A parking lot intelligent management method

Abstract

The application discloses a kind of intelligent management methods of parking lot, through parking space reservation application, first, target parking difficulty evaluation is carried out to parking area idle parking space, subsequently, all target parking difficulty evaluation value is sorted in descending order after difficulty screening, select the first three optimal parking spaces after sorting as idle pre-target parking space, then, idle pre-target parking space is calculated with the same parking space multi-path difficulty, finally, select appropriate value as parking space path and drive to target parking space.Not only can realize the efficient use and intelligent distribution of parking space, but also can effectively reduce the parking difficulty and time cost of driver.At the same time, the system can also monitor and safely guard the parked vehicles in real time, ensure the safety of vehicles.This intelligent parking lot management method not only improves the overall management efficiency and intelligent level of parking lot, but also brings more convenient and efficient parking experience for drivers.

Description

Technical Field

[0001] This invention relates to the field of intelligent parking management technology, and in particular to an intelligent parking management method. Background Technology

[0002] In the current urbanization process, parking lots, as a crucial component of urban transportation, directly impact drivers' parking experience and the smoothness of urban traffic flow through their management efficiency and level of intelligence. However, traditional parking lots often face numerous challenges, such as uneven utilization of parking spaces, difficulty in finding parking, long search times, and difficulties in ensuring vehicle safety. These problems not only increase parking inconvenience for drivers but also exacerbate urban traffic congestion.

[0003] Traditional parking lots typically rely solely on simple parking space displays to guide drivers, lacking intelligent parking allocation and guidance systems. Drivers often spend a significant amount of time searching for available spaces, especially during peak hours when parking is scarce. This inefficient search not only wastes time but can also lead to traffic congestion and safety issues such as vehicle scratches. Furthermore, uneven parking space utilization is a major problem; some areas are heavily stocked while others have ample space, reducing the overall efficiency of the parking lot.

[0004] More importantly, traditional parking lots have significant shortcomings in vehicle security. Most parking lots rely solely on reviewing surveillance videos after an incident to trace vehicle damage or theft, failing to provide real-time vehicle security. This passive management approach cannot meet drivers' urgent needs for vehicle safety. Therefore, this application proposes an intelligent parking lot management method. Summary of the Invention

[0005] This application provides an intelligent parking lot management method that achieves intelligent management of parking lots through functions such as real-time data collection, parking difficulty assessment, parking space self-recommendation, and route planning. This improves parking efficiency, balances parking space utilization, and strengthens vehicle security monitoring, thereby effectively solving the problems existing in the background technology.

[0006] This application provides a parking lot intelligent management system, including:

[0007] S101 connects the parking lot with the intelligent parking management system. When a driver needs to park, they can register and log in to the intelligent parking management system through a 5G user terminal. When parking spaces are scarce, they can send a parking request to reserve a parking space.

[0008] S102, assess the difficulty of parking in the target parking space for the vacant parking spaces in the parking area;

[0009] S103, after filtering all the difficulty assessment values ​​of the target parking spaces, sort them in descending order, and select the top three best parking spaces after sorting as the available pre-target parking spaces;

[0010] S104, calculate the difficulty of multiple paths within the same parking space for the vacant pre-target parking space; S201, select the obstacle-free section of the road that must be passed through the entrance between the parking lot entrance and the parking area as the evaluation area, and set an entry point at the end of this area; S202, when the driving distance between the vacant parking space and the parking lot entrance exceeds a first distance, the entry point is activated for detection; S203, collect driver driving data to calculate the driving evaluation index; when the driver drives into the parking lot from the entrance, the intelligent parking management system starts timing, and when the vehicle passes the entry point, the system records the time at that moment as part of the driving time;

[0011] A driving assessment index is calculated based on the vehicle's speed from the entrance to the entry point, travel time, and turning speed. The driver's driving ability is then evaluated based on this index. The formula for calculating the driving assessment index is as follows: , where, definition Vehicle speed, i.e., the speed at which a vehicle travels in a straight line before entering a curve. Turning speed, which is the average speed of a vehicle in a curve; Time taken, that is, the time it takes for a vehicle to go from entering a curve to completely exiting it; Turning efficiency is the average turning speed that a vehicle can maintain within a given time. It is a speed stability factor used to assess the smoothness of a driver's speed change before and after entering a curve;

[0012] S204, Preset driving assessment index threshold range to assess driver's driving ability; S205, When performing route planning, consider the route difficulty. It is directly proportional to the driver's driving ability;

[0013] S105, Choose an appropriate path difficulty The value serves as the route to the target parking space;

[0014] S106, the driver registers and logs into the intelligent parking management system through a 5G user terminal and sends a parking request when parking spaces are scarce; after receiving the request, the intelligent parking management system pushes the corresponding parking space information and parking space route to the driver based on the optimal parking space and route selected in S105.

[0015] S107: Drivers park their vehicles in the selected target parking spaces according to the guided route, and the parked vehicles are monitored and secured in real time.

[0016] Preferably, S102, parking difficulty assessment, includes:

[0017] Distance from the parking lot entrance to the target parking space, length of the entrance path, parking space availability, and obstacles encountered along the way;

[0018] The formula for calculating parking difficulty is as follows:

[0019]

[0020] in, and These are the length and width of the parking space, respectively.

[0021] and It is a weighting coefficient for the impact of parking space size, reflecting the influence of parking space size on parking difficulty;

[0022] It is a weighting coefficient for the straight-line distance from the parking space to the parking lot entrance. It is the straight-line distance from the parking entrance to the target available parking space, measured in meters. The farther the distance, the more difficult it is to park.

[0023] It is the impact coefficient of temporary train conditions. This is a vehicle availability coefficient on both sides of an empty parking space. It is set based on whether there are cars on either side of the empty parking space or whether it is against a wall. If there are cars on both sides... =3. There is a car on the side. =2. Against a wall or pillar =1. Both sides are open. =0;

[0024] This is the obstacle impact coefficient, which takes into account whether there are obstacles such as pillars, walls, or other vehicles passing by during the vehicle's journey, and the degree to which these obstacles affect the parking operation. When there are no obstacles =0, when passing 5 or fewer obstacles. =0.5, passing through more than 5 obstacles. =1;

[0025] Preferably, the step of calculating the difficulty of multiple paths within the same parking space for the vacant pre-target parking space includes:

[0026] Rank all possible paths to the target parking space and define the sum of the angles of all turns along the path to the target parking space. ;

[0027] when The sum is greater than If the angle threshold is 700°, it is difficult to determine the path, so the path should be discarded.

[0028] If more than 5 routes are difficult to determine, then the parking space should be abandoned.

[0029] when The sum is less than Angle threshold, calculation path difficulty Path difficulty The calculation formula is as follows:

[0030] ,in It is the parking difficulty assessment value.

[0031] Preferably, setting an entry point includes:

[0032] The road segment starts at the parking lot entrance and ends at the entry point. A specific entry point is set at the end of this road segment, which can be identified by electronic sensors to detect when a vehicle reaches the entry point.

[0033] Preferably, the preset driving assessment index threshold range for assessing a driver's driving ability includes:

[0034] S301, the average driving ability of a parking space is derived based on the historical parking ability of drivers in that parking space;

[0035] S302, calculate the average parking difficulty value for all parking spaces for each parking space;

[0036] S303 is a difficulty balance index that calculates the average driving ability and average parking difficulty of a parking space.

[0037] S304 divides parking spaces into zones of varying difficulty based on a difficulty balance index.

[0038] Preferably, the difficulty balance index includes:

[0039]

[0040] The recommended balance coefficient in the formula is 0.6, but it can be adjusted in actual application.

[0041] Preferably, dividing parking spaces into zones of varying difficulty based on a difficulty balance index includes:

[0042] S401, based on the physical distance characteristics of each parking space, the parking lot is divided into comprehensive zones;

[0043] S402, calculate the overall difficulty of the comprehensive partition;

[0044] S403, dynamically calculates the driver's driving skill level;

[0045] S404 assigns a target parking space to the driver.

[0046] Preferably, the calculation of the overall difficulty of the comprehensive partition includes:

[0047] .

[0048] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0049] 1. This application comprehensively assesses parking difficulty by considering multiple factors, such as parking space size, distance from the parking space to the parking lot entrance, nearby vehicles, and obstacles encountered along the way. This multi-dimensional assessment method can more accurately reflect the difficulty level in the actual parking process, providing drivers with more reliable parking selection suggestions. Secondly, this technical solution quantifies various influencing factors by setting clear assessment formulas and coefficients, making the assessment of parking difficulty more objective and scientific. This not only improves the accuracy of the assessment but also enhances the comparability of the assessment results, facilitating drivers to compare and select between different parking spaces.

[0050] 2. This application ranks and calculates the difficulty of all possible routes to the target parking space, providing drivers with multiple parking options. This multi-route recommendation method increases drivers' choices, allowing them to select the most suitable parking route based on actual conditions and personal preferences. Simultaneously, by setting angle thresholds to filter routes, overly complex or difficult routes are avoided from being recommended to drivers, thereby improving parking efficiency and safety. Furthermore, the route with the lowest difficulty is selected as the target parking space selection route and pushed to the driver in real time via 5G technology, enabling drivers to quickly obtain optimal parking route guidance information, further enhancing the convenience and intelligence of parking.

[0051] 3. This application collects real-time driving data from drivers as they enter the parking lot, including driving speed, turning speed, and driving time, and then calculates a Driving Evaluation Index (DEI). This index comprehensively reflects the driver's turning efficiency and speed stability when driving on curves, providing a scientific basis for subsequent parking space allocation. Based on the DEI value, the system can automatically classify drivers into different driving ability levels and formulate differentiated parking space allocation strategies for different levels. This personalized parking space allocation method not only improves the convenience of parking but also significantly enhances the driver's parking experience.

[0052] 4. By introducing a difficulty balance index, the scientific quantification and classification of parking space difficulty is achieved. First, by collecting driving evaluation indices from each driver at historical parking spaces, the average driving ability for that space is calculated, providing a data foundation for assessing parking space difficulty. Then, combining the average parking difficulty value of the space with the difficulty balance index formula, the relationship between driving ability and parking difficulty is comprehensively considered, making the classification of parking space difficulty more objective and accurate. This method not only improves parking space utilization but also optimizes the parking experience, providing drivers with more suitable parking options.

[0053] 5. By comprehensively calculating the parking difficulty of different areas within the parking lot and dynamically assessing the driving skills of vehicles, intelligent and personalized parking allocation is achieved. It not only divides the parking lot into comprehensive zones based on the physical distance characteristics and calculates the parking difficulty of each zone, but also assesses the driver's driving skills in real time when a vehicle enters the parking lot. This allows for precise matching of driver ability with parking space difficulty, improving parking efficiency and safety while optimizing the driver's parking experience. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of a parking lot intelligent management process according to an embodiment of the present invention. Detailed Implementation

[0055] To facilitate understanding of the present invention, a more complete description of this application will be given below with reference to the accompanying drawings, which illustrate preferred embodiments of the invention. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to enable a more thorough and complete understanding of the disclosure of the present invention.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to limit the invention; the term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0057] Example 1: As Figure 1 As shown, a parking lot intelligent management method includes the following steps:

[0058] S101 connects the parking lot with the intelligent parking management system. When a driver needs to park, they can register and log in to the intelligent parking management system through a 5G user terminal. When parking spaces are scarce, they can send a parking request to reserve a parking space.

[0059] Specifically, sensors, cameras, and other devices are used to synchronously update the intelligent parking management system with information on the layout of the parking lot, the number of parking spaces, and the real-time parking situation.

[0060] S102, assess the difficulty of parking in the target parking space for the vacant parking spaces in the parking area.

[0061] The parking difficulty assessment coefficient includes:

[0062] The distance from the parking lot entrance to the target parking space, the length of the entrance path, the parking space's proximity to other vehicles (cars on both sides, against a wall, or a car on one side), and obstacles encountered along the way.

[0063] The formula for calculating parking difficulty is as follows:

[0064]

[0065] in, It is a parking difficulty assessment value, and the assessment value is directly proportional to the parking difficulty. and These are the length and width of the parking space, respectively.

[0066] and It is a weighting coefficient for the impact of parking space size, reflecting the influence of parking space size on parking difficulty;

[0067] It is a weighting coefficient for the straight-line distance from the parking space to the parking lot entrance. It is the straight-line distance from the parking entrance to the target available parking space, measured in meters. The farther the distance, the more difficult it is to park.

[0068] It is the impact coefficient of temporary train conditions. This is a vehicle availability coefficient on both sides of an empty parking space. It is set based on whether there are cars on either side of the empty parking space or whether it is against a wall. If there are cars on both sides... =3. There is a car on the side. =2. Against a wall or pillar =1. Both sides are open. =0;

[0069] This is the obstacle impact coefficient, which considers whether there are obstacles such as pillars, walls, or other vehicles passing by during the vehicle's journey, and the degree to which these obstacles affect the parking operation. The obstacle impact coefficient can be set according to the actual situation; if there are no obstacles... =0, the path passes through 5 or fewer obstacles. =0.5, passing through more than 5 obstacles. The value is 1.

[0070] It should be noted that the influence coefficients in the above formulas are defined according to specific practical situations, and require... .

[0071] Specifically, the length and width of each vacant parking space are measured and the ratio to the standard vehicle size is calculated. The path length from each parking space to the parking lot entrance is calculated. The obstacles around the parking space are assessed and assigned a corresponding obstacle influence coefficient. The above data are then substituted into the formula to calculate the parking difficulty assessment value for each parking space.

[0072] S103, after filtering all the difficulty assessment values ​​of the target parking spaces by difficulty, sort them in descending order, and select the top three best parking spaces after sorting as the available pre-target parking spaces.

[0073] S104, calculate the difficulty of multiple paths within the same parking space for the vacant pre-target parking space.

[0074] This involves ranking all possible paths to the target parking space and defining the sum of the angles of all turns along the path to the target parking space. ,when The sum is greater than If the angle threshold is 700°, the path is difficult to determine and the path is discarded. If more than 5 paths are difficult to determine, the parking space is discarded.

[0075] when The sum is less than Angle threshold, calculation path difficulty Path difficulty The calculation formula is as follows:

[0076]

[0077] ,in It is the parking difficulty assessment value.

[0078] S105, choose the appropriate The value serves as the route to the target parking space.

[0079] S106, the driver registers and logs into the intelligent parking management system through a 5G user terminal and sends a parking request when parking spaces are scarce; after receiving the request, the intelligent parking management system pushes the corresponding parking space information and guidance route to the driver based on the optimal parking space and route selected in S105.

[0080] S107: Drivers park their vehicles in the selected target parking spaces according to the guided route, and the parked vehicles are monitored and secured in real time.

[0081] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0082] 1. This application comprehensively assesses parking difficulty by considering multiple factors, such as parking space size, distance from the parking space to the parking lot entrance, nearby vehicles, and obstacles encountered along the way. This multi-dimensional assessment method can more accurately reflect the difficulty level in the actual parking process, providing drivers with more reliable parking selection suggestions. Secondly, this technical solution quantifies various influencing factors by setting clear assessment formulas and coefficients, making the assessment of parking difficulty more objective and scientific. This not only improves the accuracy of the assessment but also enhances the comparability of the assessment results, facilitating drivers to compare and select between different parking spaces.

[0083] 2. This application ranks and calculates the difficulty of all possible routes to the target parking space, providing drivers with multiple parking options. This multi-route recommendation method increases drivers' choices, allowing them to select the most suitable parking route based on actual conditions and personal preferences. Simultaneously, by setting angle thresholds to filter routes, overly complex or difficult routes are avoided from being recommended to drivers, thereby improving parking efficiency and safety. Furthermore, the route with the lowest difficulty is selected as the target parking space selection route and pushed to the driver in real time via 5G technology, enabling drivers to quickly obtain optimal parking route guidance information, further enhancing the convenience and intelligence of parking.

[0084] Example 2: Example 1, by constructing a comprehensive parking difficulty assessment system and path planning algorithm, comprehensively considers multiple factors related to parking spaces and quantifies the difficulty in real time, providing drivers with scientific parking space selection. Simultaneously, it combines angle thresholds to filter the optimal path, achieving full-process visualization and intelligent guidance for parking, significantly improving parking efficiency and experience. To further improve parking efficiency and optimize the parking experience, Example 1 is further improved by setting an entry point for the parking area and calculating the time from the parking entrance to the entry point to assess the driver's driving ability and recommend target parking spaces.

[0085] Now, based on step S105 of Example 1, a further improvement is made, specifically as follows:

[0086] S201, between the parking lot entrance and the parking area, select an unobstructed section of road that must be passed through the entrance as the evaluation area, and set an entry point at the end of this area.

[0087] The road segment starts at the parking lot entrance and ends at the entry point. A specific entry point is set at the end of this road segment, which can be identified by electronic sensors to detect when a vehicle reaches the entry point.

[0088] S202, when the driving distance between an empty parking space and the parking lot entrance exceeds the first distance, the entry point is activated for detection.

[0089] The first distance is defined as a driving distance of 200 meters. If 40% of the parking spaces within a 200-meter driving distance from the entrance are vacant, then parking spaces within a 200-meter driving distance from the entrance will be recommended first. When the vacancy rate of parking spaces reaches 10%, the entrance point will be activated to detect and recommend vacant parking spaces at a distance of 200 meters.

[0090] S203 collects driver driving data to calculate the driving evaluation index.

[0091] Specifically, when a driver drives into the parking lot from the entrance, the intelligent parking management system starts timing. When the vehicle passes the entry point, the system records the time at that moment as part of the driving time.

[0092] The driving evaluation index is calculated based on the vehicle's speed from the entrance to the entry point, the travel time, and the turning speed. The driving ability of the driver is then assessed based on the driving evaluation index.

[0093] The formula for calculating the driving assessment index is as follows:

[0094]

[0095] Among them, the definition Vehicle speed, which is the straight-line speed of a vehicle before entering a curve; Turning speed, which is the average speed of a vehicle in a curve; The time taken is the time it takes for a vehicle to go from entering a curve to fully exiting it.

[0096] Cornering efficiency represents the average turning speed a vehicle can maintain within a given time. Higher scores are awarded for high-speed cornering and shorter turn times.

[0097] This is the speed stability factor, used to assess the smoothness of a driver's speed changes before and after entering a curve. If the driving speed and the turning speed are similar, it indicates that the driver can smoothly decelerate or accelerate into the curve, resulting in a higher stability score. If the speed change is large, the stability score will decrease.

[0098] Based on driving time and speed using the driving assessment index, the driving ability level of a driver is assessed by setting assessment standard time thresholds and speed ranges.

[0099] S204, a preset driving assessment index threshold range is used to assess the driver's driving ability.

[0100] Specifically, an excellent (strong driving ability) DEI value range is ≥0.8. When the DEI value reaches or exceeds 0.8, it indicates that the driver has demonstrated efficient and stable speed control when driving on curves, with high turning efficiency, smooth speed changes, and strong driving ability.

[0101] Good (strong driving ability) DEI value range 0.6-0.79. Drivers with DEI values ​​in this range perform well when driving on curves, with relatively high turning efficiency and speed stability, and have strong driving ability.

[0102] Generally (medium driving ability) DEI value ranges from 0.4 to 0.59. When the DEI value is in this range, the driver's performance in cornering is average, and there is room for improvement in cornering efficiency and speed stability. The driving ability is at an average level.

[0103] Poor (weak driving ability) DEI value ranges from 0.2 to 0.39. Drivers with DEI values ​​in this range may have problems such as unstable speed control and low turning efficiency when driving on curves, and their driving ability is relatively weak.

[0104] Poor driving ability (DEI value < 0.2) indicates that the driver's speed control is extremely unstable when driving on curves, the turning efficiency is low, and the driving ability is poor.

[0105] S205, When performing route planning, the path difficulty... It is directly proportional to the driver's driving ability.

[0106] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0107] 1. This application collects real-time driving data from drivers when they enter the parking lot, including driving speed, turning speed, and driving time, and then calculates a Driving Evaluation Index (DEI). This index comprehensively reflects the driver's turning efficiency and speed stability when driving on curves, providing a scientific basis for subsequent parking space allocation. Based on the DEI value, the system can automatically classify drivers into different driving ability levels and formulate differentiated parking space allocation strategies for different levels. This personalized parking space allocation method not only improves the convenience of parking but also significantly enhances the driver's parking experience.

[0108] Example 3: Based on the parking difficulty assessment formula in step S102 of Examples 1 and 2, step S104 calculates the difficulty of multiple paths to the same target parking space, and steps S203 to S205 assess the driver's driving ability and formulate rules for allocating available target parking spaces based on the assessment results. This comprehensive assessment and decision-making across multiple steps and dimensions achieves a balance in parking difficulty and provides drivers with optimal parking space recommendations. To further improve driver parking efficiency and experience, the specific steps are further improved after calculating driver driving ability as follows:

[0109] S301, the average driving ability of a parking space is derived based on the historical parking ability of drivers.

[0110] Specifically, it involves collecting driving evaluation indices for each driver in historical parking spaces. Calculate the average driving ability for this parking space. .

[0111] S302, calculate the average parking difficulty value for all parking spaces for each parking space.

[0112] The formula for calculating the average parking difficulty value for all parking spaces is as follows:

[0113]

[0114] S303 is a difficulty balance index that calculates the average driving ability and average parking difficulty of a parking space.

[0115] The formula for calculating the difficulty balance index is as follows:

[0116]

[0117] In this embodiment, the balance coefficient is defined as 0.6, but it can be adjusted in actual applications.

[0118] S304 divides parking spaces into zones of varying difficulty based on a difficulty balance index.

[0119] Among them, the difficulty balance index is inversely proportional to the parking difficulty. The smaller the difficulty balance value, the more difficult the parking is. When the difficulty balance coefficient is ≤0.3, the parking space is defined as relatively difficult. The parking space with the difficulty balance coefficient in the range of (0.3, 0.5) is defined as difficult. The parking space with the difficulty balance coefficient in the range of (0.5, 0.8) is defined as medium. The parking space with the difficulty balance coefficient >0.8 is defined as easy.

[0120] It should be noted that all historical data collected must be within a specified window period. All data collected must be within this window period. Data collected outside the window period must be re-collected and the average difficulty level updated.

[0121] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0122] 1. The technical solution in this application introduces a difficulty balance index to scientifically quantify and classify parking space difficulty. First, by collecting the driving evaluation index of each driver at a historical parking space, the average driving ability of that parking space is calculated, providing a data foundation for assessing parking space difficulty. Then, combining the average parking difficulty value of the parking space with the difficulty balance index formula, the relationship between driving ability and parking difficulty is comprehensively considered, making the classification of parking space difficulty more objective and accurate. This method not only improves parking space utilization but also optimizes the parking experience, providing drivers with more suitable parking options.

[0123] Example 4: Example 3, by dividing the parking lot into zones based on the difficulty of finding parking spaces, significantly reduced the difficulty for drivers and enhanced their parking experience when allocating spaces according to their driving abilities. To further improve driving efficiency and enhance the parking experience, Example 3 is further improved by calculating the overall difficulty of large-area zones and dynamically calculating the driver's skill level to obtain the final target parking space.

[0124] Now, based on step S304 of embodiment three, a further improvement is made, specifically as follows:

[0125] S401, based on the physical distance characteristics of each parking space, comprehensively divides the parking lot into zones.

[0126] The principle of comprehensive area zoning is that 50-100 parking spaces within the same geographical location constitute one comprehensive area.

[0127] S402, calculate the overall difficulty of the comprehensive partition.

[0128] in, .

[0129] S403 dynamically calculates the driver's driving skill level.

[0130] Specifically, the driver's driving skill level is immediately determined when the driver passes the entry point.

[0131] S404 assigns a target parking space to the driver.

[0132] Specifically, after calculating the driver's skill level, the system first locates the nearest first comprehensive parking zone and then queries the difficulty level of parking spaces within that zone. If the difficulty of finding an available parking space exceeds the driver's ability level, the system will query the difficulty of available parking spaces in the second parking zone, which is further away from the first parking zone, and match them with the driver's ability level until a target parking space that matches the driver's ability level is found. Based on the target parking space, a driving route will be planned, prioritizing the route with the fewest turning angles. After the optimal route is planned, the route and the target parking space will be pushed to the driver.

[0133] The technical solutions described in the embodiments of this application have at least the following technical effects or advantages:

[0134] 1. By comprehensively calculating the parking difficulty of different areas within a parking lot and dynamically assessing the driver's skill level, intelligent and personalized parking allocation is achieved. It not only divides parking lots into integrated zones based on their physical distance characteristics and calculates the parking difficulty of each zone, but also assesses the driver's skill level in real time when a vehicle enters the parking lot. This allows for precise matching of driver ability with parking space difficulty, improving parking efficiency and safety while optimizing the driver's parking experience.

[0135] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A parking lot intelligent management method, characterized in that, include: S101 connects the parking lot with the intelligent parking management system. When a driver needs to park, they can register and log in to the intelligent parking management system through a 5G user terminal. When parking spaces are scarce, they can send a parking request to reserve a parking space. S102, assess the parking difficulty of the target parking spaces in the parking area; S103, filter all the difficulty assessment values ​​of the target parking spaces and sort them in descending order, and select the top three best parking spaces after sorting as the available target parking spaces. S104, calculate the difficulty of multiple paths for vacant pre-target parking spaces; including: S201, selecting an unobstructed road section that must be passed through the entrance between the parking lot entrance and the parking area as the evaluation area, and setting an entry point at the end of this area; S202, when the driving distance between the vacant parking space and the parking lot entrance exceeds a first distance, the entry point is activated for detection; S203, collect driver driving data to calculate the driving evaluation index; when the driver drives into the parking lot from the entrance, the intelligent parking management system starts timing, and when the vehicle passes the entry point, the system records the time at that moment as part of the driving time; A driving assessment index is calculated based on the vehicle's speed from the entrance to the entry point, travel time, and turning speed. The driver's driving ability is then evaluated based on this index. The formula for calculating the driving assessment index is as follows: , where, definition Vehicle speed, i.e., the speed at which a vehicle travels in a straight line before entering a curve. Turning speed, which is the average speed of a vehicle in a curve; Time taken, that is, the time it takes for a vehicle to go from entering a curve to completely exiting it; Turning efficiency is the average turning speed that a vehicle can maintain within a given time. It is a speed stability factor used to assess the smoothness of a driver's speed change before and after entering a curve; S204, Preset driving assessment index threshold range to assess driver's driving ability; S205, When performing route planning, consider the route difficulty. It is directly proportional to the driver's driving ability; S105, Choose an appropriate path difficulty The driver travels to the target parking space using the parking space route selected in S105; in S106, the driver registers and logs into the intelligent parking management system via a 5G user terminal and sends a parking request when parking spaces are scarce; after receiving the request, the intelligent parking management system pushes the corresponding parking space information and parking space route to the driver based on the optimal parking space and route selected in S105; in S107, the driver parks the vehicle in the selected target parking space according to the guided route, and the parked vehicle is monitored and secured in real time.

2. The intelligent parking management method as described in claim 1, characterized in that, The parking difficulty assessment includes: The calculation formula for parking difficulty assessment includes the distance from the parking lot entrance to the target parking space, the length of the entrance path, the availability of vehicles near the parking space, and obstacles encountered along the way. ， in, and These are the length and width of the parking space, respectively. and It is a weighting coefficient for the impact of parking space size, reflecting the influence of parking space size on parking difficulty; It is a weighting coefficient for the straight-line distance from the parking space to the parking lot entrance. It is the straight-line distance from the parking entrance to the target available parking space, measured in meters. The farther the distance, the more difficult it is to park. It is the impact coefficient of temporary train conditions. This is a vehicle availability coefficient on both sides of an empty parking space. It is set based on whether there are cars on either side of the empty parking space or whether it is against a wall. If there are cars on both sides... =3. There is a car on the side. =2. Against a wall or pillar =1. Both sides are open. =0; This is the obstacle impact coefficient, which takes into account whether there are pillars, walls, or other obstacles that could cause oncoming vehicles to pass during the vehicle's journey, and the degree to which these obstacles affect the parking operation. When there are no obstacles =0, when passing 5 or fewer obstacles. =0.5, passing through more than 5 obstacles. =1.

3. The intelligent parking management method as described in claim 1, characterized in that, The calculation of the difficulty of multiple paths within the same parking space for the vacant pre-target parking space includes: Rank all possible paths to the target parking space and define the sum of the angles of all turns along the path to the target parking space. ;when The sum is greater than If the angle threshold is 700°, the path is difficult to determine and should be discarded; if more than 5 paths are difficult to determine, the parking space should be discarded; when The sum is less than Angle threshold, calculation path difficulty Path difficulty The calculation formula is as follows: ,in It is the parking difficulty assessment value.

4. The intelligent parking management method as described in claim 1, characterized in that, Setting an entry point includes: The road segment starts at the parking lot entrance and ends at the entry point. A specific entry point is set at the end of this road segment, which can be identified by electronic sensors to detect when a vehicle reaches the entry point.

5. The intelligent parking management method as described in claim 1, characterized in that, The preset driving evaluation index threshold range assesses the driver's driving ability, including: S301, derive the average driving ability of the parking space based on the historical parking driver's ability; S302, calculate the average parking difficulty value of all parking spaces for each parking space; S303, calculate the difficulty balance index of the average driving ability and average parking difficulty of the parking space; S304, divide the parking space into areas of different difficulty based on the difficulty balance index.

6. The intelligent parking management method as described in claim 5, characterized in that, The difficulty balance index includes: , where the balance coefficient is 0.

6.

7. The intelligent parking management method as described in claim 5, characterized in that, The method of dividing parking spaces into zones of varying difficulty based on a difficulty balance index includes: S401, Based on the physical distance characteristics of each parking space, the parking lot is divided into comprehensive zones; S402, The overall difficulty of the comprehensive zones is calculated; S403, The driver's driving skill is dynamically calculated; S404, Target parking spaces are assigned to drivers.

8. The intelligent parking management method as described in claim 7, characterized in that, The overall difficulty of calculating the comprehensive partition includes: .

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