CN109191906A - A kind of parking lot distributed intelligence guidance system and method - Google Patents
A kind of parking lot distributed intelligence guidance system and method Download PDFInfo
- Publication number
- CN109191906A CN109191906A CN201811338514.2A CN201811338514A CN109191906A CN 109191906 A CN109191906 A CN 109191906A CN 201811338514 A CN201811338514 A CN 201811338514A CN 109191906 A CN109191906 A CN 109191906A
- Authority
- CN
- China
- Prior art keywords
- module
- parking
- vehicle
- parking lot
- information
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000012544 monitoring process Methods 0.000 claims abstract description 54
- 230000002265 prevention Effects 0.000 claims abstract description 9
- 238000004422 calculation algorithm Methods 0.000 claims description 29
- 238000013439 planning Methods 0.000 claims description 14
- 238000011160 research Methods 0.000 claims description 10
- 201000004569 Blindness Diseases 0.000 claims description 8
- 238000012423 maintenance Methods 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 7
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 6
- 229910052744 lithium Inorganic materials 0.000 claims description 6
- 230000001681 protective effect Effects 0.000 claims description 6
- 230000009467 reduction Effects 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 4
- 238000005457 optimization Methods 0.000 claims description 4
- 241000257303 Hymenoptera Species 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000003869 coulometry Methods 0.000 claims description 3
- 230000006698 induction Effects 0.000 claims description 3
- 239000003016 pheromone Substances 0.000 claims description 3
- 238000001514 detection method Methods 0.000 claims description 2
- 238000012512 characterization method Methods 0.000 claims 1
- 238000000465 moulding Methods 0.000 claims 1
- 230000002159 abnormal effect Effects 0.000 abstract description 4
- 239000011159 matrix material Substances 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000010276 construction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 230000000977 initiatory effect Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
- 230000007306 turnover Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
- G08G1/146—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas where the parking area is a limited parking space, e.g. parking garage, restricted space
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
- G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Finance (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention belongs to parking lot guide technical fields; a kind of parking lot distributed intelligence guidance system and method is disclosed, it includes: video monitoring module, information acquisition module, parking stall monitoring modular, central control module, anti-blocking module, route guidance module, warning module, parking charge module, data protection module, display module that parking lot distributed intelligence, which guides system,.The present invention is able to solve by parking stall monitoring modular, anti-blocking module, route guidance module: dynamic monitoring can be carried out to parking stall, the generation of parking stall problem is fought in prevention;The Parking Fee that no license plate vehicle generates in parking lot is accurately calculated by parking charge module;Solves parking lot when there are the failures such as computer glitch, abnormal power-down, database file damage by data protection module; cause sentry box terminal that cannot normally complete the problem of admission, charge etc. seriously affect the operation of parking lot normal operation, reduces parking lot to greatest extent because of loss caused by failure.
Description
Technical field
The invention belongs to parking lot guide technical field more particularly to a kind of parking lot distributed intelligence guidance system and sides
Method.
Background technique
With China's expanding economy, automobile quantity cumulative year after year.Automobile has been popularized, and parking lot is also towards large size
The trend development of change, many parking lots are all the super-huge parking lot that parking stall number crosses thousand, especially airport, railway station, hospital, surpass
The place of the public gatherings such as city, square, hotel, hotel, amusement park;Large parking lot solves the problems, such as that parking stall is insufficient, but by
Still exist in the problem of necessary truck space guiding system of inner part of parking lot shortage, parking difficulty, vehicle needs after entering parking lot
Long time is wanted to find parking stall, this process consumes a large amount of time and the energy.It even will appear local congestion and part
Idle phenomenon, so that parking stall utilization rate reduces, the essence of problem is that idle parking space information can not be transmitted to vehicle, so that parking
Field can not play its due social and economic effects.However, at present existing stopping guide system general lack of Lighting control,
Region vehicle flowrate control, high construction cost, poor reliability, information publication relatively lag behind, cannot reflect parking space information in field in time
Dynamic change, driver do not know about flow in park state, in parking lot traveling have very big blindness and with
Machine, so that the probability that local congestion occurs becomes larger, to be easy to cause the congestion of parking lot inner region, fight for the problems such as parking stall;
Meanwhile traditional parking mode can not solve the problems, such as the parking charge of no license plate vehicle;If parking lot occur computer glitch,
When the failures such as abnormal power-down, database file damage, data cannot be protected in time, cause heavy losses.
In conclusion problem of the existing technology is:
(1) at present existing stopping guide system general lack of Lighting control, the control of region vehicle flowrate, high construction cost,
Poor reliability, information publication relatively lags behind, cannot reflect the dynamic change of parking space information in field in time, and driver is to parking lot
Wagon flow state is not known about, and traveling has very big blindness and randomness in parking lot, so that the probability that local congestion occurs
Become larger, to be easy to cause the congestion of parking lot inner region, fight for the problems such as parking stall.
(2) parking space state monitoring is fairly perfect, and existing main problem is:
A, vehicle level monitoring system itself is without relevant fault pre-alarming mechanism, i.e., when event occurs in vehicle level monitoring system itself
Barrier, parking lot management personnel can not obtain malfunction in first time and carry out corresponding troubleshooting;This subject study exists
There is partial fault in vehicle level monitoring system, i.e., parking stall monitoring system basic functions it is complete under the premise of issue warning information, notify
Administrative staff carry out necessary maintenance, and vehicle level monitoring system still being capable of normal use before maintenance.
B, lack dynamic parking stall monitoring technology, i.e., vehicle before reaching idle parking stall, do not believe traveling vehicle by system
Breath and parking space information are pre-processed, and are pre-allocated to parking stall, and the generation of parking stall problem is fought in prevention.
(3) the main reason for local congestion generates is:
A, not in time, driver does not know about flow in park state for information transmission between parking lot and vehicle, drives
Personnel travel in parking lot has very big blindness and randomness, so that the probability that local congestion occurs becomes larger;
B, the phychology of comforming on psychology, by analyzing most of drivers in the feelings for not knowing about parking lot real-time status
It under condition, is typically chosen and follows front vehicles, such case further increases the risk probability of local congestion.
(5) traditional parking mode can not solve the problems, such as the parking charge of no license plate vehicle;
It (6), cannot be timely if parking lot is when there are the failures such as computer glitch, abnormal power-down, database file damage
Data are protected, heavy losses are caused.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of parking lot distributed intelligence guidance system and sides
Method.
The invention is realized in this way a kind of parking lot distributed intelligence guides system, the parking lot distributed intelligence
Guidance system includes:
Video monitoring module is connect with central control module, for monitoring parking lot in real time by image pick-up device;
Information acquisition module is connect with central control module, for reading car owner's parking card information by card reader;
Parking stall monitoring modular, connect with central control module, for detecting parking stall changes of magnetic field by geomagnetism detecting device,
When judging parking space state;
Central control module draws with video monitoring module, information acquisition module, parking stall monitoring modular, anti-blocking module, path
Guide module, warning module, parking charge module, data protection module, display module connection, it is each for being controlled by single-chip microcontroller
Module works normally;
Anti-blocking module, connect with central control module, for realizing vehicle point by the research of local congestion prevention algorithm
Stream guidance, reduction parking stall is fought for and the risk probability of local congestion.
Route guidance module is connect with central control module, for the research of passage path guidance planning algorithm, eliminates vehicle
The blindness and randomness of traveling, improve parking stall utilization rate, save corresponding time cost and energy cost for driver,
Realize environmentally protective trip.
Warning module is connect with central control module, for being warned in time by alarm to vehicle trouble;
Parking charge module, connect with central control module, carries out charging for stopping by accounting routine to car owner;
Data protection module is connect with central control module, for being taken by main database server and backup database
Business device backs up monitoring data, user data;
Display module is connect with central control module, for showing monitored picture by display, acquiring in owner information
Hold;
Selftest module is connect with central control module, and can alarm maintenance when going out minor issue for system.
Another object of the present invention is to provide a kind of large sizes for being equipped with the parking lot distributed intelligence guidance system
Shopping plaza parking lot.
Another object of the present invention is to provide a kind of parking lot distributed intelligence bootstrap techniques to include:
Passage path guiding module utilizes Route guiding planning algorithm, carries out parking stall guidance;Route guiding planning algorithm is
Based on the hierarchical algorithms for improving ant colony clustering (Ant Colony Optimization, ACO), the sorting of optimal parking stall is carried out, it is right
Parking stall congestion index carries out automatic cluster, implementation level classification;Index of crowding data point is considered as and has several attributes
Ant, and index of crowding Classification Center is considered as food source will be with n attribute on the basis of clearly classification number M
N number of index of crowding to be analyzed is defined as follows:
X={ Xa|Xa=(xa1,xa2,…,xan), a=1,2, N }
Biased error between different index of crowding is measured with Euclidean distance, apart from smaller, biased error
With regard to smaller;Index of crowding a is distributed into b-th of cluster centreAnt is just in index of crowding sample
A is to cluster centrePath (a, b) on leave pheromones τab(c), it usesIndicate index of crowding XaAnd XbAttribute space
Weighted euclidean distance, pab(c) probability of path (a, b) is selected for ant, calculation formula is as follows:
R is cluster radius in formula,Indicate ant XbAlternative road
Diameter;It is expected β is heuristic factor, characterize ant heuristic information during the motion by attention degree;It is k iteration
Middle index of crowding i is assigned to j-th of cluster centreThe numerical value of heuristic information is determined using the inverse of distance between the two
Justice;Work as pab(c)≥P0When, Xa is integrated into Xb neighborhood;It is crowded included in each class after moving all ants
Degree index will change, then the cluster centre point needs of each class recalculate, and the biased error inside same class also needs
It calculates and updates;Use CbIndicate all cluster sets for being integrated into the field Xi, new cluster centreIt is calculated with biased error E as follows:
In formula, J indicates CbElement number, CabIt indicatesA-th of component;
Meanwhile given maximum iteration maxiter, as long as meeting: 1) the biased error total amount of all classes is less than parameter ε;2) iteration
Number reaches given the number of iterations maximum value, when any condition, then end of clustering, and provide analysis result;Otherwise, it answers
Calculating is re-started, is terminated until meeting condition;
Improved ant colony clustering algorithm is programmed using Matlab tool, solves crowding degree index Critical Grading
Value, process are as follows:
Step 1: the sample size N of index of crowding, maximum number of iterations G, sample size attribute number initiation parameter: are determined
N and initial global information prime matrix;
Step 2: according to global information prime matrix, start to be iterated, determine ant walking path, and be marked;
Step 3: obtaining current cluster centre according to ID of trace route path, and calculates all samples to the inclined of corresponding cluster centre
From error total amount E, minimum biased error E_min is obtained;
Step 4: random number is generated, and thus current optimal path is changed, and calculate all samples under new route
To the biased error total amount E ' of corresponding cluster centre;
Step 5: judging whether E ' is less than E_min, if so, current path is optimal path, directly output is as a result, algorithm
Terminate;If it is not, then carrying out step 6;
Step 6: judging whether current the number of iterations reaches maximum value G, if then directly output is as a result, algorithm terminates;
Otherwise step 2 is returned, next round iteration is carried out.
Further, the parking lot distributed intelligence bootstrap technique specifically includes:
Parking lot is monitored in real time using image pick-up device by video monitoring module;
Car owner's parking card information is read using card reader by information acquisition module;
Parking stall changes of magnetic field is detected using geomagnetism detecting device by parking stall monitoring modular, when judging parking space state;In
Entreat control module to realize vehicle shunting guidance by the research of local congestion prevention algorithm of anti-blocking module, reduce parking stall fight for
The risk probability of local congestion;
Passage path guiding module utilizes Route guiding planning algorithm, carries out parking stall guidance;
Vehicle trouble is warned in time using alarm by warning module;
It is stopped using accounting routine to car owner by parking charge module and carries out charging;
By data protection module using main database server and backup database server to monitoring data, number of users
According to being backed up;
Monitored picture, acquisition owner information content are shown using display by display module;
By selftest module, can alarm maintenance when going out minor issue to system, operate normally system.
Further, the parking stall monitoring module monitors method is as follows:
(1) geomagnetism detecting device detects parking stall changes of magnetic field, when judging that parking space state changes, is drawn by interrupting
Foot wakes up single-chip microcontroller;
(2) single-chip microcontroller control is closed for connecting the electronic switch of lithium Asia battery, and lithium Asia battery is to temperature detector, electricity
Detector power supply;
(3) single-chip microcontroller obtains temperature information from temperature detector, obtains information about power from coulometric detector;
(4) single-chip microcontroller control wireless transmitter externally sends parking space state information, the temperature judged by parking stall changes of magnetic field
Spend information, information about power;
(5) wireless transmitter enters SLLEP state after having sent data, and electronic switch disconnects, and single-chip microcontroller enters suspend mode mould
Formula.
Further, the parking charge module charging method is as follows:
1) when vehicle admission, detect whether the vehicle is no license plate vehicle;
2) if so, requesting and obtaining by charge system distribution for calculating the admission letter without license plate vehicle parking expense
Breath, and the vehicle of the admission information and admission is bound;
3) when vehicle appears on the scene, judge whether the vehicle is no license plate vehicle;
4) if so, obtaining admission information bound in the vehicle of appearance, and the admission information is sent to institute
Charge system is stated to calculate Parking Fee;
The request is simultaneously obtained by charge system distribution for calculating the admission information without license plate vehicle parking expense, and
The vehicle of the admission information and admission, which is carried out binding, includes:
The request of distribution admission information is issued to the charge system;
Obtain the admission information that the charge system is issued according to the request;The admission information includes the vehicle
The entry time of picture, the electronic license plate for distributing to the vehicle and the vehicle;
The vehicle and the admission information are bound;
It is described to obtain admission information bound in the vehicle to appear on the scene, and the admission information is sent to the charging
System includes: to calculate Parking Fee
In control screen display without license plate matched interface;The no license plate matched interface includes whole in parking lot
Picture without license plate vehicle;
Obtain the picture corresponding with the vehicle of appearance chosen in the no license plate matched interface by fee-collector;
The corresponding electronic license plate of the picture and entry time are sent to the charge system to calculate the vehicle
Parking Fee;
The request is simultaneously obtained by charge system distribution for calculating the admission information without license plate vehicle parking expense, and
The admission information, which is carried out binding with the vehicle, includes:
Whether induction fee-collector clicks the button of distribution pattern;
If so, issuing the request of distribution pattern to the charge system;
Obtain the pattern comprising admission information that the charge system is issued according to the request;
The vehicle and the pattern are bound.
Further, the data protection module guard method is as follows:
Firstly, main database server and backup database server is locally located in parking lot, and primary database is taken
Business device is communicated as the server of work at present with parking lot sentry box terminal;
Then, the main database server is controlled to arrive the data variation real-time synchronization in the main database server
The backup database server;
Finally, monitor the operating status of the main database server, when monitoring that main database server failure causes
When parking lot sentry box terminal can not just be often connected to the main database server, the server of work at present is cut in control
It is changed to the backup database server.
Another object of the present invention is to provide a kind of computers for realizing the parking lot distributed intelligence bootstrap technique
Program.
Another object of the present invention is to provide a kind of terminal, the terminal, which is at least carried, realizes that the parking lot is distributed
The controller of intelligent guide method.
Another object of the present invention is to provide a kind of computer readable storage mediums, including instruction, when it is in computer
When upper operation, so that computer executes the parking lot distributed intelligence bootstrap technique.
Advantages of the present invention and good effect are as follows:
The present invention is believed between the specific parking stall of large parking lot and vehicle by researching and solving for parking lot intelligent guidance system
Unsmooth problem is ceased, so that vehicle can fast and accurately find idle parking stall after entering parking lot, eliminating local congestion phenomenon is
Driver and conductor saves time cost and energy cost, eliminates the idle phenomenon in part and improves parking turnover rate, stops simultaneously
The development trend in the intelligent and following parking lot in field;It can be solved by parking stall monitoring modular, anti-blocking module, route guidance module
Certainly: dynamic monitoring can be carried out to parking stall, i.e. before reaching idle parking stall, system can believe traveling vehicle information and parking stall vehicle
Breath is pre-processed, and is pre-allocated to parking stall, and the generation of parking stall problem is fought in prevention.Eliminate vehicle driving blindness and with
Machine improves parking stall utilization rate, saves corresponding time cost and energy cost for driver, realizes environmentally protective trip.
There is perfect vehicle level monitoring system, warning information can be issued, administrative staff is notified to carry out necessary maintenance to failure, and is tieing up
Vehicle level monitoring system still being capable of normal use before shield;Meanwhile through parking charge module in vehicle admission, described in detection
Whether vehicle is no license plate vehicle;If so, requesting and obtaining by charge system distribution for calculating without license plate vehicle parking
The admission information of expense, and the vehicle of the admission information and admission is bound;When vehicle appears on the scene, the vehicle is judged
It whether is no license plate vehicle;If so, obtaining admission information bound in the vehicle to appear on the scene, and the admission information is sent out
The charge system is given to calculate Parking Fee.Since binding one is used to calculate when entering parking lot for no license plate vehicle
Admission information without license plate vehicle parking expense, so that when appearing on the scene convenient for accurately identifying no license plate vehicle, while accurately meter
Calculate the Parking Fee generated in parking lot without license plate vehicle;Going out in addition, solving parking lot by data protection module
When the failures such as existing computer glitch, abnormal power-down, database file damage, cause sentry box terminal that cannot normally complete admission, charge
The problem of etc. the operation for seriously affecting parking lot normal operation, reduces parking lot because of loss caused by failure to greatest extent.
Passage path guiding module of the present invention utilizes Route guiding planning algorithm, carries out parking stall guidance;Route guiding planning
Algorithm is to carry out optimal parking stall based on the hierarchical algorithms for improving ant colony clustering (Ant Colony Optimization, ACO)
Sorting provides foundation for the guidance of parking lot distributed intelligence.
Detailed description of the invention
Fig. 1 is parking lot distributed intelligence guidance system construction drawing provided in an embodiment of the present invention.
In figure: 1, video monitoring module;2, information acquisition module;3, parking stall monitoring modular;4, central control module;5, prevent
Stifled module;6, route guidance module;7, warning module;8, parking charge module;9, data protection module;10, display module;
11, selftest module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, parking lot distributed intelligence guidance system provided by the invention includes: video monitoring module 1, information
Acquisition module 2, parking stall monitoring modular 3, central control module 4, anti-blocking module 5, route guidance module 6, warning module 7, parking
Accounting module 8, data protection module 9, display module 10.
Video monitoring module 1 is connect with central control module 4, for monitoring parking lot in real time by image pick-up device;
Information acquisition module 2 is connect with central control module 4, for reading car owner's parking card information by card reader;
Parking stall monitoring modular 3 is connect with central control module 4, for detecting that parking stall magnetic field becomes by geomagnetism detecting device
Change, when judging parking space state;
Central control module 4, with video monitoring module 1, information acquisition module 2, parking stall monitoring modular 3, anti-blocking module 5,
Route guidance module 6, warning module 7, parking charge module 8, data protection module 9, display module 10 connect, for passing through list
Piece machine controls modules and works normally;
Anti-blocking module 5, connect with central control module 4, for realizing vehicle by the research of local congestion prevention algorithm
Guidance is shunted, reduction parking stall is fought for and the risk probability of local congestion.
Route guidance module 6 is connect with central control module 4, for the research of passage path guidance planning algorithm, is eliminated
The blindness and randomness of vehicle driving improve parking stall utilization rate, for driver save corresponding time cost and the energy at
This, realizes environmentally protective trip.
Warning module 7 is connect with central control module 4, for being warned in time by alarm to vehicle trouble;
Parking charge module 8 is connect with central control module 4, carries out charging for stopping by accounting routine to car owner;
Data protection module 9 is connect with central control module 4, for passing through main database server and backup database
Server backs up monitoring data, user data;
Display module 10 is connect with central control module 4, for showing monitored picture, acquisition car owner's letter by display
Cease content.
Selftest module 11, connect with central control module, and can alarm maintenance when going out minor issue for system.
Monitoring modular 3 monitoring method in parking stall provided by the invention is as follows:
(1) geomagnetism detecting device detects parking stall changes of magnetic field, when judging that parking space state changes, is drawn by interrupting
Foot wakes up single-chip microcontroller;
(2) single-chip microcontroller control is closed for connecting the electronic switch of lithium Asia battery, and lithium Asia battery is to temperature detector, electricity
Detector power supply;
(3) single-chip microcontroller obtains temperature information from temperature detector, obtains information about power from coulometric detector;
(4) single-chip microcontroller control wireless transmitter externally sends parking space state information, the temperature judged by parking stall changes of magnetic field
Spend information, information about power;
(5) wireless transmitter enters SLLEP state after having sent data, and electronic switch disconnects, and single-chip microcontroller enters suspend mode mould
Formula.
8 charging method of parking charge module provided by the invention is as follows:
1) when vehicle admission, detect whether the vehicle is no license plate vehicle;
2) if so, requesting and obtaining by charge system distribution for calculating the admission letter without license plate vehicle parking expense
Breath, and the vehicle of the admission information and admission is bound;
3) when vehicle appears on the scene, judge whether the vehicle is no license plate vehicle;
4) if so, obtaining admission information bound in the vehicle of appearance, and the admission information is sent to institute
Charge system is stated to calculate Parking Fee.
Request provided by the invention is simultaneously obtained by charge system distribution for calculating entering without license plate vehicle parking expense
Field information, and the vehicle of the admission information and admission is subjected to binding and includes:
The request of distribution admission information is issued to the charge system;
Obtain the admission information that the charge system is issued according to the request;The admission information includes the vehicle
The entry time of picture, the electronic license plate for distributing to the vehicle and the vehicle;
The vehicle and the admission information are bound.
It is provided by the invention to obtain admission information bound in the vehicle to appear on the scene, and the admission information is sent to
The charge system includes: to calculate Parking Fee
In control screen display without license plate matched interface;The no license plate matched interface includes whole in parking lot
Picture without license plate vehicle;
Obtain the picture corresponding with the vehicle of appearance chosen in the no license plate matched interface by fee-collector;
The corresponding electronic license plate of the picture and entry time are sent to the charge system to calculate the vehicle
Parking Fee.
Request provided by the invention is simultaneously obtained by charge system distribution for calculating entering without license plate vehicle parking expense
Field information, and the admission information is subjected to binding with the vehicle and includes:
Whether induction fee-collector clicks the button of distribution pattern;
If so, issuing the request of distribution pattern to the charge system;
Obtain the pattern comprising admission information that the charge system is issued according to the request;
The vehicle and the pattern are bound.
9 guard method of data protection module provided by the invention is as follows:
Firstly, main database server and backup database server is locally located in parking lot, and primary database is taken
Business device is communicated as the server of work at present with parking lot sentry box terminal;
Then, the main database server is controlled to arrive the data variation real-time synchronization in the main database server
The backup database server;
Finally, monitor the operating status of the main database server, when monitoring that main database server failure causes
When parking lot sentry box terminal can not just be often connected to the main database server, the server of work at present is cut in control
It is changed to the backup database server.
When the invention works, firstly, monitoring parking lot in real time using image pick-up device by video monitoring module 1;Pass through information
Acquisition module 2 reads car owner's parking card information using card reader;Vehicle is detected using geomagnetism detecting device by parking stall monitoring modular 3
Position changes of magnetic field, when judging parking space state;Secondly, central control module 4 is calculated by anti-blocking module 5 using local congestion prevention
Vehicle shunting guidance is realized in the research of method, and reduction parking stall is fought for and the risk probability of local congestion.6 benefit of passage path guiding module
With the research of Route guiding planning algorithm, the blindness and randomness of vehicle driving are eliminated, improves parking stall utilization rate, is driver
Member saves corresponding time cost and energy cost, realizes environmentally protective trip.By warning module 7 using alarm to vehicle
Failure is warned in time;It is stopped using accounting routine to car owner by parking charge module 8 and carries out charging;Then, pass through number
Monitoring data, user data are backed up using main database server and backup database server according to protective module 9;Most
Afterwards, monitored picture, acquisition owner information content are shown using display by display module 10.
Passage path guiding module of the present invention utilizes Route guiding planning algorithm, carries out parking stall guidance;Route guiding planning
Algorithm is to carry out optimal parking stall based on the hierarchical algorithms for improving ant colony clustering (Ant Colony Optimization, ACO)
Sorting carries out automatic cluster, implementation level classification to parking stall congestion index;Index of crowding data point is considered as have it is several
The ant of attribute, and index of crowding Classification Center is considered as food source, on the basis of clearly classification number M, there will be n
N number of index of crowding to be analyzed of attribute is defined as follows:
X={ Xa|Xa=(xa1,xa2,…,xan), a=1,2, N }
Biased error between different index of crowding is measured with Euclidean distance, apart from smaller, biased error
With regard to smaller;Index of crowding a is distributed into b-th of cluster centreAnt is just in index of crowding sample
A is to cluster centrePath (a, b) on leave pheromones τab(c), it usesIndicate index of crowding XaAnd XbAttribute space
Weighted euclidean distance, pab(c) probability of path (a, b) is selected for ant, calculation formula is as follows:
R is cluster radius in formula,Indicate ant XbAlternative road
Diameter;It is expected β is heuristic factor, characterize ant heuristic information during the motion by attention degree;It is k iteration
Middle index of crowding i is assigned to j-th of cluster centreThe numerical value of heuristic information is determined using the inverse of distance between the two
Justice;Work as pab(c)≥P0When, Xa is integrated into Xb neighborhood;It is crowded included in each class after moving all ants
Degree index will change, then the cluster centre point needs of each class recalculate, and the biased error inside same class also needs
It calculates and updates;Use CbIndicate all cluster sets for being integrated into the field Xi, new cluster centreIt is calculated with biased error E as follows:
In formula, J indicates CbElement number, CabIt indicatesA-th of component;
Meanwhile given maximum iteration maxiter, as long as meeting: 1) the biased error total amount of all classes is less than parameter ε;2) iteration
Number reaches given the number of iterations maximum value, when any condition, then end of clustering, and provide analysis result;Otherwise, it answers
Calculating is re-started, is terminated until meeting condition;
Improved ant colony clustering algorithm is programmed using Matlab tool, solves crowding degree index Critical Grading
Value, process are as follows:
Step 1: the sample size N of index of crowding, maximum number of iterations G, sample size attribute number initiation parameter: are determined
N and initial global information prime matrix;
Step 2: according to global information prime matrix, start to be iterated, determine ant walking path, and be marked;
Step 3: obtaining current cluster centre according to ID of trace route path, and calculates all samples to the inclined of corresponding cluster centre
From error total amount E, minimum biased error E_min is obtained;
Step 4: random number is generated, and thus current optimal path is changed, and calculate all samples under new route
To the biased error total amount E ' of corresponding cluster centre;
Step 5: judging whether E ' is less than E_min, if so, current path is optimal path, directly output is as a result, algorithm
Terminate;If it is not, then carrying out step 6;
Step 6: judging whether current the number of iterations reaches maximum value G, if then directly output is as a result, algorithm terminates;
Otherwise step 2 is returned, next round iteration is carried out.
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or any combination thereof real
It is existing.When using entirely or partly realizing in the form of a computer program product, the computer program product include one or
Multiple computer instructions.When loading on computers or executing the computer program instructions, entirely or partly generate according to
Process described in the embodiment of the present invention or function.The computer can be general purpose computer, special purpose computer, computer network
Network or other programmable devices.The computer instruction may be stored in a computer readable storage medium, or from one
Computer readable storage medium is transmitted to another computer readable storage medium, for example, the computer instruction can be from one
A web-site, computer, server or data center pass through wired (such as coaxial cable, optical fiber, Digital Subscriber Line (DSL)
Or wireless (such as infrared, wireless, microwave etc.) mode is carried out to another web-site, computer, server or data center
Transmission).The computer-readable storage medium can be any usable medium or include one that computer can access
The data storage devices such as a or multiple usable mediums integrated server, data center.The usable medium can be magnetic Jie
Matter, (for example, floppy disk, hard disk, tape), optical medium (for example, DVD) or semiconductor medium (such as solid state hard disk Solid
State Disk (SSD)) etc..
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (10)
1. a kind of parking lot distributed intelligence guides system, which is characterized in that the parking lot distributed intelligence guides system packet
It includes:
Video monitoring module is connect with central control module, for monitoring parking lot in real time by image pick-up device;
Information acquisition module is connect with central control module, for reading car owner's parking card information by card reader;
Parking stall monitoring modular, connect with central control module, for detecting parking stall changes of magnetic field by geomagnetism detecting device, when sentencing
Disconnected parking space state out;
Central control module, with video monitoring module, information acquisition module, parking stall monitoring modular, anti-blocking module, Route guiding mould
Block, warning module, parking charge module, data protection module, display module connection, for controlling modules by single-chip microcontroller
It works normally;
Anti-blocking module, connect with central control module, for realizing that vehicle shunting draws by the research of local congestion prevention algorithm
It leads, reduction parking stall is fought for and the risk probability of local congestion.
Route guidance module is connect with central control module, for the research of passage path guidance planning algorithm, eliminates vehicle row
The blindness and randomness sailed improve parking stall utilization rate, save corresponding time cost and energy cost for driver, realize
Environmentally protective trip.
Warning module is connect with central control module, for being warned in time by alarm to vehicle trouble;
Parking charge module, connect with central control module, carries out charging for stopping by accounting routine to car owner;
Data protection module is connect with central control module, for passing through main database server and backup database server
Monitoring data, user data are backed up;
Display module is connect with central control module, for showing monitored picture, acquisition owner information content by display;
Selftest module is connect with central control module, and can alarm maintenance when going out minor issue for system.
2. a kind of shopping mall market parking lot for being equipped with the guidance system of parking lot distributed intelligence described in claim 1.
3. a kind of parking lot distributed intelligence bootstrap technique of parking lot distributed intelligence guidance system as described in claim 1,
It is characterized in that, the parking lot distributed intelligence bootstrap technique includes:
Passage path guiding module utilizes Route guiding planning algorithm, carries out parking stall guidance;Route guiding planning algorithm be based on
The hierarchical algorithms for improving ant colony clustering (Ant Colony Optimization, ACO), carry out the sorting of optimal parking stall, to parking stall
Congestion index carries out automatic cluster, implementation level classification;Index of crowding data point is considered as to the ant for having several attributes,
And index of crowding Classification Center is considered as food source, on the basis of clearly classification number M, by with n attribute it is N number of to
The index of crowding of analysis is defined as follows:
X={ Xa|Xa=(xa1,xa2,…,xan), a=1,2 ..., N }
Biased error between different index of crowding is measured with Euclidean distance, and apart from smaller, biased error is got over
It is small;Index of crowding a is distributed into b-th of cluster centreAnt just arrives in index of crowding sample a
Cluster centrePath (a, b) on leave pheromones τab(c), it usesIndicate index of crowding XaAnd XbAttribute space adds
Weigh Euclidean distance, pab(c) probability of path (a, b) is selected for ant, calculation formula is as follows:
R is cluster radius in formula,Indicate ant XbAlternative path;β
It is expected heuristic factor, characterization ant heuristic information during the motion by attention degree;It is to be gathered around in k iteration
It squeezes degree index i and is assigned to j-th of cluster centreThe numerical value of heuristic information is defined using the inverse of distance between the two;When
pab(c)≥P0When, Xa is integrated into Xb neighborhood;After moving all ants, crowding included in each class refers to
Number will change, then the cluster centre point needs of each class recalculate, and the biased error inside same class also needs to calculate
It updates;Use CbIndicate all cluster sets for being integrated into the field Xi, new cluster centreIt is calculated with biased error E as follows:
In formula, J indicates CbElement number, CabIt indicatesA-th of component;
Meanwhile given maximum iteration maxiter, as long as meeting: 1) the biased error total amount of all classes is less than parameter ε;2) the number of iterations
Reach given the number of iterations maximum value, when any condition, then end of clustering, and provide analysis result;It otherwise, should be again
It is calculated, is terminated until meeting condition.
4. the parking lot distributed intelligence bootstrap technique of parking lot distributed intelligence guidance system as claimed in claim 3, special
Sign is that the parking lot distributed intelligence bootstrap technique specifically includes:
Parking lot is monitored in real time using image pick-up device by video monitoring module;
Car owner's parking card information is read using card reader by information acquisition module;
Parking stall changes of magnetic field is detected using geomagnetism detecting device by parking stall monitoring modular, when judging parking space state;Center control
Molding block realizes vehicle shunting guidance by the research of local congestion prevention algorithm of anti-blocking module, and reduction parking stall is fought for and part
The risk probability of congestion;
Passage path guiding module utilizes Route guiding planning algorithm, carries out parking stall guidance;
Vehicle trouble is warned in time using alarm by warning module;
It is stopped using accounting routine to car owner by parking charge module and carries out charging;
By data protection module using main database server and backup database server to monitoring data, user data into
Row backup;
Monitored picture, acquisition owner information content are shown using display by display module;
By selftest module, can alarm maintenance when going out minor issue to system, operate normally system.
5. distributed intelligence bootstrap technique in parking lot as claimed in claim 4, which is characterized in that the parking stall monitoring module monitors
Method is as follows:
(1) geomagnetism detecting device detects parking stall changes of magnetic field, when judging that parking space state changes, is called out by interrupt pin
Awake single-chip microcontroller;
(2) single-chip microcontroller control is closed for connecting the electronic switch of lithium Asia battery, and lithium Asia battery is to temperature detector, electric power detection
Device power supply;
(3) single-chip microcontroller obtains temperature information from temperature detector, obtains information about power from coulometric detector;
(4) single-chip microcontroller control wireless transmitter is externally sent because parking space state information, temperature that parking stall changes of magnetic field is judged are believed
Breath, information about power;
(5) wireless transmitter enters SLLEP state after having sent data, and electronic switch disconnects, and single-chip microcontroller enters suspend mode.
6. distributed intelligence bootstrap technique in parking lot as claimed in claim 4, which is characterized in that the parking charge module charging
Method is as follows:
1) when vehicle admission, detect whether the vehicle is no license plate vehicle;
2) if so, requesting and obtaining by charge system distribution for calculating the admission information without license plate vehicle parking expense,
And the vehicle of the admission information and admission is bound;
3) when vehicle appears on the scene, judge whether the vehicle is no license plate vehicle;
4) if so, obtaining admission information bound in the vehicle of appearance, and the admission information is sent to the meter
Charge system is to calculate Parking Fee;
The request is simultaneously obtained by charge system distribution for calculating the admission information without license plate vehicle parking expense, and by institute
The vehicle for stating admission information and admission carries out binding and includes:
The request of distribution admission information is issued to the charge system;
Obtain the admission information that the charge system is issued according to the request;The admission information includes the figure of the vehicle
The entry time of piece, the electronic license plate for distributing to the vehicle and the vehicle;
The vehicle and the admission information are bound;
It is described to obtain admission information bound in the vehicle to appear on the scene, and the admission information is sent to the charge system
Include: to calculate Parking Fee
In control screen display without license plate matched interface;The no license plate matched interface includes being located at whole no vehicles in parking lot
The picture of board vehicle;
Obtain the picture corresponding with the vehicle of appearance chosen in the no license plate matched interface by fee-collector;
Send the parking that the corresponding electronic license plate of the picture and entry time calculate the vehicle to the charge system
Expense;
The request is simultaneously obtained by charge system distribution for calculating the admission information without license plate vehicle parking expense, and by institute
It states admission information and bind with the vehicle and include:
Whether induction fee-collector clicks the button of distribution pattern;
If so, issuing the request of distribution pattern to the charge system;
Obtain the pattern comprising admission information that the charge system is issued according to the request;
The vehicle and the pattern are bound.
7. distributed intelligence bootstrap technique in parking lot as claimed in claim 4, which is characterized in that the data protection module protection
Method is as follows:
Firstly, be locally located main database server and backup database server in parking lot, and by main database server
Server as work at present is communicated with parking lot sentry box terminal;
Then, the main database server is controlled by the data variation real-time synchronization in the main database server to described
Backup database server;
Finally, monitor the operating status of the main database server, when monitoring that it is described that main database server failure causes
When parking lot sentry box terminal can not just be often connected to the main database server, the server of work at present is switched to by control
The backup database server.
8. a kind of computer program for realizing distributed intelligence bootstrap technique in parking lot described in claim 4~7 any one.
9. a kind of terminal, which is characterized in that the terminal, which is at least carried, realizes parking lot described in claim 4~7 any one
The controller of distributed intelligence bootstrap technique.
10. a kind of computer readable storage medium, including instruction, when run on a computer, so that computer executes such as
Parking lot distributed intelligence bootstrap technique described in claim 4-7 any one.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811338514.2A CN109191906A (en) | 2018-11-12 | 2018-11-12 | A kind of parking lot distributed intelligence guidance system and method |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201811338514.2A CN109191906A (en) | 2018-11-12 | 2018-11-12 | A kind of parking lot distributed intelligence guidance system and method |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109191906A true CN109191906A (en) | 2019-01-11 |
Family
ID=64938832
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201811338514.2A Pending CN109191906A (en) | 2018-11-12 | 2018-11-12 | A kind of parking lot distributed intelligence guidance system and method |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109191906A (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109754638A (en) * | 2019-02-19 | 2019-05-14 | 浙江大学城市学院 | A kind of parking space allocation method based on distributed computing technology |
CN109767647A (en) * | 2019-03-04 | 2019-05-17 | 天津中德应用技术大学 | A kind of intelligent parking management system |
CN110675652A (en) * | 2019-09-29 | 2020-01-10 | 福建工程学院 | LORA technology-based intelligent parking guidance method for large parking lot |
CN110930761A (en) * | 2019-11-06 | 2020-03-27 | 合肥齐赢网络技术有限公司 | Intelligent parking management system |
CN114550451A (en) * | 2022-02-18 | 2022-05-27 | 平安国际智慧城市科技股份有限公司 | Vehicle congestion early warning method, device, equipment and storage medium for parking lot |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN203552312U (en) * | 2013-11-07 | 2014-04-16 | 成都曙光光纤网络有限责任公司 | Intelligent parking management system |
CN203630979U (en) * | 2013-11-06 | 2014-06-04 | 西安中科麦特电子技术设备有限公司 | Intelligent parking lot management system |
CN106021902A (en) * | 2016-05-16 | 2016-10-12 | 宁波工程学院 | Grading method used for urban rail transit passenger flow congestion index |
CN106452864A (en) * | 2016-09-30 | 2017-02-22 | 北京悦畅科技有限公司 | Parking lot fault protection method, apparatus and system thereof |
KR20170107113A (en) * | 2016-03-14 | 2017-09-25 | 지엘에스이 주식회사 | Parking guidance camera system |
CN107680399A (en) * | 2017-08-17 | 2018-02-09 | 广东中科陆普物联网络科技有限公司 | Wireless method for detecting parking stalls and parking space detector |
CN107730608A (en) * | 2016-10-18 | 2018-02-23 | 西安艾润物联网技术服务有限责任公司 | Parking charge method and device |
-
2018
- 2018-11-12 CN CN201811338514.2A patent/CN109191906A/en active Pending
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN203630979U (en) * | 2013-11-06 | 2014-06-04 | 西安中科麦特电子技术设备有限公司 | Intelligent parking lot management system |
CN203552312U (en) * | 2013-11-07 | 2014-04-16 | 成都曙光光纤网络有限责任公司 | Intelligent parking management system |
KR20170107113A (en) * | 2016-03-14 | 2017-09-25 | 지엘에스이 주식회사 | Parking guidance camera system |
CN106021902A (en) * | 2016-05-16 | 2016-10-12 | 宁波工程学院 | Grading method used for urban rail transit passenger flow congestion index |
CN106452864A (en) * | 2016-09-30 | 2017-02-22 | 北京悦畅科技有限公司 | Parking lot fault protection method, apparatus and system thereof |
CN107730608A (en) * | 2016-10-18 | 2018-02-23 | 西安艾润物联网技术服务有限责任公司 | Parking charge method and device |
CN107680399A (en) * | 2017-08-17 | 2018-02-09 | 广东中科陆普物联网络科技有限公司 | Wireless method for detecting parking stalls and parking space detector |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109754638A (en) * | 2019-02-19 | 2019-05-14 | 浙江大学城市学院 | A kind of parking space allocation method based on distributed computing technology |
CN109754638B (en) * | 2019-02-19 | 2020-09-22 | 浙江大学城市学院 | Parking space allocation method based on distributed technology |
CN109767647A (en) * | 2019-03-04 | 2019-05-17 | 天津中德应用技术大学 | A kind of intelligent parking management system |
CN110675652A (en) * | 2019-09-29 | 2020-01-10 | 福建工程学院 | LORA technology-based intelligent parking guidance method for large parking lot |
CN110930761A (en) * | 2019-11-06 | 2020-03-27 | 合肥齐赢网络技术有限公司 | Intelligent parking management system |
CN110930761B (en) * | 2019-11-06 | 2021-05-07 | 深圳市亿悠网络科技有限公司 | Intelligent parking management system |
CN114550451A (en) * | 2022-02-18 | 2022-05-27 | 平安国际智慧城市科技股份有限公司 | Vehicle congestion early warning method, device, equipment and storage medium for parking lot |
CN114550451B (en) * | 2022-02-18 | 2023-08-18 | 平安国际智慧城市科技股份有限公司 | Vehicle congestion early warning method, device and equipment for parking lot and storage medium |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109191906A (en) | A kind of parking lot distributed intelligence guidance system and method | |
CN105469457B (en) | A kind of Roadside Parking toll collection system based on big-dipper satellite positioning | |
CN102254429B (en) | Video identification-based detection method of detection device of violation vehicles | |
CN110619751A (en) | Intelligent parking management system based on cloud server | |
CN103337161A (en) | Optimization method of intersection dynamic comprehensive evaluation and signal control system based on real-time simulation model | |
CN106128130B (en) | Construction area operating status control method based on earth magnetism wagon detector and system | |
CN102800212B (en) | Intelligent parking system under a kind of environment of internet of things | |
CN105469610A (en) | Expressway intelligent OBU device based on real-time data interactions | |
CN109910881A (en) | A kind of detection processing method and system of turning road vision dead zone information | |
CN105261231A (en) | Regional induction method and system of parking lot | |
CN106601021A (en) | Intelligent indicating system for urban public parking spaces | |
CN205104025U (en) | Intelligence bus management system | |
CN106530704A (en) | Floating car aggregation detection method based on multivariate data fusion | |
CN203163853U (en) | Automatic weighing management system | |
CN110400462A (en) | Track traffic for passenger flow monitoring and pre-alarming method and its system based on fuzzy theory | |
CN109637127A (en) | A kind of determination method and system of signal lamp approximation duration | |
CN207115750U (en) | A kind of radar traffic event automatic detection system | |
CN105489010B (en) | A kind of through street journey time reliability monitoring analysis system and method | |
CN106781533A (en) | A kind of traffic intelligent detecting system for intersection | |
CN106710199A (en) | Electric vehicle monitoring method and system based on Internet of Things technology | |
CN208271259U (en) | A kind of conveniently system of real name intelligence pedestrian passage gate | |
CN114743382B (en) | Vehicle violation behavior identification method and device based on intelligent lamp pole system | |
CN103729891B (en) | Road side unit equipment and process transaction method and ETC system | |
CN109615863A (en) | A kind of traffic congestion detection and communication device and detection method based on Car license recognition | |
CN109677324A (en) | Parked vehicle collision alarm method based on NB-IoT technology |
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 | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190111 |
|
RJ01 | Rejection of invention patent application after publication |