Parking information management method and system, automobile and computer readable medium

Abstract

The invention provides a parking information management method, which comprises the steps of acquiring first position information of a target automobile in a driving process of the target automobile; according to the first position information and a preset parking lot interest point database, whether the target automobile is suspected to be parked in the parking lot is detected, and multiple pieces of parking lot interest point information are recorded in the preset parking lot interest point database; after it is detected that the target automobile is suspected to be parked into the parking lot, responding to power-off parking of the target automobile within a first preset duration, and obtaining second position information of the target automobile; according to the second position information and the position description information of the target parking lot suspected to be parked, detecting whether the target automobile is parked in the target parking lot in a power-off manner; when it is detected that the target automobile is parked in the target parking lot in a power-off mode, a parking entering record is generated, the parking entering record comprises the parking lot name of the target parking lot and parking entering time, and the parking entering time is the time corresponding to the time when it is detected that the target automobile is suspected to park and enter the parking lot.

Description

Technical Field

[0001] This invention relates to the field of intelligent vehicle technology, and in particular to a parking information management method, system, vehicle, and computer-readable medium. Background Technology

[0002] With the continuous growth of car ownership, intelligent parking information management systems have been significantly improved and upgraded. Currently, networked smart parking lots based on automatic license plate recognition are becoming increasingly popular. These parking lots generally use license plate scanning data at the time of entry and exit as the basis for parking fee calculation and management.

[0003] Existing parking information management systems are all deployed by parking lot operators, who are responsible for collecting and managing the relevant parking data. Users cannot directly access or analyze the data. When users wish to view or analyze parking information, they must send a request to the corresponding parking lot operator and obtain the information only with the operator's permission. However, in practice, it has been found that obtaining comprehensive parking information often requires sending requests to numerous parking lot operators, making the process extremely cumbersome and complex. Furthermore, most parking lot operators do not support providing parking information to users.

[0004] Therefore, providing a technical solution that can be applied to the vehicle and can generate parking information automatically at least on the vehicle side has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art, and proposes a parking information management method, system, vehicle and computer-readable medium.

[0006] Firstly, this disclosure provides a parking information management method, including:

[0007] During the driving process of the target vehicle, obtain the target vehicle's initial location information;

[0008] Based on the first location information and the preset parking lot point of interest database, it is detected whether the target vehicle is suspected of parking. The preset parking lot point of interest database contains information on multiple parking lot points of interest, including: parking lot name and parking lot location description information.

[0009] After detecting that the target vehicle is suspected of parking, the system responds by powering down and stopping the target vehicle within a first preset time period, and obtains the second location information of the target vehicle.

[0010] Based on the second location information and the location description information of the target parking lot suspected of being parked, it is detected whether the target vehicle is powered off and parked in the target parking lot;

[0011] When the target vehicle is detected to have lost power and stopped in the target parking lot, a parking entry record is generated. The parking entry record includes: the name of the target parking lot and the parking entry time. The parking entry time is the time corresponding to when the target vehicle is suspected of parking.

[0012] In some embodiments, after the step of generating a parking entry record, the method further includes:

[0013] When the target vehicle is powered on and started, the third location information of the target vehicle is obtained;

[0014] Based on the third location information and the location description information of the target parking lot, detect whether the target vehicle is powered on and started in the target parking lot;

[0015] After detecting that the target vehicle is powered on and started in the target parking lot, the fourth location information of the target vehicle is obtained;

[0016] Based on the fourth location information and the location description information of the target parking lot, detect whether the target vehicle has left the target parking lot;

[0017] When the target vehicle is detected to have left the target parking lot, a parking exit record is generated. The parking exit record includes: the name of the target parking lot and the parking exit time of the target parking lot. The parking exit time is the time corresponding to when the target vehicle is detected to have left the target parking lot.

[0018] In some embodiments, the location description information includes: the area of ​​the parking lot;

[0019] The step of detecting whether the target vehicle is powered on and started within the target parking lot, based on the third location information and the location description information of the target parking lot, includes:

[0020] Based on the third location information and the orientation of the target vehicle when it is powered on and started, the overall third vehicle area of ​​the target vehicle is determined;

[0021] Calculate the third area overlap rate between the third overall vehicle area and the target parking lot area;

[0022] When the third area overlap rate is 1, the target vehicle is detected to be powered on and started in the target parking lot; when the third area overlap rate is not 1, the target vehicle is detected not to be powered on and started in the target parking lot.

[0023] And / or,

[0024] The step of detecting whether the target vehicle has left the target parking lot based on the fourth location information and the location description information of the target parking lot includes:

[0025] Based on the fourth location information and the orientation of the target vehicle when the fourth location information is acquired, the fourth overall vehicle area of ​​the target vehicle is determined;

[0026] Calculate the fourth area overlap rate between the fourth overall vehicle area and the target parking lot area;

[0027] When the fourth area overlap rate is 0, the target car is detected to have left the target parking lot; when the third area overlap rate is not 0, the target car is detected to have not left the target parking lot.

[0028] In some embodiments, after the step of generating a parking exit record, the method further includes:

[0029] A complete parking record is generated based on the parking entry record and the parking exit record. The parking record includes: the name of the target parking lot, the parking entry time, and the parking exit time.

[0030] In some embodiments, the parking entry time includes: the parking entry date and the parking entry time on that day; the parking exit time includes: the parking exit date and the parking exit time on that day.

[0031] The method further includes:

[0032] Obtain all parking records of the target vehicle within a preset statistical period;

[0033] The parking records are subjected to standardized preprocessing, which includes determining the parking entry date and parking time period information based on the parking entry time and parking exit time. The parking time period information includes the parking entry time period and the parking hour duration. The parking records after standardized preprocessing include the parking lot name, parking entry date and parking time period information.

[0034] According to the classification rule of seven different dates from Monday to Sunday, all parking records are divided into 7 parking record groups based on the different days of the week to which the parking entry date recorded in the parking record belongs;

[0035] The combination of parking lot name and parking time information is defined as parking behavior. For each parking record group, the parking behavior is classified according to the different parking behaviors in the parking record group to obtain the classification results of various parking behaviors in the parking record group.

[0036] For each type of parking behavior in each parking record group, based on the classification results of that type of parking behavior, detect whether the corresponding parking behavior belongs to parking habit behavior;

[0037] When the corresponding parking behavior is detected as a habitual parking behavior, corresponding parking habit data is generated. The parking habit data records the week of the corresponding parking behavior, the name of the parking lot, the time of entry, and the duration of parking.

[0038] In some embodiments, after the step of generating a parking entry record, the method further includes:

[0039] The parking name of the target parking lot recorded in the parking entry record, the weekday corresponding to the parking entry date recorded in the parking entry record, and the parking entry time corresponding to the parking entry time recorded in the parking entry record are matched with the parking habit data recorded in the parking habit database.

[0040] If matching parking habit data exists in the parking habit database, the corresponding parking hour duration is obtained from the matching parking habit data to serve as the predicted parking hour duration for the target vehicle's current parking behavior.

[0041] In some embodiments, the location description information includes: the area of ​​the parking lot;

[0042] The steps for detecting whether the target vehicle is suspected of parking based on the first location information and a preset parking lot point of interest database include:

[0043] Parking lots whose distance between the center point of the range and the coordinate point corresponding to the first location information is less than a preset distance threshold are selected from the preset parking lot point of interest database as candidate parking lots;

[0044] Based on the first location information and the orientation of the target vehicle when the first location information was acquired, the first overall vehicle area of ​​the target vehicle is determined;

[0045] Calculate the first area overlap rate of the first overall vehicle area with the range area of ​​each of the candidate parking lots;

[0046] Detect whether the maximum value among all the first area overlap rates is greater than or equal to a preset overlap rate threshold;

[0047] When the maximum value among all the first area overlap rates is greater than or equal to the preset overlap rate threshold, the target vehicle is suspected of parking and entering the parking lot. The candidate parking lot corresponding to the maximum value of the first area overlap rate is the target parking lot suspected of parking and entering the parking lot.

[0048] If the maximum value among all the first area overlap rates is less than the preset overlap rate threshold, then the target vehicle is not suspected of parking.

[0049] And / or,

[0050] Based on the second location information and the location description information of the target parking lot suspected of being parked, the step of detecting whether the target vehicle is powered off and parked in the target parking lot includes:

[0051] Based on the second location information and the orientation of the target vehicle when it was powered off and stopped, the second overall vehicle area of ​​the target vehicle is determined;

[0052] Calculate the second area overlap rate between the second overall vehicle area and the target parking lot area;

[0053] When the third area overlap rate is 1, the target vehicle is detected to be powered off and parked in the target parking lot; when the third area overlap rate is not 1, the target vehicle is detected to be powered off and parked in the target parking lot.

[0054] Secondly, this disclosure also provides a parking information management system that can implement the parking information management method provided in the first aspect. The system includes: an acquisition module, a detection module, and a generation module.

[0055] The acquisition module is used to acquire the first location information of the target vehicle during the driving process.

[0056] The detection module is used to detect whether the target vehicle is suspected of parking and entering the parking lot based on the first location information and the preset parking lot point of interest database. The preset parking lot point of interest database contains information on multiple parking lot points of interest, including: parking lot name and parking lot location description information.

[0057] The acquisition module is also used to acquire the second location information of the target vehicle after the detection module detects that the target vehicle is suspected of parking and entering the parking lot, in response to the target vehicle being powered off and stopped within a first preset time period.

[0058] The detection module is also used to detect whether the target vehicle is powered off and parked in the target parking lot based on the second location information and the location description information of the target parking lot suspected of being parked.

[0059] The generation module is used to generate a parking entry record when the detection module detects that the target car has lost power and is parked in the target parking lot. The parking entry record includes: the name of the target parking lot and the parking entry time, wherein the parking entry time is the time corresponding to when the target car is suspected of parking.

[0060] Thirdly, this disclosure also provides a vehicle, including: a vehicle body and a parking information management system as described in the second aspect.

[0061] Fourthly, this disclosure also provides a computer-readable medium storing a computer program, characterized in that, when executed by a processor, the computer program implements the steps of the method provided in the first aspect.

[0062] This disclosure provides a parking information management method. The method involves acquiring the first location information of a target vehicle while it is in motion; then, based on the first location information and a preset parking lot point-of-interest database, detecting whether the target vehicle is suspected of parking; and upon detection of suspected parking, shutting down the target vehicle within a first preset time period and acquiring its second location information; further, based on the second location information and the location description information of the suspected parking lot, detecting whether the target vehicle is indeed parked in the target parking lot after a power outage; and, upon detection of the target vehicle being parked in the target parking lot after a power outage, generating a parking entry record. This parking entry record includes the parking lot name and the parking entry time, which corresponds to the time when the suspected parking was detected. This technical solution allows for the automatic generation of parking entry records on the vehicle itself, facilitating parking information management on the vehicle's end.

[0063] In addition, some of the technical solutions disclosed herein can also enable the automatic generation of parking exit records and complete parking records on the vehicle side.

[0064] In addition, some of the technical solutions disclosed herein can also analyze the parking habits of cars based on local parking records and predict parking duration in certain scenarios. Attached Figure Description

[0065] Figure 1 A flowchart of a parking information management method provided in this embodiment of the present disclosure;

[0066] Figure 2 This is a flowchart of an optional implementation method of step S2 in this embodiment of the present disclosure;

[0067] Figure 3 This is a schematic diagram illustrating the determination of the overall vehicle area of ​​the target vehicle based on the vehicle's location information and current orientation in an embodiment of this disclosure.

[0068] Figure 4 This is a flowchart of an optional implementation method of step S4 in this embodiment of the present disclosure;

[0069] Figure 5 A flowchart illustrating another parking information management method provided in this embodiment of the disclosure;

[0070] Figure 6 This is a flowchart of an optional implementation method of step S7 in the embodiments of this disclosure;

[0071] Figure 7 This is a flowchart of an optional implementation method of step S9 in the embodiments of this disclosure;

[0072] Figure 8 A flowchart illustrating another parking information management method provided in this disclosure embodiment;

[0073] Figure 9 A flowchart illustrating another parking information management method provided in this embodiment of the present disclosure;

[0074] Figure 10 A structural block diagram of a parking information management system provided in this embodiment of the present disclosure;

[0075] Figure 11 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0076] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0077] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0078] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0079] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0080] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0081] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0082] Figure 1 This is a flowchart illustrating a parking information management method provided in an embodiment of this disclosure. Figure 1 As shown, this parking information management method is applied to the vehicle side, and the parking information management method includes:

[0083] Step S1: During the driving process of the target vehicle, obtain the first location information of the target vehicle.

[0084] In practical applications, cars are generally equipped with vehicle positioning systems, such as Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS). The vehicle positioning system can provide the car's location information in real time (usually latitude and longitude coordinates). Therefore, in step S1, the parking information management system deployed on the car can directly obtain the corresponding location information from the vehicle positioning system.

[0085] Step S2: Based on the first location information and the preset parking lot point of interest database, detect whether the target car is suspected of parking.

[0086] The preset parking lot point of interest (POI) database contains information on multiple parking lot points of interest, including the parking lot name and location description. The location description describes the location of the parking lot.

[0087] In some embodiments, the location description information of the parking lot includes: the area of ​​the parking lot; wherein, the area can be a rectangular area, a circular area, a polygonal area, an irregular area, etc., and this disclosure does not limit it; of course, more specifically, the location description information of the parking lot may also include the locations of each entrance and each exit of the parking lot.

[0088] In this embodiment of the disclosure, by comparing the first location information with the parking interest point information in the preset parking interest point database, it is possible to detect whether the target car is approaching a parking lot and whether it is suspected of parking; a detailed description will follow with specific examples.

[0089] In some embodiments, when a target vehicle is suspected of parking, the parking information management system can generate a corresponding suspected parking entry record, which contains the name of the parking lot where the suspected parking entry did not occur and the suspected parking entry time.

[0090] Optionally, if the target vehicle is not detected as having parked, step S1 can be executed again to perform location monitoring. If the target vehicle is detected as having parked, step S3 is executed as follows.

[0091] Step S3: After detecting that the target car is suspected of parking, the target car is powered off and stopped within a first preset time period, and the second location information of the target car is obtained.

[0092] After detecting that a target vehicle is suspected of entering the parking lot, the parking information management system will initialize the built-in timer and start timing, while monitoring whether the target vehicle has lost power and stopped.

[0093] When the built-in timer reaches the first preset duration (e.g., 5 minutes) and the target car is detected to be parked without power failure, it indicates that the target car did not park in the parking lot; for example, the target car may have temporarily entered the parking lot. It should be noted that if the parking information management system generates a suspected parking entry record at the end of step S2, this suspected parking entry record can be deleted. Afterward, step S1 can be executed again for location monitoring.

[0094] If the built-in timer fails to reach the first preset duration and the target car is detected to have lost power and stopped, it indicates that the target car is very likely to be parked in the parking lot; thereafter, step S4 is executed for further verification.

[0095] Step S4: Based on the second location information and the location description information of the target parking lot suspected of being parked, detect whether the target car is powered off and parked in the target parking lot.

[0096] When step S4 detects that the target vehicle has lost power and is parked in the target parking lot, it indicates that the target vehicle is indeed parked in the target parking lot, and then proceed to step S5. It should be noted that if the parking information management system generates a suspected parking entry record at the end of step S2, the suspected parking entry record can be deleted at this time.

[0097] When step S4 detects that the target vehicle has lost power and is parked outside the target parking lot, it indicates that the target vehicle was not parked in the target parking lot (it may have been parked nearby). It should be noted that if the parking information management system generates a suspected parking entry record at the end of step S2, this suspected parking entry record can be deleted at this time. Afterwards, step S1 can be executed again for location monitoring.

[0098] Step S5: Generate parking entry record.

[0099] The parking entry record includes: the name of the target parking lot and the parking entry time. The parking entry time is the time when the parking information management system detects that the target vehicle is suspected of parking. Generally, the parking entry time includes: the parking entry date and the exact time of entry (usually accurate to the minute or second). As a specific example of parking entry time: July 30, 2025, 19:06:25.

[0100] As can be seen from the above, the technical solution disclosed herein can automatically generate parking entry records on the vehicle side, which facilitates the management of parking information on the vehicle side.

[0101] Figure 2 This is a flowchart of an optional implementation method for step S2 in an embodiment of this disclosure. Figure 2 As shown, in some embodiments, the location description information of the parking lot includes: the area of ​​the parking lot; step S2 includes:

[0102] Step S201: Select parking lots from the preset parking lot point of interest database that are less than a preset distance threshold between the center point of the range area and the coordinate point corresponding to the first location information, and use them as candidate parking lots.

[0103] That is, step S201 is to select some parking lots located near the target car as alternative parking lots.

[0104] Step S202: Based on the first location information and the orientation of the target vehicle when the first location information was acquired, determine the first overall area of ​​the target vehicle.

[0105] The vehicle's orientation can be provided by an onboard attitude monitoring system. This system can monitor the vehicle's attitude information in real time, such as orientation, speed, acceleration, and steering angle.

[0106] Figure 3 This is a schematic diagram illustrating the determination of the overall vehicle area of ​​the target vehicle based on the vehicle's location information and current orientation in an embodiment of this disclosure. For example... Figure 3 As shown, the orthographic projection area of ​​a car on the ground can generally be considered as a rectangular projection area, and the length and width of this rectangular projection area are determined (by the length and width dimensions of the car). The car's orientation is consistent with the length direction of this rectangular area, and the car's position information is generally represented by a two-dimensional coordinate. Generally, the two-dimensional coordinate used to represent the car's position information represents the center of the rectangular projection area. With the center point, length, and width of the rectangular projection area determined, the area covered by the rectangular projection area can be determined, that is, the overall area of ​​the car is fixed.

[0107] Of course, in certain special cases, the two-dimensional coordinates representing the vehicle's position information can also be used as other calibration points of the vehicle's rectangular projection area, such as the upper left corner of the rectangular projection area, the lower left corner of the rectangular projection area, etc. In this case, the area covered by the rectangular projection area can also be determined.

[0108] In other words, given that the car's location and orientation are determined, the specific location of the entire car area can be obtained based on the preset location information of the car within the car's overall area.

[0109] Step S203: Calculate the first area overlap rate of the first overall area of ​​the first car to the range area of ​​each candidate parking lot.

[0110] It should be noted that the area overlap rate of the first region A to the second region B described in this disclosure refers to the ratio of the area S(A∩B) of the overlapping region A∩B of the first region A and the second region B to the area S(A) of the total area of ​​the first region A, S(A). Here, S(A∩B) / S(A) takes the value [0, 1]. When S(A∩B) / S(A) is 0, it indicates that the first region A does not extend into the second region B; when S(A∩B) / S(A) is in the range (0, 1), it indicates that the first region A partially extends into the second region B, and the larger the value of S(A∩B) / S(A), the more the first region A extends into the second region B; when S(A∩B) / S(A) is 1, it indicates that the first region A completely extends into the second region B.

[0111] Step S204: Detect whether the maximum value among all first area overlap rates is greater than or equal to the preset overlap rate threshold.

[0112] In step S204, when the maximum value among all first area overlap rates is detected to be greater than or equal to the preset overlap rate threshold, step S205 is executed; when the maximum value among all first area overlap rates is detected to be less than the preset overlap rate threshold, step S206 is executed.

[0113] Step S205: If a target car is suspected of parking, the candidate parking lot corresponding to the maximum value of the first area overlap rate is the target parking lot suspected of parking.

[0114] Step S206: The target vehicle was detected as not having entered the parking area.

[0115] In practical applications, an overlap rate threshold can be preset according to actual needs. When the overlap rate between the overall area of ​​the target vehicle and the area of ​​the parking lot of a certain parking lot is greater than the preset overlap rate threshold, the target vehicle can be considered to have likely entered the parking lot; otherwise, the target vehicle can be considered not to have likely entered the parking lot. In this disclosure, the preset overlap rate threshold is a value in the range (0,1). For example, 0.1, 0.3, 0.5, 0.7, 0.9, etc.

[0116] Figure 4 This is a flowchart of an optional implementation method for step S4 in an embodiment of this disclosure. Figure 4 As shown, in some embodiments, step S4 includes:

[0117] Step S401: Determine the second overall area of ​​the target vehicle based on the second location information and the orientation of the target vehicle when it is powered off and stopped.

[0118] Step S402: Calculate the second area overlap rate between the second overall vehicle area and the target parking lot area.

[0119] When the second area overlap rate is 1, step S403 is executed; when the second area overlap rate is not 1, step S404 is executed.

[0120] Step S403: Detect that the target car has stopped due to power failure in the target parking lot.

[0121] When step S403 ends, step S5 is executed.

[0122] Step S404: Detect that the target car is not stopped by power off in the target parking lot.

[0123] Optionally, at the end of step S404, step S1 can be executed again to perform position monitoring.

[0124] Figure 5 A flowchart illustrating another parking information management method provided in this embodiment of the disclosure. Figure 5 As shown, the parking information management method not only includes steps S1 to S5 in the previous embodiment, but also includes steps S6 to S11 after step S5.

[0125] Step S6: When the target vehicle is powered on and started, obtain the third location information of the target vehicle.

[0126] Step S7: Based on the third location information and the location description information of the target parking lot, detect whether the target car is powered on and started in the target parking lot.

[0127] In step S7, when the target car is detected to be powered on and started in the target parking lot, it indicates that the target car has a tendency to leave the parking lot, and then step S8 is executed; when the target car is detected to be powered on and started outside the target parking lot, it indicates that the target car has abnormally left the target parking lot.

[0128] Step S8: Obtain the fourth location information of the target vehicle.

[0129] Step S9: Based on the fourth location information and the location description information of the target parking lot, detect whether the target car has left the target parking lot.

[0130] Specifically, if the target vehicle is detected to have left the target parking lot, step S10 is executed; if the target vehicle is detected not to have left the target parking lot, step S8 is executed to continuously monitor the target vehicle's position within the parking lot.

[0131] Step S10: Generate parking exit record.

[0132] The parking exit record includes: the name of the target parking lot and the parking exit time. The parking exit time is the time when the target vehicle is detected leaving the target parking lot. Generally, the parking exit time includes: the parking exit date and the parking exit time on that day (usually accurate to the minute or second). As a specific example of parking exit time, parking exit time: July 31, 2025, 07:23:49.

[0133] Figure 6 This is a flowchart of an optional implementation method for step S7 in an embodiment of this disclosure. Figure 6 As shown, step S7 includes:

[0134] Step S701: Determine the overall third vehicle area of ​​the target vehicle based on the third position information and the orientation of the target vehicle when it is powered on.

[0135] Step S702: Calculate the third area overlap rate between the overall area of ​​the third car and the range area of ​​the target parking lot.

[0136] When the third area overlap rate is 1, step S703 is executed; when the third area overlap rate is not 1, step S704 is executed.

[0137] Step S703: Detect that the target car is powered on and started in the target parking lot.

[0138] Step S704: Detect that the target car is not in the target parking lot and power it on.

[0139] Figure 7 This is a flowchart of an optional implementation method for step S9 in an embodiment of this disclosure. Figure 7 As shown, step S9 includes:

[0140] Step S901: Based on the fourth position information and the orientation of the target car when the fourth position information is acquired, determine the fourth overall area of ​​the target car.

[0141] Step S902: Calculate the fourth area overlap rate between the fourth overall vehicle area and the target parking lot area.

[0142] When the fourth area overlap rate is 0, step S903 is executed; when the third area overlap rate is not 0, step S904 is executed.

[0143] Step S903: Detect the target car leaving the target parking lot.

[0144] Step S904: Detection indicates that the target car has not left the target parking lot.

[0145] As can be seen from the above, the technical solution disclosed herein can automatically generate parking exit records on the vehicle side, which facilitates the management of parking information on the vehicle side.

[0146] In some embodiments, after step S10, step S11 is further included.

[0147] Step S11: Generate a complete parking record based on the parking entry record and parking exit record. The parking record includes: the name of the target parking lot, the parking entry time, and the parking exit time.

[0148] In this embodiment of the disclosure, a parking record of a complete parking behavior of the target vehicle can be obtained based on the above steps S1 to S11, so as to facilitate the management of parking information on the vehicle side.

[0149] Figure 8 This is a flowchart illustrating another parking information management method provided in an embodiment of this disclosure. Figure 8 As shown, in practical applications, as the target vehicle performs multiple parking actions, steps S1 to S11 above are executed multiple times to generate corresponding multiple parking records. Subsequently, these parking records can be used to analyze the target vehicle's parking habits. In some embodiments, the parking information management method further includes:

[0150] Step Sa1: Obtain all parking records of the target vehicle within the preset statistical period.

[0151] The preset statistical period can be designed in advance according to actual needs. For example, the preset statistical period can be a continuous 30 days, 50 days or 100 days.

[0152] Step Sa2: Perform standardized preprocessing on each parking record.

[0153] In this disclosure, considering that the original parking records are accurate to the minute or second of a specific day to ensure data precision, such overly precise data would greatly increase the difficulty of subsequent parking habit behavior classification analysis. Therefore, this disclosure will perform standardized preprocessing on each parking record before conducting parking habit behavior classification analysis.

[0154] Standardized preprocessing includes determining the parking entry date and parking time period based on each parking entry and exit time. The parking time period information includes the parking entry time period and the parking hour duration. The standardized preprocessed parking record includes the parking lot name, parking entry date, and parking time period information. Unlike the original parking records, which use parking entry and exit times to describe parking time, the standardized preprocessed parking record uses the parking entry date, parking entry time period, and parking hour duration to describe parking time.

[0155] Specifically, a day is divided into 24 time periods: 0:00-1:00 (excluding 1:00), 1:00-2:00 (excluding 2:00), 2:00-3:00 (excluding 3:00)... 23:00-24:00 (excluding 24:00); parking time is also counted in whole hours by rounding up.

[0156] As an example, the original parking record is as follows:

[0157] Parking lot name: Parking lot A;

[0158] Parking entry time: 19:06:25 on July 30, 2025;

[0159] Parking exit time: July 31, 2025, 07:23:49;

[0160] Based on the parking entry and exit times, the parking duration is calculated to be 12 hours, 17 minutes, and 14 seconds.

[0161] The parking records after standardized preprocessing are as follows:

[0162] Parking lot name: Parking lot A;

[0163] Parking entry date: July 30, 2025;

[0164] Parking entry time: 7 PM to 8 PM;

[0165] Parking duration: 13 hours

[0166] Among them, based on the parking entry time and parking hour duration, the parking time information can be represented by a two-dimensional vector as: [19:00 to 20:00 time period, 13 hours].

[0167] Step Sa3: According to the classification rules of seven different dates from Monday to Sunday, all parking records are divided into 7 parking record groups based on the different days of the week to which the parking entry date recorded in the parking record belongs.

[0168] In this disclosure, all parking records are categorized according to different weekly cycles. This is because users' parking habits generally repeat on a weekly basis, and multiple parking records belonging to the same week can effectively identify users' parking habits. In this disclosure, parking behaviors with fixed parking locations, periodic patterns, and fixed parking times are defined as parking habit behaviors.

[0169] Step Sa3 yields seven parking record groups: Monday parking record group, Tuesday parking record group, ... Sunday parking record group.

[0170] Step Sa4: Define the combination of parking lot name and parking time period information as a parking behavior. For each parking record group, classify all parking records in the group according to different parking behaviors to obtain the classification results of each type of parking behavior in the parking record group. That is, what types of parking behaviors are included in the parking record group, and which parking records in the group are included in each type of parking behavior.

[0171] Taking the Monday parking record group as an example, this group contains parking records of the target vehicle on each Monday within a preset statistical period. The combination of parking lot name and parking time information is defined as a parking behavior. The parking records in the Monday parking record group are then categorized and statistically analyzed according to different parking behaviors, resulting in a classification of each type of parking behavior within the Monday parking record group. That is, it identifies the types of parking behaviors included in the parking record group, and which parking records are included in each type of parking behavior.

[0172] As an example, based on different combinations of parking lot name and parking time information, there are 6 different types of parking behavior in the Monday parking record group:

[0173] Parking behavior 1: Parking lot name X1, parking time period information Y1, number of parking records belonging to this category Z1;

[0174] Parking behavior 2: Parking lot name X1, parking time period information Y2, number of parking records belonging to this category Z2;

[0175] Parking behavior 3: Parking lot name X2, parking time period information Y3, number of parking records belonging to this category Z3;

[0176] Parking behavior 4: Parking lot name X3, parking time period information Y4, number of parking records belonging to this category Z4;

[0177] Parking behavior 5: Parking lot name X3, parking time period information Y5, number of parking records belonging to this category Z5;

[0178] Parking behavior 6: Parking lot name X4, parking time period information y6, number of parking records belonging to this category Z6.

[0179] The classification results of various parking behaviors in the Monday parking record group can be recorded using corresponding triples (X, Y, Z), where X represents the parking lot name, Y represents the parking time information, and Z represents the frequency of the parking behavior (X, Y); Y is a two-dimensional vector composed of the parking entry time t and the parking hour duration T, Y=[t, T]. Therefore, by statistically analyzing the classification results, six triples corresponding to the six types of parking behaviors in the Monday parking record group can be obtained.

[0180] Similarly, we can obtain the classification results of various parking behaviors in the other 6 parking record groups, such as Tuesday parking record group, Wednesday parking record group, ... Sunday parking record group.

[0181] Step Sa5: For each type of parking behavior in each parking record group, based on the classification results of that type of parking behavior, detect whether the corresponding parking behavior belongs to parking habit behavior.

[0182] In this disclosure, for each type of parking behavior in each parking record group, a periodic pattern analysis is performed on each parking record belonging to that type of parking behavior based on the classification results of that type of parking behavior, and the corresponding parking behavior is judged to be a parking habit behavior based on the periodic pattern analysis results.

[0183] In some embodiments, a preset date periodicity analysis algorithm (e.g., Fast Fourier Transform, Wavelet Transform, Autocorrelation Function, Chi-square Test, etc.) can be used to quantify the periodicity of parking entry dates recorded in all parking records belonging to the target parking behavior category (i.e., quantify whether a set of dates exhibits a periodicity), obtaining the corresponding periodicity index value. Generally, the larger the periodicity index value, the stronger the periodicity of the corresponding parking entry dates. By comparing the periodicity index value with a preset index threshold, if the periodicity index value is greater than or equal to the preset index threshold, it indicates that the periodicity of parking entry dates recorded in all parking records of the target parking behavior category is strong, and the target parking behavior belongs to habitual parking behavior; if the periodicity index value is less than the preset index threshold, it indicates that the periodicity of parking entry dates recorded in all parking records of the target parking behavior category is weak, and the target parking behavior does not belong to habitual parking behavior (i.e., occasional parking behavior).

[0184] In other embodiments, the following steps may also be used to detect whether the target parking behavior of the target vehicle in the target parking record group belongs to parking habit behavior. The parking lot where the target vehicle is parked in the target parking behavior is recorded as the selected parking lot.

[0185] Step Sa501: Calculate the percentage of times the target car parks in the selected parking lot within the preset statistical period, denoted as the first percentage k1:

[0186] k1=a1 / a2

[0187] Where a1 represents the total number of times the target vehicle parks in the selected parking lot within the preset statistical period (this can be obtained by counting the frequency of parking records whose parking lot names correspond to the selected parking lot from all parking records obtained in step Sa1), and a2 represents the total number of times the selected parking lot parks within the preset statistical period (a2 can be obtained by requesting the relevant data from the selected parking lot). k1 reflects the importance of the target vehicle to the selected parking lot, or the degree of closeness between the target vehicle and the selected parking lot.

[0188] Step Sa502: Calculate the percentage of target vehicles engaging in target parking behavior within all dates corresponding to the target parking record group, denoted as the second percentage k2:

[0189] k2=b1 / b2

[0190] Where b1 represents the total number of times the target vehicle performs the target parking behavior within all dates corresponding to the target parking record group (the frequency Z of the target parking behavior in the target parking record group can be obtained from the classification results of various parking behaviors in the parking record group obtained in step Sa4); b2 is the total number of parking behaviors of the target vehicle within all dates corresponding to the target parking record group (i.e., the total number of parking records included in the target parking record group). k2 can reflect the target vehicle's preference for the selected parking lot when parking.

[0191] Step Sa503: Calculate the continuity index k3 of the target vehicle's target parking behavior across all dates corresponding to the target parking record group.

[0192]

[0193] In this disclosure, the probability density function is based on the exponential distribution of the parking record date interval. To conduct a continuous analysis of parking behavior; among which, Indicates the interval (in days) between occurrences of the target parking behavior. This represents the average rate at which target parking behavior occurs per unit of time. The smaller the value, the stronger the continuity and the more stable the habit.

[0194] In the above formula, n represents the total number of parking records belonging to the target parking behavior in the target parking record group. This represents the time interval between the parking entry date in the (i+1)th parking record and the parking entry date in the ith parking record after arranging the parking records belonging to the target parking behavior in the target parking record group according to the order of parking entry date (i+1th parking record minus the parking entry date in the ith parking record).

[0195] at this time, and , The average time interval is used. In this disclosure, the average time interval is directly used as the continuity index k3. The larger the average time interval, the stronger the continuity and the more stable the continuity.

[0196] Step Sa504: The first proportion k1, the second proportion k2, and the continuity index k3 are weighted and summed to obtain the habit factor K.

[0197] K = α*k1 + β*k2 + γ*k3

[0198] Wherein, α, β, and γ are pre-configured weight coefficients, all of which are greater than 0. The K value comprehensively considers the correlation between the target car and the selected parking lot, the target car's tendency to park in the selected parking lot, and the continuity of the target car's parking behavior.

[0199] Step Sa505: Based on the habit factor K and the frequency Z of the target parking behavior in the target parking record group, obtain the habit behavior score Q of the target parking behavior.

[0200] Q = K*Z

[0201] The habitual behavior score Q comprehensively considers the correlation between the target car and the selected parking lot, the target car's tendency to park in the selected parking lot, the continuity of the target car's target parking behavior, and the frequency of the target parking behavior. It can effectively reflect whether the target parking behavior belongs to the parking habitual behavior.

[0202] Specifically, if the habitual behavior score Q of the target parking behavior is greater than or equal to the preset score threshold, the target parking behavior is detected as a habitual parking behavior; otherwise, the target parking behavior is detected as not a habitual parking behavior.

[0203] Step Sa6: When the corresponding parking behavior is detected as a parking habit behavior, the corresponding parking habit data is generated. The parking habit data records the week of the corresponding parking behavior, the name of the parking lot, the time of entry, and the duration of parking.

[0204] Steps Sa5 and Sa6 effectively detect parking habits and generate corresponding parking habit data, ultimately forming a parking habit database for the target vehicle. Based on this database, the parking duration of the target vehicle can be predicted in specific scenarios.

[0205] Figure 9 This is a flowchart illustrating another parking information management method provided in an embodiment of the present disclosure. Figure 9 As shown, after the parking habit database is formed, the parking information management system continuously monitors the target vehicle and executes step S5 again to generate a corresponding parking entry record for the target vehicle's current parking behavior. This may also include the following steps:

[0206] Step Sb1: Match the parking name of the target parking lot, the weekday corresponding to the parking entry date recorded in the parking entry record, and the parking entry time corresponding to the parking entry time recorded in the parking entry record with the parking habit data recorded in the parking habit database.

[0207] If a matching parking habit is found in the parking habit database, it indicates that the target car's current parking behavior is highly likely to be a habitual parking behavior, and step Sb2 is then executed; otherwise, it indicates that the target car's current parking behavior is an accidental parking behavior.

[0208] Step Sb2: Obtain the corresponding parking hour duration from the matched parking habit data to serve as the predicted parking hour duration for the target car's current parking behavior.

[0209] In practical applications, once the parking information management system receives the predicted parking duration of a target vehicle's current parking behavior, it can send this predicted duration to the parking lot operator. Based on the received predicted parking durations from multiple vehicles, the parking lot operator can predict the number of remaining parking spaces within a certain future period, enabling them to formulate appropriate parking management plans. For example, if the parking lot operator predicts a low number of remaining parking spaces in the future, they can implement traffic restrictions at the entrance for a specified period.

[0210] Based on the same inventive concept, this disclosure also provides a parking information management system, which can be used to implement the parking information management method provided in the preceding embodiments. Figure 10 This is a structural block diagram of a parking information management system provided in an embodiment of this disclosure. Figure 10 As shown, the parking information management system includes: an acquisition module, a detection module, and a generation module.

[0211] The acquisition module is used to acquire the first location information of the target vehicle while it is in motion.

[0212] The detection module is used to detect whether a target vehicle is suspected of parking in a parking lot based on the first location information and a preset parking lot point of interest database. The preset parking lot point of interest database contains information on multiple parking lot points of interest, including the parking lot name and the location description of the parking lot.

[0213] The acquisition module is also used to acquire the second location information of the target vehicle after the detection module detects that the target vehicle is suspected of parking and entering the parking lot, in response to the target vehicle being powered off and stopped within a first preset time period.

[0214] The detection module is also used to detect whether the target car is powered off and parked in the target parking lot based on the second location information and the location description information of the target parking lot suspected of being parked.

[0215] The generation module is used to generate a parking entry record when the detection module detects that the target car has lost power and is parked in the target parking lot. The parking entry record includes: the name of the target parking lot and the parking entry time determined based on the power outage time of the target car.

[0216] In some embodiments, the acquisition module can also be used to implement steps S6 and S8 in the preceding embodiments, the detection module can also be used to implement steps S7 and S9 in the preceding embodiments, and the generation module can also be used to implement steps S10 and S11 in the preceding embodiments.

[0217] In some embodiments, the parking information management system further includes a data processing module, which can be used to implement steps Sa1 to Sa6 and steps Sb1 to Sb2 in the preceding embodiments.

[0218] For a detailed description of each of the above functional modules, please refer to the content in the previous embodiments, which will not be repeated here.

[0219] Based on the same inventive concept, this disclosure also provides an automobile, which includes an automobile body and a parking information management system, wherein the parking information management system adopts the parking information management system provided in the previous embodiment.

[0220] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 11This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 11 As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement any of the parking information management methods described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0221] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0222] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0223] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0224] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the parking information management methods described in the above embodiments. The computer-readable storage medium may be volatile or non-volatile.

[0225] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described parking information management method.

[0226] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0227] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0228] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0229] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0230] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0231] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0232] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0233] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0234] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0235] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A parking information management method, characterized in that, include: During the driving process of the target vehicle, obtain the target vehicle's initial location information; Based on the first location information and the preset parking lot point of interest database, it is detected whether the target vehicle is suspected of parking. The preset parking lot point of interest database contains information on multiple parking lot points of interest, including: parking lot name and parking lot location description information. After detecting that the target vehicle is suspected of parking, the system responds by powering down and stopping the target vehicle within a first preset time period, and obtains the second location information of the target vehicle. Based on the second location information and the location description information of the target parking lot suspected of being parked, it is detected whether the target vehicle is powered off and parked in the target parking lot; When the target vehicle is detected to have lost power and stopped in the target parking lot, a parking entry record is generated. The parking entry record includes: the name of the target parking lot and the parking entry time. The parking entry time is the time corresponding to when the target vehicle is suspected of parking.

2. The method according to claim 1, characterized in that, Following the step of generating the parking entry record, the following is also included: When the target vehicle is powered on and started, the third location information of the target vehicle is obtained; Based on the third location information and the location description information of the target parking lot, detect whether the target vehicle is powered on and started in the target parking lot; After detecting that the target vehicle is powered on and started in the target parking lot, the fourth location information of the target vehicle is obtained; Based on the fourth location information and the location description information of the target parking lot, detect whether the target vehicle has left the target parking lot; When the target vehicle is detected to have left the target parking lot, a parking exit record is generated. The parking exit record includes: the name of the target parking lot and the parking exit time of the target parking lot. The parking exit time is the time corresponding to when the target vehicle is detected to have left the target parking lot.

3. The method according to claim 2, characterized in that, The location description information includes: the area of ​​the parking lot; The step of detecting whether the target vehicle is powered on and started within the target parking lot, based on the third location information and the location description information of the target parking lot, includes: Based on the third location information and the orientation of the target vehicle when it is powered on and started, the overall third vehicle area of ​​the target vehicle is determined; Calculate the third area overlap rate between the third overall vehicle area and the target parking lot area; When the third area overlap rate is 1, the target vehicle is detected to be powered on and started in the target parking lot; when the third area overlap rate is not 1, the target vehicle is detected not to be powered on and started in the target parking lot. And / or, The step of detecting whether the target vehicle has left the target parking lot based on the fourth location information and the location description information of the target parking lot includes: Based on the fourth location information and the orientation of the target vehicle when the fourth location information is acquired, the fourth overall vehicle area of ​​the target vehicle is determined; Calculate the fourth area overlap rate between the fourth overall vehicle area and the target parking lot area; When the fourth area overlap rate is 0, the target car is detected to have left the target parking lot; when the third area overlap rate is not 0, the target car is detected to have not left the target parking lot.

4. The method according to claim 2, characterized in that, After the step of generating the parking exit record, the following steps are also included: A complete parking record is generated based on the parking entry record and the parking exit record. The parking record includes: the name of the target parking lot, the parking entry time, and the parking exit time.

5. The method according to claim 4, characterized in that, The parking entry time includes: the parking entry date and the parking entry time on that day; the parking exit time includes: the parking exit date and the parking exit time on that day. The method further includes: Obtain all parking records of the target vehicle within a preset statistical period; The parking records are subjected to standardized preprocessing, which includes determining the parking entry date and parking time period information based on the parking entry time and parking exit time. The parking time period information includes the parking entry time period and the parking hour duration. The parking records after standardized preprocessing include the parking lot name, parking entry date and parking time period information. According to the classification rule of seven different dates from Monday to Sunday, all parking records are divided into 7 parking record groups based on the different days of the week to which the parking entry date recorded in the parking record belongs; The combination of parking lot name and parking time information is defined as parking behavior. For each parking record group, the parking behavior is classified according to the different parking behaviors in the parking record group to obtain the classification results of various parking behaviors in the parking record group. For each type of parking behavior in each parking record group, based on the classification results of that type of parking behavior, detect whether the corresponding parking behavior belongs to parking habit behavior; When the corresponding parking behavior is detected as a habitual parking behavior, corresponding parking habit data is generated. The parking habit data records the week of the corresponding parking behavior, the name of the parking lot, the time of entry, and the duration of parking.

6. The method according to claim 5, characterized in that, After the step of generating the parking entry record, the following steps are also included: The parking name of the target parking lot recorded in the parking entry record, the weekday corresponding to the parking entry date recorded in the parking entry record, and the parking entry time corresponding to the parking entry time recorded in the parking entry record are matched with the parking habit data recorded in the parking habit database. If matching parking habit data exists in the parking habit database, the corresponding parking hour duration is obtained from the matching parking habit data to serve as the predicted parking hour duration for the target vehicle's current parking behavior.

7. The method according to any one of claims 1 to 6, characterized in that, The location description information includes: the area of ​​the parking lot; The steps for detecting whether the target vehicle is suspected of parking based on the first location information and a preset parking lot point of interest database include: Parking lots whose distance between the center point of the range and the coordinate point corresponding to the first location information is less than a preset distance threshold are selected from the preset parking lot point of interest database as candidate parking lots; Based on the first location information and the orientation of the target vehicle when the first location information was acquired, the first overall vehicle area of ​​the target vehicle is determined; Calculate the first area overlap rate of the first overall vehicle area with the range area of ​​each of the candidate parking lots; Detect whether the maximum value among all the first area overlap rates is greater than or equal to a preset overlap rate threshold; When the maximum value among all the first area overlap rates is greater than or equal to the preset overlap rate threshold, the target vehicle is suspected of parking and entering the parking lot. The candidate parking lot corresponding to the maximum value of the first area overlap rate is the target parking lot suspected of parking and entering the parking lot. If the maximum value among all the first area overlap rates is less than the preset overlap rate threshold, then the target vehicle is not suspected of parking. And / or, Based on the second location information and the location description information of the target parking lot suspected of being parked, the step of detecting whether the target vehicle is powered off and parked in the target parking lot includes: Based on the second location information and the orientation of the target vehicle when it was powered off and stopped, the second overall vehicle area of ​​the target vehicle is determined; Calculate the second area overlap rate between the second overall vehicle area and the target parking lot area; When the third area overlap rate is 1, the target vehicle is detected to be powered off and parked in the target parking lot; when the third area overlap rate is not 1, the target vehicle is detected to be powered off and parked in the target parking lot.

8. A parking information management system, characterized in that, It can implement the following modules: acquisition module, detection module, and generation module; The acquisition module is used to acquire the first location information of the target vehicle during the driving process. The detection module is used to detect whether the target vehicle is suspected of parking and entering the parking lot based on the first location information and the preset parking lot point of interest database. The preset parking lot point of interest database contains information on multiple parking lot points of interest, including: parking lot name and parking lot location description information. The acquisition module is also used to acquire the second location information of the target vehicle after the detection module detects that the target vehicle is suspected of parking and entering the parking lot, in response to the target vehicle being powered off and stopped within a first preset time period. The detection module is also used to detect whether the target vehicle is powered off and parked in the target parking lot based on the second location information and the location description information of the target parking lot suspected of being parked. The generation module is used to generate a parking entry record when the detection module detects that the target car has lost power and is parked in the target parking lot. The parking entry record includes: the name of the target parking lot and the parking entry time, wherein the parking entry time is the time corresponding to when the target car is suspected of parking.

9. A car, characterized in that, include: The vehicle body and the parking information management system as described in claim 8.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

Images