CN115050188B - Method for predicting remaining parking spaces of indoor parking lot - Google Patents
Method for predicting remaining parking spaces of indoor parking lot Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
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- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
Abstract
The invention relates to the field of data processing methods suitable for prediction purposes, and aims to solve the problems that the existing indoor parking lot cannot accurately predict the remaining parking space in a certain time period in the future and is easy to cause difficulty in parking in the indoor parking lot, in particular to a method for predicting the remaining parking space in the indoor parking lot; the prediction method carries out prediction through a residual parking space prediction system of the indoor parking lot, wherein the residual parking space prediction system of the indoor parking lot comprises an information acquisition module, a processor, a data analysis module, a parking space reservation module and a margin display module; the prediction method realizes accurate prediction of the remaining parking spaces in the indoor parking lot in the future time period, provides reliable travel information for the user by means of an accurate prediction result, helps the user to make travel planning, reduces the time wasted by the user in searching for the parking spaces, and relieves urban traffic pressure.
Description
Technical Field
The invention relates to the field of data processing methods suitable for prediction purposes, in particular to a method for predicting remaining parking spaces of an indoor parking lot.
Background
With the increasing living standard of people, the quantity of motor vehicles in cities is increased year by year, the number of parking spaces cannot meet the demand, and the difficulty in parking becomes a big problem day by day. Patent CN106503840A provides a method and system for predicting available parking spaces in a parking lot, where the method includes: acquiring historical parking data of a target parking lot at each sampling moment in a sampling period; calculating a correlation coefficient between any two parking data samples in the historical parking data; classifying the historical parking data according to a preset correlation threshold and a correlation coefficient to obtain at least one parking data sample subset; smoothing each parking data sample subset to respectively obtain the average parking number of vehicles at each sampling time of different parking data samples of each parking data sample subset in one day; respectively establishing a stable poisson process model between all adjacent sampling points according to the average parking number of the vehicles and the acquisition time information of the historical parking data to form a non-stable poisson process model corresponding to each parking data sample subset; and estimating the available parking spaces of the target parking lot at the moment to be predicted according to the non-stable Poisson process model corresponding to each parking data sample subset.
However, the available parking space prediction method for the parking lot cannot accurately predict the remaining parking space of the indoor parking lot in a certain period of time in the future, the problem of parking of the indoor parking lot cannot be solved efficiently is easily caused, the phenomena of road traffic congestion and everywhere parking occur, and great troubles and troubles are caused for the standardized management of the indoor parking lot.
The key point of the invention is how to improve the problem that the existing method for predicting the available parking space of the parking lot cannot accurately predict the remaining parking space of the indoor parking lot in a certain period of time in the future, and the problem that the indoor parking lot cannot efficiently solve the parking is easily caused.
Disclosure of Invention
In order to overcome the technical problem, the invention aims to provide a method for predicting the remaining parking space of an indoor parking lot, which comprises the following steps: the processor can obtain historical parking information of the vehicle through the vehicle information, further obtain a predicted parking time period and a predicted parking probability, the predicted parking time period and the predicted parking probability can indicate the parking habit of the vehicle owner, so that the future parking condition of the vehicle owner can be predicted, the time-sharing parking probability value obtained through the data analysis module can comprehensively predict the future parking conditions of all the vehicle owners entering the vehicle in the indoor parking lot, and the predicted time-sharing value can be obtained through comprehensive analysis of the total number of parking spaces, the vehicle entering value, the vehicle leaving value, the vehicle preset value, the time-sharing parking probability value and the partial average coefficient.
The purpose of the invention can be realized by the following technical scheme:
a method for predicting remaining parking spaces of an indoor parking lot comprises the following steps:
the method comprises the following steps: the information acquisition module acquires vehicle information i of vehicles entering or leaving the indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, acquires the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, marks the vehicle information i as a vehicle entering value CJ and a vehicle leaving value CL, and sends the vehicle information i, the vehicle entering value CJ and the vehicle leaving value CL to the processor;
step two: the processor receives vehicle information i and obtains historical parking information of a vehicle according to the license plate number, wherein the historical parking information comprises total parking times, parking entrance time each time, parking departure time each time and parking star number, counts the parking entrance time each time, marks the starting time of a time period with the most frequent occurrence of the parking entrance time in a unit time period as predicted entrance time, counts the parking exit time each time, marks the ending time of the time period with the most frequent occurrence of the parking exit time in the unit time period as predicted exit time, obtains predicted parking time period Di according to the predicted entrance time and the predicted exit time, divides and classifies the total parking times according to the parking star number, obtains the parking times of each parking star number, obtains the parking probability of each parking star number according to the ratio of the parking times to the total parking times, and marks the parking probability Gi as the predicted parking probability;
step three: the processor sends the predicted parking time interval Di and the predicted parking probability Gi to the data analysis module;
step four: the data analysis module enables the parking probabilities in the predicted parking time period Di to be equal to the predicted parking probability Gi, at the time, the time-sharing parking probability GDi = the predicted parking probability Gi, the parking probabilities except the time in the predicted parking time period Di are marked to be zero, and at the time, the time-sharing parking probability GDi =0;
step five: the data analysis module acquires the time-sharing parking probability GDi corresponding to each piece of vehicle information i and sums the time-sharing parking probabilities to obtain time-sharing parking probability values CG of all pieces of vehicle information i;
step six: the data analysis module sends the time-sharing parking probability value CG to the processor;
step seven: the user presets the rest parking spaces of the indoor parking lot through the terminal, the parking space reserving module generates a preset time period after the parking spaces are reserved successfully, and the parking space reserving module sends the preset time period to the processor;
step eight: the processor obtains the historical daily vehicle parking times of the indoor parking lot, sums the historical daily vehicle parking times, calculates an average value, marks the average value as a total average value ZJ, obtains the vehicle parking times of the first three days of the indoor parking lot, sorts the vehicle parking times according to the parking times, marks the parking times in the middle as a single average value DJ, and substitutes the total average value ZJ and the single average value DJ into a formula
Obtaining a partial mean coefficient PJ;
step nine: the processor adds one to the preset number of vehicles in the time period according to the preset time period, and marks the preset number of vehicles as a preset vehicle value CY;
step ten: the processor obtains the total number CW of the parking spaces of the indoor parking lot, and substitutes the total number CW of the parking spaces, the vehicle entering value CJ, the vehicle leaving value CL, the vehicle preset value CY, the time-sharing parking probability value CG and the deviation coefficient PJ into a formula
（CW-CJ+CL-CY-CG）]Obtaining a predicted time division value YC, wherein gamma is a preset correction factor, and gamma is taken as 0.998;
step eleven: the processor sends the predicted time division value YC to the allowance display module;
step twelve: the allowance display module obtains an integer digit numerical value and a first numerical value after a decimal point according to the received forecast time division value YC, the integer digit numerical value and the first numerical value are respectively marked as a forecast position value and an adjustment numerical value, if the adjustment numerical value is larger than or equal to 5, the forecast position value is increased by one, if the adjustment numerical value is smaller than 5, the forecast position value is increased by zero, then the forecast position value is updated and displayed on an entrance parking space display screen of the indoor parking lot, meanwhile, the forecast position value is sent to the terminal through the Internet and is updated and displayed on the terminal, the display content is the forecast position value, and the forecast position value is expressed as the forecast remaining parking space number of the indoor parking lot.
As a further scheme of the invention: the method for predicting the remaining parking spaces of the indoor parking lot predicts the remaining parking spaces of the indoor parking lot through a system for predicting the remaining parking spaces of the indoor parking lot;
the system for predicting the remaining parking spaces of the indoor parking lot comprises an information acquisition module, a processor, a data analysis module, a parking space reservation module and a surplus display module;
the system comprises an information acquisition module, a processor and a data processing module, wherein the information acquisition module is used for acquiring vehicle information i of vehicles entering or leaving an indoor parking lot, counting vehicle entering values CJ and vehicle leaving values CL, and sending the vehicle information i, the vehicle entering values CJ and the vehicle leaving values CL to the processor;
the processor is used for acquiring a predicted parking time period Di and a predicted parking probability Gi according to the vehicle information i and sending the predicted parking time period Di and the predicted parking probability Gi to the data analysis module, and is also used for acquiring a deviation average coefficient PJ according to the historical vehicle parking times of the indoor parking lot, acquiring a vehicle preset value CY according to the preset time period, acquiring a predicted time division value YC according to the total number CW of parking spaces of the indoor parking lot, and sending the total number CW of the parking spaces, a vehicle entrance value CJ, a vehicle separation value CL, the vehicle preset value CY, a time-sharing parking probability value CG and the deviation average coefficient PJ to the allowance display module;
the data analysis module is used for acquiring time-sharing parking probability GDi according to the predicted parking time period Di and the predicted parking probability Gi, acquiring time-sharing parking probability values CG of all vehicle information i according to the time-sharing parking probability GDi and sending the time-sharing parking probability values CG to the processor;
the parking space reservation module is used for reserving the remaining parking spaces of the indoor parking lot and sending a reservation time period generated by successful parking space reservation to the processor;
and the allowance display module is used for obtaining a predicted bit value according to the predicted time division value YC and updating and displaying the remaining parking spaces of the indoor parking lot according to the predicted bit value.
As a further scheme of the invention: the specific working process of the information acquisition module is as follows:
the method comprises the steps of collecting vehicle information i of vehicles entering or leaving the indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, collecting the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, respectively marking the vehicle information i as a vehicle entering value CJ and a vehicle leaving value CL, and sending the vehicle information i, the vehicle entering value CJ and the vehicle leaving value CL to a processor.
As a further scheme of the invention: the specific working process of the parking space reservation module is as follows:
the user performs reservation on the remaining parking spaces of the indoor parking lot through the terminal, the parking space reservation module generates a reservation time period after the parking spaces are reserved successfully, and the parking space reservation module sends the reservation time period to the processor.
As a further scheme of the invention: the specific working process of the processor is as follows:
obtaining historical parking information of a vehicle according to a license plate number after receiving vehicle information i, wherein the historical parking information comprises total parking times, parking entrance time each time, parking departure time each time and parking week number, counting the parking entrance time each time, marking the starting time of the time period with the most frequent occurrence of the parking entrance time in a unit time period as predicted entrance time, counting the parking departure time each time, marking the ending time of the time period with the most frequent occurrence of the parking exit time in the unit time period as predicted exit time, obtaining predicted parking time period Di according to the predicted entrance time and the predicted exit time, classifying the total parking times according to the parking week number, obtaining the parking times of each parking week number, obtaining the parking probability of each parking week number according to the ratio of the parking times and the total parking times, and marking the parking probability as predicted parking probability Gi;
the predicted parking time period Di and the predicted parking probability Gi are sent to a data analysis module;
obtaining historical daily vehicle parking times of an indoor parking lot, summing and calculating an average value, marking the average value as a total average value ZJ, obtaining the vehicle parking times of the front three days of the indoor parking lot, sequencing according to the parking times, marking the parking times in the middle as a single average value DJ, substituting the total average value ZJ and the single average value DJ into a formula
Obtaining a partial mean coefficient PJ;
adding one to the preset number of vehicles in the preset time period according to the preset time period, and marking the preset number of vehicles as a preset vehicle value CY;
acquiring the total number CW of the parking spaces of the indoor parking lot, and substituting the total number CW of the parking spaces, a vehicle entering value CJ, a vehicle leaving value CL, a vehicle preset value CY, a time-sharing parking probability value CG and a deviation coefficient PJ into a formula
（CW-CJ+CL-CY-CG）]Obtaining a predicted time division value YC, wherein gamma is a preset correction factor, and gamma is taken as 0.998;
sending the predicted time division value YC to a margin display module;
wherein, the formula
Whether the number of parking times of the past three days is increased or decreased relative to the average value of the number of parking times of all the past days is represented, if yes, the number of parking times is expected to be increased, 1-PJ represents that the amount of the remaining parking spaces is reduced, and if not, the number of parking times is expected to be reduced, 1-PJ represents that the amount of the remaining parking spaces is increased;
CG represents the sum of the predicted parking probabilities of all parked vehicles, the number of parking spaces needs to be provided for the vehicles at a future time under the general condition, for example, the first predicted parking probability is 20%, the 0.2 number of parking spaces needs to be provided for the vehicles at a future time, the second predicted parking probability is 30%, the 0.3 number of parking spaces needs to be provided for the vehicles at a future time, the third predicted parking probability is 15%, the 0.15 number of parking spaces needs to be provided for the vehicles at a future time after all people are accumulated, the 23.8 number of parking spaces needs to be provided for the vehicles at a future time after all people are accumulated, and the time-sharing parking probability value CG has universality under the condition that the population of the number of the vehicles is large;
CW-CJ + CL-CY-CG represents that the total parking space is removed of the number of parked vehicles, then the number of left vehicles in the number of parked vehicles is added, the preset number of parking spaces is subtracted, and the number of vehicles which are predicted to be provided at a future time is subtracted;
As a further scheme of the invention: the specific working process of the data analysis module is as follows:
the parking probabilities in the predicted parking time period Di are all equal to the predicted parking probability Gi, the time-sharing parking probability GDi = the predicted parking probability Gi, the parking probabilities except the time in the predicted parking time period Di are marked as zero, and the time-sharing parking probability GDi =0;
acquiring time-sharing parking probability GDi corresponding to each vehicle information i, and summing the time-sharing parking probabilities to obtain time-sharing parking probability values CG of all the vehicle information i;
and sending the time-sharing parking probability value CG to a processor.
As a further scheme of the invention: the specific working process of the allowance display module is as follows:
and acquiring a first numerical value after an integer numerical value and a decimal point of the integral numerical value and the first numerical value according to the received predicted time division value YC, respectively marking the first numerical value as a predicted bit value and an adjusted numerical value, if the adjusted numerical value is more than or equal to 5, adding one to the predicted bit value, if the adjusted numerical value is less than 5, adding zero to the predicted bit value, then updating and displaying the predicted bit value on an entrance parking space display screen of the indoor parking lot, simultaneously sending the predicted bit value to the terminal through the Internet and updating and displaying the terminal, wherein the displayed content is the predicted bit value, and the predicted bit value is expressed as the predicted remaining parking space number of the indoor parking lot.
The invention has the beneficial effects that:
the invention discloses a method for predicting remaining parking spaces of an indoor parking lot, which comprises the steps of acquiring vehicle information of vehicles entering the indoor parking lot, obtaining historical parking information of the vehicles through the vehicle information by a processor, further obtaining a predicted parking time period and a predicted parking probability, wherein the predicted parking time period and the predicted parking probability can indicate the parking habits of the vehicle owners, so that the future parking conditions of the vehicle owners can be predicted, obtaining a time-sharing parking probability value through a data analysis module, comprehensively predicting the future parking conditions of all the vehicles entering the indoor parking lot, obtaining a predicted time-sharing value through comprehensive analysis of total parking spaces, vehicle entering values, vehicle leaving values, vehicle preset values, time-sharing parking probability values and average coefficients, obtaining the predicted time-sharing probability value through the total parking space number, vehicle entering values, vehicle leaving values, vehicle preset values, vehicle leaving values, time-sharing parking probability values and average coefficients, obtaining the predicted time periods of the future parking spaces of the indoor parking lot through the analysis of the total parking spaces and the historical parking conditions, providing reliable information for users through accurate prediction results, helping users to plan the traveling of the remaining parking spaces, reducing the time wasted by the users, and relieving the pressure of searching for the urban traffic.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of a system for predicting remaining parking spaces in an indoor parking lot.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
referring to fig. 1, the present embodiment is a system for predicting remaining parking spaces in an indoor parking lot, including an information acquisition module, a processor, a data analysis module, a parking space reservation module, and a remaining space display module;
the information acquisition module is used for acquiring vehicle information i of vehicles entering or leaving the indoor parking lot, counting vehicle entering values CJ and vehicle leaving values CL, and sending the vehicle information i, the vehicle entering values CJ and the vehicle leaving values CL to the processor, and specifically comprises the following steps:
collecting vehicle information i of vehicles entering or leaving an indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, collecting the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, respectively marking the vehicle information i as a vehicle entering value CJ and a vehicle leaving value CL, and sending the vehicle information i, the vehicle entering value CJ and the vehicle leaving value CL to a processor;
the processor is used for acquiring the predicted parking time period Di and the predicted parking probability Gi according to the vehicle information i and sending the predicted parking time period Di and the predicted parking probability Gi to the data analysis module, and the data analysis module specifically comprises the following steps:
obtaining historical parking information of a vehicle according to a license plate number by receiving vehicle information i, wherein the historical parking information comprises total parking times, parking entrance time each time, parking exit time each time and parking star number, counting the parking entrance time each time, marking the starting time of a time period with the most frequent occurrence of the parking entrance time in a unit time period as predicted entrance time, counting the parking exit time each time, marking the ending time of the time period with the most frequent occurrence of the parking exit time in the unit time period as predicted exit time, obtaining a predicted parking time period Di according to the predicted entrance time and the predicted exit time, classifying the total parking times according to the parking star number, obtaining the parking times of each parking star number, obtaining the parking probability of each parking star number according to the ratio of the parking times and the total parking times, and marking the parking probability Gi as the predicted parking probability;
the predicted parking time period Di and the predicted parking probability Gi are sent to a data analysis module;
the data analysis module is used for acquiring time-sharing parking probability GDi according to the predicted parking time period Di and the predicted parking probability Gi, acquiring time-sharing parking probability values CG of all vehicle information i according to the time-sharing parking probability GDi, and sending the time-sharing parking probability values CG to the processor, and the data analysis module specifically comprises the following steps:
the parking probabilities in the predicted parking time period Di are all equal to the predicted parking probability Gi, the time-sharing parking probability GDi = the predicted parking probability Gi, the parking probabilities except the time in the predicted parking time period Di are marked as zero, and the time-sharing parking probability GDi =0;
acquiring time-sharing parking probability GDi corresponding to each vehicle information i, and summing the time-sharing parking probabilities to obtain time-sharing parking probability values CG of all the vehicle information i;
sending the time-sharing parking probability value CG to a processor;
the parking space reservation module is used for reserving the remaining parking spaces in the indoor parking lot and sending a reservation time period generated by successful parking space reservation to the processor, and the parking space reservation module specifically comprises the following components:
the user presets the rest parking spaces of the indoor parking lot through the terminal, the parking space reserving module generates a preset time period after the parking spaces are reserved successfully, and the parking space reserving module sends the preset time period to the processor;
the processor is further used for obtaining a deviation average coefficient PJ according to the historical vehicle parking times of the indoor parking lot, obtaining a vehicle preset value CY according to a preset time period, obtaining a predicted deviation average value YC according to the total parking space CW of the indoor parking lot, the vehicle entering value CJ, the vehicle leaving value CL, the vehicle preset value CY, the time-sharing parking probability value CG and the deviation average coefficient PJ, and sending the predicted deviation average value YC to the allowance display module, wherein the predicted deviation average value YC is as follows:
obtaining historical daily vehicle parking times of an indoor parking lot, summing and calculating an average value, marking the average value as a total average value ZJ, obtaining the vehicle parking times of the front three days of the indoor parking lot, sequencing according to the parking times, marking the parking times in the middle as a single average value DJ, substituting the total average value ZJ and the single average value DJ into a formula
Obtaining a partial mean coefficient PJ;
adding one to the preset number of vehicles in the time period according to the preset time period, and marking the preset number of vehicles as a preset vehicle value CY;
acquiring the total number CW of the parking spaces of the indoor parking lot, and substituting the total number CW of the parking spaces, a vehicle entering value CJ, a vehicle leaving value CL, a vehicle preset value CY, a time-sharing parking probability value CG and a deviation average coefficient PJ into a formula
（CW-CJ+CL-CY-CG）]Obtaining a predicted time division value YC, wherein gamma is a preset correction factor, and gamma is taken as 0.998;
sending the predicted time division value YC to a margin display module;
and the allowance display module is used for updating and displaying the remaining parking spaces of the indoor parking lot according to the predicted time division value YC, and specifically comprises the following steps:
and acquiring a first numerical value after an integer numerical value and a decimal point of the predicted parking space according to the received predicted time division value YC, respectively marking the first numerical value as a predicted bit value and an adjusted numerical value, if the adjusted numerical value is more than or equal to 5, adding one to the predicted bit value, if the adjusted numerical value is less than 5, adding zero to the predicted bit value, then updating and displaying the predicted bit value on a display screen of the entrance parking space of the indoor parking lot, simultaneously sending the predicted bit value to the terminal through the Internet and updating and displaying the terminal, wherein the displayed content is the predicted bit value, and the predicted bit value is expressed as the predicted remaining parking space number of the indoor parking lot.
Example 2:
referring to fig. 1, the present embodiment is a method for predicting remaining parking spaces in an indoor parking lot, including the following steps:
the method comprises the following steps: the information acquisition module acquires vehicle information i of vehicles entering or leaving the indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, acquires the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, marks the vehicle information i as a vehicle entering value CJ and a vehicle leaving value CL respectively, and sends the vehicle information i, the vehicle entering value CJ and the vehicle leaving value CL to the processor;
step two: the processor receives vehicle information i and obtains historical parking information of a vehicle according to the license plate number, the historical parking information comprises total parking times, parking entrance time each time, parking departure time each time and parking star number, statistics is carried out on the parking entrance time each time, the starting time of a time period with the most frequent occurrence of the parking entrance time in a unit time period is marked as predicted entrance time, statistics is carried out on the parking exit time each time, the ending time of a time period with the most frequent occurrence of the parking departure time in the unit time period is marked as predicted departure time, a predicted parking time period Di is obtained according to the predicted entrance time and the predicted departure time, the total parking times are classified according to the parking star number, the parking times of each parking star number are obtained, the parking probability of each parking star number is obtained according to the ratio of the parking times and the total parking times, and the parking probability is marked as predicted parking probability Gi;
step three: the processor sends the predicted parking time period Di and the predicted parking probability Gi to the data analysis module;
step four: the data analysis module enables the parking probabilities in the predicted parking time period Di to be equal to the predicted parking probability Gi, at the time, the time-sharing parking probability GDi = the predicted parking probability Gi, the parking probabilities except the time in the predicted parking time period Di are marked to be zero, and at the time, the time-sharing parking probability GDi =0;
step five: the data analysis module acquires the time-sharing parking probability GDi corresponding to each piece of vehicle information i and sums the time-sharing parking probabilities to obtain time-sharing parking probability values CG of all pieces of vehicle information i;
step six: the data analysis module sends the time-sharing parking probability value CG to the processor;
step seven: the user presets the rest parking spaces of the indoor parking lot through the terminal, the parking space reserving module generates a preset time period after the parking spaces are reserved successfully, and the parking space reserving module sends the preset time period to the processor;
step eight: the processor obtains the historical daily vehicle parking times of the indoor parking lot, sums the historical daily vehicle parking times, calculates an average value, marks the average value as a total average value ZJ, obtains the vehicle parking times of the first three days of the indoor parking lot, sorts the vehicle parking times according to the parking times, marks the parking times in the middle as a single average value DJ, and substitutes the total average value ZJ and the single average value DJ into a formula
Obtaining a partial mean coefficient PJ;
step nine: the processor adds one to the preset number of vehicles in the time period according to the preset time period, and marks the preset number of vehicles as a preset vehicle value CY;
step ten: the processor obtains the total number CW of the parking spaces of the indoor parking lot, and substitutes the total number CW of the parking spaces, the vehicle entering value CJ, the vehicle leaving value CL, the vehicle preset value CY, the time-sharing parking probability value CG and the deviation coefficient PJ into a formula
（CW-CJ+CL-CY-CG）]Obtaining a predicted time division value YC, wherein gamma is a preset correction factor, and gamma is 0.998;
step eleven: the processor sends the predicted time division value YC to the allowance display module;
step twelve: the allowance display module obtains an integer digit numerical value and a first numerical value after a decimal point according to the received forecast time division value YC, the integer digit numerical value and the first numerical value are respectively marked as a forecast position value and an adjustment numerical value, if the adjustment numerical value is larger than or equal to 5, the forecast position value is increased by one, if the adjustment numerical value is smaller than 5, the forecast position value is increased by zero, then the forecast position value is updated and displayed on an entrance parking space display screen of the indoor parking lot, meanwhile, the forecast position value is sent to the terminal through the Internet and is updated and displayed on the terminal, the display content is the forecast position value, and the forecast position value is expressed as the forecast remaining parking space number of the indoor parking lot.
The above formulas are all obtained by collecting a large amount of data and performing software simulation, and the formula is selected to be close to the true value, and the coefficients in the formulas are set by the person skilled in the art according to the actual situation.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is illustrative and explanatory only, and it will be understood by those skilled in the art that various modifications, additions and substitutions can be made to the specific embodiments described without departing from the scope of the present invention as defined in the accompanying claims.
Claims (7)
1. The method for predicting the remaining parking spaces in the indoor parking lot is characterized by comprising the following steps of:
the method comprises the following steps: the information acquisition module acquires vehicle information i of vehicles entering or leaving the indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, acquires the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, marks the vehicle information i as a vehicle entering value CJ and a vehicle leaving value CL respectively, and sends the vehicle information i, the vehicle entering value CJ and the vehicle leaving value CL to the processor;
step two: the processor receives vehicle information i and obtains historical parking information of a vehicle according to the license plate number, the historical parking information comprises total parking times, parking entrance time each time, parking departure time each time and parking star number, statistics is carried out on the parking entrance time each time, the starting time of a time period with the most frequent occurrence of the parking entrance time in a unit time period is marked as predicted entrance time, statistics is carried out on the parking exit time each time, the ending time of a time period with the most frequent occurrence of the parking departure time in the unit time period is marked as predicted departure time, a predicted parking time period Di is obtained according to the predicted entrance time and the predicted departure time, the total parking times are classified according to the parking star number, the parking times of each parking star number are obtained, the parking probability of each parking star number is obtained according to the ratio of the parking times and the total parking times, and the parking probability is marked as predicted parking probability Gi;
step three: the processor sends the predicted parking time interval Di and the predicted parking probability Gi to the data analysis module;
step four: the data analysis module enables the parking probabilities in the predicted parking time period Di to be equal to the predicted parking probability Gi, the time-sharing parking probability GDi = the predicted parking probability Gi, the parking probabilities except the time in the predicted parking time period Di are marked as zero, and the time-sharing parking probability GDi =0;
step five: the data analysis module acquires the time-sharing parking probability GDi corresponding to each piece of vehicle information i and sums the time-sharing parking probabilities to obtain time-sharing parking probability values CG of all pieces of vehicle information i;
step six: the data analysis module sends the time-sharing parking probability value CG to the processor;
step seven: the user presets the rest parking spaces of the indoor parking lot through the terminal, the parking space reserving module generates a reserving time period after the parking spaces are reserved successfully, and the parking space reserving module sends the reserving time period to the processor;
step eight: the processor obtains the historical daily vehicle parking times of the indoor parking lot, sums and calculates an average value, marks the average value as a total average value ZJ, obtains the vehicle parking times of the first three days of the indoor parking lot, sorts the vehicle parking times according to the parking times, marks the parking times in the middle as a single average value DJ, and substitutes the total average value ZJ and the single average value DJ into a formula
Obtaining a partial mean coefficient PJ;
step nine: the processor adds one to the preset number of vehicles in the time period according to the preset time period, and marks the preset number of vehicles as a preset vehicle value CY;
step ten: the processor obtains the total number CW of the parking spaces of the indoor parking lot, and substitutes the total number CW of the parking spaces, the vehicle entering value CJ, the vehicle leaving value CL, the vehicle preset value CY, the time-sharing parking probability value CG and the deviation coefficient PJ into a formula
（CW-CJ+CL-CY-CG）]Obtaining a predicted time division value YC, wherein gamma is a preset correction factor, and gamma is 0.998;
step eleven: the processor sends the predicted time division value YC to the allowance display module;
step twelve: the allowance display module obtains an integer digit numerical value and a first numerical value after a decimal point according to the received forecast time division value YC, the integer digit numerical value and the first numerical value are respectively marked as a forecast position value and an adjustment numerical value, if the adjustment numerical value is larger than or equal to 5, the forecast position value is increased by one, if the adjustment numerical value is smaller than 5, the forecast position value is increased by zero, then the forecast position value is updated and displayed on an entrance parking space display screen of the indoor parking lot, meanwhile, the forecast position value is sent to the terminal through the Internet and is updated and displayed on the terminal, the display content is the forecast position value, and the forecast position value is expressed as the forecast remaining parking space number of the indoor parking lot.
2. The method for predicting the remaining parking space of the indoor parking lot according to claim 1, wherein the method for predicting the remaining parking space of the indoor parking lot is used for predicting by a system for predicting the remaining parking space of the indoor parking lot;
the system for predicting the remaining parking spaces of the indoor parking lot comprises an information acquisition module, a processor, a data analysis module, a parking space reservation module and a surplus display module;
the system comprises an information acquisition module, a processor and a data processing module, wherein the information acquisition module is used for acquiring vehicle information of vehicles entering or leaving an indoor parking lot, counting vehicle entering values and vehicle leaving values and sending the vehicle information, the vehicle entering values and the vehicle leaving values to the processor;
the processor is used for acquiring a predicted parking time period and a predicted parking probability according to the vehicle information and sending the predicted parking time period and the predicted parking probability to the data analysis module, and is also used for acquiring a deviation average coefficient according to the historical vehicle parking times of the indoor parking lot, acquiring a vehicle preset value according to the predicted time period, acquiring a predicted time division value according to the total number of the parking places of the indoor parking lot, and sending the predicted time division value to the allowance display module;
the data analysis module is used for acquiring time-sharing parking probability according to the predicted parking time period and the predicted parking probability, acquiring time-sharing parking probability values of all vehicle information according to the time-sharing parking probability, and sending the time-sharing parking probability values to the processor;
the parking space reservation module is used for reserving the remaining parking spaces of the indoor parking lot and sending a reservation time period generated by successful parking space reservation to the processor;
and the allowance display module is used for obtaining a prediction bit value according to the prediction time-division value and updating and displaying the remaining parking spaces of the indoor parking lot according to the prediction bit value.
3. The method for predicting the remaining parking spaces in the indoor parking lot according to claim 2, wherein the specific working process of the information acquisition module is as follows:
the method comprises the steps of collecting vehicle information of vehicles entering or leaving the indoor parking lot, wherein the vehicle information comprises license plate numbers and entering time, collecting the total number of the vehicles entering the indoor parking lot and the total number of the vehicles leaving the indoor parking lot, respectively marking the total numbers as vehicle entering values and vehicle leaving values, and sending the vehicle information, the vehicle entering values and the vehicle leaving values to a processor.
4. The method for predicting the remaining parking spaces in the indoor parking lot according to claim 2, wherein the parking space reservation module specifically works as follows:
the user performs reservation on the remaining parking spaces of the indoor parking lot through the terminal, the parking space reservation module generates a reservation time period after the parking space reservation is successful, and the parking space reservation module sends the reservation time period to the processor.
5. The method for predicting the remaining parking spaces in the indoor parking lot according to claim 3, wherein the specific working process of the processor is as follows:
obtaining historical parking information of a vehicle according to license plate numbers after receiving vehicle information, wherein the historical parking information comprises total parking times, parking entrance time each time, parking exit time each time and parking star number, counting the entrance time each time, marking the starting time of the time period with the most frequent occurrence of the parking entrance time in a unit time period as predicted entrance time, counting the exit time each time, marking the ending time of the time period with the most frequent occurrence of the parking exit time in the unit time period as predicted exit time, obtaining the predicted parking time period according to the predicted entrance time and the predicted exit time, classifying the total parking times according to the parking star number, obtaining the parking times of each parking star number, obtaining the parking probability of each star number according to the ratio of the parking times and the total parking times, and marking the parking probability as predicted parking probability;
the predicted parking time period and the predicted parking probability are sent to a data analysis module;
obtaining historical daily vehicle parking times of an indoor parking lot, summing and calculating an average value, marking the average value as a total average value, obtaining the vehicle parking times of the first three days of the indoor parking lot, sequencing according to the parking times, marking the parking times in the middle as a single average value, and analyzing the total average value and the single average value to obtain a partial average coefficient;
adding one to the preset number of vehicles in the preset time period according to the preset time period, and marking the preset number of vehicles as a preset vehicle value;
acquiring the total number of parking spaces of an indoor parking lot, and analyzing according to the total number of the parking spaces, a vehicle entering value, a vehicle leaving value, a vehicle preset value, a time-sharing parking probability value and a deviation average coefficient to obtain a predicted time-sharing value;
and sending the predicted time-sharing value to a margin display module.
6. The method for predicting the remaining parking spaces in the indoor parking lot according to claim 5, wherein the specific working process of the data analysis module is as follows:
the parking probabilities in the predicted parking time period are all equal to the predicted parking probability, the time-sharing parking probability = the predicted parking probability, the parking probabilities except the time in the predicted parking time period are marked as zero, and the time-sharing parking probability =0;
the data analysis module acquires the time-sharing parking probability corresponding to each piece of vehicle information i and sums the time-sharing parking probabilities to obtain the time-sharing parking probability values of all pieces of vehicle information;
and sending the time-sharing parking probability value to a processor.
7. The method for predicting the remaining parking spaces in the indoor parking lot according to claim 5, wherein the specific working process of the remaining space display module is as follows:
and acquiring a first numerical value after the integral number value and the decimal point according to the received forecasting time-sharing value, respectively marking the first numerical value as a forecasting place value and an adjusting numerical value, if the adjusting numerical value is more than or equal to 5, adding one to the forecasting place value, if the adjusting numerical value is less than 5, adding zero to the forecasting place value, then updating and displaying the forecasting place value on an entrance parking space display screen of the indoor parking lot, simultaneously sending the forecasting place value to a terminal through the Internet and updating and displaying the terminal, wherein the display content is the forecasting place value, and the forecasting place value is expressed as the forecasting remaining parking space number of the indoor parking lot.
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