CN117392867B - Intelligent Parking Lot Management System Based on Neural Network - Google Patents
Intelligent Parking Lot Management System Based on Neural Network Download PDFInfo
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- G—PHYSICS
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- 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
- G08G1/148—Management of a network of parking areas
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- 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
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096733—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096827—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed onboard
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/0969—Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map
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- 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
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
- G08G1/144—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces on portable or mobile units, e.g. personal digital assistant [PDA]
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
- H04M1/72409—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality by interfacing with external accessories
- H04M1/724098—Interfacing with an on-board device of a vehicle
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Abstract
The invention discloses an intelligent parking lot management system based on a neural network, wherein a vehicle identification module is used for identifying vehicle information entering a parking lot, constructing a communication channel for a vehicle owner and sending the communication channel to a server; the parking space management module is used for acquiring parking lot management information and grading the parking areas of the parking lot based on the optimal parking environment values of the parking areas obtained by the management information; the route navigation module constructs a map unit based on the parking area of the parking lot and the internal route of the parking lot, positions the parking spaces for the vehicles in the parking lot according to the real-time positioning information of the vehicles on the map unit, and constructs the traveling path from the vehicle positions to the target parking spaces.
Description
Technical Field
The invention relates to the technical field of intelligent parking, in particular to an intelligent parking lot management system based on a neural network.
Background
In urban development, parking lot construction has become one of the indispensable parts of building planning. With the increase of demands, the construction area of modern parking lots is increased, and the parking spaces are increased, so that new requirements are put forward for the management of the parking lots.
As disclosed in patent application number 201810445494.2, the system uses front-rear distance radars and front-rear cameras on vehicles in parking space to detect and judge parking space of vehicles entering and exiting the parking space nearby, and then the parking space management system carries out charge management on the vehicles entering and exiting the parking space.
In the prior art, although unmanned management and intelligent payment are realized in an intelligent parking lot, certain defects still exist for regional management in the parking lot, people cannot be reasonably distributed to maintain and manage different parking areas, and meanwhile, an owner of the unattended parking lot has certain limitation on finding a parking space.
Disclosure of Invention
The invention aims to provide an intelligent parking lot management system based on a neural network, which is characterized in that vehicle information entering a parking lot is identified through a vehicle identification module, and the condition of a vehicle in the parking lot is pushed to a vehicle owner client through a small program, so that the vehicle owner can acquire the parking information of the vehicle in the parking lot in time, meanwhile, the parking space information of the parking lot is classified through a parking space management module, the parking space number, the number of cameras and the accident frequency of the parking area are processed in the classification process, and the intelligent management of different parking areas by parking lot managers is facilitated after the classification is completed.
The aim of the invention can be achieved by the following technical scheme:
an intelligent parking lot management system based on a neural network, comprising:
The vehicle identification module is used for identifying vehicle information entering the parking lot, constructing a communication channel for a vehicle owner and sending the communication channel to the server;
The parking space management module is used for acquiring parking lot management information and classifying parking areas of the parking lot based on optimal parking environment values of the parking areas obtained by the management information;
the route navigation module is used for constructing a map unit based on a parking area of the parking lot and a route in the parking lot, positioning a parking space for a vehicle in the parking lot according to real-time positioning information of the vehicle on the map unit, and constructing a travel path from the position of the vehicle to a target parking space.
As a further scheme of the invention: the vehicle information comprises vehicle contour information and vehicle owner related information;
the vehicle contour information includes vehicle color information and vehicle exterior damage information;
the vehicle associated information comprises vehicle entrance time and vehicle owner contact information;
the car owner contact information is generally connected with a car owner microcomputer through an app applet and is used for recommending the car information to the car owner.
As a further scheme of the invention: dividing a parking lot into n parking area units through an area or function, and respectively acquiring management information of each parking area;
the management information includes the number of parking spaces, the number of cameras, and accident frequency of the parking area.
As a further scheme of the invention: marking the number of parking spaces in a parking area as T1;
The number of cameras in the parking area is marked as T2;
marking the accident frequency of the parking area as T3;
By the formula Obtaining an optimal value JCn of a parking environment of the parking area, wherein d1, d2 and d3 are preset proportionality coefficients, and delta is a correction coefficient.
As a further scheme of the invention: the limit of the optimal value of the parking environment of the preset parking area is Jcn1 and Jcn2, wherein Jcn1< Jcn2;
When Jcn < Jcn1, then the parking environment of the parking area is indicated to be poor;
When Jcn1< Jcn2, the parking environment of the parking area is indicated to be general;
When Jcn > Jcn2, it indicates that the parking environment of the parking area is good.
As a further scheme of the invention: the process for acquiring the position information of the vehicle on the map unit comprises the following steps:
the route navigation module is accessed into each parking area and the internal route of the parking lot, and draws an electronic map according to the scenes of each parking area and the internal route of the parking lot, so as to construct a map unit;
and according to the map unit, the vehicle client identifies the position of the vehicle in the map unit according to the network positioning unit, and real-time positioning information of the vehicle on the map unit is obtained.
As a further scheme of the invention: the construction of the navigation path comprises the following steps:
obtaining parking area unit information transmitted by a server, and marking a parking area as cn, wherein n=1, … … and m;
Setting the distance between the real-time positioning information of the vehicle on the map unit and a parking space in the parking area and marking the distance as Hcn;
Marking the number of driving curves in a preset navigation path as Wcn;
Marking Zcn the total number of parking spaces within the parking area;
Marking the ratio of the total number of parked vehicles to the total number of parked vehicles in the parking area as Kcn;
By the formula Calculating to obtain a route recommended value Tcn; wherein, f1, f2, f3, f4 and f5 are all preset proportionality coefficients; gcn is the number of abnormal parking spaces in the parking area, and JCN is the optimal value threshold of the parking environment in the parking area.
As a further scheme of the invention: the vehicle identification module sends the selected target parking space to the vehicle owner client through the app applet.
As a further scheme of the invention: the abnormal parking spaces in the parking area are parking spaces affecting normal parking in the parking area.
The invention has the beneficial effects that:
(1) According to the invention, the vehicle information entering the parking lot is identified through the vehicle identification module, the condition of the vehicle in the parking lot is pushed to the vehicle owner client through the small program, so that the vehicle owner can timely acquire the parking information of the vehicle in the parking lot, meanwhile, the parking space management module is used for classifying the parking areas according to the parking space information of the parking lot, the number of the parking spaces in the parking areas, the number of cameras and the accident frequency are processed in the classifying process, and the intelligent management of parking lot managers on different parking areas is facilitated after the classifying is completed, so that the practicability is high;
(2) According to the invention, each parking area and the internal route of the parking lot are accessed through the route navigation module, an electronic map is drawn according to scenes of each parking area and the internal route of the parking lot, a map unit is constructed, and a vehicle client identifies the position of a vehicle in the map unit according to the network positioning unit, so that real-time positioning information of the vehicle on the map unit is obtained; the navigation path of the vehicle in the map unit is constructed by taking the map unit as a basis and taking the parking space information of the parking area and the parking space at the corresponding position as a support, and the navigation path constructed by the route navigation module provides intelligent guidance for the vehicle owner to the parking space, so that the intelligent degree of the parking lot is high, the time for the vehicle owner to find the parking space in the parking lot is greatly saved, and the vehicle owner can find the optimal parking space conveniently.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a flow chart of the present invention for constructing a navigation path;
FIG. 3 is a flow chart of the positioning of a vehicle within a map unit in accordance with the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention discloses an intelligent parking lot management system based on a neural network, which comprises a vehicle identification module, a parking space management module, a route navigation module and a server;
The vehicle identification module, the parking space management module and the route navigation module are electrically connected with the server;
The vehicle identification module is used for identifying vehicle information entering the parking lot, constructing a communication channel for a vehicle owner and sending the communication channel to the server through the constructed communication channel;
the parking space management module is used for acquiring parking space information of a parking lot, and classifying parking areas of the parking lot based on optimal values of parking environments of the parking areas obtained by the parking space information;
the route navigation module constructs a map unit based on a parking area of the parking lot and a route inside the parking lot, positions parking spaces for vehicles in the parking lot according to real-time positioning information of the vehicles on the map unit, and constructs a traveling path from the positions of the vehicles to the target parking spaces.
The vehicle information comprises vehicle contour information and vehicle owner related information;
the vehicle contour information includes vehicle color information and vehicle exterior damage information;
the vehicle associated information comprises vehicle entrance time and vehicle owner contact information;
in this embodiment, the contact information of the vehicle owner is generally connected with the vehicle owner through an app applet for recommending the vehicle information to the vehicle owner.
The pushed vehicle information includes, but is not limited to, information such as a parking time period of the vehicle in the parking lot, a vehicle state of the vehicle in the parking lot, and the like.
The parking space management module is used for acquiring parking space information of the parking lot and classifying parking areas of the parking lot based on the parking space information;
the obtaining process of the optimal value of the parking environment in the parking area comprises the following steps:
Dividing a parking lot into n parking area units through an area or function, and respectively acquiring the number of parking spaces, the number of cameras and accident frequency of each parking area;
The optimal value JCn of the parking environment of the parking area is obtained by processing the number of parking spaces, the number of cameras and the accident frequency of the parking area;
accident frequencies include, but are not limited to, car-to-car collisions, car-to-pedestrian friction, car-to-ground building scrapes, etc.;
specific: the process for obtaining the optimal value of the parking environment of the parking area comprises the following steps of
Marking the number of parking spaces in a parking area as T1;
The number of cameras in the parking area is marked as T2;
marking the accident frequency of the parking area as T3;
By the formula Obtaining an optimal value JCn of a parking environment of the parking area, wherein d1, d2 and d3 are preset proportionality coefficients, delta is a correction coefficient, and delta is 0.5673.
The limit of the optimal value of the parking environment of the preset parking area is Jcn1 and Jcn2, wherein Jcn1< Jcn2;
When Jcn < Jcn1, then the parking environment of the parking area is indicated to be poor;
When Jcn1< Jcn2, the parking environment of the parking area is indicated to be general;
When Jcn > Jcn2, it indicates that the parking environment of the parking area is good.
The route navigation module is accessed into each parking area and the internal route of the parking lot, and draws an electronic map according to the scenes of each parking area and the internal route of the parking lot, so as to construct a map unit;
According to the map unit, the vehicle client identifies the position of the vehicle in the map unit according to the network positioning unit, and real-time positioning information of the vehicle on the map unit is obtained;
and constructing a navigation path of the vehicle in the map unit by taking the map unit as a basis and taking the parking space information of the parking area and the parking spaces at the corresponding positions as supports.
The positioning process of the network positioning unit to the vehicle in the map unit is as follows:
shooting a road sign indicating board on a vehicle driving road in real time through a parking lot camera device, and recording shooting time;
Comparing the photographed road sign with the road sign stored in the map unit, and matching the photographed road sign with the coordinates corresponding to the road sign;
updating the position of the vehicle in the map unit;
counting left turn time, right turn time, running time and running average speed of the vehicle after updating the current position coordinates;
calculating a travel displacement of the vehicle using the travel average speed and the travel time; then according to the left turning time and the right turning time of the vehicle, the positioning of the vehicle is obtained on the map unit through calculation;
When the next road sign is shot, matching the coordinates corresponding to the road sign and the road sign, updating the position coordinates, and counting the left turn times and right turn times, the left turn time and right turn time, the running time and the running average speed of the vehicle again; and calculating to obtain real-time positioning information of the vehicle on the map unit.
Specifically, the construction of the navigation path includes:
obtaining parking area unit information transmitted by a server, and marking a parking area as cn, wherein n=1, … … and m;
Setting the distance between the real-time positioning information of the vehicle on the map unit and a parking space in the parking area and marking the distance as Hcn;
Marking the number of driving curves in a preset navigation path as Wcn;
Marking Zcn the total number of parking spaces within the parking area;
Marking the ratio of the total number of parked vehicles to the total number of parked vehicles in the parking area as Kcn;
By the formula Calculating to obtain a route recommended value Tcn; wherein, f1, f2, f3, f4 and f5 are all preset proportionality coefficients; gcn is the number of abnormal parking spaces in the parking area, and JCN is the optimal value threshold value of the parking environment in the parking area;
selecting a parking space corresponding to a maximum route recommended value in a parking area as a target parking space, and sending the selected target parking space to a vehicle owner client by a vehicle identification module through an app applet;
When new vehicles enter the parking area, namely the ratio of the total number of the parked vehicles to the total number of parking digits in the parking area is increased, the number of the vacant parking spaces in the parking area is reduced, and the corresponding obtained route recommended value is correspondingly reduced;
The smaller the distance between the real-time positioning information of the parking space and the parking space in the parking area is, the shorter the distance between the vehicle and the parking space is, and the vehicle can quickly reach the parking space, and the correspondingly obtained recommended route value is correspondingly increased;
the more the number of the driving curves in the navigation path is, the greater the risk of the vehicle driving in the parking lot is, and the correspondingly obtained route recommended value is correspondingly reduced;
The closer the parking environment optimal value of the parking area of the selected parking area in the navigation path is to the parking environment optimal value threshold value of the parking area, the better the parking environment of the parking area selected by the navigation path is, and the correspondingly obtained route recommended value is correspondingly increased;
the more the number of abnormal parking spaces in the parking area is, the more the vehicles are parked in the parking area, and the correspondingly obtained route recommended values are correspondingly reduced.
The acquisition process of the number of the abnormal parking spaces in the parking area comprises the following steps:
Acquiring parking spaces through a parking lot camera device, and marking all the parking spaces affecting normal parking as abnormal parking spaces;
conditions for an abnormal parking spot include, but are not limited to, the following conditions:
1. The parking space has foreign matters, so that the parking space can not park normally;
2. The parking space is occupied by vehicles on adjacent berths, so that the parking space can not park smoothly;
3. the parking space has a deep pit, resulting in a parking space that cannot be parked.
One of the core points of the present invention is: the vehicle information entering the parking lot is identified through the vehicle identification module, the condition of the vehicle in the parking lot is pushed to the vehicle owner client through the small program, so that the vehicle owner can timely acquire the parking information of the vehicle in the parking lot, meanwhile, the parking space management module is used for carrying out parking area classification on the parking space information of the parking lot, the number of parking spaces in the parking area, the number of cameras and accident frequency are processed in the classification process, intelligent management of parking lot management personnel on different parking areas is facilitated after classification is completed, and the practicability is high;
the second core point of the invention is: the method comprises the steps that a route navigation module is used for accessing each parking area and the internal route of a parking lot, an electronic map is drawn according to scenes of each parking area and the internal route of the parking lot, a map unit is constructed, and a vehicle client identifies the position of a vehicle in the map unit according to a network positioning unit, so that real-time positioning information of the vehicle on the map unit is obtained; the navigation path of the vehicle in the map unit is constructed by taking the map unit as a basis and taking the parking space information of the parking area and the parking space at the corresponding position as a support, and the navigation path constructed by the route navigation module provides intelligent guidance for the vehicle owner to the parking space, so that the intelligent degree of the parking lot is high, the time for the vehicle owner to find the parking space in the parking lot is greatly saved, and the vehicle owner can find the optimal parking space conveniently.
The foregoing describes one embodiment of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (3)
1. Intelligent parking area management system based on neural network, its characterized in that includes: the vehicle identification module is used for identifying vehicle information entering the parking lot, constructing a communication channel for a vehicle owner and sending the vehicle information to the server through the constructed communication channel; the parking space management module is used for acquiring parking lot management information and classifying parking areas of the parking lot based on optimal parking environment values of the parking areas obtained by the management information; the route navigation module is used for constructing a map unit based on a parking area of the parking lot and a route in the parking lot, positioning a parking space for a vehicle in the parking lot according to real-time positioning information of the vehicle on the map unit, and constructing a travel path from the position of the vehicle to a target parking space;
Dividing a parking lot into n parking area units through an area or function, and respectively acquiring management information of each parking area; the management information comprises the number of parking spaces in a parking area, the number of cameras and accident frequency;
Marking the number of parking spaces in a parking area as T1; the number of cameras in the parking area is marked as T2; marking the accident frequency of the parking area as T3; by the formula
Obtaining an optimal value JCn of a parking environment of a parking area, wherein d1, d2 and d3 are preset proportionality coefficients, and delta is a correction coefficient;
The limit of the optimal value of the parking environment of the preset parking area is Jcn1 and Jcn2, wherein Jcn1< Jcn2;
When Jcn < Jcn1, then the parking environment of the parking area is indicated to be poor;
When Jcn1< Jcn2, the parking environment of the parking area is indicated to be general;
when Jcn > Jcn2, the parking environment of the parking area is good;
The process for acquiring the position information of the vehicle on the map unit comprises the following steps: the route navigation module is accessed into each parking area and the internal route of the parking lot, and draws an electronic map according to the scenes of each parking area and the internal route of the parking lot, so as to construct a map unit; according to the map unit, the vehicle client identifies the position of the vehicle in the map unit according to the network positioning unit, and real-time positioning information of the vehicle on the map unit is obtained;
The construction of the navigation path comprises the following steps: obtaining parking area unit information transmitted by a server, and marking a parking area as cn, wherein n=1, … … and m; setting the distance between the real-time positioning information of the vehicle on the map unit and a parking space in the parking area and marking the distance as Hcn; marking the number of driving curves in a preset navigation path as Wcn; marking Zcn the total number of parking spaces within the parking area; marking the ratio of the total number of parked vehicles to the total number of parked vehicles in the parking area as Kcn; by the formula
Calculating to obtain a route recommended value Tcn; wherein, f1, f2, f3, f4 and f5 are all preset proportionality coefficients; gcn is the number of abnormal parking spaces in the parking area, JCN is the threshold value of the optimal parking environment in the parking area, and the abnormal parking spaces in the parking area are parking spaces affecting normal parking in the parking area.
2. The intelligent parking lot management system based on a neural network of claim 1, wherein the vehicle information includes vehicle profile information and vehicle-related information; the vehicle contour information includes vehicle color information and vehicle exterior damage information; the vehicle associated information comprises vehicle entrance time and vehicle owner contact information; the car owner contact information is generally connected with a car owner microcomputer through an app applet and is used for recommending the car information to the car owner.
3. The intelligent parking lot management system based on the neural network according to claim 1, wherein the route navigation module selects a parking space corresponding to a maximum route recommended value in a parking area as a target parking space, and the vehicle identification module sends the selected target parking space to a vehicle owner client through an app applet.
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