying the taxi data according to the time period;
the second acquisition module is used for acquiring the path information of the taxi passing through the preset node in a time period;
the first statistical module is used for counting a path information set of all taxies passing through paths between two adjacent nodes in a time period;
the second statistical module is used for counting the path information sets of all taxis passing through the paths between the two adjacent nodes in all time periods;
the calculation module is used for calculating the corresponding weight of the path according to the path information set;
and the first storage module is used for storing the paths and the weights corresponding to the paths according to time period classification.
The taxi experience data-based path setting system has the beneficial effects that: the first acquisition module acquires data of a preset node and taxi, and provides a data basis for path setting; the classification module classifies taxi data according to time periods, path information of taxis passing through two adjacent preset nodes in one time period is obtained through the second obtaining module, the path information of one time period is obtained, path information sets of all time periods are obtained through the first statistical module and the second statistical module, the finally obtained path information is representative and can represent road conditions of different time periods, the calculating module calculates corresponding weights according to the counted path information sets, each weight reflects one type of path information, each path can obtain the road condition through weight calculation, the storage module stores the paths and the weights corresponding to the paths in a classified mode, and reliable data are provided for navigation route selection.
Drawings
Fig. 1 is a flowchart of a route setting method based on taxi experience data according to an embodiment of the present invention;
fig. 2 is a flow chart of a preset node of a route setting method based on taxi experience data according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a route setting system based on taxi experience data according to a second embodiment of the present invention.
Description of reference numerals:
11. a third obtaining module; 12. a first selection module; 13. a fourth obtaining module; 14. a second selection module; 15. a third selecting module; 16. a second storage module; 2. a first acquisition module; 3. a classification module; 4. a second acquisition module; 41. a fifth obtaining module; 42. a processing module; 43. a recording module; 5. a first statistical module; 6. a second statistical module; 7. a calculation module; 8. a first storage module.
Detailed Description
In order to explain technical contents, achieved objects, and effects of the present invention in detail, the following description is made with reference to the accompanying drawings in combination with the embodiments.
The most key concept of the invention is as follows: classifying the taxi data according to the time periods, obtaining a path information set between two adjacent nodes in different time periods according to the taxi data, and calculating the corresponding weight of the path according to the path information set.
The technical terms related to the invention are explained as follows:
referring to fig. 1 and fig. 2,
a route setting method based on taxi experience data comprises the following steps:
s2, acquiring preset nodes and all taxi data;
s3, classifying the taxi data according to the time period;
s4, obtaining path information of the taxi passing through the preset node in a time period;
s5, counting path information sets of all taxies passing through paths between two adjacent nodes in a time period;
s6, counting path information sets of all taxis passing through paths between two adjacent nodes in all time periods;
s7, calculating the corresponding weight of the path according to the path information set;
and S8, storing the paths and the weights corresponding to the paths according to time period classification.
As can be seen from the above description, the route setting method based on taxi experience data of the present invention has the following beneficial effects: classifying taxi data according to time periods, respectively obtaining path information sets of taxis passing through two adjacent preset nodes in each time period, counting the path information sets in each time period to enable the finally obtained path information to be representative and to represent road conditions in different time periods, calculating corresponding weights according to the counted path information sets to enable each weight to reflect one type of path information, calculating each path to obtain the road condition through the weight, and finally classifying and storing the paths and the weights corresponding to the paths to provide reliable data for navigation route selection.
Further, the specific presetting step of the preset node is as follows:
s11, obtaining map data and taxi data, and averagely dividing the map into basic grids;
s12, obtaining node grids to be selected according to the throughput of basic grid taxis;
s13, obtaining map data, and averagely dividing the map into grids with the number less than that of the basic grids;
s14, obtaining node grids according to the number of the node grids to be selected in the grids;
s15, obtaining preset nodes according to the POI of the node grids and the map;
and S16, storing the preset nodes.
According to the description, the node grids to be selected are obtained according to the throughput of the taxis, the workload caused by data processing of regions where the taxis do not pass or rarely pass is reduced, resource waste is avoided, the node grids are obtained according to the number of the node grids to be selected in the large grid, the node density distribution is reasonable, meanwhile, the preset nodes are obtained by combining the POI of the map, and therefore the preset nodes and the POI of the map can correspond to each other and are convenient to find.
Further, the step of obtaining the path information of the taxi passing through the preset node in a certain time period includes:
acquiring data of a taxi passing through two adjacent nodes within a time period;
processing data of the taxi passing through two adjacent preset nodes in the time period and obtaining path information of the two adjacent preset nodes;
and recording the path information of the taxi passing through the two adjacent nodes in the time period.
As can be seen from the above description, the route information of two adjacent nodes in a time period can be obtained by acquiring and processing data of a taxi passing through the two adjacent nodes in the time period.
Further, the "obtaining a node grid according to the number of node grids to be selected in the grid" specifically includes:
removing the grids with the number of the node grids to be selected smaller than 1;
taking the grids with the number of the node grids to be selected equal to 1 as node grids;
quartering grids with the number of the node grids to be selected larger than 1 for a preset number of times;
and taking the grid to be selected with the maximum taxi throughput in the grids divided into four times by the preset times as a node grid.
From the above description, the node grids are obtained according to the number of the node grids to be selected, so that the node density distribution is reasonable.
Further, the "obtaining a preset node according to the node grid and the POI of the map" specifically includes:
taking the central position of a road in a node grid with the POI number smaller than 1 as a preset node;
taking the POI in the node grid with the number of the POI equal to 1 as a preset node;
and taking the POI closest to the center position of the node grid in the node grid with the POI number larger than 1 as a preset node.
As can be seen from the above description, the preset node corresponds to the POI of the map, which is convenient for searching.
Referring to fig. 3 of the drawings,
a route setting system based on taxi experience data comprises:
the first obtaining module 2 is used for obtaining preset nodes and all taxi data;
the classification module 3 is used for classifying the taxi data according to the time period;
the second obtaining module 4 is configured to obtain path information of the taxi passing through the preset node in a time period;
the first statistical module 5 is used for counting a path information set of all taxis passing through paths between two adjacent nodes in a time period;
the second statistical module 6 is used for counting the path information sets of all taxis passing through the paths between the two adjacent nodes in all time periods;
the calculating module 7 is used for calculating the corresponding weight of the path according to the path information set;
and the first storage module 8 is configured to store the paths and the weights corresponding to the paths according to time period classification.
The taxi experience data-based path setting system has the beneficial effects that: the first acquisition module 2 acquires data of a preset node and taxi, and provides a data basis for path setting; the classification module 3 classifies taxi data according to time periods, the second acquisition module 4 obtains path information of taxis passing through two adjacent preset nodes in one time period, the path information of one time period is obtained, the path information sets of all time periods are obtained through the first statistical module 5 and the second statistical module 6, the finally obtained path information is representative and can represent road conditions of different time periods, the calculation module 7 calculates corresponding weights according to the counted path information sets, each weight reflects one type of path information, each path can obtain the road condition through weight calculation, the storage module 8 stores the paths and the weights corresponding to the paths in a classified mode, and reliable data are provided for navigation route selection.
Further, the route setting system based on taxi experience data further comprises:
the third obtaining module 11 is configured to obtain map data and taxi data, and divide the map into basic grids;
the first selection module 12 is used for obtaining node grids to be selected according to the throughput of basic grid taxis;
a fourth obtaining module 13, configured to obtain map data, and divide the map into grids smaller than the number of basic grids;
the second selection module 14 is configured to obtain a node grid according to the number of node grids to be selected in the grid;
the third selection module 15 is used for obtaining preset nodes according to the node grids and the POI of the map;
and a second storage module 16, configured to store the preset node.
According to the description, the first selection module obtains the node grids to be selected according to the throughput of taxis, the workload caused by data processing of regions where taxis do not pass or pass rarely is reduced, and resource waste is avoided.
Further, the "second obtaining module 4" includes:
a fifth obtaining module 41, configured to obtain data that a taxi passes through two adjacent nodes within a time period;
the processing module 42 is configured to process data of the taxi passing through two adjacent preset nodes in the time period and obtain path information of the two adjacent preset nodes;
and the recording module 43 is configured to record the route information of the taxi passing through the two adjacent nodes in the time period.
Referring to fig. 1 and fig. 2, a first embodiment of the present invention is:
s11, obtaining map data and taxi data, and averagely dividing the map into basic grids; for example, map data of fuzhou and travel data of all taxis in fuzhou city in the last week are obtained, and the map of fuzhou city is averagely divided into basic grids, such as 1000 × 1000 basic grids; a vehicle-mounted GPS positioning device is arranged on a taxi, data of the taxi is returned to a server every N seconds (generally 10-30 seconds), the data comprises information such as the ID number, GPS coordinates, speed, direction and time of the taxi, and the server side can acquire travel data of the taxi;
s12, obtaining node grids to be selected according to the throughput of basic grid taxis; for example, if the throughput of taxis in a certain basic grid is greater than the preset value of 5, the grid is used as a node grid to be selected, the throughput of taxis in another basic grid is 2, and is less than the preset value, the basic grid is not used as the node grid to be selected, and the preset value can be other values depending on the specific regional situation;
s13, obtaining map data, and averagely dividing the map into grids with the number less than that of the basic grids; obtaining map data of Fuzhou city, and averagely dividing the map of the Fuzhou city into grids with the number less than that of the basic grids, such as 250-by-250 grids;
s14, obtaining node grids according to the number of the node grids to be selected in the grids; removing the grids with the number of the node grids to be selected smaller than 1; taking the grids with the number of the node grids to be selected equal to 1 as node grids; quartering grids with the number of the node grids to be selected larger than 1 for a preset number of times; taking the grid to be selected with the maximum taxi throughput in the grids quartered for preset times as a node grid; if the number of the grids to be selected in a certain grid is 16, assuming that the preset times is 2, dividing the grid into four parts for 2 times to obtain 16 grids, and taking the grid with the maximum taxi throughput in the 16 grids as a node grid;
s15, obtaining preset nodes according to the POI of the node grids and the map; taking the central position of a road in a node grid with the POI number smaller than 1 as a preset node; taking the POI in the node grid with the number of the POI equal to 1 as a preset node; taking the POI closest to the center position of the node grid in the node grid with the number of the POI larger than 1 as a preset node; for example, in combination with POIs of a fuzhou city map, if there is no POI in a certain node grid, the central position of a white road in the node grid is used as a preset node, if only one POI park south gate is arranged in another node grid, the park south gate is used as the preset node, and if there are three POI park north gates, Yonghui supermarkets and west lake bus stations in the other node grid, wherein the west lake bus station is closest to the center of the grid, then the west lake bus station is used as the preset node;
s16, storing preset nodes; storing all preset nodes;
s2, acquiring preset nodes and all taxi data; acquiring the stored preset nodes and all taxi travel data of Fuzhou city in the last week;
s3, classifying the taxi data according to the time period; classifying the taxi data according to date and time period, such as working day, non-working day, peak time of commuting, day, night, morning and the like;
s4, obtaining path information of the taxi passing through the preset node in a time period; acquiring data of a taxi passing through two adjacent nodes within a time period; processing data of the taxi passing through two adjacent preset nodes in the time period and obtaining path information of the two adjacent preset nodes; recording the path information of the taxi passing through the two adjacent nodes in the time period; for example, data of a certain taxi passing through a park south gate and a park north gate of two adjacent nodes during a working day on-duty peak are obtained and processed, the average speed of the taxi is calculated, and the throughput of the taxi is analyzed to obtain path information between the park south gate and the park north gate; recording the path information of the taxi passing through the adjacent two nodes during the peak period of work and work on the working day;
s5, counting path information sets of all taxies passing through paths between two adjacent nodes in a time period; counting a path information set of all taxis passing through paths between two adjacent nodes in the peak period of work day and work peak;
s6, counting path information sets of all taxis passing through paths between two adjacent nodes in all time periods;
s7, calculating the corresponding weight of the path according to the path information set; for example, the corresponding weight of the path of the taxi passing through the south gate and the north gate of the adjacent node park in the rush hour of working day is calculated as M;
and S8, storing the paths and the weights corresponding to the paths according to time period classification.
Referring to fig. 3, the second embodiment of the present invention is:
a route setting system based on taxi experience data comprises:
the third obtaining module 11 is configured to obtain map data and taxi data, and divide the map into basic grids;
the first selection module 12 is used for obtaining node grids to be selected according to the throughput of basic grid taxis;
a fourth obtaining module 13, configured to obtain map data, and divide the map into grids smaller than the number of basic grids;
the second selection module 14 is configured to obtain a node grid according to the number of node grids to be selected in the grid;
the third selection module 15 is used for obtaining preset nodes according to the node grids and the POI of the map;
a second storage module 16, configured to store a preset node;
the first obtaining module 2 is used for obtaining preset nodes and all taxi data;
the classification module 3 is used for classifying the taxi data according to the time period;
the second obtaining module 4 is configured to obtain path information of the taxi passing through the preset node in a time period; the method comprises the following steps: a fifth obtaining module 41, configured to obtain data that a taxi passes through two adjacent nodes within a time period; the processing module 42 is configured to process data of the taxi passing through two adjacent preset nodes in the time period and obtain path information of the two adjacent preset nodes; the recording module 43 is configured to record path information of the taxi passing through the two adjacent nodes within the time period;
the first statistical module 5 is used for counting a path information set of all taxis passing through paths between two adjacent nodes in a time period;
the second statistical module 6 is used for counting the path information sets of all taxis passing through the paths between the two adjacent nodes in all time periods;
the calculating module 7 is used for calculating the corresponding weight of the path according to the path information set;
and the first storage module 8 is configured to store the paths and the weights corresponding to the paths according to time period classification.
In the scheme, the paths stored according to the time period classification and the weights corresponding to the paths are applied to a navigation system, the navigation system matches nodes according to the current position and the target position of a user, and then selects the optimal navigation route according to the paths between the matched nodes and the weights corresponding to the paths, but the application of the scheme is not limited to the navigation system.
In summary, according to the route setting method and system based on taxi experience data provided by the invention, the third obtaining module obtains the map data and the taxi data, and divides the map into the basic grids; the first selection module obtains node grids to be selected according to the basic grids with less taxi throughput; the fourth acquisition module, the second selection module and the third selection module obtain preset nodes with reasonable density and proper positions according to the grid distribution condition of the nodes to be selected and the POI of the map; the second storage module stores preset nodes; the method comprises the steps that a first obtaining module obtains preset nodes and all taxi data; the system comprises a classification module, a second acquisition module, a first statistic module and a second statistic module, wherein the classification module, the second acquisition module, the first statistic module and the second statistic module are used for counting the path information of all taxis passing through two adjacent nodes according to a time period; calculating the corresponding weight of the path according to the path information set through a calculation module; each weight reflects path information, each path can obtain road conditions through weight calculation, and the first storage module stores the paths and the weights corresponding to the paths according to time period classification and provides data for route navigation.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (2)
1. A reliable navigation path setting method based on taxi experience data is characterized by comprising the following steps:
acquiring preset nodes and all taxi data;
classifying the taxi data according to time periods;
acquiring path information of the taxi passing through the preset node in a time period;
counting a path information set of all taxis passing through paths between two adjacent preset nodes in a time period;
counting path information sets of all taxis passing through paths between two adjacent preset nodes in all time periods;
calculating the corresponding weight of the path according to the path information set;
classifying and storing the paths and the weights corresponding to the paths according to time periods;
the specific presetting step of the preset node is as follows:
obtaining map data and taxi data, and dividing the map into basic grids;
obtaining node grids to be selected according to the throughput of basic grid taxis;
obtaining map data, and dividing a map into grids with the number less than that of basic grids;
obtaining node grids according to the number of the node grids to be selected in the grids;
obtaining preset nodes according to the node grids and POI of the map;
the step of obtaining the path information of the taxi passing through the preset node in a certain time period specifically comprises the following steps:
acquiring data of a taxi passing through two adjacent preset nodes within a time period;
processing data of the taxi passing through two adjacent preset nodes in the time period and obtaining path information of the two adjacent preset nodes; the specific steps of obtaining the preset nodes according to the POI of the node grids and the map are as follows:
taking the central position of a road in a node grid with the POI number smaller than 1 as a preset node;
taking the POI in the node grid with the number of the POI equal to 1 as a preset node;
and taking the POI closest to the center position of the node grid in the node grid with the POI number larger than 1 as a preset node.
2. The method for setting the reliable navigation path based on the taxi experience data as claimed in claim 1, wherein the step of obtaining the node grids according to the number of the node grids to be selected in the grids specifically comprises the steps of:
taking the grids with the number of the node grids to be selected equal to 1 as node grids;
quartering grids with the number of the node grids to be selected larger than 1 for a preset number of times;
and taking the node grid to be selected with the maximum taxi throughput in the grids divided by four times into the preset number of times as the node grid.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711069146.1A CN108051011B (en) | 2015-07-27 | 2015-07-27 | Reliable navigation path setting method based on taxi experience data |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510444191.5A CN105067001B (en) | 2015-07-27 | 2015-07-27 | Path setting method and system based on taxi empirical data |
| CN201711069146.1A CN108051011B (en) | 2015-07-27 | 2015-07-27 | Reliable navigation path setting method based on taxi experience data |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510444191.5A Division CN105067001B (en) | 2015-07-27 | 2015-07-27 | Path setting method and system based on taxi empirical data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108051011A CN108051011A (en) | 2018-05-18 |
| CN108051011B true CN108051011B (en) | 2020-10-23 |
Family
ID=54496427
Family Applications (4)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711069859.8A Active CN108088452B (en) | 2015-07-27 | 2015-07-27 | Path weight obtaining method |
| CN201510444191.5A Active CN105067001B (en) | 2015-07-27 | 2015-07-27 | Path setting method and system based on taxi empirical data |
| CN201711069146.1A Active CN108051011B (en) | 2015-07-27 | 2015-07-27 | Reliable navigation path setting method based on taxi experience data |
| CN201711069850.7A Active CN108020235B (en) | 2015-07-27 | 2015-07-27 | Method and system for dynamically acquiring path weight based on taxi experience data |
Family Applications Before (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711069859.8A Active CN108088452B (en) | 2015-07-27 | 2015-07-27 | Path weight obtaining method |
| CN201510444191.5A Active CN105067001B (en) | 2015-07-27 | 2015-07-27 | Path setting method and system based on taxi empirical data |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711069850.7A Active CN108020235B (en) | 2015-07-27 | 2015-07-27 | Method and system for dynamically acquiring path weight based on taxi experience data |
Country Status (1)
| Country | Link |
|---|---|
| CN (4) | CN108088452B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI646495B (en) * | 2017-07-31 | 2019-01-01 | 元智大學 | Route planning system for looking for passenger using for taxi and carsharing and method thereof |
| CN108985506A (en) * | 2018-07-03 | 2018-12-11 | 蔚来汽车有限公司 | Planning driving path recommended method, prediction technique, acquisition methods and its device |
| CN111832768A (en) * | 2019-08-13 | 2020-10-27 | 北京嘀嘀无限科技发展有限公司 | POI feature generation method and device, electronic equipment and storage medium |
| JP6810978B1 (en) * | 2020-03-16 | 2021-01-13 | 株式会社ピース企画 | Cluster generator, cluster generation method and cluster generation program |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19954971A1 (en) * | 1999-11-16 | 2001-06-07 | Daimler Chrysler Ag | System, for affecting vehicle traffic flow, uses traffic position detectors to record and transmit data indicating traffic positions to a computer-aided traffic central office prior to its analysis regarding effect on traffic flow |
| CN101364345A (en) * | 2008-09-25 | 2009-02-11 | 北京航天智通科技有限公司 | Real-time dynamic information processing method based on car detecting technique |
| CN102110364A (en) * | 2009-12-28 | 2011-06-29 | 日电（中国）有限公司 | Traffic information processing method and traffic information processing device based on intersections and sections |
| CN103218915A (en) * | 2013-03-05 | 2013-07-24 | 中山大学 | Experience route generation method based on probe vehicle data |
| CN103218672A (en) * | 2013-03-24 | 2013-07-24 | 吉林大学 | Taxi cruising action analytical method based on global position system (GPS) data grid statistic |
| CN103646560A (en) * | 2013-11-27 | 2014-03-19 | 福建工程学院 | Extraction method of taxi driving track experience knowledge paths |
| 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 |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002039775A (en) * | 2000-07-28 | 2002-02-06 | Neutral Corp | Traveling system for servicing vehicle |
| JP2002269669A (en) * | 2001-03-09 | 2002-09-20 | Matsushita Electric Ind Co Ltd | Fcd collection system, fcd collection method, and device thereof |
| US7188026B2 (en) * | 2003-05-12 | 2007-03-06 | Dash Navigation, Inc. | Hierarchical floating car data network |
| CN101373559B (en) * | 2007-08-24 | 2010-08-18 | 同济大学 | Method for evaluating city road net traffic state based on floating vehicle data |
| CN101908276A (en) * | 2010-07-29 | 2010-12-08 | 北京世纪高通科技有限公司 | Method and device for evaluating traffic information |
| CN102063793B (en) * | 2011-01-12 | 2012-10-31 | 上海炬宏信息技术有限公司 | Road condition information detection method and system |
| CN102110363B (en) * | 2011-03-30 | 2013-07-10 | 北京世纪高通科技有限公司 | Floating vehicle data processing method and device |
| CN103632540B (en) * | 2012-08-20 | 2015-11-25 | 同济大学 | Based on the major urban arterial highway traffic circulation information processing method of floating car data |
| CN103531023B (en) * | 2013-10-18 | 2016-01-20 | 北京世纪高通科技有限公司 | A kind of data processing method and device |
-
2015
- 2015-07-27 CN CN201711069859.8A patent/CN108088452B/en active Active
- 2015-07-27 CN CN201510444191.5A patent/CN105067001B/en active Active
- 2015-07-27 CN CN201711069146.1A patent/CN108051011B/en active Active
- 2015-07-27 CN CN201711069850.7A patent/CN108020235B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19954971A1 (en) * | 1999-11-16 | 2001-06-07 | Daimler Chrysler Ag | System, for affecting vehicle traffic flow, uses traffic position detectors to record and transmit data indicating traffic positions to a computer-aided traffic central office prior to its analysis regarding effect on traffic flow |
| CN101364345A (en) * | 2008-09-25 | 2009-02-11 | 北京航天智通科技有限公司 | Real-time dynamic information processing method based on car detecting technique |
| CN102110364A (en) * | 2009-12-28 | 2011-06-29 | 日电（中国）有限公司 | Traffic information processing method and traffic information processing device based on intersections and sections |
| CN103218915A (en) * | 2013-03-05 | 2013-07-24 | 中山大学 | Experience route generation method based on probe vehicle data |
| CN103218672A (en) * | 2013-03-24 | 2013-07-24 | 吉林大学 | Taxi cruising action analytical method based on global position system (GPS) data grid statistic |
| CN103646560A (en) * | 2013-11-27 | 2014-03-19 | 福建工程学院 | Extraction method of taxi driving track experience knowledge paths |
| 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 |
Non-Patent Citations (6)
| Title |
|---|
| Taxi-aware map: Identifying and predicting vacant taxis in the city;Phithakkitnukoon S.等;《International Joint Conference on Ambient Intelligence》;20101231;第86-95页 * |
| 出租车经验知识建模与路径规划算法;唐炉亮 等;《测绘学报》;20100831;第39卷(第04期);第404-409页 * |
| 基于浮动车数据的实时交通状态估计;江波;《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》;20120415(第04期);第C034-717页 * |
| 基于浮动车数据的道路单向限行状态动态识别;蒋新华 等;《计算机应用》;20130601;第33卷(第06期);第1759-1762+1766页 * |
| 浮动车地图匹配算法研究;王美玲 等;《测绘学报》;20120228;第41卷(第01期);第133-138页 * |
| 融合出租车驾驶经验的层次路径规划方法;胡继华 等;《交通运输系统工程与信息》;20130228;第13卷(第01期);第189-196页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108088452A (en) | 2018-05-29 |
| CN108051011A (en) | 2018-05-18 |
| CN108088452B (en) | 2020-08-18 |
| CN108020235A (en) | 2018-05-11 |
| CN105067001B (en) | 2017-11-24 |
| CN105067001A (en) | 2015-11-18 |
| CN108020235B (en) | 2020-10-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105677804B (en) | Method and device for determining authoritative site and establishing database of authoritative site | |
| CN108564226B (en) | Bus route optimization method based on taxi GPS and mobile phone signaling data | |
| CN104167092B (en) | A kind of method determining center, on-board and off-board hot spot region of hiring a car and device | |
| CN103035123B (en) | Abnormal data acquisition methods and system in a kind of traffic track data | |
| US11403938B2 (en) | Method for determining traffic metrics of a road network | |
| US10489431B2 (en) | Digital location-based data methods and product | |
| CN108051011B (en) | Reliable navigation path setting method based on taxi experience data | |
| WO2021082464A1 (en) | Method and device for predicting destination of vehicle | |
| CN107403550B (en) | Public transport road network data acquisition method and device and terminal equipment | |
| US20200279491A1 (en) | Methods and systems for spatial clustering based on mobility data | |
| CN105632222A (en) | Method and system for predicting station arrival time | |
| CN108573604A (en) | Public transport OD data capture methods based on mobile terminal location and storage medium | |
| WO2016123867A1 (en) | Method and device for position search cognition | |
| CN110362640B (en) | Task allocation method and device based on electronic map data | |
| KR101206570B1 (en) | Apparatus and method for generating a road map | |
| US20210156696A1 (en) | Method and system to validate road signs | |
| US10460410B1 (en) | Location services platform, apparatus and method for informing law enforcement personnel placement | |
| CN109520499B (en) | Method for realizing regional real-time isochrones based on vehicle GPS track data | |
| CN112579915B (en) | Analysis method and device for trip chain | |
| CN113888867A (en) | Parking space recommendation method and system based on LSTM position prediction | |
| CN113160542A (en) | Riding method and device based on information feedback | |
| CN110986992A (en) | Navigation method and device for unmanned vending vehicle, electronic equipment and storage medium | |
| US20200278214A1 (en) | Method, system, and computer program product for generating synthetic demand data of vehicle rides | |
| Elleuch et al. | Collection and exploration of GPS based vehicle traces database | |
| CN115129769A (en) | Resident travel survey sample expansion method and device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |