Shared parking demand prediction and parking space distribution system

Abstract

The invention discloses a shared parking demand prediction and parking space distribution system applied to the field of parking space distribution, and the system enables the parking spaces in different areas to be mutually linked through sharing the parking spaces in a residential area with a high vacancy rate in the daytime and the parking spaces in a working area with a high vacancy rate at night in different time periods. Therefore, under the condition that existing parking space planning is not increased, the parking contradiction is effectively solved; meanwhile, the parking space can be locked and reserved in advance before parking, so that the user can effectively shorten the time for finding the parking space, the time for the vehicle to stay on the road surface before parking is shortened, and the traffic jam phenomenon caused by temporary gathering of the vehicle in the peak period is effectively reduced; the automatic locking device is designed to be in a form capable of transversely moving in a small range, when accidental collision occurs, the automatic locking device can generate certain avoiding buffering, a vehicle is effectively protected against damage caused by collision with the automatic locking device, meanwhile, a user can respond in time, and excessive extrusion is not prone to occurring between the vehicle and the automatic locking device.

Description

Technical Field

[0001] This invention relates to the field of parking space allocation, and in particular to a shared parking demand prediction and parking space allocation system. Background Technology

[0002] In the existing technology, although some smart parking spaces have been added by utilizing part of the road surface, such as the roadside smart parking system disclosed in Chinese patent CN216014473U, the number of smart parking spaces is limited and still cannot meet the parking demand, resulting in the following technical defects in the existing parking management.

[0003] Parking conflicts are prominent in key areas such as old residential communities, hospitals, and schools. Although renovations have been carried out in old residential communities to alleviate parking problems, such as the IoT-based smart community service system disclosed in Chinese patent application CN112700359A, the limited space and the limited number of parking spaces after the renovation mean that such renovations are still only a temporary solution. Furthermore, the lack of a dynamic scheduling mechanism for cross-regional linkage leads to a large number of vehicles being unable to park effectively and in a timely manner during scenarios such as school drop-off and pick-up times, hospital morning rush hours, and peak tourist seasons. This results in some vehicles lingering on the road, causing traffic congestion due to the sudden accumulation of vehicles. At the same time, due to the lack of a macro-level understanding of parking availability, users have to spend a lot of time searching for parking spaces, resulting in some parking spaces remaining vacant and difficult to use in a timely manner, thus exacerbating traffic congestion. Summary of the Invention

[0004] The core of this invention lies in sharing parking spaces in residential areas with high daytime vacancy rates and parking spaces in work areas with high nighttime vacancy rates, enabling different areas to work together and effectively resolving parking conflicts without increasing existing parking space planning. Simultaneously, parking spaces can be reserved in advance, effectively reducing the time users spend searching for parking spaces and minimizing the time vehicles spend on the road before parking. This effectively reduces traffic congestion caused by temporary vehicle gatherings during peak hours in key areas such as older residential areas, hospitals, and schools, achieving a proactive "reservation first, parking later" service model.

[0005] To solve the above problems, the present invention adopts the following technical solution.

[0006] A shared parking demand forecasting and parking space allocation system includes a central controller and a data acquisition module, a demand forecasting module, a parking space allocation module, an identity authentication module, and a user interaction module that communicate with the central controller. The data acquisition module is used to collect parking space status data, user behavior data, traffic flow data, and environmental data. The demand forecasting module builds a parking demand forecasting model based on multi-source data to predict parking demand in different areas and at different times. The parking space allocation module includes a static locking unit and a dynamic allocation unit; The static locking unit is used to receive user reservation requests, lock the designated parking space, and automatically unlock it when the user arrives. The static locking unit includes an automatic locking device installed at the center of the parking space ground and a timer module installed on the automatic locking device. The automatic locking device is installed on the ground of the parking space and is controlled by a central controller to lock and unlock the parking space; The timer module records the reserved locking time and automatically unlocks the device if the time expires before it is locked. The extension module allows users to request an extension once within the locked time period; The dynamic allocation unit enables dynamic scheduling of parking space resources across regions based on demand forecasts and user behavior patterns. The dynamic allocation unit includes a regional linkage matching module, which is used to identify residential areas, work areas and school information under different regions associated with the user, and match cross-regional shared parking spaces based on the user's behavior trajectory.

[0007] The identity authentication module is used to verify the authenticity of users' identities in different areas such as residential areas, workplaces, and schools, ensuring the safety of people in shared areas; The user interaction module provides functions such as parking space search, reservation, sharing and posting, credit inquiry and navigation guidance; The central controller is used to receive real-time data from the data acquisition module, call the prediction results from the demand forecasting module, issue control commands to the parking space allocation module, and coordinate data interaction and task scheduling between the modules.

[0008] Furthermore, the demand forecasting module includes an LSTM neural network forecasting model, and the input data of the LSTM neural network forecasting model includes historical parking data, meteorological data, holiday information and regional event data. The output data of the LSTM neural network forecasting model is the probability distribution of parking space demand in future periods.

[0009] Furthermore, different areas include, but are not limited to, residential areas, work areas, schools, and hospitals; The regional linkage matching module includes at least: Commuting scenario matching unit: Identifies user's workplace and residence information, and matches shared parking spaces in residential areas during the day with shared parking spaces in office areas at night; School pick-up and drop-off scenario matching unit: Identifies the relationship between student information and parents, and matches parking spaces in designated areas around the school during dismissal time; Medical Treatment Scenario Matching Unit: Connects with the hospital registration system to match nearby parking resources during the consultation period.

[0010] Optionally, a credit management module is also included. This module records user performance and establishes a credit score system. Credit scores are positively correlated with reservation privileges, parking space lock-in duration, and fee discounts.

[0011] Optionally, a flexible reservation module is also included, whereby parking space publishers set a mandatory reservation period when publishing shared parking spaces. When the publisher returns early, the system automatically searches for nearby available parking spaces and provides replacement guidance.

[0012] A shared parking demand forecasting and parking space allocation system includes the following steps in its parking space allocation method: S1. Collect multi-source data, including parking space status, user behavior, traffic flow and environmental data; S2. Predict parking demand in different areas at different times based on the LSTM model; S3. Receive user reservation requests and allocate parking spaces based on demand forecasts and user identity information; S4. Identify user-associated area information and match cross-regional shared parking space resources; S5: Lock the assigned parking space and unlock it automatically when the user arrives; S6. Record user performance and update credit scores.

[0013] Furthermore, the specific steps for cross-regional parking space sharing in step S4 are as follows: S41. User Profile Construction: After each user registers and completes multi-scenario authentication, the system constructs a set of associated area tags, which include residential area identifiers, work area identifiers, school identifiers, and typical time periods for users to use parking spaces in each area; S42. Shared parking space posting: Users with fixed parking spaces (such as owners and long-term tenants) can post parking space sharing information through the user interaction module. When posting, they need to specify the sharing time period, the scope of sharing targets, the charging standard, and the mandatory retention period. S43. Parking space reservation and locking: Based on the user's destination, the user interaction module displays the destination and the occupancy status of parking spaces in and around it, and recommends some open parking spaces that meet the user's needs. The user selects one of the open parking spaces on the user interaction module and reserves it online. After the reservation and locking, the central controller controls the automatic locking device on the corresponding parking space to temporarily lock the parking space. S44. Dynamic adjustment of parking space status: The reservation and locking results of parking spaces are updated in real time. If the user cancels or fails to arrive within the time limit, the central controller immediately controls the automatic locking device on the corresponding parking space to unlock, reopen the parking space, and trigger re-matching.

[0014] Furthermore, the specific operation of step S6 includes the following steps: S61. Behavior monitoring: The central controller continuously monitors the entire parking process of users, including whether they arrive within the locked time, the match between the actual parking duration and the reserved time period, whether they leave on time, and whether they cancel the reservation. S62. Points Calculation: A dynamic points system is adopted, with a base score of 100 points. Points are adjusted based on behavior monitoring results. Points are added for arriving on time and parking, successfully sharing a parking space, and reporting illegal parking. Points are deducted for not arriving on time, parking beyond the time limit, and temporarily canceling parking. S63. Points Application: Points are synchronized to the user's account and affect the user's subsequent parking space reservation and locking privileges in real time. The higher the points, the longer the reservation and locking period and the wider the range of time slots that can be reserved. When the points are below 60, the system will suspend the user's reservation privileges for 7 days and push a credit improvement guide.

[0015] Optionally, the automatic locking device includes an adaptive base, a transverse support column that moves through the adaptive base, and a semi-ring locking plate connected to the outer end via an electric rotating shaft. The adaptive base includes a mounting base plate, a limiting ring fixedly connected to the upper edge of the mounting base plate, and a buffer layer fixedly connected to the upper end of the limiting ring. A sliding space is formed between the buffer layer and the mounting base plate. The transverse support column includes a sliding piece located in the sliding space, a central shaft fixedly connected to the middle of the upper end of the sliding piece, and an upper fixed plate fixedly connected to the outer end of the central shaft. The connection between the semi-ring locking plate and the transverse support column is located on the upper fixed plate, and the upper fixed plate and the sliding piece are in contact with the upper and lower surfaces of the buffer layer, respectively.

[0016] Furthermore, the buffer layer includes a hard rubber layer, multiple elastic rubber teeth uniformly fixedly connected to the inner wall of the hard rubber layer, and multiple arc-shaped grooves respectively carved into the inner wall of the hard rubber layer. Adjacent elastic rubber teeth do not contact each other and form a buffer gap between them. The middle part of the multiple arc-shaped grooves corresponds to the multiple buffer gaps. The ends of the multiple elastic rubber teeth away from the hard rubber layer form an annulus, and the central axis moves through the annulus. The diameter of the slider is larger than the inner diameter of the hard rubber layer.

[0017] Compared with the prior art, the advantages of this invention are: (1) This plan shares parking spaces in residential areas with high daytime vacancy rates and parking spaces in work areas with high nighttime vacancy rates in different time periods, so that different areas can work together and thus effectively solve the parking problem without increasing the existing parking space plan.

[0018] (2) At the same time, parking spaces can be reserved in advance before parking, which can effectively reduce the time users spend looking for parking spaces and reduce the time vehicles stay on the road before parking. This can effectively reduce traffic congestion caused by temporary gathering of vehicles during peak hours in key areas such as old residential areas, hospitals, and schools, and realize the proactive service model of "reservation first, parking later".

[0019] (3) The automatic locking device is designed to be able to move laterally within a small range. In the event of an accidental collision, it can generate a certain amount of avoidance and buffer, effectively protecting the vehicle from damage caused by collision with the automatic locking device. At the same time, it enables the user to react in time, so that there is less excessive squeezing between the vehicle and the automatic locking device. Attached Figure Description

[0020] Figure 1 This is a main system block diagram of the present invention; Figure 2 This is a schematic diagram illustrating the interconnected and shared parking spaces in different areas according to the present invention. Figure 3 This is a schematic diagram illustrating how, during the daytime, when vehicles gather in the work area, some vehicles are diverted to shared parking spaces in the surrounding residential areas. Figure 4 This is a schematic diagram illustrating how, when vehicles gather in residential areas at night, some vehicles are diverted to shared parking spaces in work areas surrounding the residential areas. Figure 5 This is a perspective view of the automatic locking device of the present invention; Figure 6 This is a schematic diagram of the buffer movement after an accidental collision between the vehicle and the automatic locking device in this invention; Figure 7 This is a cross-sectional view of the automatic locking device of the present invention; Figure 8 This is a schematic diagram of the buffer movement after an accidental collision between the vehicle and the automatic locking device in this invention; Figure 9 This is a schematic diagram illustrating the buffering movement process of the semi-ring lock plate after an accidental collision between the vehicle and the automatic locking device in this invention.

[0021] Explanation of the labels in the diagram: 11 Mounting base plate, 12 Limiting edge ring, 13 Buffer layer, 131 Hard rubber layer, 132 Elastic rubber teeth, 133 Arc groove, 2 Semi-ring locking plate, 3 Horizontal movement support column, 31 Upper fixed plate, 32 Sliding plate. Detailed Implementation

[0022] The technical solutions will now be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention.

[0023] First implementation method: like Figure 1 A shared parking demand forecasting and parking space allocation system includes a central controller and a data acquisition module, a demand forecasting module, a parking space allocation module, an identity authentication module, and a user interaction module that communicate with the central controller. The data acquisition module is used to collect parking space status data, user behavior data, traffic flow data, and environmental data. The demand forecasting module builds a parking demand forecasting model based on multi-source data to predict parking demand in different areas and at different times. The parking space allocation module includes a static locking unit and a dynamic allocation unit; The static locking unit is used to receive user reservation requests, lock the designated parking space, and automatically unlock it when the user arrives. The static locking unit includes an automatic locking device installed at the center of the parking space ground and a timer module installed on the automatic locking device. The automatic locking device is installed on the ground of the parking space and is controlled by a central controller to lock and unlock the parking space; The timer module is used to record the reservation lock time. The timer module has a preset time threshold. If the reserved parking space is not reached after the time threshold is exceeded, the space will be automatically unlocked to open the corresponding parking space so that it can be reserved and locked by other users. It is worth noting that the time threshold can be set to 10 minutes, meaning that after reserving and locking a parking space, you need to arrive at the target parking space within 10 minutes. The specific value of the time threshold can also be set according to actual needs during implementation. After reserving and locking a parking space, if it is difficult to arrive on time due to traffic jams or other unforeseen circumstances, you can apply for an extension to reserve the parking space. The specific extension duration depends on the user's credit score. The higher the credit score, the longer the extension duration (for example, those with a score below 60 do not have the right to extend, those with a score of 61-70 can extend for a maximum of 1 minute, those with a score of 71-80 can extend for a maximum of 2 minutes, those with a score of 81-90 can extend for a maximum of 3 minutes, and those with a score of 91-100 can extend for a maximum of 5 minutes). If you do not apply for an extension and do not arrive within 10 minutes, or if you do not arrive on time after extending the time, the parking space will be automatically unlocked.

[0024] In addition, to ensure the normal use of parking spaces, the maximum duration of extended parking time shall not exceed 5 minutes.

[0025] The dynamic allocation unit enables dynamic scheduling of parking space resources across regions based on demand forecasts and user behavior patterns. The dynamic allocation unit includes a regional linkage matching module, which is used to identify information in different regions associated with a user and match cross-regional shared parking spaces based on the user's behavior trajectory.

[0026] The identity authentication module is used to verify the authenticity of users' identities in different areas such as residential areas, workplaces, and schools, ensuring the safety of people in shared areas; The user interaction module provides functions such as parking space search, reservation, sharing and posting, credit inquiry and navigation guidance; The central controller is used to receive real-time data from the data acquisition module, call the prediction results from the demand forecasting module, issue control commands to the parking space allocation module, and coordinate data interaction and task scheduling between the modules.

[0027] The demand forecasting module includes an LSTM neural network prediction model. The input data for this model includes historical parking data, weather data, holiday information, and regional event data. The output data is the probability distribution of parking space demand for future periods. The LSTM neural network prediction model has a 3-layer hidden layer structure with 64 neurons per layer. The model training parameters are set as follows: learning rate 0.001, 500 iterations, and mean squared error (MSE) loss function. After training, the model is validated on a test set, and it can only be deployed if its accuracy reaches 85% or higher.

[0028] The LSTM neural network prediction model is an existing technology, and the specific model will not be described in detail.

[0029] Different areas include, but are not limited to, residential areas, work areas, schools, and hospitals. These areas can also be tourist areas. By renting local vehicles with real names, when traveling in unfamiliar cities, users can access this parking allocation system when parking, or link with surrounding residential or work areas through ID cards or attraction ticket information to achieve shared parking spaces for convenient parking.

[0030] The regional linkage matching module includes at least a commuting scenario matching unit, a school pick-up and drop-off scenario matching unit, and a medical treatment scenario matching unit.

[0031] like Figures 2-4 The commuting scenario matching unit identifies the user's workplace and residence information, matching shared parking spaces in residential areas during the day with shared parking spaces in office areas at night. Since residential areas have higher vacancy rates and lower parking demand during the day, but higher demand at night, while office areas (e.g., office buildings) have higher parking demand during the day and higher vacancy rates at night, automatic locking devices can be installed in existing parking spaces in both residential and work areas. This allows for monitoring of parking space usage and facilitates users to lock parking spaces in advance and share them at different times. During the day, when vehicles converge towards work areas, some can be diverted to nearby residential areas; conversely, at night, when vehicles converge towards residential areas, some can be diverted to nearby work areas. Compared to existing methods of adding parking spaces by allocating land, this significantly reduces land use pressure, effectively utilizes existing parking resources, and alleviates urban parking pressure.

[0032] School drop-off and pick-up scenario matching unit: Identifies the relationship between student information and parents, and matches parking spaces in designated areas around the school during dismissal time, so that when parents pick up and drop off their children, their vehicles can be parked in designated parking spaces, which is less likely to cause traffic congestion around the school. Users can reserve parking spaces in office buildings or residences around the school in advance, thereby significantly reducing the time that vehicles stay on the road near the school, thus effectively alleviating the phenomenon of congestion at the school gate. Medical Treatment Scenario Matching Unit: Connects with the hospital registration system to match nearby parking resources during the consultation period, allowing users to reserve parking spaces in office buildings or residences near the hospital in advance, thereby significantly reducing the time vehicles spend searching for parking spaces around the hospital and reducing congestion in local areas.

[0033] A parking space allocation method for a shared parking demand forecasting and allocation system includes the following steps: S1. Collect multi-source data, including parking space status, user behavior, traffic flow and environmental data; Among these technologies, laser sensing and radar can be used to monitor the occupancy status of each parking space.

[0034] It is worth noting that when retrofitting parking spaces in residential and office areas with automatic locking devices, at least one-third of the parking spaces should not be equipped with automatic locking devices. This allows users who cannot reserve parking spaces online to park normally. Furthermore, the automatic locking device will only activate when the parking space is reserved and locked. Otherwise, the automatic locking device will not activate, allowing users in the corresponding residential or office areas to park normally even when the space is not reserved and locked. In other words, it is available for users to park normally, just like a regular parking space.

[0035] It is worth noting that for users from different areas, only those who have made advance reservations and locked their vehicles will have the right to enter residential areas, office areas, and other areas that are not associated with them. This effectively prevents social vehicles from occupying parking spaces in large numbers and affecting the normal parking needs of people in residential and office areas.

[0036] S2. Predict parking demand in different areas at different times based on the LSTM model; S3. Receive user reservation requests and allocate parking spaces based on demand forecasts and user identity information. The parking space allocation criteria include at least the following: the parking space is not occupied by other reservations; the parking space permissions match the user's identity (e.g., shared parking spaces within the community can only be reserved by users who have been certified by the residential area or the workplace); the parking space type meets the user's needs (e.g., whether it has a charging pile or is for disabled persons); the parking space is closest to the user's current location or target destination; the parking space has the lowest cost; and the user's historical preferences (e.g., frequently parked areas, frequently selected floors). The priority order of parking space allocation conditions is as follows: "parking space not reserved → parking space permissions match user identity → distance priority → parking space type matching → lowest cost → user historical preferences", etc.

[0037] S4. Identify user-associated area information and match cross-regional shared parking space resources; S5: Lock the assigned parking space and unlock it automatically when the user arrives.

[0038] The specific steps for cross-regional parking space sharing in step S4 are as follows: S41. User Profile Construction: After each user registers and completes multi-scenario authentication, the system constructs a set of associated area tags, which include residential area identifiers, work area identifiers, school identifiers, and typical time periods for users to use parking spaces in each area; S42. Shared parking space posting: Users with fixed parking spaces (such as owners and long-term tenants) can post parking space sharing information through the user interaction module. When posting, they need to specify the sharing time period, the scope of sharing targets, the charging standard, and the mandatory retention period. S43. Parking space reservation and locking: Based on the user's destination, the user interaction module displays the destination and the occupancy status of parking spaces in and around it, and recommends some open parking spaces that meet the user's needs. The user selects one of the open parking spaces on the user interaction module and reserves it online. After the reservation and locking, the central controller controls the automatic locking device on the corresponding parking space to temporarily lock the parking space. S44. Dynamic adjustment of parking space status: The reservation and locking results of parking spaces are updated in real time. If the user cancels or fails to arrive within the time limit, the central controller immediately controls the automatic locking device on the corresponding parking space to unlock, reopen the parking space, and trigger re-matching.

[0039] It is worth noting that this system also includes a flexible reservation module. When posting a shared parking space, the poster can set a mandatory reservation period. For example, when posting a shared parking space information, it can be set that the space must be returned before 20:00. When the poster returns the space early, the system will automatically search for shared parking spaces posted by other users nearby and provide replacement guidance according to the priority of "distance priority → parking space type matching → lowest cost" to reduce parking space usage conflicts.

[0040] Second implementation method: This implementation adds a credit management module to the first implementation, while the rest remains the same as the first implementation.

[0041] This system also includes a credit management module, which records users' performance and establishes a credit score system. Credit scores are positively correlated with reservation privileges, parking space lock-in duration, and fee discounts.

[0042] Accordingly, the parking space allocation method includes the following steps: S6. Record user performance behavior and update credit score. The specific operations of step S6 include the following steps: S61. Behavior monitoring: The central controller continuously monitors the entire parking process of users, including whether they arrive within the locked time (the time difference from the start of locking to successful unlocking), the matching degree between the actual parking time and the reserved time period (overtime parking time), whether they leave on time (judged by the ground lock rising again or the gate exit record), and whether they cancel the reservation (the length of time between the cancellation time and the start time of the reservation). S62. Points Calculation: A dynamic points system is adopted, with a base score of 100 points. Points are changed based on behavior monitoring results. Points are added for arriving on time and parking, successfully sharing a parking space, and reporting illegal parking. The specific points added can be set according to actual needs. Points are deducted for not arriving on time, exceeding the parking time limit, and temporarily canceling the parking. The specific points deducted can be set according to actual needs. Among these measures, the daily cap is increased or decreased by 10 points to prevent score manipulation. S63. Points Application: Points are synchronized to the user's account and affect the user's subsequent parking space reservation and locking privileges in real time. The higher the points, the longer the reservation and locking period and the wider the range of time slots that can be reserved. When the points are below 60, the system will suspend the user's reservation privileges for 7 days and push a credit improvement guide.

[0043] By using credit management, the sharing of parking spaces across regions and the advance reservation and locking of parking spaces can be made more standardized, making it less likely for malicious parking space locking to occur and improving the convenience of this reservation-before-parking method.

[0044] The third implementation method: Based on the first two implementation methods, the automatic locking device is further improved as follows: Because the automatic locking device is low to the ground, it is easily overlooked in poor lighting conditions, making it easy for vehicles to collide with it. Therefore, the automatic locking device is designed to be able to move laterally within a small range. In the event of an accidental collision, it can provide a certain degree of avoidance and buffer, effectively protecting the vehicle from damage caused by collision with the automatic locking device. At the same time, it allows the user to react in time, preventing excessive compression between the vehicle and the automatic locking device.

[0045] like Figure 5The automatic locking device includes an adaptive base, a transverse support column 3 that moves through the adaptive base, and a semi-ring locking piece 2 connected to the outer end of the transverse support column 3 via an electric rotating shaft. The adaptive base includes a mounting base plate 11, a limiting edge ring 12 fixedly connected to the upper edge of the mounting base plate 11, and a buffer layer 13 fixedly connected to the upper end of the limiting edge ring 12. A sliding space is formed between the buffer layer 13 and the mounting base plate 11. The transverse support column 3 includes a sliding piece 32 located in the sliding space, a central shaft fixedly connected to the middle of the upper end of the sliding piece 32, and an upper fixed plate 31 fixedly connected to the outer end of the central shaft. The connection between the semi-ring locking piece 2 and the transverse support column 3 is located on the upper fixed plate 31, and the upper fixed plate 31 and the sliding piece 32 are in contact with the upper and lower surfaces of the buffer layer 13, respectively.

[0046] like Figure 7 The buffer layer 13 includes a hard rubber layer 131, multiple elastic rubber teeth 132 uniformly fixedly connected to the inner wall of the hard rubber layer 131, and multiple arc-shaped grooves 133 respectively carved into the inner wall of the hard rubber layer 131. Two adjacent elastic rubber teeth 132 do not contact each other and form a buffer gap between them. The middle part of the multiple arc-shaped grooves 133 corresponds to the multiple buffer gaps. The ends of the multiple elastic rubber teeth 132 away from the hard rubber layer 131 form a ring, and the central axis moves through the ring. This ring is used to restrict the transverse support 3 and the semi-ring locking piece 2 on it. At the same time, it makes it less likely to affect the radial movement of the transverse support 3 as a whole. The diameter of the sliding piece 32 is larger than the inner diameter of the hard rubber layer 131, which effectively ensures that the transverse support 3 as a whole is difficult to separate from the adaptive base, so that the overall stability of this automatic locking device is strong and it can stably perform the advance reservation locking of the parking space.

[0047] like Figure 6 , Figure 8 and Figure 9 If a vehicle accidentally collides with this automatic locking device, firstly, because the semi-ring locking plate 2 and the lateral support 3 connected to it are not fixed, they will deflect to a certain extent in the direction of the force in the initial stage of the collision, until the radial surface of the semi-ring locking plate 2 is directly facing the vehicle body, thereby increasing the contact area between the semi-ring locking plate 2 and the vehicle body. This reduces the stress concentration on the vehicle body due to the small force area. This deflection can partially unload the force and reduce collision damage. At the same time, under the pushing force of the vehicle body on the semi-ring locking plate 2, the semi-ring locking plate 2 will move laterally away from the vehicle body. During this process, the central shaft will be embedded between two adjacent elastic rubber teeth 132, causing multiple elastic rubber teeth 132 to deform to both sides, achieving a radial buffering effect, thus effectively reducing the damage to the vehicle body in the event of an accidental collision.

[0048] In summary, by designing the semi-ring locking plate 2 to allow for a small range of lateral movement, it can provide a certain degree of buffering and avoidance in the event of an accidental collision, effectively protecting the vehicle from damage caused by collision with the automatic locking device. At the same time, it allows the user to react in time, thus preventing the vehicle from being continuously squeezed by the semi-ring locking plate 2.

[0049] It is worth noting that radar can also be installed on the semi-ring locking plate 2. When a vehicle accidentally approaches it, the radar alarm can be triggered in time to remind the user and reduce the possibility of the vehicle accidentally colliding with the automatic locking device.

[0050] The above description is merely a preferred embodiment of the present invention; it encompasses all the protection scope of the present invention. Any equivalent substitutions or modifications made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solutions and improved concepts of the present invention, should be covered within the protection scope of the present invention.

Claims

1. A shared parking demand prediction and parking space allocation system, characterized in that: It includes a central controller and data acquisition modules, demand forecasting modules, parking space allocation modules, identity authentication modules, and user interaction modules that communicate with the central controller; The parking space allocation module includes a static locking unit and a dynamic allocation unit; The static locking unit is used to receive user reservation requests, lock the designated parking space, and automatically unlock it when the user arrives. The static locking unit includes an automatic locking device installed at the center of the parking space ground and a timer module installed on the automatic locking device. The dynamic allocation unit includes a regional linkage matching module, which is used to identify information in different regions associated with a user and match cross-regional shared parking spaces based on the user's behavior trajectory. The data acquisition module is used to collect parking space status data, user behavior data, traffic flow data, and environmental data. The demand forecasting module builds a parking demand forecasting model based on multi-source data to predict parking demand in different areas and at different times. The identity authentication module is used to verify the authenticity of users' identities in different areas, ensuring the safety of people in shared areas; The user interaction module provides functions such as parking space search, reservation, sharing and posting, credit inquiry and navigation guidance; The central controller is used to receive real-time data from the data acquisition module, call the prediction results from the demand forecasting module, issue control commands to the parking space allocation module, and coordinate data interaction and task scheduling between the modules.

2. The shared parking demand prediction and parking space allocation system according to claim 1, characterized in that: The demand forecasting module includes an LSTM neural network forecasting model. The input data of the LSTM neural network forecasting model includes historical parking data, meteorological data, holiday information, and regional event data. The output data of the LSTM neural network forecasting model is the probability distribution of parking space demand in future time periods.

3. The shared parking demand prediction and parking space allocation system according to claim 2, characterized in that: The different areas include, but are not limited to, two of the following: residential areas, work areas, schools, and hospitals; The regional linkage matching module includes at least: Commuting scenario matching unit: Identifies user's workplace and residence information, and matches shared parking spaces in residential areas during the day with shared parking spaces in office areas at night; School pick-up and drop-off scenario matching unit: Identifies the relationship between student information and parents, and matches parking spaces in designated areas around the school during dismissal time; Medical Treatment Scenario Matching Unit: Connects with the hospital registration system to match nearby parking resources during the consultation period.

4. The shared parking demand prediction and parking space allocation system according to claim 3, characterized in that: It also includes a credit management module, which records users' performance and establishes a credit score system. Credit scores are positively correlated with reservation privileges, parking space lock-in duration, and fee discounts.

5. The shared parking demand prediction and parking space allocation system according to claim 4, characterized in that: It also includes a flexible reservation module, where parking space publishers can set a mandatory reservation period when publishing shared parking spaces. When the publisher returns early, the system automatically searches for nearby available parking spaces and provides replacement guidance.

6. The shared parking demand prediction and parking space allocation system according to claim 5, characterized in that: The parking space allocation method includes the following steps: S1. Collect multi-source data, including parking space status, user behavior, traffic flow and environmental data; S2. Predict parking demand in different areas at different times based on the LSTM model; S3. Receive user reservation requests and allocate parking spaces based on demand forecasts and user identity information; S4. Identify user-associated area information and match cross-regional shared parking space resources; S5: Lock the assigned parking space and unlock it automatically when the user arrives; S6. Record user performance and update credit scores.

7. A shared parking demand prediction and parking space allocation system according to claim 6, characterized in that: The specific steps for sharing parking spaces across regions in step S4 are as follows: S41. User profile construction: After each user registers and completes multi-scenario authentication, the system constructs a set of associated area tags, which include residential area identifiers, work area identifiers, school identifiers, and typical time periods for users to use parking spaces in each area; S42. Shared Parking Space Posting: Users with fixed parking spaces can post parking space sharing information through the user interaction module. When posting, they can simultaneously specify information such as the sharing time period, the scope of sharing targets, the charging standard, and the mandatory retention period. S43. Parking space reservation and locking: Based on the user's destination, the user interaction module displays the destination and the occupancy status of parking spaces in and around it, and recommends some open parking spaces that meet the user's needs. The user can select one of the open parking spaces to reserve and lock it. S44. Dynamic adjustment of parking space status: The reservation and locking results of parking spaces are updated in real time. If the user cancels or fails to arrive within the time limit, the central controller immediately controls the automatic locking device on the corresponding parking space to unlock and open the corresponding parking space.

8. A shared parking demand prediction and parking space allocation system according to claim 7, characterized in that: The specific operation of step S6 includes the following steps: S61. Behavior monitoring: The central controller continuously monitors the entire parking process of users, including whether they arrive within the locked time, the match between the actual parking duration and the reserved time period, whether they leave on time, and whether they cancel the reservation. S62. Indicator Calculation: Dynamic indicator rules are adopted, and the indicator changes are triggered based on the behavior monitoring results. S63. Points Application: Points are synchronized to the user's account and affect the user's subsequent parking space reservation and locking permissions in real time.

9. A shared parking demand prediction and parking space allocation system according to claim 1, characterized in that: The automatic locking device includes an adaptive base, a transverse support column (3) that moves through the adaptive base, and a semi-ring locking piece (2) connected to the outer end of the transverse support column (3) via an electric rotating shaft. The adaptive base includes a mounting base plate (11), a limiting edge ring (12) fixedly connected to the upper edge of the mounting base plate (11), and a buffer layer (13) fixedly connected to the upper end of the limiting edge ring (12). A sliding space is formed between the buffer layer (13) and the mounting base plate (11). The transverse support column (3) includes a sliding piece (32) located in the sliding space, a central shaft fixedly connected to the middle of the upper end of the sliding piece (32), and an upper fixed plate (31) fixedly connected to the outer end of the central shaft. The connection between the semi-ring locking piece (2) and the transverse support column (3) is located on the upper fixed plate (31), and the upper fixed plate (31) and the sliding piece (32) are in contact with the upper and lower surfaces of the buffer layer (13), respectively.

10. A shared parking demand prediction and parking space allocation system according to claim 9, characterized in that: The buffer layer (13) includes a hard rubber layer (131), a plurality of elastic rubber teeth (132) uniformly fixedly connected to the inner wall of the hard rubber layer (131), and a plurality of arc-shaped grooves (133) respectively carved into the inner wall of the hard rubber layer (131). Two adjacent elastic rubber teeth (132) do not contact each other and form a buffer gap between them. The middle part of the plurality of arc-shaped grooves (133) corresponds to the plurality of buffer gaps. The ends of the plurality of elastic rubber teeth (132) away from the hard rubber layer (131) form an annulus, and the central axis moves through the annulus. The diameter of the sliding piece (32) is larger than the inner diameter of the hard rubber layer (131).

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