A smart parking management method based on parking gate communication information sharing

Abstract

The present invention discloses a smart parking management method based on parking gate communication information sharing, which relates to the field of parking management technology, including: dividing a parking lot into several parking areas; determining the correlation between each parking gate and each parking area of ​​the parking lot; obtaining the in-and-out data of each parking gate; evaluating and predicting the future entry data of the parking gate based on the in-and-out data of the parking gate; predicting the parking saturation of each parking area in the parking lot; judging whether there is a single parking area with a parking saturation greater than a preset saturation threshold, if so, controlling the vehicle flow of each parking gate based on a diversion control algorithm, if not, not responding. The advantages of the present invention are: it can effectively avoid the oversaturation of vehicles in a single area, thereby effectively improving the parking efficiency of vehicles, while reducing the probability of vehicle collisions, and greatly improving the management level of the parking lot.

Description

Technical Field

[0001] The present invention relates to the technical field of parking management, and in particular to a smart parking management method based on parking gate communication information sharing. Background Art

[0002] A parking lot is a place for vehicles to park. There are simple parking lots with only parking spaces but no management or charging, and there are paid parking lots with entrances and exits, parking managers and timekeepers. Modern parking lots often have automated timekeeping and charging systems, closed-circuit televisions and video recorder systems.

[0003] Existing parking lot management systems usually lack data analysis for vehicle entry and exit. When conducting parking management, manual vehicle guidance is often carried out only after a certain area has reached saturation. Due to the delay in this method, it is difficult for vehicles to find parking spaces in time after entering the saturated parking area, resulting in a waste of time costs. In addition, oversaturation of vehicles in a single area will increase the probability of vehicle collisions and easily cause asset losses. Summary of the invention

[0004] In order to solve the above technical problems, a smart parking management method based on parking gate communication information sharing is provided. This technical solution solves the problem that the above-mentioned existing parking lot management system usually lacks data analysis for vehicle entry and exit. When performing parking management, manual vehicle guidance is often carried out only after the vehicles in a certain area reach saturation. Due to the delay in this method, after the vehicle enters the parking saturated area, it is difficult to find a parking space in time, resulting in a waste of time and cost. In addition, the oversaturation of vehicles in a single area will increase the probability of vehicle collisions, which may easily cause asset losses.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A smart parking management method based on parking gate communication information sharing, comprising:

[0007] Acquire layout data of the parking lot, and divide the parking lot into a plurality of parking areas based on the layout data of the parking lot;

[0008] Determine at least one parking gate corresponding to the parking lot based on the layout data of the parking lot, and determine the relevance of each parking gate to each parking area of ​​the parking lot based on the historical operation data of the parking lot;

[0009] Get the entry and exit data of each parking gate;

[0010] Predicting the future entry data of parking gates based on the entry and exit data of parking gates;

[0011] Based on the future in-and-out data of multiple parking gates and the correlation between each parking gate and each parking area in the parking lot, the parking saturation of each parking area in the parking lot is predicted;

[0012] Determine whether there is a single parking area whose parking saturation is greater than a preset saturation threshold. If so, control the traffic flow of each parking gate based on the diversion control algorithm. If not, do not respond.

[0013] Preferably, the determining the correlation between each parking gate and each parking area in the parking lot based on the historical operation data of the parking lot specifically includes:

[0014] Set a parking analysis cycle;

[0015] Retrieving the operation log of the parking gate in at least one historical parking analysis cycle closest to the current moment;

[0016] Based on the operation log, information about vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained, and the total number of vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained;

[0017] Based on the vehicle entry information, determine the total number of vehicles that eventually park in each parking area from the vehicles that enter the parking gate;

[0018] The total number of vehicles entering the parking gate and finally parking in each parking area is compared with the total number of vehicles entering the parking gate to obtain the correlation between the parking gate and each parking area in the parking lot.

[0019] Preferably, the method of evaluating and predicting the future entry data of the parking gate based on the entry and exit data of the parking gate specifically includes:

[0020] Determine several evaluation criteria for vehicle entry and exit;

[0021] Based on each evaluation scale of vehicle entry and exit, the future entry data fitting value of the parking gate at each evaluation scale is predicted based on the fitting prediction method;

[0022] The future approach data of the parking gate is obtained by averaging the fitted values ​​of the future approach data of the parking gate under each evaluation scale.

[0023] Preferably, the method of predicting the future approach data fitting value of the parking gate at each evaluation scale based on each evaluation scale of vehicle entry and exit based on the fitting prediction method specifically includes:

[0024] Based on each evaluation scale, a number of historical values ​​of the number of parking gates entering the parking gate corresponding to the evaluation scale are selected from the operation log of the parking gate and recorded as sample data of the evaluation scale;

[0025] The sample data of the evaluation scale are numbered in order from the earliest to the latest time;

[0026] According to the fitting formula, the fitting value of the parking gate's future entry data under the evaluation scale is calculated;

[0027] The fitting formula is:

[0028] In the formula, To evaluate the future parking barrier data fitting value under the scale, Sample data numbered j, is the total number of sample data.

[0029] Preferably, the predicting of the parking saturation of each parking area in the parking lot based on the future entry and exit data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot specifically includes:

[0030] Determine future vehicle exit data for each parking area in the parking lot based on historical operation data of each parking area in the parking lot;

[0031] Based on the future entry and exit data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot, based on the comprehensive fitting formula, the future vehicle entry expectations of each parking area in the parking lot are predicted;

[0032] Based on the current parking quantity of each parking area in the parking lot plus the future vehicle entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, the future parking quantity expectation of each parking area in the parking lot is obtained;

[0033] The ratio of the expected number of parking lots in each parking area of ​​the parking lot in the future to the total number of parking lots in each parking area of ​​the parking lot is taken as the parking saturation of each parking area of ​​the parking lot;

[0034] Wherein, the comprehensive fitting formula is specifically:

[0035] In the formula, is the expected number of parking spaces in the future for the i-th parking area in the parking lot, is the correlation between the kth parking gate and the i-th parking area in the parking lot, is the future entry data of the kth parking gate, is the total number of parking barriers.

[0036] Preferably, determining the future vehicle exit data of each parking area in the parking lot based on the historical operation data of each parking area in the parking lot specifically includes:

[0037] Set a vehicle exit analysis cycle;

[0038] An average value of the number of vehicle exits in the parking area in at least one historical vehicle exit analysis cycle closest to the current moment is calculated as future vehicle exit data for the parking area.

[0039] Preferably, the flow control algorithm is specifically:

[0040] Determine a parking area in which the parking saturation of at least one parking area is greater than a preset saturation threshold, and record it as a saturated parking area;

[0041] The maximum vehicle entry expectation of the saturated parking area is obtained based on the preset saturation threshold of the saturated parking area plus the future vehicle exit data of the parking area minus the current number of parking lots in each parking area of ​​the parking lot;

[0042] Based on the maximum vehicle entry expectation in the saturated parking area, a parking gate entry inequality group is constructed;

[0043] Solve the parking gate approach inequality group to obtain at least one parking gate approach restriction array;

[0044] Based on the regional balance algorithm, determine the optimal parking gate entry restriction array;

[0045] Determine whether the number of vehicles entering each parking gate reaches the number limited by the optimal parking gate entry restriction array. If so, suspend the entry of vehicles at the parking gate. If not, do not respond.

[0046] The parking gate approach inequality group is specifically:

[0047]

[0048] In the formula,

[0049] is the kth parking gate and the parking lot

[0050] The correlation of saturated parking areas, is the entry restriction number of the kth parking gate, For the The maximum vehicle entry expectation for a saturated parking area.

[0051] Preferably, the regional balancing algorithm is specifically:

[0052] The parking gate entry restriction array is A. ;

[0053] Based on the comprehensive fitting formula, the future vehicle restricted entry expectations of each parking area in the parking lot are calculated under the parking gate entry restriction array;

[0054] Based on the current parking quantity of each parking area in the parking lot plus the future vehicle restriction entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, obtaining the future parking restriction quantity expectation of each parking area in the parking lot;

[0055] The ratio of the expected number of parking restrictions in each parking area of ​​the parking lot in the future to the total number of parking spaces in each parking area of ​​the parking lot is taken as the parking restriction saturation of each parking area of ​​the parking lot;

[0056] Find the standard deviation of parking restriction saturation of all parking areas in the parking lot as the regional balance indicator of the parking gate access restriction array;

[0057] The parking gate entry restriction array corresponding to the minimum value of the regional balance index is filtered out, which is the optimal parking gate entry restriction array.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The present invention proposes a smart parking management method based on parking gate communication information sharing. By analyzing the historical data of vehicle entry at each parking gate in the parking lot, the number of vehicles entering through the parking gate in the future time period is predicted by multi-scale fitting, and the future parking status of each parking area is comprehensively fitted in combination with the correlation between the parking gate and each parking area. When there is an area in the predicted parking lot that triggers a preset saturation threshold, a diversion control algorithm is used at this time to pre-set the vehicle entry restriction of each parking gate, thereby realizing pre-intelligent management of the parking lot, which can effectively avoid vehicle oversaturation in a single area, thereby effectively improving vehicle parking efficiency, while reducing the probability of vehicle collision, and greatly improving the management level of the parking lot. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 Flowchart of the smart parking management method based on parking gate communication information sharing proposed in this scheme;

[0061] Figure 2 A flow chart of a method for determining the relevance of each parking gate to each parking area in the parking lot based on the historical operation data of the parking lot in the present solution;

[0062] Figure 3 A flow chart of a method for predicting future parking gate entry data based on parking gate entry and exit data evaluation in this solution;

[0063] Figure 4 A flow chart of the method for predicting the future approach data fitting value of the parking gate at each evaluation scale in this scheme;

[0064] Figure 5A flow chart of a method for predicting parking saturation of each parking area in a parking lot in this solution;

[0065] Figure 6 A flow chart of a method for determining future vehicle exit data for each parking area in a parking lot in this solution;

[0066] Figure 7 This is a method flow chart of the diversion control algorithm in this scheme;

[0067] Figure 8 This is a method flow chart of the regional balancing algorithm in this solution;

[0068] Fig. 9 This is a schematic diagram of the electronic device in this solution;

[0069] Fig.10 This is a schematic diagram of the computer-readable storage medium structure in this solution. DETAILED DESCRIPTION

[0070] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0071] Reference Figure 1 As shown, a smart parking management method based on parking gate communication information sharing includes:

[0072] Acquire layout data of the parking lot, and divide the parking lot into a plurality of parking areas based on the layout data of the parking lot;

[0073] Determine at least one parking gate corresponding to the parking lot based on the layout data of the parking lot, and determine the relevance of each parking gate to each parking area of ​​the parking lot based on the historical operation data of the parking lot;

[0074] Get the entry and exit data of each parking gate;

[0075] Predicting the future entry data of parking gates based on the entry and exit data of parking gates;

[0076] Based on the future in-and-out data of multiple parking gates and the correlation between each parking gate and each parking area in the parking lot, the parking saturation of each parking area in the parking lot is predicted;

[0077] Determine whether there is a single parking area whose parking saturation is greater than a preset saturation threshold. If so, control the traffic flow of each parking gate based on the diversion control algorithm. If not, do not respond.

[0078] This solution analyzes the historical data of vehicle entry at each parking gate in the parking lot, predicts the number of vehicles entering through the parking gate in the future time period through multi-scale fitting, and combines the correlation between the parking gate and each parking area to comprehensively fit the future parking status of each parking area. When there is an area in the predicted parking lot that triggers the preset saturation threshold, the diversion control algorithm is used to pre-set the vehicle entry restrictions for each parking gate, thereby realizing pre-intelligent management of the parking lot.

[0079] Reference Figure 2 As shown, determining the relevance of each parking gate to each parking area in the parking lot based on the historical operation data of the parking lot specifically includes:

[0080] Set a parking analysis cycle;

[0081] Retrieving the operation log of the parking gate in at least one historical parking analysis cycle closest to the current moment;

[0082] Based on the operation log, information about vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained, and the total number of vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained;

[0083] Based on the vehicle entry information, determine the total number of vehicles that eventually park in each parking area from the vehicles that enter the parking gate;

[0084] The total number of vehicles entering the parking gate and finally parking in each parking area is compared with the total number of vehicles entering the parking gate to obtain the correlation between the parking gate and each parking area in the parking lot.

[0085] It is understandable that the final parking area of ​​vehicles entering the parking lot from parking gates at different locations is usually close to the parking gates at which they enter the parking lot. This leads to a parking correlation between the parking gates and the parking areas. Therefore, in the initial management stage of the parking lot, due to the lack of the parking lot operation log as the analysis basis, the distance between the parking gate and each parking area can be used as the initial correlation analysis indicator. The greater the distance between the parking gate and the parking area, the smaller the correlation. Conversely, the smaller the distance between the parking gate and the parking area, the greater the correlation. However, since parking is a subjective behavior, its influencing factors are often not limited to the distance between the area and the gate. Based on this, in this solution, based on the operation data of the parking lot, the parking frequency of vehicles entering the parking lot from the gate in each area within a certain period of time is counted as the correlation between the parking gate and each parking area of ​​the parking lot. The correlation is dynamically adjusted based on the actual parking management status to ensure that the correlation between the parking gate and each parking area of ​​the parking lot is compatible with the actual parking status.

[0086] Reference Figure 3 As shown, the evaluation and prediction of the parking gate's future entry data based on the parking gate's entry and exit data specifically includes:

[0087] Determine several evaluation criteria for vehicle entry and exit;

[0088] Based on each evaluation scale of vehicle entry and exit, the future entry data fitting value of the parking gate at each evaluation scale is predicted based on the fitting prediction method;

[0089] The future approach data of the parking gate is obtained by averaging the fitted values ​​of the future approach data of the parking gate under each evaluation scale.

[0090] Reference Figure 4 As shown, based on each evaluation scale of vehicle entry and exit, the future entry data fitting value of the parking gate at each evaluation scale is predicted based on the fitting prediction method, specifically including:

[0091] Based on each evaluation scale, a number of historical values ​​of the number of parking gates entering the parking gate corresponding to the evaluation scale are selected from the operation log of the parking gate and recorded as sample data of the evaluation scale;

[0092] The sample data of the evaluation scale are numbered in order from the earliest to the latest time;

[0093] According to the fitting formula, the fitting value of the parking gate's future entry data under the evaluation scale is calculated;

[0094] The fitting formula is:

[0095] In the formula, To evaluate the future parking barrier data fitting value under the scale, Sample data numbered j, is the total number of sample data.

[0096] It is understandable that the change in the number of parking lots may exist in different cycles, such as annual cycle changes, seasonal cycle changes, monthly cycle changes and other different time scales. For example, the parking lot of a shopping mall has different changes in the number of parking lots at different time periods of a day, and the number of parking lots also varies on different days of a week, with fewer parking lots on weekdays and more parking lots on non-weekdays. Therefore, in this solution, when calculating the future entry data of the parking gate, the impact of various time scale cycles on the changes in the number of vehicles entering the parking lot is fully considered, and a linear prediction method is used to predict the future entry data fitting value of the parking gate at each evaluation scale, and the future entry data fitting values ​​of the parking gate at multiple evaluation scales are averaged as the future entry data of the parking gate.

[0097] Reference Figure 5 As shown, based on the future in-and-out data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot, the parking saturation of each parking area in the parking lot is predicted, including:

[0098] Determine future vehicle exit data for each parking area in the parking lot based on historical operation data of each parking area in the parking lot;

[0099] Based on the future entry and exit data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot, based on the comprehensive fitting formula, the future vehicle entry expectations of each parking area in the parking lot are predicted;

[0100] Based on the current parking quantity of each parking area in the parking lot plus the future vehicle entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, the future parking quantity expectation of each parking area in the parking lot is obtained;

[0101] The ratio of the expected number of parking lots in each parking area of ​​the parking lot in the future to the total number of parking lots in each parking area of ​​the parking lot is taken as the parking saturation of each parking area of ​​the parking lot;

[0102] Among them, the comprehensive fitting formula is specifically:

[0103]

[0104] In the formula, is the expected number of parking spaces in the future for the i-th parking area in the parking lot, is the correlation between the kth parking gate and the i-th parking area in the parking lot, is the future entry data of the kth parking gate, is the total number of parking barriers.

[0105] Reference Figure 6 As shown, based on the historical operation data of each parking area in the parking lot, determining the future vehicle exit data of each parking area in the parking lot specifically includes:

[0106] Set a vehicle exit analysis cycle;

[0107] An average value of the number of vehicle exits in the parking area in at least one historical vehicle exit analysis cycle closest to the current moment is calculated as future vehicle exit data for the parking area.

[0108] Reference Figure 7 As shown in the figure, the specific flow control algorithm is:

[0109] Determine a parking area in which the parking saturation of at least one parking area is greater than a preset saturation threshold, and record it as a saturated parking area;

[0110] The maximum vehicle entry expectation of the saturated parking area is obtained based on the preset saturation threshold of the saturated parking area plus the future vehicle exit data of the parking area minus the current number of parking lots in each parking area of ​​the parking lot;

[0111] Based on the maximum vehicle entry expectation in the saturated parking area, a parking gate entry inequality group is constructed;

[0112] Solve the parking gate approach inequality group to obtain at least one parking gate approach restriction array;

[0113] Based on the regional balance algorithm, determine the optimal parking gate entry restriction array;

[0114] Determine whether the number of vehicles entering each parking gate reaches the number limited by the optimal parking gate entry restriction array. If so, suspend the entry of vehicles at the parking gate. If not, do not respond.

[0115] Among them, the parking gate approach inequality group is specifically:

[0116] In the formula, is the kth parking gate and the parking lot The correlation of saturated parking areas, is the entry restriction number of the kth parking gate, For the The maximum vehicle entry expectation for a saturated parking area.

[0117] In this scheme, a preset saturation threshold is set as the trigger point for triggering the parking gate diversion control algorithm. In actual situations, when a single parking gate has a traffic restriction, vehicles will choose other parking gates to enter, which will cause a surge in the number of vehicles entering other parking gates. This surge in the number of vehicles entering is not reflected in historical data, and this surge in the number of vehicles entering usually causes an increase in the number of vehicles in each parking area. In order to avoid regional parking overload, the preset saturation threshold in this scheme is usually less than 100%. In some preferred embodiments, the preset saturation threshold is set to 85%. By reserving 15% of the fault tolerance, it is ensured that the surge in vehicle entry beyond the consideration of the parking gate entry restriction array does not cause regional parking overload.

[0118] Reference Figure 8 As shown in the figure, the regional balancing algorithm is specifically as follows:

[0119] The parking gate entry restriction array is A. ;

[0120] Based on the comprehensive fitting formula, the future vehicle restricted entry expectations of each parking area in the parking lot are calculated under the parking gate entry restriction array;

[0121] Based on the current parking quantity of each parking area in the parking lot plus the future vehicle restriction entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, the future parking restriction quantity expectation of each parking area in the parking lot is obtained; the ratio of the future parking restriction quantity expectation of each parking area in the parking lot to the total number of parking spaces in each parking area in the parking lot is taken as the parking restriction saturation of each parking area in the parking lot;

[0122] Find the standard deviation of parking restriction saturation of all parking areas in the parking lot as the regional balance indicator of the parking gate access restriction array;

[0123] The parking gate entry restriction array corresponding to the minimum value of the regional balance index is filtered out, which is the optimal parking gate entry restriction array.

[0124] When a parking area triggers the preset saturation threshold, it means that the number of parking lots in each area of ​​the parking lot has reached a certain number. At this time, in order to ensure the efficient management of the parking lot, it is necessary to balance the management of each area within the parking lot, that is, to ensure that the vehicle saturation of each area is at a similar level. Based on this, this scheme adopts the standard deviation of the parking restriction saturation of all parking areas in the parking lot under each scheme as the regional balance indicator. The smaller the regional balance index, the more concentrated the parking restriction saturation values ​​of all parking areas in the parking lot are, and the more balanced the number of parking lots in each area is.

[0125] Furthermore, the method according to the embodiment of the present application can also be performed by Fig. 9 The electronic device architecture shown in FIG. Fig. 9 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as ROM 503 or hard disk 507, may store a smart parking management method based on parking gate communication information sharing provided by the present application. The electronic device 500 may also include a user interface 508. Of course, Fig. 9 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Fig. 9 One or more components of an electronic device are shown.

[0126] Fig.10 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Fig.10As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, a smart parking management method based on parking gate communication information sharing according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache). Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0127] In summary, the advantages of the present invention are: it can effectively avoid oversaturation of vehicles in a single area, thereby effectively improving vehicle parking efficiency, while reducing the probability of vehicle collisions, and greatly improving the management level of the parking lot.

[0128] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A smart parking management method based on parking gate communication information sharing, characterized in that: include: Acquire layout data of the parking lot, and divide the parking lot into a plurality of parking areas based on the layout data of the parking lot; Determine at least one parking gate corresponding to the parking lot based on the layout data of the parking lot, and determine the relevance of each parking gate to each parking area of ​​the parking lot based on the historical operation data of the parking lot; Get the entry and exit data of each parking gate; Predicting the future entry data of parking gates based on the entry and exit data of parking gates; Based on the future in-and-out data of multiple parking gates and the correlation between each parking gate and each parking area in the parking lot, the parking saturation of each parking area in the parking lot is predicted; Determine whether there is a single parking area where the parking saturation is greater than a preset saturation threshold. If so, control the vehicle flow of each parking gate based on the diversion control algorithm. If not, do not respond. Determining the relevance of each parking gate to each parking area of ​​the parking lot based on the historical operation data of the parking lot specifically includes: Set a parking analysis cycle; Retrieving the operation log of the parking gate in at least one historical parking analysis cycle closest to the current moment; Based on the operation log, information about vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained, and the total number of vehicles entering all parking barriers in at least one historical parking analysis cycle closest to the current moment is obtained; Based on the vehicle entry information, determine the total number of vehicles that eventually park in each parking area from the vehicles that enter the parking gate; Compare the total number of vehicles entering the parking gate in each parking area with the total number of vehicles entering the parking gate to obtain the correlation between the parking gate and each parking area in the parking lot; The method of evaluating and predicting the future entry data of the parking gate based on the entry and exit data of the parking gate specifically includes: Determine several evaluation criteria for vehicle entry and exit; Based on each evaluation scale of vehicle entry and exit, the future entry data fitting value of the parking gate at each evaluation scale is predicted based on the fitting prediction method; The future entry data of the parking gate is obtained by averaging the fitted values ​​of the future entry data of the parking gate under each evaluation scale; The method of predicting the future approach data fitting value of the parking gate at each evaluation scale based on each evaluation scale of vehicle entry and exit based on the fitting prediction method specifically includes: Based on each evaluation scale, a number of historical values ​​of the number of parking gates entering the parking gate corresponding to the evaluation scale are selected from the operation log of the parking gate and recorded as sample data of the evaluation scale; The sample data of the evaluation scale are numbered in order from the earliest to the latest time; According to the fitting formula, the fitting value of the parking gate's future entry data under the evaluation scale is calculated; The fitting formula is: In the formula, To evaluate the future parking barrier data fitting value under the scale, Sample data numbered j, is the total number of sample data.

2. According to claim 1, a smart parking management method based on parking gate communication information sharing is characterized in that: The prediction of the parking saturation of each parking area in the parking lot based on the future entry and exit data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot specifically includes: Determine future vehicle exit data for each parking area in the parking lot based on historical operation data of each parking area in the parking lot; Based on the future entry and exit data of multiple parking gates combined with the correlation between each parking gate and each parking area in the parking lot, based on the comprehensive fitting formula, the future vehicle entry expectations of each parking area in the parking lot are predicted; Based on the current parking quantity of each parking area in the parking lot plus the future vehicle entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, the future parking quantity expectation of each parking area in the parking lot is obtained; The ratio of the expected number of parking lots in each parking area of ​​the parking lot in the future to the total number of parking lots in each parking area of ​​the parking lot is taken as the parking saturation of each parking area of ​​the parking lot; Wherein, the comprehensive fitting formula is specifically: In the formula, is the expected number of parking spaces in the future for the i-th parking area in the parking lot, is the correlation between the kth parking gate and the i-th parking area in the parking lot, is the future entry data of the kth parking gate, is the total number of parking barriers.

3. According to claim 2, a smart parking management method based on parking gate communication information sharing is characterized in that: The method of determining the future vehicle exit data of each parking area in the parking lot based on the historical operation data of each parking area in the parking lot specifically includes: Set a vehicle exit analysis cycle; An average value of the number of vehicle exits in the parking area in at least one historical vehicle exit analysis cycle closest to the current moment is calculated as future vehicle exit data for the parking area.

4. According to claim 3, a smart parking management method based on parking gate communication information sharing is characterized in that: The flow control algorithm is specifically as follows: Determine a parking area in which the parking saturation of at least one parking area is greater than a preset saturation threshold, and record it as a saturated parking area; obtain a maximum vehicle entry expectation for the saturated parking area based on the preset saturation threshold of the saturated parking area plus the future vehicle exit data of the parking area minus the current number of parking lots in each parking area of ​​the parking lot; Based on the maximum vehicle entry expectation in the saturated parking area, a parking gate entry inequality group is constructed; Solve the parking gate approach inequality group to obtain at least one parking gate approach restriction array; Based on the regional balance algorithm, determine the optimal parking gate entry restriction array; Determine whether the number of vehicles entering each parking gate reaches the number limited by the optimal parking gate entry restriction array. If so, suspend the entry of vehicles at the parking gate. If not, do not respond. The parking gate approach inequality group is specifically: In the formula, is the kth parking gate and the parking lot The correlation of saturated parking areas, is the entry restriction number of the kth parking gate, For the The maximum vehicle entry expectation for a saturated parking area.

5. According to claim 4, a smart parking management method based on parking gate communication information sharing is characterized in that: The regional balancing algorithm is specifically as follows: let the parking gate entry restriction array be A, ; Based on the comprehensive fitting formula, the future vehicle restricted entry expectations of each parking area in the parking lot are calculated under the parking gate entry restriction array; Based on the current parking quantity of each parking area in the parking lot plus the future vehicle restriction entry expectation of each parking area in the parking lot minus the future vehicle exit data of each parking area in the parking lot, obtaining the future parking restriction quantity expectation of each parking area in the parking lot; The ratio of the expected number of parking restrictions in each parking area of ​​the parking lot in the future to the total number of parking spaces in each parking area of ​​the parking lot is taken as the parking restriction saturation of each parking area of ​​the parking lot; Find the standard deviation of parking restriction saturation of all parking areas in the parking lot as the regional balance indicator of the parking gate access restriction array; The parking gate entry restriction array corresponding to the minimum value of the regional balance index is filtered out, which is the optimal parking gate entry restriction array.

6. An electronic device, characterized in that: include: at least one processor; And a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a smart parking management method based on parking gate communication information sharing as described in any one of claims 1-5.

7. A computer-readable storage medium storing a computer-readable program, characterized in that: When the computer-readable program is executed by the processor, the intelligent parking management method based on parking gate communication information sharing according to any one of claims 1 to 5 is implemented.

Images