CN107633374A - It is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method - Google Patents
It is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method Download PDFInfo
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Abstract
The invention discloses it is a kind of can the vehicle of self-teaching include on way station acquisition density intelligence adaptive method, including vehicle and location application server, the vehicle：Position positioning terminal, wireless communication module, authentication module, the location application server include：Locating module, data collection module, strategy analysis module, self-optimization module, standard strategy storehouse, wireless receiving module, data memory module, display module, enquiry module, the vehicle pass through wireless connection with the location application server.
Description
Technical field
The present invention relates to logistics transportation field, and in particular to it is a kind of can self-teaching vehicle in way station acquisition density intelligence
Adapt to method.
Background technology：
With the development of logistic industry, the travelling speed of logistics is more and more faster, therefore the also more and more higher of the requirement to positioning,
It using a kind of positioning method and time for refreshing is also fixed that logistic industry of today, which apart from length is all, for short
The positioning requirements of distance can be positioned more accurately, and positioned and can suitably be loosened over long distances, but the length of judging distance
If it is short using think calculate efficiency it is too low, and according to transport vehicle speed speed, the time used in same distance is also different,
Therefore needing to design a kind of algorithm of optimization voluntarily to judge.
Such as Chinese Patent Application No.：201210329789.6 a kind of Vehicle positioning system is disclosed, including base in RFID rooms
Stand, GPS positioning unit, car-mounted terminal, phonetic synthesis unit, visual element, RFID indoor base stations, the vehicle are installed indoors
The internal field positioning of alignment system triggers RFID technique using low frequency, and GPS positioning unit is housed on car, and work(is positioned when being provided with internal field
The vehicle of the car-mounted terminal of energy is waken up when getting in base station area, and the RSSI value of its each passage is issued into car-mounted terminal,
Calculated by the car-mounted terminal and be converted into the longitude and latitude data format mutually compatible with GPS location subsystem in way, and set GIS
Visual techniques, user is intuitively shown to, while by speech synthesis technique, carries out internal field guiding；Whole system using 3G with
Center to center communications.Vehicle positioning system of the present invention, the positioning of RFID internal fields and the interior outfield of GPS location in way are triggered using low frequency
Integration technology, the purpose of vehicle indoor and outdoor full process positioning is realized, the positioning and whole process for facilitating vehicle are dispatched, but this kind
Positioning method does not carry out optimum position using corresponding algorithm.
Chinese Patent Application No.：201610228374.8 disclose a kind of density peak cluster based on degree adaptive distance
Algorithm, mainly solve the problems, such as that the density peak clustering algorithm based on Euclidean distance can not effectively handle complex types of data collection.It is real
Now process is：(1) Euclidean distance and adaptive Similarity Measure degree adaptive distance are based on, preferably to describe data space
Distributed architecture；(2) degree adaptive distance is based on, the ratio value of data set total sample number is accounted for according to the neighbours of data point point sum
The input parameter of computational algorithm, that is, block distance；(3) basis blocks distance and degree adaptive distance calculates each data point
Local density and the point draw decision diagram, choose cluster centre to the beeline with Geng Gao local densities point；(4) will be surplus
Under each point be assigned to cluster belonging to the nearest neighbor point with Geng Gao local densities, obtain cluster result.In artificial data collection
Show with the experiment on UCI True Data collection, compared with the density peak clustering algorithm based on Euclidean distance, the present invention can not only
Effectively processing complex types of data collection, and there is higher accuracy rate, the density clustering algorithm of this kind of degree adaptive distance,
It is the algorithm for solving distance, can not applies it in this kind of positioning method.
The content of the invention
It is an object of the invention to provide it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method,
To solve caused above-mentioned multinomial defect in the prior art.
It is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, including vehicle and location application clothes
It is engaged in device, includes on the vehicle：
Position positioning terminal：Vehicle interior is arranged to position vehicle for location application server；
Wireless communication module：Handled for information periodically to be sent to location application server, take location application
Business device can be analyzed and positioned to the positional information of vehicle；
Authentication module：The personal information and information of vehicles of driver is included by APP, facilitates user to check；
The location application server includes：
Locating module：Inside is provided with station acquisition program, for the collection of the position data of vehicle, while to the position of vehicle
Put and carry out contrast confirmation, positioning method includes GPS location and the Big Dipper positions；
Data collection module：It is divided into PC computers collection mode and standard interface collection mode, for collecting cargo type, industry
The type of service type, user's custom and vehicle；
Strategy analysis module：Inside be provided with analysis of strategies program, to be collected into collection module cargo type, service class
Type and user's habits information do Macro or mass analysis and processing, analyze the path length of dispatching, for different types of service and user
Custom formulates different path policy, and distribution time is calculated according to the type of the length in path and vehicle, according to dispatching away from
Discrete time determines that vehicle periodically sends the time interval of positional information, and distance more short time interval is shorter；
Self-optimization module：Inside is provided with self-optimization program, further right according to the analysis result of strategy analysis module
Path policy is optimized, and most suitable strategy protocol is selected from numerous policy informations；
Standard strategy storehouse：For the rule of path division, locating periodically is determined according to the length in path, when path is shorter
When, due to positioning, to change big therefore locating periodically short, during path length, positioning change it is small and if frequently positioning can consume it is very big
Resource therefore grow by locating periodically, makes strategy analysis module have foundation to follow, and can accelerate the efficiency of analysis；
Wireless receiving module：The data sended over for receiving wireless communication module, and transfer data to strategy point
Analyzed and processed in analysis module；
Data memory module：For the information after the completion of strategy analysis module resume module to be carried out into storage encryption, and
The information result that will be stored before storage is sent to locating module, makes to form positioning strategy information in locating module, facilitates it to do
Positioning contrast；
Display module：For showing the information after the completion of the information of stored mistake or display information processing module, goods
Thing information, positional information, and can situation of the real-time display goods in map；
Enquiry module：Shown for inquiring about the situation of goods, and by result in display module；
The vehicle passes through wireless connection with the location application server.
Preferably, the type of the vehicle is provided with rank not of the same race, rank according to the size of vehicle and the speed of speed
Higher dispatching speed is faster, and efficiency is higher, and cost is also high.
Preferably, the standard of the vehicle divided rank is that the identical faster higher grade of volume of freight speed, under identical speed
Cargo transport is more, and higher grade.
Preferably, the positioning method also has architecture, hand of the architecture using the base station around driver to driver
Machine is positioned.
Preferably, the grade of the Distribution path is that city distribution is A levels by advanced to rudimentary dividing condition, short-distance transport
For B levels, short-distance transport is C levels, and midway transport is D levels, is transported for long-distance as E levels.
Preferably, the cargo type information includes type of merchandize, weight, volume, quantity, origin and destination.
Preferably, the Distribution path according to distance from short to long by Distribution path be divided into city distribution, short-distance transport,
Short-distance transport, midway are transported and long-distance transport, and the distance of city distribution is in the kilometer range of radius 50 or affiliated same
In city, the distance of short-distance transport is 50 kilometers to 200 kilometers, and the distance of short-distance transport is 200 kilometers to 500 kilometers, in
The distance of way transport is 500 kilometers to 1000 kilometers, and the distance of long-distance transport is more than 1000 kilometers.
Preferably, the result of the strategy analysis module analysis can also be manually adjusted.
Preferably, it is described it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, it operates step
Suddenly it is：
1) user fills in the weight of goods for needing to send, volume, quantity, originated in cell phone application or on PC computers
Ground, destination, the information of type of vehicle and positioning method type；
2) data that data collection module is filled in from computer or by standard interface reading user, including goods class
Type, type of service, user's custom and type of vehicle and positioning method；
3) strategy analysis module goes out the path of dispatching according to the information analysis on data collection module, is divided according to path
Grade, type of service, user's custom, analyze effective path policy, then operation according to the analysis rule in standard strategy storehouse
Personnel are confirmed whether rationally, to be manually adjusted if unreasonable, are then calculated according to type of vehicle and positioning method type
Go out ultimate cost and result be presented into user to confirm；
4) user can view giving a present personal information, information of vehicles and matching somebody with somebody for goods for dispatching driver on APP after confirming
Condition.
The advantage of the invention is that：This kind can self-teaching vehicle in way station acquisition density intelligence adaptive method, can
To select corresponding type of vehicle and positioning method type according to user's request, user is extracted by cell phone application or computer and filled out
The information write, the grade in path and corresponding expense are judged according to user profile and cartographic information, positioned so as to draw
The time interval positioned in journey, it is possible thereby to the dispatching situation of vehicle is monitored in real time, and vehicle is provided with authentication module, can
To be supplied to user, allow user to learn the personal information and information of vehicles of the driver of dispatching, user can be allowed to feel at ease.
Brief description of the drawings
Fig. 1 is the flow chart of method in the present invention.
Fig. 2 is the internal module block diagram of vehicle in the present invention.
Fig. 3 is the internal module block diagram of position application server in the present invention.
Embodiment
To be easy to understand the technical means, the inventive features, the objects and the advantages of the present invention, with reference to
Embodiment, the present invention is expanded on further.
As shown in Figure 1 to Figure 3, it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, including
Vehicle and location application server, include on the vehicle：
Position positioning terminal：Vehicle interior is arranged to position vehicle for location application server；
Wireless communication module：Handled for information periodically to be sent to location application server, take location application
Business device can be analyzed and positioned to the positional information of vehicle, can be by the letter of the information and vehicle of location information and driver
Breath is sent to location application server, location application server is understood the information of vehicle in real time；
Authentication module：The personal information and information of vehicles of driver is included by APP, facilitates user to check；
The location application server includes：
Locating module：Inside is provided with station acquisition program, for the collection of the position data of vehicle, while to the position of vehicle
Put and carry out contrast confirmation, positioning method includes GPS location and the Big Dipper positions；
Data collection module：It is divided into PC computers collection mode and standard interface collection mode, for collecting cargo type, industry
The type of service type, user's custom and vehicle；
Strategy analysis module：Inside be provided with analysis of strategies program, to be collected into collection module cargo type, service class
Type and user's habits information do Macro or mass analysis and processing, analyze the path length of dispatching, for different types of service and user
Custom formulates different path policy, and distribution time is calculated according to the type of the length in path and vehicle, according to dispatching away from
Discrete time determines that vehicle periodically sends the time interval of positional information, and distance more short time interval is shorter；
Self-optimization module：Inside is provided with self-optimization program, further right according to the analysis result of strategy analysis module
Path policy is optimized, and most suitable strategy protocol is selected from numerous policy informations；
Standard strategy storehouse：For the rule of path division, locating periodically is determined according to the length in path, when path is shorter
When, due to positioning, to change big therefore locating periodically short, during path length, positioning change it is small and if frequently positioning can consume it is very big
Resource therefore grow by locating periodically, makes strategy analysis module have foundation to follow, and can accelerate the efficiency of analysis；
Wireless receiving module：The data sended over for receiving wireless communication module, and transfer data to strategy point
Analyzed and processed in analysis module；
Data memory module：For the information after the completion of strategy analysis module resume module to be carried out into storage encryption, and
The information result that will be stored before storage is sent to locating module, makes to form positioning strategy information in locating module, facilitates it to do
Positioning contrast, either after the completion of order or ongoing order be required for storing in real time, have data certain
Integrality, just in case occur surprisingly connect in time, and data, which are encrypted, prevents other staff from deleting or distorting
Order data, cause unexpected consequence；
Display module：For showing the information after the completion of the information of stored mistake or display information processing module, goods
Thing information, positional information, and can situation of the real-time display goods in map；
Enquiry module：Shown for inquiring about the situation of goods, and by result in display module；
The vehicle passes through wireless connection with the location application server.
It is worth noting that, the type of the vehicle is provided with level not of the same race according to the size of vehicle and the speed of speed
Not, the higher dispatching speed of rank is faster, and efficiency is higher, and cost is also high, and user can make a choice according to the needs of itself, simultaneously
Also need payment expense.
In the present embodiment, the standard of the vehicle divided rank is that the identical faster higher grade of volume of freight speed, identical
Being freighted under speed, much higher grades, and travelling speed is faster for transport, and efficiency is higher, and caused expense is also higher,
And in the case where identical dispenses speed, cargo transport is more, and efficiency is also higher.
In the present embodiment, the positioning method also has architecture, and architecture is using the base station around driver to department
The mobile phone of machine is positioned.
In the present embodiment, the grade of the Distribution path is that city distribution is A levels by advanced to rudimentary dividing condition, short
Way transport is B levels, and short-distance transport is C levels, and midway transport is D levels, is transported for long-distance as E levels.
In the present embodiment, the cargo type information includes type of merchandize, weight, volume, quantity, origin and purpose
Ground.
In the present embodiment, Distribution path is divided into city distribution, short by the Distribution path from short to long according to distance
Way transport, short-distance transport, midway is transported and long-distance transport, and the distance of city distribution is in the kilometer range of radius 50 or affiliated
In same city, the distance of short-distance transport is 50 kilometers to 200 kilometers, and the distance of short-distance transport is public for 200 kilometers to 500
In, the distance of midway transport is 500 kilometers to 1000 kilometers, and the distance of long-distance transport is more than 1000 kilometers.
In the present embodiment, the result of the strategy analysis module analysis can also be manually adjusted.
In addition, it is described it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its operating procedure
For：
1) user fills in the weight of goods for needing to send, volume, quantity, originated in cell phone application or on PC computers
Ground, destination, the information of type of vehicle and positioning method type；
2) data that data collection module is filled in from computer or by standard interface reading user, including goods class
Type, type of service, user's custom and type of vehicle and positioning method；
3) strategy analysis module goes out the path of dispatching according to the information analysis on data collection module, is divided according to path
Grade, type of service, user's custom, analyze effective path policy, then operation according to the analysis rule in standard strategy storehouse
Personnel are confirmed whether rationally, to be manually adjusted if unreasonable, are then calculated according to type of vehicle and positioning method type
Go out ultimate cost and result be presented into user to confirm；
4) user can view giving a present personal information, information of vehicles and matching somebody with somebody for goods for dispatching driver on APP after confirming
Condition.
As known by the technical knowledge, the present invention can pass through the embodiment party of other essence without departing from its spirit or essential feature
Case is realized.Therefore, embodiment disclosed above, for each side, all it is merely illustrative, is not only.Institute
Have within the scope of the present invention or be included in the invention in the change being equal in the scope of the present invention.
Claims (9)
1. it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, including vehicle and location application service
Device, it is characterised in that include on the vehicle：
Position positioning terminal：Vehicle interior is arranged to position vehicle for location application server；
Wireless communication module：Handled for sending information to location application server, enable location application server
The positional information of vehicle is analyzed and positioned；
Authentication module：The personal information and information of vehicles of driver is included by APP, facilitates user to check；
The location application server includes：
Locating module：Inside is provided with station acquisition program, enters for the collection of the position data of vehicle, while to the position of vehicle
Row contrast confirms that positioning method includes GPS location and the Big Dipper positions；
Data collection module：It is divided into PC computers collection mode and standard interface collection mode, for collecting cargo type, service class
The type of type, user's custom and vehicle；
Strategy analysis module：Inside be provided with analysis of strategies program, to be collected into collection module cargo type, type of service and
User's habits information does Macro or mass analysis and processing, analyzes the path length of dispatching, is accustomed to for different types of service and user
Formulate different path policies, distribution time calculated according to the type of the length in path and vehicle, according to dispatching distance and
Time determines that vehicle periodically sends the time interval of positional information, and distance more short time interval is shorter；
Self-optimization module：Inside is provided with self-optimization program, according to the analysis result of strategy analysis module, further to path
Strategy is optimized, and most suitable strategy protocol is selected from numerous policy informations；
Standard strategy storehouse：For the rule of path division, locating periodically is determined according to the length in path, when path is shorter,
Due to positioning, to change big therefore locating periodically short, and during path length, positioning changes that small and if frequently positioning can consume very big money
Therefore locating periodically is grown in source, makes strategy analysis module have foundation to follow, and can accelerate the efficiency of analysis；
Wireless receiving module：The data sended over for receiving wireless communication module, and transfer data to analysis of strategies mould
Analyzed and processed in block；
Data memory module：For the information after the completion of strategy analysis module resume module to be carried out into storage encryption, and storing
Before the information result that will store be sent to locating module, make to form positioning strategy information in locating module, facilitate it to position
Contrast；
Display module：For showing the information after the completion of the information of stored mistake or display information processing module, goods letter
Breath, positional information, and can situation of the real-time display goods in map；
Enquiry module：Shown for inquiring about the situation of goods, and by result in display module；
The vehicle passes through wireless connection with the location application server.
2. it is according to claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its
It is characterised by：The type of the vehicle is provided with rank not of the same race according to the size of vehicle and the speed of speed, and rank is higher to match somebody with somebody
Send speed faster, efficiency is higher, and cost is also high.
3. it is according to claim 2 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its
It is characterised by：The standard of the vehicle divided rank is that the identical faster higher grade of volume of freight speed, freights and gets under identical speed
Few higher grade.
4. it is according to claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its
It is characterised by：The positioning method also has architecture, and architecture is carried out using the base station around driver to the mobile phone of driver
Positioning.
5. it is according to claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its
It is characterised by：The grade of the Distribution path is that city distribution is A levels by advanced to rudimentary dividing condition, and short-distance transport is B levels,
Short-distance transport is C levels, and midway transport is D levels, is transported for long-distance as E levels.
6. it is according to claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method, its
It is characterised by：The cargo type information includes type of merchandize, weight, volume, quantity, origin and destination.
7. according to described in claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method,
It is characterized in that：The Distribution path according to distance from short to long by Distribution path be divided into city distribution, short-distance transport, in it is short
Way transport, midway are transported and long-distance transport, and the distance of city distribution is in the kilometer range of radius 50 or affiliated same city
Interior, the distance of short-distance transport is 50 kilometers to 200 kilometers, and the distance of short-distance transport is 200 kilometers to 500 kilometers, and midway is transported
Defeated distance is 500 kilometers to 1000 kilometers, and the distance of long-distance transport is more than 1000 kilometers.
8. according to described in claim 1 it is a kind of can self-teaching vehicle in way station acquisition density intelligence adaptive method,
It is characterized in that：The result of the strategy analysis module analysis can also be manually adjusted.
9. according to claim 1-8 any one can self-teaching vehicle way station acquisition density intelligence adaptation side
Method, its operating procedure are：
1) user fills in the weight of goods for needing to send, volume, quantity, origin, mesh in cell phone application or on PC computers
Ground, the information of type of vehicle and positioning method type；
2) data that data collection module is filled in from computer or by standard interface reading user, including cargo type, industry
Service type, user's custom and type of vehicle and positioning method；
3) strategy analysis module goes out the path of dispatching according to the information analysis on data collection module, according to path divide etc.
Level, type of service, user's custom, effective path policy, subsequent operator are analyzed according to the analysis rule in standard strategy storehouse
Member is confirmed whether rationally, to be manually adjusted if unreasonable, then calculated according to type of vehicle and positioning method type
Result is simultaneously presented to user's confirmation by ultimate cost；
4) user can view the dispatching situation of the personal information for dispensing driver, information of vehicles and goods on APP after confirming.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109255574A (en) * | 2018-09-21 | 2019-01-22 | 北京智行者科技有限公司 | logistics distribution method and system |
| CN116839596A (en) * | 2023-09-01 | 2023-10-03 | 矽佳半导体(嘉兴)有限公司 | Intelligent tracking and positioning system based on data analysis |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100082238A1 (en) * | 2006-05-16 | 2010-04-01 | Aisin Aw Co., Ltd. | Vehicle positioning information update device |
| CN105223593A (en) * | 2015-09-17 | 2016-01-06 | 北京奇虎科技有限公司 | Terminal positioning frequency adjustment method, system and positioning interval control method, system |
| CN105786150A (en) * | 2014-12-22 | 2016-07-20 | 联想(北京)有限公司 | Information processing method and electronic device |
| CN205541419U (en) * | 2016-02-01 | 2016-08-31 | 刘超 | Operation vehicle automobile -mounted terminal and supervisory systems based on identification |
| CN106548320A (en) * | 2016-12-27 | 2017-03-29 | 青岛市光电工程技术研究院 | A kind of Big Dipper carries logistics platform without car with city |
| CN206061152U (en) * | 2016-09-29 | 2017-03-29 | 神州伟智（天津）科技有限公司 | A kind of running fix data delay reporting system |
| CN106842259A (en) * | 2017-01-06 | 2017-06-13 | 宇龙计算机通信科技(深圳)有限公司 | Localization method and positioner |
| CN107085777A (en) * | 2017-04-13 | 2017-08-22 | 合肥市群智科技有限公司 | A kind of live tracking of logistics goods and device |
-
2017
- 2017-09-07 CN CN201710800904.6A patent/CN107633374A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100082238A1 (en) * | 2006-05-16 | 2010-04-01 | Aisin Aw Co., Ltd. | Vehicle positioning information update device |
| CN105786150A (en) * | 2014-12-22 | 2016-07-20 | 联想(北京)有限公司 | Information processing method and electronic device |
| CN105223593A (en) * | 2015-09-17 | 2016-01-06 | 北京奇虎科技有限公司 | Terminal positioning frequency adjustment method, system and positioning interval control method, system |
| CN205541419U (en) * | 2016-02-01 | 2016-08-31 | 刘超 | Operation vehicle automobile -mounted terminal and supervisory systems based on identification |
| CN206061152U (en) * | 2016-09-29 | 2017-03-29 | 神州伟智（天津）科技有限公司 | A kind of running fix data delay reporting system |
| CN106548320A (en) * | 2016-12-27 | 2017-03-29 | 青岛市光电工程技术研究院 | A kind of Big Dipper carries logistics platform without car with city |
| CN106842259A (en) * | 2017-01-06 | 2017-06-13 | 宇龙计算机通信科技(深圳)有限公司 | Localization method and positioner |
| CN107085777A (en) * | 2017-04-13 | 2017-08-22 | 合肥市群智科技有限公司 | A kind of live tracking of logistics goods and device |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109255574A (en) * | 2018-09-21 | 2019-01-22 | 北京智行者科技有限公司 | logistics distribution method and system |
| CN109255574B (en) * | 2018-09-21 | 2021-07-23 | 北京智行者科技有限公司 | Logistics distribution method and system |
| CN116839596A (en) * | 2023-09-01 | 2023-10-03 | 矽佳半导体(嘉兴)有限公司 | Intelligent tracking and positioning system based on data analysis |
| CN116839596B (en) * | 2023-09-01 | 2023-11-14 | 矽佳半导体(嘉兴)有限公司 | Intelligent tracking and positioning system based on data analysis |
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