CN116978136B - ETC-based intelligent charging management system for urban road side parking - Google Patents
ETC-based intelligent charging management system for urban road side parking Download PDFInfo
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Abstract
The invention belongs to the field of urban road side parking intelligent charging management, and particularly discloses an ETC-based urban road side parking intelligent charging management system, which comprises the following components: the invention uses ETC to identify the relevant information of each target vehicle, monitors the parking condition of each target vehicle in real time through monitoring videos, analyzes the charging time, the parking normalization coefficient and the parking early warning coefficient of each target vehicle to obtain the estimated parking cost of each target vehicle, analyzes the parking charge level of each target vehicle, and further analyzes the parking cost of each target vehicle, thereby improving the parking normalization and charging rate and realizing safer and more convenient parking intelligent charge management.
Description
Technical Field
The invention belongs to the field of urban road side parking intelligent charging management, and relates to an ETC-based urban road side parking intelligent charging management system.
Background
Along with the increase of the quantity of the stored cars, the parking experience of parking difficulty and disordered management is gradually highlighted, the development of cities is influenced, in order to meet the increasing parking demand and alleviate the problem of parking difficulty, in recent years, urban roadside parking spaces with charging property are arranged in non-main roads in various large cities, the intelligent modification process of a roadside parking charging management system is continuously advancing, however, no matter manual management or unattended operation is carried out, all roadside parking at present needs autonomous payment of car owners, a convenient and effective intelligent settlement mode is not integrated in the payment process all the time, and after the car owners leave the parking spaces, the condition of forgetting payment is often existed through APP or code scanning payment according to ticket indication, and the rate is uncontrollable.
The ETC payment mode is the safest and convenient payment mode at present, the ETC technology is basically popularized on the expressway in recent years, convenience is brought to a plurality of vehicle owners, the ETC payment is not exclusive to high-speed charging at present, and the ETC payment mode is gradually released to a parking lot and a road side parking space for use, so that the problem of parking charging is solved.
The existing urban road side parking charging has some defects, and is mainly characterized in the following aspects: (1) At present, a plurality of vehicle owners exist in urban road side parking spaces, parking is not standard, even more, the phenomenon that other vehicle owners use road side parking spaces is influenced, the actual utilization rate of the urban road side parking spaces is low, and meanwhile, the urban road image is influenced.
(2) The vehicles are parked on the road beyond the parking space area, so that the running of the vehicles on the traffic road is influenced, various accidents are caused, the degree of traffic jam is increased, and the safety of the road is reduced.
(3) The existing urban road side parking spaces mostly adopt the geomagnetic sensing vehicle parking state and time length, and adopt the manual charging or code scanning payment mode of the vehicle owners, however, the service life and the reliability of geomagnetism are limited to a certain extent, so that the management cost and the labor cost are increased, and meanwhile, a plurality of vehicle owners often forget to pay, the rate is high, and the cost burden and the management difficulty of the urban road side parking spaces are greatly improved.
Disclosure of Invention
In order to overcome the defects in the background technology, the embodiment of the invention provides an ETC-based intelligent charging management system for urban road side parking, which can effectively solve the problems related to the background technology.
The aim of the invention can be achieved by the following technical scheme: the invention provides an ETC-based intelligent charging management system for urban road side parking, which comprises the following components: the vehicle information identification module is used for identifying vehicles entering the specified roadside parking areas by using ETC equipment installed in the specified roadside parking areas and marking the vehicles as target vehicles, and further identifying ETC electronic tag information of the target vehicles.
The vehicle charging duration analysis module is used for analyzing the starting charging time of each target vehicle entering the parking space and the ending charging time of each target vehicle leaving the parking space according to the real-time monitoring video, so as to analyze the charging duration of each target vehicle.
The vehicle parking normalization analysis module is used for analyzing the parking condition of each target vehicle and further analyzing the parking normalization coefficient of each target vehicle.
The vehicle parking early warning analysis module is used for analyzing the parking early warning coefficient of each target vehicle, and if the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold value, an early warning is sent out and a vehicle owner is contacted.
The vehicle estimated parking cost analysis module is used for acquiring the parking cost of unit time corresponding to different charging time grades from the database, and analyzing the estimated parking cost of each target vehicle by combining the charging time and the parking standardization coefficient.
The vehicle parking charge level analysis module is used for acquiring the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period from the database and analyzing the parking charge level of each target vehicle.
The vehicle parking fee analysis and adjustment module is used for acquiring charging discounts corresponding to different parking charging grades from the database, analyzing the parking fee of each target vehicle by combining the parking charging grade and the predicted parking fee of each target vehicle, and automatically deducting money.
The database is used for storing the area of the parking space, the parking cost corresponding to unit time of different charging time classes, the charging discount corresponding to different parking charging classes, the charging time of each target vehicle at each monitoring time point in the set historical time period, the parking normalization coefficient and the parking early warning coefficient.
Further, the ETC electronic tag information of each target vehicle comprises a license plate number of the vehicle, a vehicle owner contact mode and a payment mode of the vehicle owner.
Further, the specific analysis process of the charging duration of each target vehicle is as follows: according to the state that the real-time monitoring video monitors that each target vehicle enters the parking space, if the vehicle door is opened and closed and the vehicle keeps stable for more than the set time, starting timing, recording the starting charging time of each target vehicle, namely Ti1, monitoring the state that each target vehicle leaves the parking space, taking the time point that each target vehicle rear wheel leaves the parking space as the ending charging time of each target vehicle, namely Ti2, analyzing the charging time of each target vehicle, namely Ti, wherein the calculation formula is as follows: t i＝Ti2-Ti1, wherein i represents the number of the target vehicle, i=1, 2,..n.
Further, the parking condition of each target vehicle is specifically analyzed as follows: after each target vehicle starts timing, the contour extraction algorithm is used for extracting the contour of each target vehicle in the corresponding parking space from the monitoring video, the extracted contour is removed Yu Zao and holes are filled, and then the contour area of each target vehicle in the corresponding parking space is obtained by using the image measurement technology and is recorded as S i.
If a certain target vehicle exceeds a corresponding parking space and is parked in an adjacent parking space, the target vehicle is marked as an offending vehicle, and the contour area of each offending vehicle exceeding the corresponding parking space is similarly obtained by using a contour extraction algorithm and an image measurement technology and is marked as S j', wherein j represents the number of the offending vehicle, and j=1, 2.
Otherwise, the distance between the front left wheel and the front right wheel of each conventional vehicle and the front boundary of the parking space is obtained from the monitoring video by using an image measurement technology, the longest distance is recorded as the distance D k1 between the front wheel of each conventional vehicle and the front boundary of the parking space, the distance between the rear left wheel and the rear right wheel of each conventional vehicle and the rear boundary of the parking space is obtained in the same way, and the longest distance is recorded as the distance D k2 between the rear wheel of each conventional vehicle and the rear boundary of the parking space, wherein k represents the number of the conventional vehicle, k=1, 2, and v, and n=m+v.
Further, the parking normalization coefficient of each target vehicle is specifically analyzed as follows: the area of the parking space of the designated road side parking area is acquired from the database and is marked as S 0, the outline area of each offending vehicle in the corresponding parking space is screened out from the outline area of each target vehicle in the corresponding parking space and is marked as S j, and the outline area of each conventional vehicle in the corresponding parking space is screened out and is marked as S k.
And (3) analyzing the parking normalization coefficient of each illegal vehicle, marking as omega j, wherein the calculation formula is as follows: Where ΔS' represents the appropriate profile area of the set offending vehicle beyond the corresponding parking space,/> And respectively representing the set outline area of the illegal vehicle in the corresponding parking space and the influence duty factor of the outline area exceeding the corresponding parking space on the parking standardability of the illegal vehicle.
The parking normalization coefficient of each conventional vehicle is analyzed and marked as omega k, and the calculation formula is as follows: Where Δd represents an appropriate difference between the distance of the front-most wheel of the set regular vehicle from the front boundary of the parking space and the distance of the rear-most wheel from the rear boundary of the parking space, and γ 1、γ2 represents an influence duty factor of the difference between the profile distance of the set regular vehicle in the corresponding parking space and the distance of the front-most wheel from the front boundary of the parking space and the distance of the rear-most wheel from the rear boundary of the parking space on the parking standardability of the regular vehicle.
And further, according to the parking normalization coefficient of each illegal vehicle and the parking normalization coefficient of each regular vehicle, counting the parking normalization coefficient of each target vehicle, and marking as omega i.
Further, the parking early warning coefficient of each target vehicle comprises the following specific analysis process: the parking images of all target vehicles are obtained from the monitoring video, the positions of front wheels and rear wheels on the road side of all target vehicles are obtained from the parking images of all target vehicles, and the distances between the front wheels and the rear wheels on the road side of all target vehicles and the boundaries on the road side of the corresponding parking spaces are measured by using an image measuring technology and are respectively marked as X i1 and X i2.
Further, the parking early warning coefficient of each target vehicle is analyzed and marked as eta i, and the calculation formula is as follows: Wherein P 1 and P 2 represent that the front wheel and the rear wheel on the road side of the target vehicle are in the parking area, respectively,/> And/>The method comprises the steps of respectively representing that a front wheel and a rear wheel on the road side of a target vehicle are outside a parking area, wherein DeltaX represents the set suitable distance from the boundary on the road side of a parking space when the wheel on the road side of the target vehicle is in the parking area, deltaX' represents the set suitable distance from the boundary on the road side of the parking space when the wheel on the road side of the target vehicle is outside the parking area, and lambda 1、λ2 represents the influence duty factors of the distances from the front wheel and the rear wheel on the road side of the target vehicle to the boundary on the road side of the parking space on the parking early warning of the target vehicle.
When the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold, an early warning is sent out and the contact mode of the owner of the target vehicle is obtained, so that the owner is contacted to park again.
Further, the predicted parking cost of each target vehicle is specifically analyzed as follows: the method comprises the steps of screening the charging duration T j of each offending vehicle and the charging duration T k of each conventional vehicle from the charging duration T i of each target vehicle, acquiring the parking cost of unit time corresponding to different charging duration grades from a database, and further acquiring the parking cost r j of unit time corresponding to each offending vehicle and the parking cost r k of unit time corresponding to each conventional vehicle.
According to the parking normalization coefficient omega j of each offending vehicle, the estimated parking cost of each offending vehicle is analyzed and marked as R j, and the calculation formula is as follows: Where Δω represents the set offending vehicle reference parking normalization coefficient.
The estimated parking cost of each conventional vehicle is analyzed in a similar way and is recorded as R k, and the calculation formula is as follows: r k＝Tk*rk, and further, the estimated parking costs for each target vehicle are counted and noted as R i.
Further, the parking charge level of each target vehicle is specifically analyzed as follows: according to the identified license plate number of the corresponding vehicle in ETC electronic tag information of each target vehicle, the license plate number is matched with the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period, which are acquired in a database, so as to obtain the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each detection time point in the set historical time period, and the charging duration, the parking normalization coefficient and the parking early warning coefficient are respectively recorded asAnd/>Where α represents the number of monitoring time points within the set history time period, α=1, 2.
The parking charge grade coefficient of each target vehicle is analyzed and marked as kappa i, and the calculation formula is as follows:
Wherein Δω' represents a set target vehicle reference parking normalization coefficient, Δη represents a set target vehicle reference parking early warning coefficient, Δt represents a set target vehicle reference charging duration, and phi 1、φ2、φ3 represents the influence duty factors of the set parking normalization coefficient, the parking early warning coefficient and the charging duration on the parking charge level of the target vehicle, respectively.
And comparing the parking charge level coefficient of each target vehicle with the parking charge level coefficient range corresponding to the set different parking charge levels, and screening the parking charge level of each target vehicle.
Further, the parking cost of each target vehicle is specifically analyzed as follows: obtaining the charging discount corresponding to each target vehicle according to the charging discount corresponding to different parking charging grades and the parking charging grade of each target vehicle obtained in the database, marking as mu i, analyzing the parking cost of each target vehicle according to the estimated parking cost R i of each target vehicle, marking as R i', and the calculation formula is as follows: ri' =ri (1- μi)*χ, where χ represents a correction factor for the set parking cost of the target vehicle.
Further, the payment mode of the vehicle owner in the ETC electronic tag information of each target vehicle is mainly used for automatically deducting money by acquiring the payment mode of the corresponding vehicle owner after the parking cost of each target vehicle is calculated again.
Compared with the prior art, the invention has the following beneficial effects: (1) According to the method, the parking condition of each target vehicle is monitored in real time through the monitoring video, and the parking normalization coefficient of each target vehicle is analyzed, so that the normalized use condition of the parking spaces can be embodied, the actual utilization rate and the parking requirement of the parking spaces can be known, the configuration of parking resources can be optimized better, the utilization efficiency of the parking spaces is improved, illegal parking is reduced, and the situation that the target vehicles occupy a plurality of parking spaces is prevented.
(2) According to the method, the distances between the wheels of each target vehicle and the boundaries on the two sides of the corresponding parking space are analyzed, and then the parking early warning coefficient of each target vehicle is analyzed, when the parking early warning coefficient exceeds the set threshold value, the vehicle owners are contacted for adjustment, the situation that the vehicles exceed the parking space to occupy the urban road can be reduced, the parking accidents and the traffic jam phenomenon are reduced, the parking efficiency and the traffic fluency are improved, the traffic environment is improved, the road safety is improved, and better traveling experience is provided.
(3) According to the method, the charging time, the parking normalization coefficient and the parking early warning coefficient of each target vehicle are analyzed in the set historical time period, so that the parking charge level of each target vehicle can be reasonably adjusted according to the past parking time, parking normalization and early warning conditions of each target vehicle, parking resources are better managed and optimized, and meanwhile, vehicles with parking normalization and non-normalization are charged in a grading manner, so that more vehicle owners are stimulated to park in a standardized manner, potential safety hazards are reduced, and images on two sides of an urban road are divided.
(4) According to the invention, ETC equipment is used for charging, so that the safety and convenience of payment are improved, the reliability is improved, after the parking cost of the target vehicle is calculated, the manual payment is not needed, the mobile phone APP payment is not needed, and the owner payment mode corresponding to the target vehicle can be acquired from the electronic tag information by ETC, thereby realizing automatic fee deduction, reducing the rate of arrearage, improving the charging efficiency and reducing the cost investment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the modular connection of the system of 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 present invention provides an ETC-based intelligent charging management system for urban roadside parking, which comprises: the system comprises a vehicle information identification module, a vehicle charging duration analysis module, a vehicle parking normalization analysis module, a vehicle parking early warning analysis module, a vehicle estimated parking cost analysis module, a vehicle parking charge grade analysis module, a vehicle parking cost analysis and adjustment module and a database.
The vehicle information identification module is connected with the vehicle charging duration analysis module, the vehicle charging duration analysis module is connected with the vehicle parking standardization analysis module, the vehicle parking standardization analysis module is connected with the vehicle parking early warning analysis module, the vehicle parking early warning analysis module is connected with the vehicle estimated parking cost analysis module, the vehicle estimated parking cost analysis module is connected with the vehicle parking charge level analysis module, the vehicle parking charge level analysis module is connected with the vehicle parking cost analysis adjustment module, and the database is respectively connected with the vehicle parking standardization analysis module, the vehicle estimated parking cost analysis module, the vehicle parking charge level analysis module and the vehicle parking cost analysis adjustment module.
The vehicle information identification module is used for identifying vehicles entering the specified road side parking area by using ETC equipment installed in the specified road side parking area and marking the vehicles as target vehicles, and further identifying ETC electronic tag information of the target vehicles.
In a specific embodiment of the present invention, the ETC electronic tag information of each target vehicle includes a license plate number of the vehicle, a contact way of the vehicle owner, and a payment way of the vehicle owner.
It should be noted that, the specific manner of identifying the ETC electronic tag information of each target vehicle by the ETC device is as follows: each target vehicle is a vehicle entering a specified roadside parking area, a unique ETC electronic tag, usually a small RFID passive radio frequency tag, is installed, the ETC electronic tag comprises a license plate number of the vehicle, a vehicle owner contact mode and a payment mode of the vehicle owner, and ETC equipment installed in the specified roadside parking area reads electronic tag information installed on each target vehicle by using a radio frequency identification technology, so that the vehicles are identified.
The vehicle charging duration analysis module is used for analyzing the starting charging time of each target vehicle entering the parking space and the ending charging time of each target vehicle leaving the parking space according to the real-time monitoring video, and further analyzing the charging duration of each target vehicle.
In a specific embodiment of the present invention, the charging duration of each target vehicle is specifically analyzed as follows: according to the state that the real-time monitoring video monitors that each target vehicle enters the parking space, if the vehicle door is opened and closed and the vehicle keeps stable for more than the set time, timing is started, the starting charging time of each target vehicle is recorded and is marked as Ti1, the state that each target vehicle leaves the parking space is monitored again, the time point that each target vehicle rear wheel leaves the parking space is used as the ending charging time of each target vehicle and is marked as T i2, the charging time of each target vehicle is analyzed and is marked as T i, and the calculation formula is as follows: t i＝Ti2-Ti1, wherein i represents the number of the target vehicle, i=1, 2,..n.
It should be noted that, the specific way of monitoring the state of each target vehicle entering into the parking space and leaving from the parking space in real time through the monitoring video is as follows: identifying each target vehicle and the corresponding vehicle door in the monitoring video by using a target detection algorithm, determining the opening and closing states of the vehicle door by using an image processing technology, extracting the characteristics of a vehicle door area by using a characteristic extraction algorithm, training a model for identifying the vehicle door state by combining the vehicle door characteristics by using a deep learning technology to identify the opening and closing states of the vehicle door, taking the image data of each target vehicle door area as input, reasoning and outputting the estimated results of the opening and closing states of the vehicle door by using the model, and processing the image frames of each target vehicle in the monitoring video in real time to acquire the continuous opening and closing states of the vehicle door.
And similarly, identifying each target vehicle and the corresponding rear wheel in the monitoring video by using a target detection algorithm, tracking the position information of each target vehicle by using a target tracking algorithm, acquiring the moving track of each target vehicle on the parking space, monitoring the motion generated in the monitoring video by using an inter-frame difference method, when the rear wheel of each target vehicle starts to move, triggering the dynamic change in a scene, detecting the change by motion detection, judging that the rear wheel leaves the parking space according to the moving track of the vehicle and the result of the motion detection, and judging the moment that the rear wheel leaves the parking space by using a machine learning algorithm.
The vehicle parking normalization analysis module is used for analyzing the parking condition of each target vehicle and further analyzing the parking normalization coefficient of each target vehicle.
In a specific embodiment of the present invention, the parking situation of each target vehicle is specifically analyzed as follows: after each target vehicle starts timing, the contour extraction algorithm is used for extracting the contour of each target vehicle in the corresponding parking space from the monitoring video, the extracted contour is removed Yu Zao and holes are filled, and then the contour area of each target vehicle in the corresponding parking space is obtained by using the image measurement technology and is recorded as S i.
If a certain target vehicle exceeds a corresponding parking space and is parked in an adjacent parking space, the target vehicle is marked as an offending vehicle, and the contour area of each offending vehicle exceeding the corresponding parking space is similarly obtained by using a contour extraction algorithm and an image measurement technology and is marked as S j', wherein j represents the number of the offending vehicle, and j=1, 2.
Otherwise, the distance between the front left wheel and the front right wheel of each conventional vehicle and the front boundary of the parking space is obtained from the monitoring video by using an image measurement technology, the longest distance is recorded as the distance D k1 between the front wheel of each conventional vehicle and the front boundary of the parking space, the distance between the rear left wheel and the rear right wheel of each conventional vehicle and the rear boundary of the parking space is obtained in the same way, and the longest distance is recorded as the distance D k2 between the rear wheel of each conventional vehicle and the rear boundary of the parking space, wherein k represents the number of the conventional vehicle, k=1, 2, and v, and n=m+v.
The specific way of obtaining the distance between the front left and right wheels and the rear left and right wheels of each conventional vehicle and the distance between the rear left and right wheels and the rear boundary of the parking space is as follows: the monitoring video provides the position information of each conventional vehicle on the video image, a target detection algorithm is used for detecting and positioning the front left wheel and the right wheel of each conventional vehicle and the rear left wheel and the right wheel of each conventional vehicle, the boundaries of the parking spaces are marked on the video image, the pixel distances between the front left wheel and the rear left wheel and the right wheel of each conventional vehicle and the boundaries corresponding to the parking spaces are analyzed, and the pixel distances are converted into actual distances through preset camera parameters, the focal length of a camera and the resolution of the video image.
In a specific embodiment of the present invention, the parking normalization coefficient of each target vehicle is specifically analyzed as follows: the area of the parking space of the designated road side parking area is acquired from the database and is marked as S 0, the outline area of each offending vehicle in the corresponding parking space is screened out from the outline area of each target vehicle in the corresponding parking space and is marked as S j, and the outline area of each conventional vehicle in the corresponding parking space is screened out and is marked as S k.
And (3) analyzing the parking normalization coefficient of each illegal vehicle, marking as omega j, wherein the calculation formula is as follows: Where ΔS' represents the appropriate profile area of the set offending vehicle beyond the corresponding parking space,/> And respectively representing the set outline area of the illegal vehicle in the corresponding parking space and the influence duty factor of the outline area exceeding the corresponding parking space on the parking standardability of the illegal vehicle.
The parking normalization coefficient of each conventional vehicle is analyzed and marked as omega k, and the calculation formula is as follows: Where Δd represents an appropriate difference between the distance of the front-most wheel of the set regular vehicle from the front boundary of the parking space and the distance of the rear-most wheel from the rear boundary of the parking space, and γ 1、γ2 represents an influence duty factor of the difference between the profile distance of the set regular vehicle in the corresponding parking space and the distance of the front-most wheel from the front boundary of the parking space and the distance of the rear-most wheel from the rear boundary of the parking space on the parking standardability of the regular vehicle.
And further, according to the parking normalization coefficient of each illegal vehicle and the parking normalization coefficient of each regular vehicle, counting the parking normalization coefficient of each target vehicle, and marking as omega i.
According to the method, the parking condition of each target vehicle is monitored in real time through the monitoring video, and the parking normalization coefficient of each target vehicle is analyzed, so that the normalized use condition of the parking spaces can be embodied, the actual utilization rate and the parking requirement of the parking spaces can be known, the configuration of parking resources can be optimized better, the utilization efficiency of the parking spaces is improved, illegal parking is reduced, and the situation that the target vehicles occupy a plurality of parking spaces is prevented.
The vehicle parking early warning analysis module is used for analyzing the parking early warning coefficient of each target vehicle, and if the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold value, an early warning is sent out and a vehicle owner is contacted.
In a specific embodiment of the present invention, the parking early warning coefficient of each target vehicle is specifically analyzed as follows: the parking images of all target vehicles are obtained from the monitoring video, the positions of front wheels and rear wheels on the road side of all target vehicles are obtained from the parking images of all target vehicles, and the distances between the front wheels and the rear wheels on the road side of all target vehicles and the boundaries on the road side of the corresponding parking spaces are measured by using an image measuring technology and are respectively marked as X i1 and X i2.
Further, the parking early warning coefficient of each target vehicle is analyzed and marked as eta i, and the calculation formula is as follows: Wherein P 1 and P 2 represent that the front wheel and the rear wheel on the road side of the target vehicle are in the parking area, respectively,/> And/>The method comprises the steps of respectively representing that a front wheel and a rear wheel on the road side of a target vehicle are outside a parking area, wherein DeltaX represents the set suitable distance from the boundary on the road side of a parking space when the wheel on the road side of the target vehicle is in the parking area, deltaX' represents the set suitable distance from the boundary on the road side of the parking space when the wheel on the road side of the target vehicle is outside the parking area, and lambda 1、λ2 represents the influence duty factors of the distances from the front wheel and the rear wheel on the road side of the target vehicle to the boundary on the road side of the parking space on the parking early warning of the target vehicle.
When the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold, an early warning is sent out and the contact mode of the owner of the target vehicle is obtained, so that the owner is contacted to park again.
According to the method, the distances between the wheels of each target vehicle and the boundaries on the two sides of the corresponding parking space are analyzed, and then the parking early warning coefficient of each target vehicle is analyzed, when the parking early warning coefficient exceeds the set threshold value, the vehicle owners are contacted for adjustment, the situation that the vehicles exceed the parking space to occupy the urban road can be reduced, the parking accidents and the traffic jam phenomenon are reduced, the parking efficiency and the traffic fluency are improved, the traffic environment is improved, the road safety is improved, and better traveling experience is provided.
The vehicle estimated parking cost analysis module is used for acquiring the parking cost of unit time corresponding to different charging time grades from the database, and analyzing the estimated parking cost of each target vehicle by combining the charging time and the parking normalization coefficient.
In a specific embodiment of the present invention, the predicted parking cost of each target vehicle is specifically analyzed as follows: the method comprises the steps of screening the charging duration T j of each offending vehicle and the charging duration T k of each conventional vehicle from the charging duration T i of each target vehicle, acquiring the parking cost of unit time corresponding to different charging duration grades from a database, and further acquiring the parking cost r j of unit time corresponding to each offending vehicle and the parking cost r k of unit time corresponding to each conventional vehicle.
According to the parking normalization coefficient omega j of each offending vehicle, the estimated parking cost of each offending vehicle is analyzed and marked as R j, and the calculation formula is as follows: Where Δω represents the set offending vehicle reference parking normalization coefficient.
The estimated parking cost of each conventional vehicle is analyzed in a similar way and is recorded as R k, and the calculation formula is as follows: r k＝Tk*rk, and further, the estimated parking costs for each target vehicle are counted and noted as R i.
The vehicle parking charge level analysis module is used for acquiring the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period from the database and analyzing the parking charge level of each target vehicle.
In a specific embodiment of the present invention, the parking charge level of each target vehicle is specifically analyzed as follows: according to the identified license plate number of the corresponding vehicle in ETC electronic tag information of each target vehicle, the license plate number is matched with the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period, which are acquired in a database, so as to obtain the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each detection time point in the set historical time period, and the charging duration, the parking normalization coefficient and the parking early warning coefficient are respectively recorded asAnd/>Where α represents the number of monitoring time points within the set history time period, α=1, 2.
The parking charge grade coefficient of each target vehicle is analyzed and marked as kappa i, and the calculation formula is as follows:
Wherein Δω' represents a set target vehicle reference parking normalization coefficient, Δη represents a set target vehicle reference parking early warning coefficient, Δt represents a set target vehicle reference charging duration, and phi 1、φ2、φ3 represents the influence duty factors of the set parking normalization coefficient, the parking early warning coefficient and the charging duration on the parking charge level of the target vehicle, respectively.
And comparing the parking charge level coefficient of each target vehicle with the parking charge level coefficient range corresponding to the set different parking charge levels, and screening the parking charge level of each target vehicle.
The vehicle parking fee analysis and adjustment module is used for acquiring charging discounts corresponding to different parking charging grades from the database, analyzing the parking fee of each target vehicle by combining the parking charging grade and the predicted parking fee of each target vehicle, and automatically deducting money.
In a specific embodiment of the present invention, the parking cost of each target vehicle is specifically analyzed as follows: obtaining the charging discount corresponding to each target vehicle according to the charging discount corresponding to different parking charging grades and the parking charging grade of each target vehicle obtained in the database, marking as mu i, analyzing the parking cost of each target vehicle according to the estimated parking cost R i of each target vehicle, marking as R i', and the calculation formula is as follows: ri' =ri (1- μi)*χ, where χ represents a correction factor for the set parking cost of the target vehicle.
According to the method, the charging time, the parking normalization coefficient and the parking early warning coefficient of each target vehicle are analyzed in the set historical time period, so that the parking charge level of each target vehicle can be reasonably adjusted according to the past parking time, parking normalization and early warning conditions of each target vehicle, parking resources are better managed and optimized, and meanwhile, vehicles with parking normalization and non-normalization are charged in a grading manner, so that more vehicle owners are stimulated to park in a standardized manner, potential safety hazards are reduced, and images on two sides of an urban road are divided.
In a specific embodiment of the present invention, the payment method of the owner in the ETC electronic tag information of each target vehicle is mainly used for automatically deducting money by obtaining the payment method of the corresponding owner after calculating the parking cost of each target vehicle.
It should be noted that, the specific way of using ETC equipment to automatically deduct money is: when each target vehicle approaches to the ETC device, the ETC device establishes communication connection with the ETC electronic tag of each target vehicle, and information is exchanged through wireless signals, and the wireless communication can realize real-time vehicle identification and data transmission so as to automatically charge.
According to the invention, ETC equipment is used for charging, so that the safety and convenience of payment are improved, the reliability is improved, after the parking cost of the target vehicle is calculated, the manual payment is not needed, the mobile phone APP payment is not needed, and the owner payment mode corresponding to the target vehicle can be acquired from the electronic tag information by ETC, thereby realizing automatic fee deduction, reducing the rate of arrearage, improving the charging efficiency and reducing the cost investment.
The database is used for storing the area of the parking space, the parking cost corresponding to unit time of different charging time classes, the charging discount corresponding to different parking charging classes, and the charging time, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period.
The foregoing is merely illustrative and explanatory of the principles of this invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of this invention or beyond the scope of this invention as defined in the claims.
Claims (8)
1. ETC-based intelligent charging management system for urban roadside parking is characterized by comprising:
The vehicle information identification module is used for identifying vehicles entering the specified roadside parking area by using ETC equipment installed in the specified roadside parking area and marking the vehicles as target vehicles, and further identifying ETC electronic tag information of the target vehicles;
The vehicle charging duration analysis module is used for analyzing the starting charging time of each target vehicle entering the parking space and the ending charging time of each target vehicle leaving the parking space according to the real-time monitoring video, so as to analyze the charging duration of each target vehicle;
The vehicle parking normalization analysis module is used for analyzing the parking condition of each target vehicle and further analyzing the parking normalization coefficient of each target vehicle;
the vehicle parking early warning analysis module is used for analyzing the parking early warning coefficient of each target vehicle, and if the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold value, an early warning is sent out and is connected with a vehicle owner;
The vehicle estimated parking cost analysis module is used for acquiring the parking cost of unit time corresponding to different charging time grades from the database, and analyzing the estimated parking cost of each target vehicle by combining the charging time and the parking standardization coefficient;
the vehicle parking charge level analysis module is used for acquiring the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period from the database and analyzing the parking charge level of each target vehicle;
the vehicle parking fee analysis and adjustment module is used for acquiring charging discounts corresponding to different parking charging grades from the database, analyzing the parking fee of each target vehicle by combining the parking charging grade and the predicted parking fee of each target vehicle, and automatically deducting money;
The database is used for storing the area of the parking space, the parking cost corresponding to unit time of different charging time grades, the charging discount corresponding to different parking charging grades, the charging time of each target vehicle at each monitoring time point in the set historical time period, the parking normalization coefficient and the parking early warning coefficient;
the parking charge grade of each target vehicle is specifically analyzed as follows:
According to the identified license plate number of the corresponding vehicle in ETC electronic tag information of each target vehicle, the license plate number is matched with the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each monitoring time point in the set historical time period, which are acquired in a database, so as to obtain the charging duration, the parking normalization coefficient and the parking early warning coefficient of each target vehicle at each detection time point in the set historical time period, and the charging duration, the parking normalization coefficient and the parking early warning coefficient are respectively recorded as 、/>And/>Wherein/>Number indicating monitoring time point in set history time period,/>；
Analyzing the parking charge grade coefficient of each target vehicle and marking asThe calculation formula is as follows: Wherein/> Representing the set target vehicle with reference to the parking normalization coefficient,/>Representing the set target vehicle reference parking early warning coefficient,/>Representing the set target vehicle reference charging duration,/>、/>、/>Respectively representing the influence duty factors of the set parking normalization coefficient, parking early warning coefficient and charging duration on the parking charging level of the target vehicle;
Comparing the parking charge level coefficient of each target vehicle with the parking charge level coefficient range corresponding to the set different parking charge levels, and screening the parking charge level of each target vehicle;
The parking cost of each target vehicle is specifically analyzed as follows:
Obtaining the corresponding charging discounts of the target vehicles according to the charging discounts corresponding to the different parking charging levels and the parking charging levels of the target vehicles obtained from the database, and marking the charging discounts as Based on the estimated parking cost/>, of each target vehicleThe parking cost of each target vehicle was analyzed and noted as/>The calculation formula is as follows: /(I)Wherein/>A correction factor indicating the set parking cost of the target vehicle.
2. The ETC-based intelligent city roadside parking charging management system of claim 1, wherein: the ETC electronic tag information of each target vehicle comprises a license plate number of the vehicle, a vehicle owner contact mode and a payment mode of the vehicle owner.
3. The ETC-based intelligent city roadside parking charging management system of claim 1, wherein: the charging duration of each target vehicle comprises the following specific analysis processes:
According to the state of each target vehicle entering the parking space monitored by the real-time monitoring video, if the vehicle door is opened and closed and the vehicle keeps stable for more than the set time, starting timing, recording the starting charging time of each target vehicle, and recording as Then, the state that each target vehicle leaves the parking space is monitored, the time point when each target vehicle rear wheel leaves the parking space is taken as the ending charging time of each target vehicle, and the ending charging time is recorded as/>Further analyzing the charging duration of each target vehicle and marking as/>The calculation formula is as follows: Wherein/> Number indicating target vehicle,/>。
4. The ETC-based intelligent city roadside parking charging management system of claim 3, wherein: the parking condition of each target vehicle is specifically analyzed as follows:
After each target vehicle starts timing, extracting the outline of each target vehicle in the corresponding parking space from the monitoring video by using an outline extraction algorithm, removing Yu Zao and filling holes on the extracted outline, and acquiring the outline area of each target vehicle in the corresponding parking space by using an image measurement technology, and marking as ；
If a certain target vehicle exceeds the corresponding parking space and is parked in the adjacent parking space, the target vehicle is marked as an offending vehicle, and similarly, the contour area of each offending vehicle exceeding the corresponding parking space is obtained by using a contour extraction algorithm and an image measurement technology and is marked asWherein/>Number representing offending vehicle,/>；
Otherwise, the distance between the front left wheel and the front right wheel of each conventional vehicle and the front boundary of the parking space is obtained from the monitoring video by using an image measurement technology, and the longest distance is recorded as the distance between the front wheels of each conventional vehicle and the front boundary of the parking spaceThe distance between the left wheel and the right wheel behind each conventional vehicle and the rear boundary of the parking space is obtained in the same way, and the longest distance is recorded as the distance/>, between the rear wheel of each conventional vehicle and the rear boundary of the parking spaceWherein/>The number of the conventional vehicle is indicated,，/>。
5. The ETC-based intelligent city roadside parking charging management system of claim 4, wherein: the parking normalization coefficient of each target vehicle comprises the following specific analysis processes:
Obtaining the area of the parking space of the specified roadside parking area from the database, and marking the area as Screening the outline area of each offending vehicle in the corresponding parking space from the outline area of each target vehicle in the corresponding parking space, and marking the outline area as/>Screening out the outline area of each conventional vehicle in the corresponding parking space, and marking as/>；
Analyzing the parking normalization coefficient of each offending vehicle and marking asThe calculation formula is as follows: Wherein/> Indicating that the set offending vehicle exceeds the proper contour area of the corresponding parking space,/>、/>The method comprises the steps of respectively representing the set outline area of the illegal vehicle in the corresponding parking space and the influence duty factor of the outline area exceeding the corresponding parking space on the parking standardability of the illegal vehicle;
Analyzing the parking normalization coefficient of each conventional vehicle and marking as The calculation formula is as follows: Wherein/> Indicating an appropriate difference between the distance of the set front wheel of the regular vehicle from the front boundary of the parking space and the distance of the rear wheel from the rear boundary of the parking space,/>、/>The influence duty factor of the outline distance of the set conventional vehicle in the corresponding parking space and the difference value of the distance between the forefront wheel and the front boundary of the parking space and the distance between the rearmost wheel and the rear boundary of the parking space on the parking standardability of the conventional vehicle is represented;
further, according to the parking normalization coefficient of each offending vehicle and the parking normalization coefficient of each regular vehicle, the parking normalization coefficient of each target vehicle is counted and recorded as 。
6. The ETC-based intelligent city roadside parking charging management system of claim 3, wherein: the parking early warning coefficient of each target vehicle comprises the following specific analysis processes:
Obtaining the parking image of each target vehicle from the monitoring video, obtaining the positions of the front wheel and the rear wheel of each target vehicle on the road side from the parking image of each target vehicle, measuring the distance between the front wheel and the rear wheel of each target vehicle on the road side and the boundary of the corresponding parking space on the road side by using an image measuring technology, and respectively marking as And/>；
Further analyzing the parking early warning coefficient of each target vehicle and marking asThe calculation formula is as follows: Wherein/> And/>Indicating that the front wheel and the rear wheel on the road side of the target vehicle are in the parking area respectively,/>And/>Respectively indicating that the front wheel and the rear wheel on one side of the target vehicle close to the road are outside the parking area,/>Indicating the set proper distance from the road side boundary of the parking space when the road side wheel of the target vehicle is in the parking area,/>Indicating the set proper distance from the road side boundary of the parking space when the road side wheel of the target vehicle is outside the parking area,/>、/>The influence duty factors of the distances between the front wheels and the rear wheels on the road side of the target vehicle and the boundary on the road side of the parking space on the parking early warning of the target vehicle are respectively represented;
When the parking early warning coefficient of a certain target vehicle exceeds a set parking early warning coefficient threshold, an early warning is sent out and the contact mode of the owner of the target vehicle is obtained, so that the owner is contacted to park again.
7. The ETC-based intelligent city roadside parking charging management system of claim 5, wherein: the predicted parking cost of each target vehicle is specifically analyzed by the following steps:
from the length of time of billing of each target vehicle Screening the charging duration/>, of each offending vehicleAnd the billing duration/>, for each conventional vehicleObtaining parking fees corresponding to unit time of different charging time classes from a database, and further obtaining parking fees/>, corresponding to unit time, of each offending vehicleParking fee per unit time per conventional vehicle/>；
According to the parking normalization coefficient of each offending vehicleThe estimated parking cost of each offending vehicle is analyzed and recorded as/>The calculation formula is as follows: /(I)Wherein/>Indicating a set parking standardization coefficient of the illegal vehicle;
The estimated parking cost of each conventional vehicle is analyzed in a similar way and recorded as The calculation formula is as follows: /(I)Further, the estimated parking cost of each target vehicle was counted and recorded as/>。
8. The ETC-based intelligent city roadside parking charging management system of claim 2, wherein: the payment method of the vehicle owners in the ETC electronic tag information of each target vehicle is mainly used for obtaining the payment method of the corresponding vehicle owners to realize automatic deduction after the parking cost of each target vehicle is calculated again.
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