CN117037530A - Dynamic supervision and analysis method for parking resources - Google Patents
Dynamic supervision and analysis method for parking resources Download PDFInfo
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Abstract
The invention discloses a dynamic supervision and analysis method for parking resources, which belongs to the technical field of parking resource supervision, and is characterized in that target parking lots are identified, and the acquired parking resources corresponding to the target parking lots are displayed in real time according to a preset visual template to obtain a visual model; performing real-time evaluation on each target parking lot in the visual model to obtain an evaluation value corresponding to each target parking lot; displaying the evaluation value at the corresponding position in the visual model in real time; the parking resources of each parking lot are uniformly input into the visual model for display, so that management staff can intuitively know the dynamic conditions of the parking resources of each parking lot, and data islands among the parking lots are eliminated; evaluating based on the displayed data to obtain real-time evaluation values corresponding to the parking lots; and the associated marks of different time periods of each parking lot are carried out by combining the evaluation value records, so that corresponding management staff can intuitively know the resource complementation condition of each parking lot.
Description
Technical Field
The invention belongs to the technical field of parking resource supervision, and particularly relates to a dynamic supervision analysis method for parking resources.
Background
With the rapid increase of the amount of vehicles held, the contradiction between urban vehicles and parking spaces is also increasingly prominent. In cities with the size of gold, underground parking lots, ground multi-layer parking buildings and the like, occupied areas are small, and large-capacity in-situ parking facilities and roadside parking spaces become more and more important means for relieving urban parking pressure. However, parking resources are subject to supervision whether in parking lots or other public parking facilities. In the related art, two main means exist for monitoring parking resources, namely original manual monitoring and monitoring by installing a parking space detection and identification system. The manual supervision mode is that full-time management staff is arranged in a parking lot, the management staff surveys and records the vacant parking spaces in the parking lot, and then the vehicle owners are guided to park in the vacant parking spaces. The method is an original parking lot management method, a large number of full-time management staff are needed to be equipped in the parking lot to guide vehicles to stop, the parking lot management cost is high, and the method does not accord with the trend of gradual informatization of vehicle resource management and driving assistance. The parking space detection and identification system generally needs to install a detection instrument on each parking space of a parking lot to judge the current parking space state, then feeds back the collected parking space information to a management center of the parking lot for recording, and finally guides a vehicle owner to rapidly park through the display of a guide screen in the parking lot.
However, both the above two management methods are directed to a single parking lot and the like, and the information between the parking lots is isolated from each other, so that the parking resources of the parking lots cannot be fully exerted, especially, along with the rapid development of shared parking, the isolation between the supervision data of the parking lots is urgently needed to be broken, regional parking resource supervision is performed, and the parking resources of the parking lots are fully utilized.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides a dynamic supervision and analysis method for parking resources, which aims to solve the problems of the conventional supervision of the parking resources of multiple parking lots.
The aim of the invention can be achieved by the following technical scheme:
a dynamic supervision and analysis method for parking resources specifically comprises the following steps:
identifying target parking lots, and displaying the collected parking resources corresponding to the target parking lots in real time according to a preset visual template to obtain a visual model;
performing real-time evaluation on each target parking lot in the visual model to obtain an evaluation value corresponding to each target parking lot;
and displaying the evaluation value at the corresponding position in the visual model in real time.
Further, the evaluation method of the evaluation value includes:
establishing a resource evaluation model, and analyzing parking resources displayed in real time in the visual model based on the resource evaluation model to obtain corresponding correction coefficients and parking space values;
and inputting the correction coefficient and the parking space value into an evaluator value formula, and calculating a corresponding evaluation value.
Further, the evaluation value formula is: pg=c×cw;
wherein: PG is an evaluation value; c is a correction coefficient; CW is a parking space value.
Further, the method further comprises the following steps: and carrying out sharing evaluation on the target parking lot based on each evaluation value, and marking corresponding association labels for the target parking lot in each period.
Further, the method for carrying out sharing evaluation comprises the following steps:
generating an evaluation graph corresponding to each target parking lot based on evaluation value display data in the visual model, and generating an evaluation representative graph according to the evaluation graph corresponding to the target parking lot in a preset period;
determining an analysis period and an evaluation representative value corresponding to each target parking lot according to the evaluation representative graph;
and carrying out relevance evaluation based on the analysis period and the evaluation representative value, and determining the target parking lot marked with the corresponding relevance label.
Further, the evaluation graph includes an upper limit straight line and a lower limit straight line.
Further, the method for performing the relevance evaluation comprises the following steps:
step SA1: identifying a target parking lot belonging to the demand classification and the output classification, calculating an evaluation difference value between each evaluation value corresponding to the demand classification and the output classification and the evaluation value corresponding to the upper limit straight line and the lower limit straight line, and sequencing according to the sequence of the evaluation difference values from large to small to obtain an ith sequence; i=1, 2, … …, n being a positive integer;
step SA2: marking a target parking lot corresponding to the first evaluation difference value in the ith sequence as a reference parking lot, and determining each to-be-selected parking lot corresponding to the reference parking lot based on a preset sharing analysis distance;
step SA3: performing association coincidence evaluation, determining an associated parking lot corresponding to the reference parking lot, and marking the reference parking lot and the associated parking lot with corresponding association labels;
step SA4: removing the target parking lot marked with the associated label from the ith sequence to obtain an (i+1) th sequence;
step SA5: step SA2 to step SA4 are looped until the termination condition is satisfied.
The termination condition is that there is no target parking lot with unassociated mark in the demand classification or the output classification.
Further, the method for performing association compliance assessment includes:
determining a secondary sequence, marking the representative evaluation value corresponding to the reference parking lot as a reference evaluation value JPM, and marking the representative evaluation value corresponding to the candidate parking lot as a candidate evaluation value DXM j Wherein j=1, 2, … …, m is a positive integer;
GBM according to the association evaluation formula j ＝q j ×GBM j-1 -DXM j Computing corresponding association values GBM j ，GBM 0 =jpm, where q j For adjusting the coefficients;
when GBM j When the parking lot is more than or equal to 0, marking the corresponding parking lot to be selected as an associated parking lot;
when GBM j <At 0, the subsequent analysis is stopped.
Compared with the prior art, the invention has the beneficial effects that:
the parking resources of each parking lot are uniformly input into the visual model for display, so that management staff can intuitively know the dynamic conditions of the parking resources of each parking lot, and data islands among the parking lots are eliminated; evaluating based on the displayed data to obtain real-time evaluation values corresponding to the parking lots; and the associated marks of different time intervals of each parking lot are carried out by combining the evaluation value records, so that corresponding management staff can intuitively know the resource complementation condition of each parking lot, and the parking resources can be fully utilized.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic diagram of an evaluation curve according to the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, 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.
As shown in fig. 1 to 2, a method for dynamically monitoring and analyzing parking resources specifically includes:
identifying parking lots needing to uniformly manage parking resources, marking the parking lots as target parking lots, wherein the target parking lots can be all parking lots belonging to the same area in an enterprise according to different requirements, or all parking lots used for knowing the parking resources in one area by all related departments, the specific areas are divided in a manual mode according to the requirements, and determining all target parking lots based on the areas;
acquiring parking resources of each parking lot in real time, wherein the parking resources comprise all available parking spaces, idle parking spaces, parking space utilization rate, acquisition time and other data; establishing a corresponding visual template based on each target parking lot, and displaying each parking resource in real time according to the visual template; firstly, presetting a display mode of parking resources of each target parking lot, and summarizing corresponding visual templates; displaying parking resource data in real time according to the visual template; if the visual template can be set based on a distribution diagram of each target parking lot, setting a corresponding parking resource display mode at each target parking lot in the distribution diagram, and then displaying in real time according to the obtained parking resources, specifically, setting based on actual conditions; and marking templates, interfaces and the like for displaying parking resources in real time as a visual model.
According to each parking resource displayed in real time in the visual model, carrying out dynamic parking resource evaluation, evaluating the resource evaluation value of the current target parking lot in real time, and displaying the obtained resource evaluation value in real time in the visual model; the management personnel can intuitively know the current resource use condition of the parking lot; the specific evaluation method is as follows:
establishing a resource analysis model based on a CNN network or a DNN network, wherein the resource analysis model is used for analyzing the utilization rate of the parking spaces and the number of idle parking spaces, setting corresponding correction coefficients and parking space values, and the larger the number of idle parking spaces is, the larger the parking space value is, the higher the utilization rate is, and the lower the correction coefficient is; the training is performed by manually establishing a corresponding training set, and because the neural network is a prior art in the field, the specific establishment and training process is not described in detail; and analyzing parking resources displayed in real time by the resource analysis model after the training is successful, obtaining real-time correction coefficient values and parking space values, respectively marked as c and CW, and calculating a corresponding evaluation value PG according to an evaluation value formula PG=c×CW. The evaluation value is comprehensively evaluated based on the utilization rate of the parking spaces and the number of the free parking spaces, the number of the free parking spaces is taken as a benchmark, the utilization rate of the parking spaces is combined, the evaluation is performed, the specification of each parking space is considered, a certain free parking space is kept for the use of main users of the parking space, and then the corresponding correction coefficient is set according to the utilization rate; when the evaluation value is smaller than the threshold value X1, the parking lot is indicated to be unsuitable for receiving other users with smaller relativity for parking, and the method is mainly used for providing data support for follow-up shared parking planning for corresponding enterprise staff, households and the like of the parking lot.
As shown in fig. 2, real-time recording statistics is performed on the evaluation values corresponding to each target parking lot in the visual model, and recording statistics can be performed by using a table mode to record the evaluation values and the corresponding evaluation time; generating a corresponding evaluation graph according to the recorded data, namely generating an image by taking time as a horizontal axis and taking an evaluation value as a vertical axis; an upper limit straight line and a lower limit straight line are arranged in the evaluation graph, the upper limit straight line and the lower limit straight line are arranged based on a demand interval, a balance interval and an output interval, the demand interval represents a parking lot corresponding to the evaluation value in the interval, and at the moment, parking space resources are rich and can be shared; the balance interval represents a parking lot corresponding to the evaluation value in the interval, and the parking space resources are balanced at the moment; the output interval represents a parking lot corresponding to the evaluation value in the interval, at the moment, the parking space resources are insufficient, the parking needs to be carried out on other parking lots, the boundary value between the demand interval and the balance interval is an upper limit straight line, and the boundary value between the balance interval and the output interval is a lower limit straight line; the specific demand interval, the balance interval and the output interval are set manually; acquiring an evaluation graph corresponding to each day in a period, wherein the period is generally a long span of one week, one month and the like, and the evaluation graph is specifically set according to actual conditions; integrating the obtained evaluation curves into an evaluation curve graph, analyzing the evaluation curve graph to determine an evaluation representative curve, taking the average value of the evaluation values corresponding to each moment as the evaluation value on the evaluation representative curve of the moment, extracting the evaluation representative curve, generating an evaluation representative curve, carrying out time period combination according to the upper limit straight line and the lower limit straight line in the evaluation representative curve, obtaining a plurality of analysis time periods (S1, S2 and S3 … …), and carrying out combination according to the time continuity; and determining an evaluation representative value of each analysis period, wherein the evaluation representative value is generally a median value, a median value and the like of a curve corresponding to the analysis period.
Carrying out relevance evaluation according to the analysis time period, the evaluation representative value and the position of each target parking lot, evaluating which target parking lots can carry out sharing association in which time periods, giving corresponding association labels, and indicating that the target parking lots and which parking lots can carry out parking resource complementation in which time periods according to the association labels; and corresponding associated labels are displayed in the visual model.
The method for carrying out the relevance evaluation comprises the following steps:
classifying each target parking lot according to the corresponding requirements, balance and output attributes of each analysis period to obtain three classifications, namely requirement classification, balance classification and output classification, wherein the balance classification does not need sharing evaluation; subtracting the evaluation value corresponding to the upper limit straight line from each evaluation representative value corresponding to the demand classification to obtain a corresponding evaluation difference value; subtracting each evaluation representative value in the output classification from the evaluation value corresponding to the lower limit straight line to obtain a corresponding evaluation difference value; sequencing the calculated evaluation difference values in order from large to small to obtain a first sequence;
analyzing a target parking lot corresponding to a first evaluation difference value in a first sequence, marking the target parking lot as a reference parking lot, setting a sharing analysis distance in a manual mode, namely carrying out sharing analysis on the parking lots spaced in the distance, marking the parking lots with opposite attributes of the distance between each target parking lot and the reference parking lot within the sharing analysis distance as to-be-selected parking lots, namely if the reference parking lot belongs to a demand classification, the to-be-selected parking lots must belong to an output classification; and sequencing the distances between each to-be-selected parking lot and the reference parking lot according to the sequence from small to large to obtain a secondary sequence, analyzing one by one according to the sequence of the secondary sequence and a corresponding association evaluation formula, determining the to-be-selected parking lot with sharing property corresponding to the reference parking lot, marking the corresponding to-be-selected parking lot as an association parking lot, and marking the corresponding association labels on the reference parking lot and the association parking lot.
And removing the target parking lot marked with the association tag from the first sequence to obtain a second sequence, analyzing again according to the flow, marking the corresponding association tag, and pushing the second sequence until the association analysis cannot be performed, namely, the target parking lot without the unassociated tag in the requirement classification or the output classification.
The method for analyzing one by one according to the secondary sequence order and the corresponding association evaluation formula comprises the following steps:
step SC1: marking the representative evaluation value corresponding to the reference parking lot as a reference evaluation value JPM, and marking the representative evaluation value corresponding to the candidate parking lot as a candidate evaluation value DXM j Where j=1, 2, … …, m is a positive integer, ordered by secondary sequence; GBM according to the association evaluation formula j ＝q j ×GBM j-1 -DXM j Calculate the corresponding association value, GBM 0 =jpm, where q j For adjusting the coefficient, the coefficient is set according to the size of j and the scale of the corresponding parking lot to be selected for GBM j-1 Make a reduction, q as j increases j Gradually reducing;
step SC2: when GBM j When the parking lot is more than or equal to 0, the parking lot to be selected corresponding to the current j can be associated, and the parking lot to be selected is an associated parking lot;
when GBM j <And when 0, the parking lot to be selected corresponding to the current j cannot be associated, and stopping subsequent analysis.
For determining the adjustment coefficient, a reduction analysis model is specifically built based on a CNN network or a DNN network, a corresponding training set is built manually for training, and the size of j and the scale of a corresponding parking lot to be selected are analyzed through the reduction analysis model after the training is successful, so that the corresponding adjustment coefficient is obtained.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (8)
1. A method for dynamic supervision and analysis of parking resources, the method comprising:
identifying target parking lots, and displaying the collected parking resources corresponding to the target parking lots in real time according to a preset visual template to obtain a visual model;
performing real-time evaluation on each target parking lot in the visual model to obtain an evaluation value corresponding to each target parking lot;
and displaying the evaluation value at the corresponding position in the visual model in real time.
2. The method for dynamic supervision and analysis of parking resources according to claim 1, wherein the evaluation method of the evaluation value comprises:
establishing a resource evaluation model, and analyzing parking resources displayed in real time in the visual model based on the resource evaluation model to obtain corresponding correction coefficients and parking space values;
and inputting the correction coefficient and the parking space value into an evaluator value formula, and calculating a corresponding evaluation value.
3. The method for dynamically supervising and analyzing parking resources according to claim 2, wherein the evaluation value formula is: pg=c×cw;
wherein: PG is an evaluation value; c is a correction coefficient; CW is a parking space value.
4. The method of claim 1, further comprising: and carrying out sharing evaluation on the target parking lot based on each evaluation value, and marking corresponding association labels for the target parking lot in each period.
5. The method for dynamic supervision and analysis of parking resources according to claim 4, wherein the method for sharing assessment comprises:
generating an evaluation graph corresponding to each target parking lot based on evaluation value display data in the visual model, and generating an evaluation representative graph according to the evaluation graph corresponding to the target parking lot in a preset period;
determining an analysis period and an evaluation representative value corresponding to each target parking lot according to the evaluation representative graph;
and carrying out relevance evaluation based on the analysis period and the evaluation representative value, and determining the target parking lot marked with the corresponding relevance label.
6. The method of claim 5, wherein the evaluation graph includes an upper line and a lower line.
7. The method for dynamic supervision and analysis of parking resources according to claim 6, wherein the method for performing the association evaluation comprises:
step SA1: identifying a target parking lot belonging to the demand classification and the output classification, calculating an evaluation difference value between each evaluation value corresponding to the demand classification and the output classification and the evaluation value corresponding to the upper limit straight line and the lower limit straight line, and sequencing according to the sequence of the evaluation difference values from large to small to obtain an ith sequence; i=1, 2, … …, n being a positive integer;
step SA2: marking a target parking lot corresponding to the first evaluation difference value in the ith sequence as a reference parking lot, and determining each to-be-selected parking lot corresponding to the reference parking lot based on a preset sharing analysis distance;
step SA3: performing association coincidence evaluation, determining an associated parking lot corresponding to the reference parking lot, and marking the reference parking lot and the associated parking lot with corresponding association labels;
step SA4: removing the target parking lot marked with the associated label from the ith sequence to obtain an (i+1) th sequence;
step SA5: step SA2 to step SA4 are looped until the termination condition is satisfied.
8. The method for dynamic supervision and analysis of parking resources according to claim 7, wherein the method for performing association compliance assessment comprises:
determining a secondary sequence, marking the representative evaluation value corresponding to the reference parking lot as a reference evaluation value JPM, and marking the representative evaluation value corresponding to the candidate parking lot as a candidate evaluation value DXM j Wherein j=1, 2, … …, m is a positive integer;
GBM according to the association evaluation formula j ＝q j ×GBM j-1 -DXM j Computing corresponding association values GBM j ，GBM 0 =jpm, where q j For adjusting the coefficients;
when GBM j When the parking lot is more than or equal to 0, marking the corresponding parking lot to be selected as an associated parking lot;
when GBM j <At 0, the subsequent analysis is stopped.
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| CN117831338A (en) * | 2023-12-26 | 2024-04-05 | 武汉理工大学 | Data collaborative sharing method based on intelligent guidance terminal of parking lot |
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| CN117831338A (en) * | 2023-12-26 | 2024-04-05 | 武汉理工大学 | Data collaborative sharing method based on intelligent guidance terminal of parking lot |
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