CN114141025B - Unattended intelligent parking lot system - Google Patents
Unattended intelligent parking lot system Download PDFInfo
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- CN114141025B CN114141025B CN202111466601.8A CN202111466601A CN114141025B CN 114141025 B CN114141025 B CN 114141025B CN 202111466601 A CN202111466601 A CN 202111466601A CN 114141025 B CN114141025 B CN 114141025B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
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- 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
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/20—Individual registration on entry or exit involving the use of a pass
Abstract
The invention provides an unattended intelligent parking lot system, which comprises an entrance management module, an intelligent parking module and an exit management module, wherein the entrance management module is used for managing the entrance of the intelligent parking lot system; the entrance management module is used for acquiring the license plate number of a vehicle entering the parking lot and controlling an entrance gate based on the license plate number; the intelligent parking module is used for transferring the vehicle to a target parking space; the exit management module is used for acquiring the license plate number of the vehicle leaving the parking lot and controlling the entrance gate machine based on the license plate number. The intelligent parking module is used for automatically parking the vehicle, so that the parking and taking time of a driver can be saved, the phenomenon that the vehicle owner dares to park due to the fact that a luxury vehicle is arranged near the parking space can be avoided, and the parking space is prevented from being wasted.
Description
Technical Field
The invention relates to the field of parking lot management, in particular to an unattended intelligent parking lot system.
Background
The existing unattended parking lot generally needs a driver to find a position to park, and time is wasted. In reality, some parking spaces are smaller, or under the condition that a luxury vehicle is parked near some parking spaces, the vehicle owner generally dares not to park, and the parking spaces are wasted.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide an unattended intelligent parking lot system, comprising an entrance management module, an intelligent parking module and an exit management module;
the entrance management module is used for acquiring the license plate number of a vehicle entering the parking lot and controlling an entrance gate based on the license plate number;
the intelligent parking module is used for transferring the vehicle to a target parking space;
the exit management module is used for acquiring the license plate number of a vehicle leaving a parking lot and controlling an entrance gate based on the license plate number.
Furthermore, unmanned on duty intelligence parking area system still includes storage module, storage module is used for saving license plate number and the business turn over time of vehicle.
Further, the entrance management module comprises an entrance camera unit, an entrance gate unit and an entrance control unit;
the entrance camera unit is used for acquiring a first image of a license plate of a vehicle entering a parking lot and transmitting the first image to the entrance control unit;
the entrance control unit is used for carrying out image recognition processing on the first image, acquiring a license plate number contained in the first image, and transmitting the license plate number and first acquisition time of the first image to the storage module;
the storage module is used for storing the license plate number and the first acquisition time;
the entrance control unit is also used for judging whether the number of the remaining parking spaces is 0 or not, and if not, sending a first brake opening instruction to the entrance gate unit;
the entrance gate unit is used for receiving and executing the first gate opening instruction.
Further, the intelligent parking module comprises a mobile terminal unit, a cloud service unit and a vehicle transfer unit;
the mobile terminal unit is used for a vehicle owner to input an action instruction and sending the action instruction to the cloud service unit, and the action instruction comprises an entrance instruction and an exit instruction;
the cloud service unit is used for processing the action instruction:
if the action instruction is an entrance instruction, acquiring the position coordinate of a parking space closest to an exit of a parking lot, and sending the position coordinate to the vehicle transfer unit;
if the action command is a departure command, sending a vehicle moving command to a vehicle transfer unit corresponding to the vehicle;
the vehicle transfer unit is used for moving the vehicle to a target parking space corresponding to the position coordinate when receiving the position coordinate;
the vehicle transfer unit is further used for moving the vehicle to the parking lot exit when receiving the vehicle transfer instruction.
Further, the exit management module comprises an exit camera unit, a charging unit, an exit gate unit and an exit control unit;
the exit camera unit is used for acquiring a second image of a license plate of a vehicle leaving the parking lot and transmitting the second image to the charging unit;
the charging unit is used for carrying out image recognition processing on the second image, acquiring a license plate number contained in the second image, and transmitting the license plate number and second acquisition time of the second image to the charging unit;
the charging unit comprises a charging calculation subunit, a charge display subunit and a payment subunit;
the charging calculation subunit is used for acquiring first acquisition time corresponding to the license plate number in the storage module according to the license plate number and calculating parking cost based on the second acquisition time and the first acquisition time;
the expense display subunit is used for displaying the parking expense;
the payment subunit is used for acquiring a payment code displayed by a vehicle owner and finishing the collection of the parking fee based on the payment code;
the payment subunit is also used for sending a second brake opening instruction to the exit gate unit after the parking fee is collected;
and the exit gate unit is used for receiving and executing the second opening instruction.
Further, the vehicle transfer unit includes an unmanned flat car;
and the unmanned carrying flat car is used for moving the car to a target parking space corresponding to the position coordinate when receiving the position coordinate, and is used for moving the car to a parking lot exit when receiving a car transfer instruction.
The intelligent parking module is used for automatically parking the vehicle, so that the parking and taking time of a driver is saved, the phenomenon that a vehicle owner dares not to park due to the fact that a luxury vehicle is arranged near the parking space is avoided, and the parking space is avoided being wasted.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, without inventive effort, further drawings may be derived from the following figures.
Fig. 1 is a diagram illustrating an exemplary embodiment of an unattended intelligent parking lot system according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, in one embodiment, the present invention provides an unattended intelligent parking lot system, which includes an entrance management module, an intelligent parking module, and an exit management module;
the entrance management module is used for acquiring the license plate number of a vehicle entering the parking lot and controlling an entrance gate based on the license plate number;
the intelligent parking module is used for transferring the vehicle to a target parking space;
the exit management module is used for acquiring the license plate number of the vehicle leaving the parking lot and controlling the entrance gate machine based on the license plate number.
The intelligent parking module is used for automatically parking the vehicle, so that the parking and taking time of a driver is saved, the phenomenon that a vehicle owner dares not to park due to the fact that a luxury vehicle is arranged near the parking space is avoided, and the parking space is avoided being wasted.
Preferably, the unattended intelligent parking lot system further comprises a storage module, and the storage module is used for storing license plate numbers and the entering and exiting time of vehicles.
Preferably, the entrance management module includes an entrance camera unit, an entrance gate unit, and an entrance control unit;
the entrance camera unit is used for acquiring a first image of a license plate of a vehicle entering a parking lot and transmitting the first image to the entrance control unit;
the entrance control unit is used for carrying out image recognition processing on the first image, acquiring a license plate number contained in the first image, and transmitting the license plate number and first acquisition time of the first image to the storage module;
the storage module is used for storing the license plate number and the first acquisition time;
the entrance control unit is also used for judging whether the number of the remaining parking spaces is 0 or not, and if not, sending a first brake opening instruction to the entrance gate unit;
the entrance gate unit is used for receiving and executing the first opening command.
Preferably, the performing image recognition processing on the first image to obtain the license plate number included in the first image includes:
carrying out pixel point adjustment processing on the first image to obtain a first image;
carrying out graying processing on the first image to obtain a second image;
carrying out noise reduction processing on the second image to obtain a third image;
performing image segmentation processing on the third image to obtain a fourth image;
and inputting the fourth image into a pre-trained neural network model for image recognition processing to obtain the license plate number contained in the fourth image.
Preferably, the performing pixel point adjustment processing on the first image to obtain a first image includes:
acquiring an L component image corresponding to the first image in a Lab color space;
acquiring pixel points to be processed in the L component image;
adjusting the brightness of the pixel points to be processed in the L component image to obtain an L component image subjected to brightness adjustment;
converting the L component image subjected to brightness adjustment back to an RGB color space to obtain a first image;
wherein, for a pixel point s in the L component image, if it satisfies the following function, the pixel point s is a pixel point to be processed:
in the above formula, L(s) represents a pixel value of a pixel point s in an L component image, lmid represents a median value of the pixel values in the L component image, aveL(s) represents an average pixel value of the pixel points in a K × K window centered on the pixel point s, and tho and tht represent a preset first determination threshold and a preset second determination threshold, respectively; wherein tho e (30,40), tht e (10,20);
the brightness adjustment processing of the pixel points to be processed includes:
and (3) carrying out brightness adjustment processing on the pixel points to be processed by using the following functions:
wherein aL(s) represents the pixel value of a pixel point s after the brightness adjustment processing is carried out on the pixel point s, neis represents the set of the pixel points in a window with the size of K multiplied by K and taking the pixel point s as the center, L (u) represents the pixel value of a pixel point u in neis, delta represents a preset control parameter, delta belongs to (0.1,0.2),
the maximum value of the pixel values of the pixel points in neis is represented.
In the above invention, by performing the brightness adjustment processing on the pixel points after the conversion to the Lab color space, it is possible to avoid the problem that the influence of noise due to the illumination adjustment in RGB is large. On the L component image, the difference between the pixel values of the noise point and the pixel point to be processed is large, so that the noise point and the pixel point to be processed can be well distinguished, the noise point is prevented from being processed as the pixel point to be processed, and the workload for the noise reduction of the subsequent image is prevented from increasing. When the brightness adjustment processing is carried out, the difference between the currently processed pixel point and other pixel points in the window in the aspect of pixel values and the difference between the pixel values of the whole image in the median value are considered in the processing function, so that the pixel values of the reflective pixel points in the first image can be controlled, and the influence of the reflective pixel points on the subsequent license plate number identification is effectively reduced.
Preferably, the graying the first image to obtain the second image includes:
for a pixel point u in the first image, graying the pixel point u by the following formula:
Gray(u)＝w 1 ×R(u)+w 2 ×G(u)+w 3 ×B(u)
wherein w 1 、w 2 、w 3 Respectively representing preset proportionality coefficients, and R (u), G (u) and B (u) respectively represent pixel values of a red component, a green component and a blue component of a pixel point u in an RGB color space; gray (u) represents the Gray value of pixel u.
Compared with the traditional mode of only using a single component as a graying result, the graying result can keep the contrast information between pixel points in the obtained graying image as much as possible, and is favorable for improving the accuracy of subsequent license plate number identification.
Preferably, the performing image segmentation processing on the third image to obtain a fourth image includes:
performing image partitioning processing on the third image, and dividing the third image into a plurality of sub-images;
respectively carrying out image segmentation processing on each subimage by using an image segmentation algorithm to obtain a target pixel point of each subimage;
obtaining a fourth image from target pixel points in all sub-images;
wherein performing image blocking processing on the third image, and dividing the third image into a plurality of sub-images, comprises:
the third image is divided into a plurality of sub-images in a batch process,
first batch treatment:
dividing the third image into N sub-images with the same area, and storing the sub-images obtained in the batch processing into a set U 1 Performing the following steps;
respectively judge U 1 Whether each sub-image in the set needs to be processed in the next batch or not is judged, if yes, the sub-images are stored into a set dtdU 1 If not, storing the sub-image into a set aimU;
and (3) processing the q th batch:
respectively converting the sets dtdU q-1 The sub-images in the system are divided into N sub-images with the same area, and the sub-images obtained in the batch processing are stored in a set U q The preparation method comprises the following steps of (1) performing;
respectively judge U q Whether each sub-image in (1) needs to be processed in the next batch or not is judged, and if yes, the sub-images are stored into a set dtdU q If not, storing the sub-image into a set aimU;
determine dtdU q Whether the number of elements included in the third image is smaller than a preset number threshold value or not is judged, if yes, the image blocking processing on the third image is finished, the sub-images included in the set aimU are used as final blocking processing results, and if not, the q +1 th batch processing is performed;
judging whether the sub-image needs to be processed in the next batch or not by the following method:
calculating a processing index of the sub-image:
in the above formula, dealidx represents the processing index of the subimage, α, β,
Respectively representing preset weight parameters, nffp representing the proportion of pixel points with pixel values in the sub-image larger than a preset pixel value threshold, ntfp representing the proportion of the pixel points in the sub-imageThe total number is shown, snq represents the variance of the gradient amplitude of the pixel points in the sub-image, snqst represents a preset gradient variance standard value, and nfdlst represents a preset standard value of the number of the pixel points;
if the processing index is smaller than the preset processing index threshold, the subimage does not need to be processed in the next batch, otherwise, the subimage needs to be processed in the next batch.
In the above embodiment of the present invention, the image segmentation is performed without performing an integral segmentation on the entire third image by using a uniform segmentation algorithm, but the third image is divided into sub-images, then the sub-images are subjected to image segmentation processing, and finally the target pixel points of each sub-image form a fourth image. By the image segmentation mode, the problem that edge pixel points in the image are blurred easily because a segmentation threshold value cannot adapt to all image areas when a unified segmentation algorithm is used for integrally segmenting the whole third image can be avoided, and the image segmentation result is more accurate. When the sub-images are obtained, the third image is not directly divided into a plurality of sub-images at one time, but the sub-images with the processing indexes larger than or equal to the processing index threshold value are continuously processed in a batch processing mode. According to the method, each obtained sub-image can contain a target pixel point, and if a one-time division mode is adopted, firstly the number of the sub-images is not well determined, secondly, only the target pixel points or only non-target pixel points are easily contained in the obtained sub-images, when the sub-images of the types are subjected to image division, wrong division results are easily obtained, because the pixels of the same type are originally contained, but the pixels are divided into two types, and therefore serious influence is caused on the accurate obtaining of the license plate number in the follow-up process. The number of the sub-images finally acquired by the invention can be adaptively changed according to the actual pixel value distribution condition of the image, and the problem that the number is not easy to determine does not exist.
Preferably, N.epsilon. {4,9,16}.
Preferably, the target pixel point is a pixel point belonging to a foreground region obtained when the image segmentation algorithm is used for carrying out image segmentation on the subimage.
Preferably, the intelligent parking module comprises a mobile terminal unit, a cloud service unit and a vehicle transfer unit;
the mobile terminal unit is used for a vehicle owner to input an action instruction and send the action instruction to the cloud service unit, and the action instruction comprises an approach instruction and an departure instruction;
the cloud service unit is used for processing the action instruction:
if the action instruction is an entrance instruction, acquiring the position coordinate of a parking space closest to an exit of a parking lot, and sending the position coordinate to the vehicle transfer unit;
if the action command is a departure command, sending a vehicle moving command to a vehicle transfer unit corresponding to the vehicle;
the vehicle transfer unit is used for moving the vehicle to a target parking space corresponding to the position coordinate when receiving the position coordinate;
the vehicle transfer unit is further used for moving the vehicle to the parking lot exit when receiving the vehicle transfer instruction.
Specifically, after the vehicle owner enters the parking lot, the vehicle is driven to the position above the vehicle transfer unit, then the vehicle transfer unit fixes tires of the vehicle according to a set program, after the position coordinates sent by the cloud service unit are received, the vehicle is transferred to the target parking space corresponding to the position coordinates in an automatic driving mode, and at the moment, the vehicle transfer unit and the vehicle are parked in the target parking space together.
When the car owner needs to take the car, the departure instruction is input through the mobile terminal unit, and the cloud service unit sends a car moving instruction to the car transfer unit according to the departure instruction;
and the vehicle transfer unit transfers the vehicle to the exit of the parking lot after receiving the vehicle transfer instruction.
Therefore, the invention realizes the automatic parking of the vehicle, and the vehicle owner can finish the parking only at the entrance, thereby effectively saving the parking and taking time of the driver.
As another preference, the vehicle transfer unit includes a parking platform and a mobile robot;
the mobile robot is used for moving the parking flat plate to a target parking space corresponding to the position coordinate when receiving the position coordinate;
the vehicle transfer unit is further used for moving the parking platform to the parking lot outlet when receiving a vehicle transfer instruction.
The parking platform has tires that can rotate, but no power.
In the embodiment, the separation of the parking flat plate and the mobile robots is realized, and the number of the mobile robots can be far less than that of the parking flat plate, so that the cost can be effectively saved.
The mobile robot may be an unmanned vehicle with large traction.
When the mobile robot needs to move, the mobile robot is connected with the parking flat plate, so that the parking flat plate has power.
Preferably, the exit management module includes an exit camera unit, a charging unit, an exit gate unit, and an exit control unit;
the exit camera unit is used for acquiring a second image of a license plate of a vehicle leaving the parking lot and transmitting the second image to the charging unit;
the charging unit is used for carrying out image recognition processing on the second image, acquiring a license plate number contained in the second image, and transmitting the license plate number and second acquisition time of the second image to the charging unit;
the charging unit comprises a charging calculation subunit, a charge display subunit and a payment subunit;
the charging calculation subunit is used for acquiring first acquisition time corresponding to the license plate number in the storage module according to the license plate number and calculating parking cost based on the second acquisition time and the first acquisition time;
the expense display subunit is used for displaying the parking expense;
the payment subunit is used for acquiring a payment code displayed by a vehicle owner and finishing the collection of the parking fee based on the payment code;
the payment subunit is also used for sending a second brake opening instruction to the exit gate unit after the parking fee is collected;
and the exit gate unit is used for receiving and executing the second opening instruction.
Preferably, the vehicle transfer unit comprises an unmanned flat car;
and the unmanned carrying flat car is used for moving the car to a target parking space corresponding to the position coordinate when receiving the position coordinate, and is used for moving the car to a parking lot exit when receiving a car transfer instruction.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
It should be noted that the functional units/modules in the embodiments of the present invention may be integrated into one processing unit/module
In a block, each unit/module may exist alone physically, or two or more units/modules may be integrated into one unit/module. The integrated units/modules may be implemented in the form of hardware, or may be implemented in the form of software functional units/modules.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware.
In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Claims (4)
1. An unattended intelligent parking lot system is characterized by comprising an entrance management module, an intelligent parking module and an exit management module;
the entrance management module is used for acquiring the license plate number of a vehicle entering the parking lot and controlling an entrance gate based on the license plate number;
the intelligent parking module is used for transferring the vehicle to a target parking space;
the exit management module is used for acquiring the license plate number of a vehicle leaving the parking lot and controlling the entrance gate machine based on the license plate number;
the storage module is used for storing license plate numbers and the access time of vehicles;
the entrance management module comprises an entrance camera unit, an entrance gate unit and an entrance control unit;
the entrance camera unit is used for acquiring a first image of a license plate of a vehicle entering a parking lot and transmitting the first image to the entrance control unit;
the entrance control unit is used for carrying out image recognition processing on the first image, acquiring a license plate number contained in the first image, and transmitting the license plate number and first acquisition time of the first image to the storage module;
the storage module is used for storing the license plate number and the first acquisition time;
the entrance control unit is also used for judging whether the number of the remaining parking spaces is 0 or not, and if not, sending a first brake opening instruction to the entrance gate unit;
the entrance gate unit is used for receiving and executing the first gate opening instruction;
the image recognition processing of the first image to obtain the license plate number included in the first image includes:
carrying out pixel point adjustment processing on the first image to obtain a first image;
carrying out graying processing on the first image to obtain a second image;
carrying out noise reduction processing on the second image to obtain a third image;
performing image segmentation processing on the third image to obtain a fourth image;
inputting the fourth image into a pre-trained neural network model for image recognition processing to obtain a license plate number contained in the fourth image;
the pixel point adjustment processing is performed on the first image to obtain a first image, and the method comprises the following steps:
acquiring an L component image corresponding to the first image in a Lab color space;
acquiring pixel points to be processed in the L component image;
performing brightness adjustment processing on the pixel points to be processed in the L component image to obtain an L component image subjected to brightness adjustment;
converting the L component image subjected to brightness adjustment back to an RGB color space to obtain a first image;
wherein, for a pixel point s in the L component image, if it satisfies the following function, the pixel point s is a pixel point to be processed:
in the above formula, L(s) represents a pixel value of a pixel point s in an L component image, lmid represents a median value of the pixel values in the L component image, aveL(s) represents an average pixel value of the pixel points in a K × K window centered on the pixel point s, and tho and tht represent a preset first determination threshold and a preset second determination threshold, respectively; wherein tho E (30,40), tht E (10,20);
the brightness adjustment processing of the pixel points to be processed includes:
and (3) carrying out brightness adjustment processing on the pixel points to be processed by using the following functions:
wherein aL(s) represents the pixel value of a pixel point s after the brightness adjustment processing is carried out on the pixel point s, neis represents the set of the pixel points in a window with the size of K multiplied by K and taking the pixel point s as the center, L (u) represents the pixel value of a pixel point u in neis, delta represents a preset control parameter, delta belongs to (0.1,0.2),
the maximum value of the pixel values of the pixel points in neis is represented.
2. The unattended intelligent parking lot system according to claim 1, wherein the intelligent parking module comprises a mobile terminal unit, a cloud service unit and a vehicle transfer unit;
the mobile terminal unit is used for a vehicle owner to input an action instruction and sending the action instruction to the cloud service unit, and the action instruction comprises an entrance instruction and an exit instruction;
the cloud service unit is used for processing the action instruction:
if the action command is an entrance command, acquiring the position coordinate of a parking space closest to an exit of a parking lot, and sending the position coordinate to the vehicle transfer unit;
if the action command is a departure command, sending a vehicle moving command to a vehicle transfer unit corresponding to the vehicle;
the vehicle transfer unit is used for moving the vehicle to a target parking space corresponding to the position coordinate when receiving the position coordinate;
the vehicle transfer unit is further used for moving the vehicle to the parking lot exit when receiving the vehicle transfer instruction.
3. The unattended intelligent parking lot system according to claim 1, wherein the exit management module comprises an exit camera unit, a charging unit, an exit gate unit and an exit control unit;
the exit camera unit is used for acquiring a second image of a license plate of a vehicle leaving the parking lot and transmitting the second image to the charging unit;
the charging unit is used for carrying out image recognition processing on the second image, acquiring a license plate number contained in the second image, and transmitting the license plate number and second acquisition time of the second image to the charging unit;
the charging unit comprises a charging calculation subunit, a charge display subunit and a payment subunit;
the charging calculation subunit is used for acquiring first acquisition time corresponding to the license plate number in the storage module according to the license plate number and calculating parking cost based on the second acquisition time and the first acquisition time;
the expense display subunit is used for displaying the parking expense;
the payment subunit is used for acquiring a payment code displayed by a vehicle owner and finishing the collection of the parking fee based on the payment code;
the payment subunit is also used for sending a second brake opening instruction to the exit gate unit after the parking fee is collected;
and the exit gate unit is used for receiving and executing the second opening instruction.
4. The unattended intelligent parking lot system according to claim 2, wherein the vehicle transfer unit comprises an unmanned carrying flat car;
the unmanned carrying flat car is used for moving the vehicle to a target parking space corresponding to the position coordinate when receiving the position coordinate, and is used for moving the vehicle to a parking lot exit when receiving a vehicle transfer instruction.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9292743B1 (en) * | 2013-03-14 | 2016-03-22 | Puretech Systems, Inc. | Background modeling for fixed, mobile, and step- and-stare video camera surveillance |
| CN109087526A (en) * | 2018-08-06 | 2018-12-25 | 上海义嘉工业技术有限公司 | A kind of intelligent parking method based on Omni-mobile AGV |
| CN109285229A (en) * | 2018-11-06 | 2019-01-29 | 武汉找找网科技有限公司 | The high speed charging system of energy Car license recognition when a kind of vehicle is mobile |
| CN111047723A (en) * | 2019-12-12 | 2020-04-21 | 杭州昊恒科技有限公司 | City wisdom behavior analysis system based on image processing |
| WO2020130799A1 (en) * | 2018-12-21 | 2020-06-25 | Mimos Berhad | A system and method for licence plate detection |
| CN113421452A (en) * | 2021-06-03 | 2021-09-21 | 上海大学 | Open parking lot recommendation system based on visual analysis |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103065138B (en) * | 2012-12-06 | 2015-07-15 | 中通服公众信息产业股份有限公司 | Recognition method of license plate number of motor vehicle |
| CN104867191B (en) * | 2015-06-24 | 2017-07-25 | 大连海事大学 | Parking charge system and method based on electronic charging equipment |
| CN106935067B (en) * | 2015-12-31 | 2019-07-16 | 中惠创智无线供电技术有限公司 | AGV navigation parking system, unmanned parking system and the application of wireless power |
| CN107945294A (en) * | 2017-12-08 | 2018-04-20 | 大连前锋科技发展有限公司 | A kind of unattended pay parking |
| KR102023072B1 (en) * | 2018-07-16 | 2019-11-20 | 아마노코리아 주식회사 | Indoor localization system for vehicle |
| CN109166191A (en) * | 2018-08-24 | 2019-01-08 | 南通我烨智能设备科技有限公司 | A kind of high speed charging system paid the fees by Car license recognition |
| CN109345643A (en) * | 2018-09-26 | 2019-02-15 | 南京理工大学 | A kind of wisdom parking AGV system |
| KR102622851B1 (en) * | 2018-10-15 | 2024-01-10 | 현대자동차주식회사 | Unmanned charging system and method of electric car using parking position information |
| CN111833468A (en) * | 2019-03-29 | 2020-10-27 | 深圳市前海智慧交通运营科技有限公司 | Parking management method and device applied to cloud platform and terminal |
| CN110471418B (en) * | 2019-08-22 | 2021-06-04 | 北京交通大学 | AGV (automatic guided vehicle) scheduling method in intelligent parking lot |
| CN110807948A (en) * | 2019-11-12 | 2020-02-18 | 苏州国轩智能科技有限公司 | Roadside parking space intelligent management system realized by adopting unmanned trolley |
-
2021
- 2021-12-03 CN CN202111466601.8A patent/CN114141025B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9292743B1 (en) * | 2013-03-14 | 2016-03-22 | Puretech Systems, Inc. | Background modeling for fixed, mobile, and step- and-stare video camera surveillance |
| CN109087526A (en) * | 2018-08-06 | 2018-12-25 | 上海义嘉工业技术有限公司 | A kind of intelligent parking method based on Omni-mobile AGV |
| CN109285229A (en) * | 2018-11-06 | 2019-01-29 | 武汉找找网科技有限公司 | The high speed charging system of energy Car license recognition when a kind of vehicle is mobile |
| WO2020130799A1 (en) * | 2018-12-21 | 2020-06-25 | Mimos Berhad | A system and method for licence plate detection |
| CN111047723A (en) * | 2019-12-12 | 2020-04-21 | 杭州昊恒科技有限公司 | City wisdom behavior analysis system based on image processing |
| CN113421452A (en) * | 2021-06-03 | 2021-09-21 | 上海大学 | Open parking lot recommendation system based on visual analysis |
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