Vehicle management system for intelligent parking

Abstract

The invention discloses a vehicle management system for intelligent parking, and the system comprises a background monitoring device which is used for obtaining the basic information of each vehicle which is monitored by each monitoring unit and is used for entering a parking lot of a designated park in real time, and a control device which is used for determining whether the vehicle belongs to a reserved vehicle according to the basic information of the vehicle, and if yes, stopping the vehicle. And if yes, determining whether the area to which the current vehicle type belongs is idle, and if yes, sending a guide instruction to the vehicle terminal. Besides, the management system analyzes the historical data of the parking space utilization condition of the parking lot in each time period, so that the parking space availability condition of the user who prepares to park the parking lot when the user arrives at the parking lot is predicted, and the parking position selected by the user is reasonably guided according to the prediction result. The parking lot with relatively high stability is preferentially recommended, so that the recommendation accuracy can be improved, and the situation that the reserved vehicle is difficult to park when arriving at the parking lot due to sudden change of the parking quantity in the parking lot is avoided.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation technology, and specifically relates to a vehicle management system for intelligent parking. Background Art

[0002] With the development of the economy, cars have become a common means of transportation for people, but the rapid growth in the number of cars has also led to many problems, such as car parking problems, especially in areas with high population density in cities, where parking difficulties have become a widespread problem.

[0003] In the prior art, when car owners are looking for parking spaces, they mainly rely on visual observation, and cannot intuitively obtain the distribution of available parking spaces. Therefore, the efficiency is low, and it is easy for them to not find available parking spaces for a long time, which affects commuting efficiency and is not conducive to smooth traffic in the parking lot. In addition, when the car owner has a clear destination, he cannot know whether there are vacant parking spaces in the parking lot at the destination, and can only judge based on experience. It is easy for the parking lot to have no vacant spaces or few vacant spaces when arriving, which affects the parking efficiency of the car owner. In order to accurately predict whether a parking lot is suitable for parking, the present invention provides a vehicle management system for smart parking to solve the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle management system for smart parking, so as to solve the problem in the prior art that when a vehicle is about to park in a parking lot, it is impossible to determine whether there are enough spaces for parking in the parking lot when the vehicle arrives at the parking lot, and when there are multiple optional parking lots for parking, parking resources cannot be reasonably utilized.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] In a possible implementation, the present invention provides a vehicle management system for smart parking, including:

[0007] The backend monitoring device is used to obtain in real time the basic information of each vehicle monitored by each monitoring unit for entering the designated park parking lot, the basic information including: vehicle identification, time information of the vehicle entering the park, and vehicle type;

[0008] The control device is used to determine whether the vehicle is a reserved vehicle based on the basic information of the vehicle. If so, it determines whether the area to which the current vehicle type belongs is idle. If so, it sends a guidance instruction to the vehicle terminal.

[0009] Optionally, if there are multiple public parking lots and public driving areas in the designated park, and the public parking lots meet the pre-reservation mechanism, the method further includes:

[0010] The control device is also used to

[0011] receiving a reservation request of any first vehicle, wherein the reservation request of the first vehicle includes: selected free parking location information and current vehicle location information;

[0012] Obtaining a predicted time t2 when the current first vehicle arrives at the selected parking location according to the reservation request;

[0013] According to the predicted time t2, parking strategy information established by historical data in advance, and the reliability coefficient of the parking location selected in the reservation request, a response message of whether to agree is sent to the first vehicle according to the reliability coefficient.

[0014] Optionally, according to the predicted time t2, parking strategy information established by historical data in advance, and the reliability coefficient of the parking location selected in the reservation request, sending a response message of whether to agree to the first vehicle according to the reliability coefficient includes: dividing a day into r time periods; obtaining an average predicted number of parking lots kj of the parking lot to which the selected parking location belongs in each time period from the parking strategy information, where 1≤j≤r, and r is a preset value;

[0015] Mark the time period of the predicted time t2 as the target time period; obtain the average predicted parking number kj corresponding to the target time period from the parking strategy information 目标 ; and obtain the maximum number of parking lots kmax in the target time period; obtain the actual average number of parking lots kf in the parking lot in a time period before the time period corresponding to the current time; obtain the average predicted number of parking lots kjf in the parking lot in a time period before the time period corresponding to the current time;

[0016] According to the formula Q = (kj 目标 / kmax)*(kf / kjf) to calculate the reliability coefficient Q of the reserved parking lot corresponding to this reservation information;

[0017] When the reliability coefficient Q>Qy 指定数 , the response information includes information that it is not recommended to park in the parking lot; 指定数 is the preset coefficient.

[0018] Optionally, based on parking strategy information established based on historical data, the average predicted number of parking lots kj of the selected parking location in each time period is obtained from the parking strategy information, including:

[0019] In a period within a day, the actual number of parking lots ksi in the parking lot is obtained in sequence at preset time intervals tyl, where 1≤i≤n, and n represents the number of sampling times in the corresponding period;

[0020] Calculate the typical value ks of these n ksi;

[0021] Then obtain the m typical values ​​ks corresponding to this period in the past m days;

[0022] Continue to calculate the typical value kss of the m typical values ​​ks, and use the typical value kss as the average predicted parking number kj in the corresponding period;

[0023] The parking strategy information records the average predicted parking number kj and the maximum parking number kmax for each time period of a day during non-holidays obtained through historical data, and the average predicted parking number kj and the maximum parking number kmax for each time period of a day during holidays.

[0024] Optionally, the control device is further used for:

[0025] Monitor the vehicle information that sends the guidance command in real time, extract the vehicle operation behavior information in the vehicle information, and compare it with the preset vehicle operation behavior information. If there is any inconsistency, an alarm message will be issued;

[0026] Vehicle types include: concrete trucks, transport trucks, buses, private cars, and police cars;

[0027] The guidance instruction includes: sending driving information at each node of the guidance route.

[0028] Optionally, the designated park includes a part of the electronic fence area and a part of the non-electronic fence area, and the non-electronic fence area is a public driving area and an area of ​​a plurality of public parking lots;

[0029] The control device interacts with a vehicle terminal of the vehicle, and the vehicle terminal includes: a positioning unit, a navigation unit and a processing unit.

[0030] Optionally, the parking strategy information established based on historical data includes:

[0031] A reinforcement learning model is used to construct the actual parking quantity in any period before the current target period, as well as the predicted parking quantity in any period in the next three days.

[0032] Optionally, if the response information includes information that parking in the parking lot is not recommended, the vehicle terminal obtains available parking lots around the designated park; at the same time, it obtains parking information for each time period corresponding to each parking lot from the external network, and displays the distance between the parking lot to which the selected parking location belongs and the surrounding available parking lots.

[0033] Furthermore, when calculating the reliability factor Q, parking spaces reserved for one person only and vehicles with parking spaces reserved for one person only are not included in the calculation.

[0034] Furthermore, when the average number of parking lots k corresponding to each time period is obtained, the standard deviation F of the n ksi values ​​is also calculated, thereby further obtaining m standard deviations F obtained in the past m days;

[0035] Calculate the typical value Fd of these m standard deviations;

[0036] According to the above method, the typical value Fd corresponding to each time period is calculated;

[0037] After the user logs in to the platform through the terminal device, he selects the destination, and the navigation unit obtains the available parking lots around the destination;

[0038] Obtain the typical value Fd corresponding to each parking lot satisfying the reliability coefficient Q≤Qy;

[0039] The optional coefficient W corresponding to each parking lot is calculated according to the formula W = α1*Fd+α2*X; wherein α1 and α2 are both preset coefficient values;

[0040] The parking lots are recommended in ascending order of the optional coefficient W.

[0041] Beneficial effects of the present invention:

[0042] 1. The present invention analyzes historical data on parking space utilization in a parking lot in various time periods, thereby predicting the availability of parking spaces when users who are ready to park arrive at the parking lot, and provides reasonable guidance to users on where to park based on the prediction results, thereby avoiding situations where there are few or no parking spaces remaining when users arrive at the parking lot, causing difficulties for users to park in the parking lot, and reasonably utilizing the surrounding available parking resources. At the same time, the influence of temporary factors on the prediction results is also considered, thereby improving the accuracy of the prediction.

[0043] 2. The present invention introduces stability evaluation parameters of the number of parking lots in each parking lot in each time period. When recommending parking lots, parking lots with higher stability are given priority, thereby improving the accuracy of the recommendation and avoiding the situation where reserved vehicles have difficulty in parking when they arrive at the parking lot due to sudden changes in the number of parking lots in the parking lot. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] Figure 1 It is a schematic diagram of the framework structure of a vehicle management system for smart parking of the present invention;

[0046] Figure 2 It is a flowchart of the control center judging whether the parking space meets the parking needs when the user's vehicle arrives at the parking lot. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Embodiment 1

[0049] like Figure 1 As shown, this embodiment provides a vehicle management system for smart parking, which includes:

[0050] The backend monitoring device is used to obtain in real time the basic information of each vehicle monitored by each monitoring unit for entering the designated park parking lot, the basic information including: vehicle identification, time information of the vehicle entering the park, and vehicle type;

[0051] The control device is used to determine whether the vehicle is a reserved vehicle based on the basic information of the vehicle. If so, it determines whether the area to which the current vehicle type belongs is idle. If so, it sends a guidance instruction to the vehicle terminal.

[0052] For example, the control device is also used to: monitor the vehicle information that sends the guidance instruction in real time, extract the vehicle operation behavior information in the vehicle information, and compare it with the preset vehicle operation behavior information, and if there is inconsistency, issue an alarm message;

[0053] Vehicle types include: concrete trucks, transport trucks, buses, private cars, and police cars;

[0054] The guidance instruction includes: sending driving information at each node of the guidance route.

[0055] To this end, the vehicle management system in this embodiment can realize real-time monitoring of reserved vehicles, and can realize real-time comparison of vehicle operation behavior information for reserved vehicles entering the electronic fence area, ensuring safety and realizing high-level monitoring of the electronic fence area.

[0056] In a specific implementation, the designated park includes a part of the electronic fence area and a part of the non-electronic fence area, and the non-electronic fence area is a public driving area and an area of ​​multiple public parking lots;

[0057] The control device interacts with a vehicle terminal of the vehicle, and the vehicle terminal includes: a positioning unit, a navigation unit and a processing unit.

[0058] The control device in this embodiment can communicate in real time with the positioning unit, navigation unit and processing unit in the vehicle terminal to ensure the real-time and accuracy of the interaction.

[0059] In the specific implementation process, if there are multiple public parking lots and public driving areas in the designated park, and the public parking lots meet the pre-reservation mechanism, the method further includes:

[0060] The control device is also used to:

[0061] Step 1: receiving a reservation request of any first vehicle, wherein the reservation request of the first vehicle includes: selected free parking location information and current vehicle location information;

[0062] Step 2: obtaining the predicted time t2 when the current first vehicle arrives at the selected parking location according to the reservation request;

[0063] Step three: Determine the reliability coefficient of the parking location selected in the reservation request based on the predicted time t2 and parking strategy information established by prior historical data, and send a response message to the first vehicle to indicate whether it agrees based on the reliability coefficient.

[0064] Regarding step three, this embodiment may further be specifically described as follows:

[0065] A01. Divide a day into r time periods; obtain the average predicted number of parking lots in each time period kj of the parking lot to which the selected parking location belongs from the parking strategy information, where 1≤j≤r, and r is a preset value;

[0066] A02. Mark the time period of the predicted time t2 as the target time period; obtain the average predicted parking number kj corresponding to the target time period from the parking strategy information 目标 ; and obtain the maximum number of parking lots kmax in the target time period; obtain the actual average number of parking lots kf in the parking lot in a time period before the time period corresponding to the current time; obtain the average predicted number of parking lots kjf in the parking lot in a time period before the time period corresponding to the current time;

[0067] A03, according to the formula Q = (kj 目标 / kmax)*(kf / kjf) to calculate the reliability coefficient Q of the reserved parking lot corresponding to this reservation information;

[0068] A04, when the reliability coefficient Q>Qy 指定数 , the response information includes information that it is not recommended to park in the parking lot; 指定数 is the preset coefficient.

[0069] In this embodiment, based on the parking strategy information established based on historical data, the average predicted number of parking lots kj of the selected parking location in each time period is obtained from the parking strategy information, including:

[0070] In a period within a day, the actual number of parking lots ksi in the parking lot is obtained in sequence at preset time intervals ty1, where 1≤i≤n, and n represents the number of sampling times in the corresponding period; the typical value ks of the n ksi is calculated; then the m typical values ​​ks corresponding to the period in the past m days are obtained; the typical value kss of the m typical values ​​ks is calculated, and the typical value kss is used as the average predicted number of parking lots kj in the corresponding period;

[0071] The parking strategy information records the average predicted parking number kj and the maximum parking number kmax for each period of a day during non-holidays, and the average predicted parking number kj and the maximum parking number kmax for each period of a day during holidays obtained through historical data.

[0072] In this embodiment, the parking strategy information established based on historical data can be constructed using a reinforcement learning model to construct the actual parking quantity in any period before the current target period, as well as the predicted parking quantity in any period within the next three days.

[0073] Of course, the aforementioned response information includes information that parking in the parking lot is not recommended, then the vehicle terminal obtains the available parking lots around the designated park; at the same time, it obtains the parking information of each parking lot corresponding to each time period from the external network, and displays the distance between the parking lot to which the selected parking location belongs and the surrounding available parking lots.

[0074] Embodiment 2

[0075] According to another aspect of the embodiment of the present invention, the embodiment of the present invention also provides a vehicle management system for smart parking, such as Figure 2 As shown, including:

[0076] A license plate collection unit is installed in each parking lot and is used to collect license plate information of vehicles entering the parking lot;

[0077] A vehicle monitoring unit, used to monitor the position of vehicles entering the parking lot, thereby obtaining the parking position and movement path of the vehicles entering the parking lot;

[0078] The license plate collection unit and the vehicle monitoring unit are both in communication connection with the background monitoring device in the first embodiment, such as remote connection.

[0079] It is understandable that the vehicle monitoring unit is a plurality of cameras distributed in the parking lot.

[0080] The vehicle terminal of this embodiment can be a user terminal of the driver, or a vehicle terminal, or a vehicle terminal device for vehicle navigation formed by a combination of a vehicle terminal and a user terminal. The vehicle terminal or user terminal of this embodiment includes: a positioning unit, a navigation unit, and a parking lot communication unit during the vehicle navigation process;

[0081] A positioning unit, used to obtain the position of the vehicle;

[0082] The navigation unit provides navigation information for the vehicle and can also predict the time it will take for the vehicle to reach the destination based on the route;

[0083] The parking lot communication unit is used to establish a communication connection between each parking lot and the control center.

[0084] The control device is used to receive the reservation information sent by the vehicle terminal device. After receiving the reservation information, it is determined whether the parking space meets the parking needs when the vehicle belonging to the vehicle terminal arrives at the parking lot.

[0085] The control device of this embodiment may be a control center in a designated park, and the parking lot to which the corresponding user-selected parking space belongs may be a public parking lot in the designated park. If the parking lot does not belong to a parking lot in the designated park, the control device to which the parking lot belongs is interacted with, and the control device in the designated park is not interacted with. In this embodiment, the interaction with the control device in the designated park is taken as an example for explanation.

[0086] like Figure 2 As shown, the control center determines whether the parking space meets the parking requirement when the user's vehicle arrives at the parking lot by:

[0087] Stp1. When a vehicle needs to find a parking lot for parking, the vehicle owner logs into the platform through a user terminal device (such as a mobile phone), and after selecting a corresponding parking lot as a reserve parking lot, the vehicle owner sends a reservation information to the control center through the terminal device;

[0088] Stp2, obtain the location of the vehicle that issued the reservation information through the positioning unit in the user terminal device, then obtain the location of the reserved parking lot in the designated park, and predict the time t1 required for the vehicle to enter the reserved parking lot from the current location through the navigation unit in the user terminal device;

[0089] Obtain the predicted time t2 when the vehicle arrives at the reserve parking lot based on the current time and the duration t1;

[0090] Stp3, a day is divided into r time periods, and the time period division can be uniform division, or other reasonable divisions according to the application environment of the parking lot. For example, the parking lot of a tourist attraction can be divided according to the peak entrance and departure periods of tourists;

[0091] Get the average predicted number of parking lots in each time period kj, where 1≤j≤r, r is a preset value;

[0092] The calculation method of the average predicted parking number kj in each time period is:

[0093] In a period of one day, the actual number of parking lots in the parking lot ksi is obtained in sequence at preset time intervals ty1, where 1≤i≤n, and n represents the number of sampling times in the corresponding period, that is, the number of times the actual number of parking lots is obtained in the corresponding period;

[0094] Calculate the typical value ks of these n ksi;

[0095] Then obtain the m typical values ​​ks corresponding to this period in the past m days;

[0096] Continue to calculate the typical value kss of the m typical values ​​ks, and use the typical value kss as the average predicted parking number kj in the corresponding period;

[0097] The typical value refers to a parameter that can represent the group characteristics of a group of parameters. Specifically, it can be the average value, median value, or average value of the remaining values ​​after removing the values ​​with large deviations in the group of parameters.

[0098] It should be noted that when determining the past m days for sampling, these m days can be m consecutive days or m non-consecutive days, and can be specifically adjusted according to the usage background of the parking lot. For the sake of ease of understanding, an example is given as follows: For shopping mall parking lots, since the number of parking lots on weekdays and weekends is different, when sampling, the weekends are separated from the weekdays, and then m days are taken for sampling calculations separately.

[0099] When the average number of parking lots k corresponding to each time period is obtained in the above steps, the standard deviation F of the n ksi values ​​is also calculated, so as to further obtain the m standard deviations F obtained in the past m days; the typical value Fd of the m standard deviations is calculated;

[0100] The typical value Fd corresponding to each time period is calculated according to the above method.

[0101] Stp4, obtaining the time period of the reserve parking lot in which the predicted time t2 is located, and marking the time period as the target time period for easy distinction;

[0102] Get the average predicted parking number kj corresponding to the target period;

[0103] Get the maximum number of parking spaces kmax in the reserve parking lot (i.e. the number of active parking spaces that can be put into operation);

[0104] The kj and kmax parameters corresponding to each parking lot can be stored in the parking lot control device and updated according to actual changes;

[0105] Get the actual average number of parking lots kf in the reserve parking lot in a period before the period corresponding to the current time;

[0106] Get the average predicted number of parking lots kjf in a time period before the time period corresponding to the current time;

[0107] It should be noted that when performing the above steps, dedicated parking spaces and vehicles with dedicated parking spaces are not taken into consideration, that is, the above average parking number, maximum parking number, etc. do not include dedicated parking spaces;

[0108] In one embodiment of the present invention, the actual average parking number kf is calculated in the same way as ks, that is:

[0109] In a period before the period corresponding to the current moment, the actual number of parking lots in the parking lot is obtained in sequence at preset time intervals ty1, and typical values ​​of the actual number of parking lots are obtained, and the typical values ​​are used as kf;

[0110] The reliability coefficient Q of the reserved parking lot corresponding to the current reservation information is calculated according to the formula Q = (kj / kmax)*(kf / kjf);

[0111] Stp5. When the reliability coefficient Q>Qy, it is considered that when the vehicle enters the reserve parking lot, the parking space is tight and it is inconvenient to park, so it is not recommended to park in the parking lot;

[0112] On the contrary, when the reliability coefficient Q≤Qy, it is considered that when the vehicle enters the reserve parking lot, there are sufficient parking spaces and the vehicle can go there to park;

[0113] Where Qy is the preset coefficient.

[0114] The present invention analyzes historical data on parking space utilization in a parking lot in various time periods, thereby predicting the availability of parking spaces when users who are ready to park arrive at the parking lot, and provides reasonable guidance to users on where to park based on the prediction results, thereby avoiding situations where users have difficulty parking in the parking lot and making reasonable use of surrounding available parking resources. At the same time, the influence of temporary factors on the prediction results is also considered, thereby improving the accuracy of the prediction.

[0115] Optionally, after the user logs in to the platform through the vehicle terminal device, if the selected reserve parking lot does not have good parking conditions, that is, when the reliability coefficient Q>Qy in the embodiment is established, the user can also select a destination, and the navigation unit in the vehicle terminal obtains available parking lots connected to the surrounding area of ​​the destination, and interacts with the control centers of these available parking lots to obtain the reliability coefficient Q corresponding to each parking lot;

[0116] The reliability coefficient Q corresponding to each parking lot and the distance X between the parking lot and the destination can be displayed, and the user can make a selection according to needs.

[0117] In practical applications, the vehicle terminal can also sort the parking lots based on the reliability coefficient Q and the distance X between the corresponding parking lot and the destination, and intuitively display the preference of each parking lot.

[0118] The second method is exemplified as follows:

[0119] First, it is determined whether the coefficient Q satisfies Q≤Qy, and parking lots that meet this condition are selected, and parking lots are recommended in the order of distance X from small to large.

[0120] After logging into the platform through the vehicle terminal device, the user can select a destination, and the navigation unit in the vehicle terminal obtains the available parking lots around the destination;

[0121] Obtain the typical value Fd corresponding to each parking lot satisfying the reliability coefficient Q≤Qy;

[0122] The optional coefficient W corresponding to each parking lot is calculated according to the formula W = α1*Fd+α2*X; wherein α1 and α2 are both preset coefficient values;

[0123] The parking lots are recommended in ascending order of the optional coefficient W. The present invention introduces a stability evaluation parameter of the number of parking lots in each parking lot in each time period. When recommending parking lots, parking lots with higher stability are given priority, which can improve the accuracy of the recommendation and avoid the situation where the reserved vehicle has difficulty parking when arriving at the parking lot due to a sudden change in the number of parking lots in the parking lot.

[0124] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A vehicle management system for smart parking, characterized in that: include: The backend monitoring device is used to obtain in real time the basic information of each vehicle monitored by each monitoring unit for entering the designated park parking lot, the basic information including: vehicle identification, time information of the vehicle entering the park, and vehicle type; The control device is used to determine whether the vehicle is a reserved vehicle based on the basic information of the vehicle. If so, it determines whether the area to which the current vehicle type belongs is idle. If so, it sends a guidance instruction to the vehicle terminal.

2. The vehicle management system according to claim 1, characterized in that: If there are multiple public parking lots and public driving areas in the designated park, and the public parking lots meet the pre-reservation mechanism, the method further includes: The control device is also used to receiving a reservation request of any first vehicle, wherein the reservation request of the first vehicle includes: selected free parking location information and current vehicle location information; Obtaining a predicted time t2 when the current first vehicle arrives at the selected parking location according to the reservation request; According to the predicted time t2, parking strategy information established by historical data in advance, and the reliability coefficient of the parking location selected in the reservation request, a response message of whether to agree is sent to the first vehicle according to the reliability coefficient.

3. The vehicle management system according to claim 1, characterized in that: According to the predicted time t2, parking strategy information established by historical data in advance, and the reliability coefficient of the parking location selected in the reservation request, a response message of whether to agree is sent to the first vehicle according to the reliability coefficient, including: dividing a day into r time periods; obtaining the average predicted number of parking lots kj of the parking lot to which the selected parking location belongs in each time period from the parking strategy information, where 1≤j≤r, and r is a preset value; Mark the time period of the predicted time t2 as the target time period; obtain the average predicted parking number kj corresponding to the target time period from the parking strategy information 目标 ; and obtain the maximum number of parking lots kmax in the target time period; obtain the actual average number of parking lots kf in the parking lot in a time period before the time period corresponding to the current time; obtain the average predicted number of parking lots kjf in the parking lot in a time period before the time period corresponding to the current time; According to the formula Q = (kj 目标 / kmax)*(kf / kjf) to calculate the reliability coefficient Q of the reserved parking lot corresponding to this reservation information; When the reliability coefficient Q>Qy 指定数 , the response information includes information that it is not recommended to park in the parking lot; 指定数 is the preset coefficient.

4. A vehicle management system for smart parking according to claim 3, characterized in that: Based on the parking strategy information established by historical data, the average predicted number of parking lots in each time period of the selected parking location is obtained from the parking strategy information, including: In a period within a day, the actual number of parking lots ksi in the parking lot is obtained in sequence at preset time intervals ty1, where 1≤i≤n, and n represents the number of sampling times in the corresponding period; Calculate the typical value ks of these n ksi; Then obtain the m typical values ​​ks corresponding to this period in the past m days; Continue to calculate the typical value kss of the m typical values ​​ks, and use the typical value kss as the average predicted parking number kj in the corresponding period; The parking strategy information records the average predicted parking number kj and the maximum parking number kmax for each period of a day during non-holidays, and the average predicted parking number kj and the maximum parking number kmax for each period of a day during holidays obtained through historical data.

5. A vehicle management system for smart parking according to claim 1, characterized in that: The control device is also used for: Monitor the vehicle information that sends the guidance command in real time, extract the vehicle operation behavior information in the vehicle information, and compare it with the preset vehicle operation behavior information. If there is any inconsistency, an alarm message will be issued; Vehicle types include: concrete trucks, transport trucks, buses, private cars, and police cars; The guidance instruction includes: sending driving information at each node of the guidance route.

6. A vehicle management system for smart parking according to claim 2, characterized in that: The designated park includes part of the electronic fence area and part of the non-electronic fence area, and the non-electronic fence area is the public driving area and the area of ​​multiple public parking lots; The control device interacts with a vehicle terminal of the vehicle, and the vehicle terminal includes: a positioning unit, a navigation unit and a processing unit.

7. A vehicle management system for smart parking according to claim 4, characterized in that: Parking strategy information based on historical data, including: A reinforcement learning model is used to construct the actual parking quantity in any period before the current target period, as well as the predicted parking quantity in any period within the next three days.

8. A vehicle management system for smart parking according to claim 3, characterized in that: If the response information includes information that parking in the parking lot is not recommended, the vehicle terminal obtains available parking lots around the designated park; At the same time, the parking information of each parking lot corresponding to each time period is obtained from the external network, and the distance between the parking lot to which the selected parking location belongs and the surrounding available parking lots is displayed.

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