A Method and System for E-commerce Operation of Shared Parking Spaces Based on Time-Slice Trading and Intelligent Scheduling

Abstract

This application proposes a method and system for the e-commerce operation of shared parking spaces based on time-slice transactions and intelligent scheduling. The proposed solution operates parking space usage rights through time-slice e-commerce, setting flexible parameters such as core usage periods, adjustable time boundaries, and minimum continuous parking duration for each time slice. By linking actual parking space occupancy with orders, intelligent scheduling based on these flexible parameters is triggered when the system detects that a previous time slice has expired, a user for the next time slice has arrived, and all parking spaces within the flexible time window have been allocated. Within permissible limits, the actual start and end times of the next time slice and related orders are adjusted, ensuring that the next time slice still receives parking service that meets the minimum continuous parking duration, and that each parking space is occupied by only one order at any given time. This alleviates the problem of subsequent vehicles being unable to park due to previous vehicles exceeding their time limit during peak hours when no spare parking spaces are available, thereby improving reservation fulfillment rates and parking space utilization.

Description

Technical Field

[0001] This application relates to the field of parking technology, and in particular to a method and system for the e-commerce operation of shared parking spaces based on time-slice trading and intelligent scheduling. Background Technology

[0002] In busy urban areas or core business districts, due to the high concentration of traffic flow and parking demand, roadside and supporting parking lots are generally near or completely full during morning and evening rush hours and holidays. Traditional "first-come, first-served" or simple per-use charging models lack refined management of parking space usage time and entry and exit sequence, which easily leads to problems such as low parking space turnover efficiency, long periods of parking space occupation by car owners, and long waiting times, making it difficult to meet parking demand during peak hours in a timely manner.

[0003] To alleviate the aforementioned problems, some parking lots have begun to divide the right to use fixed parking spaces by time, splitting the day into several preset time slots (such as 9:00–11:00, 11:00–13:00, etc.), and selling each time slot as a "product" on e-commerce platforms or parking apps. Users can purchase the right to use a specific parking space online in advance for a specific time slot. The system then allocates parking space resources and provides entry and exit reminders based on order information, thereby improving the turnover rate and revenue of parking spaces to some extent.

[0004] However, under the aforementioned time-slot sales model, especially during peak hours in busy areas, parking spaces are often completely filled with time-slot orders, and operators typically do not reserve spare spaces for emergency allocation. When two adjacent time slots for the same parking space are purchased sequentially by different users, if the owner of the previous time slot fails to leave within the agreed end time and cannot be contacted in a short period, the owner of the next time slot who arrives on time will be unable to actually occupy the parking space, resulting in subsequent vehicles being unable to park and service commitments being difficult to fulfill. Summary of the Invention

[0005] Therefore, it is necessary to propose a shared parking space e-commerce operation method and system based on time-slice trading and intelligent scheduling to address the above problems.

[0006] A method for e-commerce operation of shared parking spaces based on time-slice trading and intelligent scheduling, the method comprising the following steps: The right to use physical parking spaces is divided into multiple time slices and listed as a product. When generating a time slice order, flexible time slice parameters are recorded for each time slice. The flexible time slice parameters include at least the core usage period, adjustable time boundaries, and minimum continuous parking duration. Collect the actual occupancy status of each parking space and the identification of the occupied vehicle, and associate the actual occupancy status with the corresponding time slot order; When the allowed end time of the previous time slot order arrives, determine whether the current time has exceeded the allowed end time and whether the corresponding parking space is still occupied by the previous time slot order. Determine whether the user of the next time slot order has arrived at the parking lot. Based on the allocation relationship between the current parking space and the time slot order, determine whether all parking spaces have been allocated to the time slot order within the flexible time window of the next time slot order. When the above conditions are met at the same time, it is determined that there is a time slot handover conflict. In the event of a time-slice handover conflict, a new parking space and time allocation scheme is calculated with the flexible time-slice parameters of the relevant time-slice orders as constraints. Within the adjustable time boundary, the actual parking start time and / or end time of at least the later time-slice order is adjusted, and the actual parking start and end times of one or more other time-slice orders can be adjusted simultaneously, so that the actual parking duration obtained by the later time-slice order within its flexible time window is greater than or equal to the minimum continuous parking duration, and each parking space corresponds to the actual occupancy of only one time-slice order at any given time.

[0007] The shared parking space e-commerce operation method and system based on time-slice transactions and intelligent scheduling provided above operates parking space usage rights in an e-commerce manner based on time slices. It sets flexible parameters such as core usage periods, adjustable time boundaries, and minimum continuous parking duration for each time slice. Combining actual parking space occupancy with order association, when it detects that the previous time slice has expired, the user of the next time slice has arrived, and all parking spaces within the flexible time window have been allocated, it triggers intelligent scheduling based on the flexible parameters. Within the allowable range, it adjusts the actual start and end times of the next time slice and related orders, so that the next time slice still obtains parking services that meet the minimum continuous parking duration and that each parking space is occupied by only one order at any given time. This alleviates the problem of subsequent vehicles being unable to park due to the previous vehicle's expired time when there are no spare parking spaces during peak periods, thereby improving the reservation fulfillment rate and parking space utilization rate. Attached Figure Description

[0008] Figure 1 This is a flowchart of a shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling in Embodiment 1 of this application.

[0009] Figure 2 This is a structural block diagram of a shared parking space e-commerce operation system based on time-slice trading and intelligent scheduling, as described in Embodiment 2 of this application. Explanation of main component symbols

[0010] 100. E-commerce operation system for shared parking spaces based on time-slice trading and intelligent scheduling; 10. Time-slice management module; 20. Occupancy association module; 30. Conflict judgment module; 40. Scheduling execution module. Detailed Implementation

[0011] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0012] Example 1 Please see Figure 1 This embodiment provides a method for the e-commerce operation of shared parking spaces based on time-slice transactions and intelligent scheduling, including the following steps: S10: Divide the right to use a physical parking space into multiple time slices and publish them as products. When generating a time slice order, record flexible time slice parameters for each time slice. The flexible time slice parameters include at least the core usage period, adjustable time boundaries, and minimum continuous parking duration.

[0013] In one embodiment of this application, the right to use each physical parking space within a settlement cycle (e.g., a calendar day) is divided into multiple consecutive or discontinuous time slices, such as 8:00–10:00, 10:00–12:00, 12:00–14:00, etc., and each time slice is published as an independent product on an e-commerce platform for users to purchase.

[0014] It's important to note that in the traditional model, parking space "product units" are typically whole-time (e.g., charged per use or by the hour) or full-day usage rights. The system only knows whether a space is available, lacking fine-grained management of the specific time dimension. During peak hours, a single parking space can often be used by multiple users sequentially. Without dividing usage rights into time slices, it's impossible to express at the system level the state that "the same parking space belongs to user A from 9:00–11:00 and user B from 11:00–13:00," let alone establish "transition points" between consecutive time slices. This solution divides physical parking space usage rights into multiple time slices and publishes them as products. On one hand, it ensures that each time slice corresponds to a specific order, forming resource granularities in the time dimension. On the other hand, it provides clear boundaries (i.e., the boundary moments between adjacent time slices) for subsequent "time slice transition conflicts," allowing the system to perform timeout detection and scheduling at these boundaries.

[0015] In one specific embodiment, a day for parking space P1 is divided into two time slices: 9:00–11:00 and 11:00–13:00. User A purchases the 9:00–11:00 time slice for P1 on an e-commerce platform, while user B purchases the 11:00–13:00 time slice for P1. The system can therefore clearly identify 11:00 as the handover time between A and B. When it detects that P1 is still occupied by A after 11:00, it can determine that a time slice handover risk related to B has occurred.

[0016] Furthermore, in one embodiment of this application, when a user completes an order for a certain time slice on an e-commerce platform, the system not only records the nominal start time and nominal end time of the time slice, but also generates and records a set of flexible time slice parameters for the order, including at least the core usage period, adjustable time boundaries, and minimum continuous parking duration.

[0017] In one specific embodiment, taking the 11:00–13:00 time slot of parking space P1 as an example, user B expects to arrive around 11:00 and park for approximately 2 hours. When generating the order, the system records flexible time slot parameters for this time slot, such as: core usage period 11:15–12:45, adjustable time boundary 11:00–13:10, and minimum continuous parking duration of 90 minutes. Thus, if the preceding vehicle slightly exceeds its time limit, the system can attempt to adjust B's actual parking time to 11:05–12:35 or 11:10–12:40. As long as the core usage period is still covered and the total duration is not less than 90 minutes, the service requirements are considered met.

[0018] Furthermore, when users reserve parking, there is usually a critical time period during which a parking space is "essential," such as a client visit, a meeting, or picking up children. If the system arbitrarily compresses or shifts this critical time period during scheduling, it will severely impact the user experience. This system explicitly records the core usage period separately and treats it as a hard constraint that is "uncompressible and cannot be omitted" during scheduling. This allows for prioritizing the sacrifice of non-critical time periods at both ends (e.g., buffering for early arrivals or reserving time after completion) when employing time shifting or duration compression strategies, thereby releasing time flexibility without affecting users' critical usage needs. For scenarios involving the joint adjustment of multiple orders, the existence of the core usage period allows the system to stagger the "non-core parts" among multiple orders, avoiding situations where conflict handling results in some users being unable to park during their critical time periods.

[0019] In one specific embodiment, user B's nominal time slice is 11:00–13:00, but their actual need is for a parking space to be available between 11:30 and 12:30 to attend a meeting from 11:40 to 12:20. The system records 11:20–12:40 as the core usage period. If the vehicle in front times out, the system can adjust B's actual parking time to 11:10–12:40 or 11:25–12:55, still fully covering the core usage period of 11:20–12:40. This provides some flexibility for scheduling while ensuring that the user is not forced to move their car or have their parking interrupted during the meeting due to scheduling issues.

[0020] Furthermore, adjustable time boundaries are used to limit the range within which the system can shift the actual start and end times of orders forward or backward during scheduling. Specifically, if the preceding vehicle has exceeded its time limit and all parking spaces are already allocated, and the start and end times of subsequent vehicle orders are completely fixed, the system has no room for adjustment. Subsequent vehicles can only wait for the preceding vehicle to leave and then park "at the originally scheduled time," or cancel the service altogether. This solution sets adjustable time boundaries for each time-slice order (e.g., allowing the start time to fluctuate 10 minutes before and after the nominal start time, and the end time to fluctuate 10 minutes before and after the nominal end time). When conflicts occur, the system can fine-tune the actual start and end times of orders within this range. As long as the core usage period and minimum continuous parking duration are still met after adjustment, it can be considered a valid service. When multiple orders simultaneously have adjustable time boundaries, the system can utilize the overlapping boundaries of different orders to slightly advance or postpone individual orders, thereby "squeezing out" a continuous time slot for subsequent vehicle orders. This allows for the resolution of conflicts through overall time rescheduling even when there are no spare parking spaces.

[0021] In one specific embodiment, user B's nominal time slice is 11:00–13:00, and the system sets adjustable time boundaries as follows: earliest start time 10:50, latest end time 13:10. If vehicle A's actual departure time is 11:08, and B has no adjustable time boundaries, the 8 minutes of service from 11:00 to 11:08 would be considered a failure. However, with adjustable time boundaries, the system can automatically adjust B's actual parking time to 11:08–13:08, still satisfying the agreed minimum continuous parking duration and core usage period, avoiding the consequences of simple cancellation or partial refund.

[0022] In one specific embodiment, user B wants to park for 2 hours at noon, and the system sets the minimum continuous parking duration for this time slice to 90 minutes. After joint adjustment of multiple orders, if the system can only find a 60-minute available time slot for B, this solution will be algorithmically determined to not meet the constraints, and the scheduler will continue to try other combinations, or ultimately determine that the service has failed and trigger compensation. Conversely, if the system finds a 100-minute continuous time slot for B from 11:10 to 12:50, which is within B's adjustable time boundary and core usage period, it can be considered that both the scheduling requirements and the user's requirement for the minimum parking duration are met.

[0023] Specifically, the time slice generation method includes the following steps: S11: Divide the nominal start time and nominal end time of each time slice order into a pre-flexible period, a core period, and a post-flexible period; It's important to note that when a user selects a time slot through an e-commerce platform, the system first obtains the user's chosen nominal start and end times, such as 9:00–11:00. The time slot generation method does not treat the entire 9:00–11:00 period as a rigid, unadjustable time slot. Instead, it automatically divides it into a pre-flexible period, a core period, and a post-flexible period. The pre-flexible period is the time immediately preceding the nominal start time, allowing for earlier start times or slight compression. The core period reflects the user's critical parking needs and requires priority. The post-flexible period is the time immediately preceding the nominal end time, allowing for later end times or slight compression.

[0024] Furthermore, if the entire nominal time period is considered a rigid interval, once a vehicle in the previous time slice slightly exceeds its time limit, the system cannot make fine adjustments in the time dimension. It can only simply cancel the order of the following vehicle or declare the service a failure, failing to consider the rights and interests of both orders. This step, by dividing the time slice into a pre-flexible period, a core period, and a post-flexible period, is equivalent to breaking down the user's parking needs into "core needs that must be met" and "negotiable buffer zones at both ends." The core period is used to ensure that users will definitely have parking spaces available during critical periods, and the scheduling algorithm must not cut out the core period. The pre-flexible and post-flexible periods can be shifted or compressed within a certain range, providing adjustment space for resolving time conflicts. Moreover, for the scheduling algorithm, the three-segment structure provides a more refined constraint dimension: when a vehicle exceeds its time limit, the algorithm can prioritize adjustments in the pre-flexible and post-flexible areas while maintaining the integrity of the core period. This maximizes time flexibility without compromising the user's critical needs, alleviating the problem of "the preceding vehicle exceeding its time limit causing the following vehicle to be completely unable to park."

[0025] In one specific embodiment, for example, user B purchases parking space P1 in a nominal time slot of 9:00–11:00. The system automatically divides this into: a pre-flexible time slot (9:00–9:20); a core time slot (9:20–10:40); and a post-flexible time slot (10:40–11:00). If user A's actual departure time in the previous time slot is 9:10, then: The core time slot of 9:20–10:40 is fully preserved; the original 20-minute pre-emptive flexible time slot is reduced to only 10 minutes. The system can adjust B's actual parking time to 9:10–11:00, still ensuring that the core time slot remains unaffected, while utilizing the pre-emptive and post-emptive flexible time slots to absorb the impact of the preceding vehicle's overtime. Through this division, the system has a rule-based foundation for scheduling that prioritizes protecting the core while flexibly handling both ends.

[0026] S12: Record the start and end times of the pre-flexible period, core period, and post-flexible period in the flexible time slice parameters, and record the earliest acceptable start time and the latest acceptable end time, so that the core period is located within the continuous time interval between the earliest acceptable start time and the latest acceptable end time.

[0027] It should be noted that after completing the three-segment division, the system writes the start and end times of the pre-flexible period, core period, and post-flexible period into the flexible time slice parameters and records them further. Among them, the earliest acceptable start time is the upper limit for allowing the entire time slice to shift forward as a whole, and the latest acceptable end time is the upper limit for allowing the entire time slice to be extended backward as a whole. The core period is constrained to fall entirely within the continuous time interval formed by "earliest acceptable start time - latest acceptable end time".

[0028] Furthermore, simply having three segments—"pre-flexible / core / post-flexible"—only provides localized flexibility within the nominal time slice. In actual operation, users often have a certain acceptable range for overall advancement or delay, such as "it's okay to arrive 10 minutes earlier" or "it's okay to leave 15 minutes later." Introducing "earliest acceptable start time" and "latest acceptable end time" is equivalent to adding another layer of "total user-acceptable time window" outside the nominal time slice. This allows the system to adjust not only the relative positions between the three segments during scheduling but also to shift the entire time slice forward or backward, while still remaining within the maximum range acceptable to the user. Limiting the core time period to this continuous interval ensures that no matter how the system shifts or compresses the pre- and post-flexible time periods within this window, the core time period will not be pushed outside of the user's unacceptable time, thus guaranteeing that critical usage requirements are not compromised at the algorithm level. When scheduling multiple orders together, the "earliest acceptable start time - latest acceptable end time" intervals of multiple time-slice orders will form a series of overlapping windows. The scheduling algorithm can utilize these window overlap relationships to squeeze out continuous parking time periods for subsequent orders through overall translation and flexible area compression, without violating the constraints of their respective windows, thus achieving a feasible solution in complex conflict situations.

[0029] In one specific embodiment, assume the system records the following parameters for user B: nominal time slice: 9:00–11:00; pre-flexible time slot: 9:00–9:20; core time slot: 9:20–10:40; post-flexible time slot: 10:40–11:00; earliest acceptable start time: 8:50; latest acceptable end time: 11:20. In a real-world scenario: vehicle A can only leave at 9:25 due to traffic congestion; all parking spaces in the parking lot are full according to orders between 9:25 and 11:05. In this case, without the constraint of "earliest / latest acceptable time," the system can only try to find a solution within the 9:00–11:00 time slot, and may not be able to find a time slot that satisfies B's minimum continuous parking duration, thus resulting in service failure. By using the parameters mentioned above, the system can shift B's actual time backward, for example, to 9:25–11:15. Within 9:25–11:15, the core time period of 9:20–10:40 is still fully covered, and the entire actual parking time is within a continuous window of 8:50–11:20. This both adheres to B's acceptable time range and avoids service failures caused by conflicts.

[0030] Furthermore, the time slice generation method also includes the following steps: S13: Record the flexibility level parameters for each time slice order. The flexibility level parameters limit the maximum compression ratio of the preceding and following flexible time periods, the maximum length of the adjustable time boundary, and the range of values ​​for the minimum continuous parking time.

[0031] It should be noted that when generating time-slice orders, in addition to recording the pre-flexible period, core period, post-flexible period, and the earliest acceptable start time and latest acceptable end time, a flexibility level parameter is also recorded for each time-slice order. The flexibility level parameter characterizes the user's acceptability of time adjustments and is used to limit the following three quantitative ranges: the maximum compression ratio of the pre-flexible period and the post-flexible period, The maximum length and minimum continuous parking duration of the adjustable time boundary can be set within a certain range. The above steps, through the flexibility level parameter, transform the user's subjective desire for more flexibility / unwillingness to be adjusted into numerical constraints that the scheduling algorithm can directly use.

[0032] Specifically, if all time-slice orders have the same flexibility parameters, when a time-slice handover conflict occurs, the system cannot distinguish which type of user is more willing to cooperate with the adjustment. It can only "averagely distribute" the adjustment cost among multiple orders, which may easily lead to unfairness to users who are unwilling to be adjusted, or insufficient scheduling space.

[0033] By introducing flexibility level parameters and assigning different maximum compression ratios, boundary lengths, and minimum continuous parking durations to different levels, the system can distinguish between "high-flexibility orders" and "low-flexibility orders." Orders with higher flexibility levels have a larger proportion of compressible time periods before and after the order, a longer adjustable time boundary, and a lower minimum continuous parking time, which means greater time flexibility and better scheduling. Orders with lower flexibility levels: are subject to stricter restrictions and are almost considered rigid demands.

[0034] Furthermore, for scheduling algorithms, when it is necessary to reschedule time among multiple orders, orders with higher flexibility levels can be compressed and shifted first. This maximizes the release of adjustable time resources without significantly affecting the user experience of users with low flexibility levels, thereby increasing the probability of finding a feasible scheduling solution when there are no spare parking spaces.

[0035] In one specific embodiment, the system is configured with three levels of flexibility: Level 1: Maximum compression ratio 10%, adjustable total time boundary length 20 minutes, minimum continuous parking time limit 100 minutes; Level 2: Maximum compression ratio 20%, adjustable total time boundary length 40 minutes, minimum continuous parking time limit 90 minutes; Level 3: Maximum compression ratio 30%, adjustable total time boundary length 60 minutes, minimum continuous parking time limit 80 minutes.

[0036] When a user selects the "cheaper, slightly adjustable" option when placing an order, a Level 3 time-slice order is generated; when they select the "stop on time, do not want to be adjusted" option, a Level 1 time-slice order is generated. In the event of a time-slice handover conflict, the system can prioritize shifting the time slot of a Level 3 order to make room for effective parking time for subsequent orders.

[0037] S14: When releasing time-slice products, set the sales price according to the flexibility level parameter, so that time-slice orders with larger flexibility level parameter values ​​correspond to lower sales prices, and in subsequent time adjustment of time-slice handover conflicts, prioritize the time-slice orders with larger flexibility level parameter values ​​to participate in the time adjustment.

[0038] It should be noted that when releasing time-slice products, this implementation method sets different sales prices based on the flexibility level parameter, so that time-slice orders with larger flexibility level parameter values ​​correspond to lower sales prices.

[0039] Specifically, if flexibility levels are introduced without price differentiation, users lack the incentive to actively choose higher flexibility levels. This could result in a low proportion of high-flexibility orders in the overall system, leading to limited time slices available for adjustment during scheduling. Linking flexibility levels to sales prices—where higher flexibility levels correspond to lower prices—can encourage users with more flexible time requirements to voluntarily choose higher flexibility levels. This naturally accumulates more "adjustable" time slice orders at the system level, forming a larger scheduling resource pool. Furthermore, this price-flexibility-level binding method effectively pre-collects a batch of orders with "high compressibility and wide time boundaries" for the scheduling algorithm. When time slice handover conflicts occur, adjustments can be made from these high-flexibility orders, mitigating conflicts in scenarios without spare parking spaces.

[0040] In one specific embodiment, for the same parking space P1 during the time slot of 9:00–11:00, three product options can be set: Option A: Flexibility Level 1, price 30 yuan; Option B: Flexibility Level 2, price 24 yuan; Option C: Flexibility Level 3, price 18 yuan.

[0041] Users with less time-sensitive requirements tend to choose the lower-priced, more flexible option C, giving the system more adjustable time resources during that period. Users with strict time requirements, on the other hand, choose option A, which reduces compression and shifting operations during scheduling. Ultimately, a group of "highly flexible, low-priced" orders naturally forms within the system, becoming the priority for scheduling adjustments in the event of conflicts.

[0042] Furthermore, when a time slice handover conflict occurs and the time adjustment phase begins, this implementation method, under the premise of satisfying the flexible time slice parameter constraints, sorts the relevant time slice orders according to the value of the flexibility level parameter, and prioritizes the time slice orders with larger flexibility level parameter values ​​to participate in the time adjustment.

[0043] Specifically, in conflict scenarios where there are no spare parking spaces and the preceding vehicle has exceeded its time limit, it is often necessary to adjust the start and end times of multiple orders simultaneously. Randomly selecting adjustment targets might inadvertently harm users with lower flexibility levels and stronger time-rigidity needs, reducing overall satisfaction. By explicitly prioritizing time-slice orders with higher flexibility levels at the algorithm level, users who received price discounts and agreed to greater time flexibility at the time of order placement are given priority in undertaking time shifting or compression adjustments, aligning with their lower price payment and forming a closed-loop mechanism between "price—flexibility—scheduling priority." This improves scheduling success rates because highly flexible orders offer greater time adjustment flexibility; and it creates a relatively fair mechanism at the user level, where users willing to relinquish some time rigidity pay a lower price for flexible scheduling, while highly rigid users pay a higher price for more stable time guarantees.

[0044] In one specific embodiment, three time-slice orders B1, B2, and B3 exist simultaneously within a certain time period, with their flexibility levels and actual situations as follows: B1: Flexibility level 3, nominal time slice 10:00–12:00; B2: Flexibility level 2, nominal time slice 10:30–12:30; B3: Flexibility level 1, nominal time slice 11:00–13:00.

[0045] When a time slice handover conflict occurs between vehicle B3 and vehicle B3 due to the current vehicle's timeout, the system, when constructing the time adjustment set, prioritizes B1 and B2 according to their flexibility level from high to low. By compressing their preceding and following flexible time periods and appropriately shifting their actual start and end times, the system frees up a continuous time period for B3 to meet the minimum continuous parking duration. B3, with its lower flexibility level, is not the primary target for compression; it is only shifted to a limited extent within its adjustable time boundaries. This approach ensures both the strong time rigidity requirement of B3 and effectively utilizes the flexibility provided by B1 and B2.

[0046] S20: Collect the actual occupancy status of each parking space and the identification of the occupied vehicle, and associate the actual occupancy status with the corresponding time slot order.

[0047] In a preferred embodiment of this application, step S20, “collecting the actual occupancy status of each parking space and the identifier of the occupant vehicle, and associating the actual occupancy status with the corresponding time slot order,” can be understood as the following three levels of work: sensing “whether there is a car in the parking space,” identifying “whose car it is,” and associating “who is actually using it” with “who is planned to use it by the system.” The purpose is to provide reliable basic data for subsequent judgment on whether the preceding vehicle has exceeded its time limit and whether it constitutes a time slot handover conflict.

[0048] In one embodiment of this application, the parking management system is equipped with an occupancy detection device at each parking space, such as a geomagnetic sensor, a parking space lock feedback device, or a video camera covering the parking space area, to collect status information on whether the parking space is currently occupied by a vehicle. The system can poll the occupancy detection results of each parking space at preset time intervals (such as every 5 seconds or every 30 seconds) to obtain the actual occupancy status of each parking space at the current moment.

[0049] Relying solely on order information or user self-reporting (such as clicking "Arrived" or "Left" in the app) is prone to delays and inaccuracies, failing to accurately reflect the true occupancy status of parking spaces. By directly sensing whether a parking space is occupied through hardware detection devices, highly reliable actual occupancy data can be continuously obtained without relying on user feedback. This provides objective evidence for determining whether previous time slots have expired or unauthorized occupancy exists. When determining conflicts during subsequent time slot handovers, if the system needs to confirm whether a parking space is still occupied after the allowed end time, it can directly retrieve the actual occupancy status of the space without depending on user actions.

[0050] In one specific embodiment, for example, a geomagnetic sensor is installed on parking space P1, and the system collects data from the sensor every 10 seconds. When the return values ​​at the three sampling points of 10:59, 11:00, and 11:01 are all "occupied," it can be considered that parking space P1 is actually continuously occupied during the time period of 10:59–11:01. This information will subsequently be combined with the corresponding time-slot orders to determine whether the previous time-slot orders have exceeded the allowed end time and the occupants have not yet left.

[0051] Furthermore, in one embodiment of this application, in order to distinguish "whose car is currently in the parking space", the system also captures license plate images through video cameras near the parking space and uses a license plate recognition algorithm to extract the identifier of the occupied vehicle (e.g., the license plate number). When a vehicle enters or exits, the camera automatically captures an image, thereby obtaining a record of "a certain parking space being occupied by a certain license plate vehicle at a certain time".

[0052] Specifically, merely knowing that "there is a vehicle in the parking space" is not sufficient to determine whether it is occupied by the vehicle corresponding to the current time slice order and whether it belongs to the timeout of the previous time slice order. By identifying the occupied vehicle identifier, the system can compare the occupancy situation of the current parking space with the admission registration information and the license plate information in the time slice order, so as to determine whether the current occupancy matches a specific time slice order. Once it is found that "the parking space is occupied by a certain license plate, but according to the plan, the parking space should not be occupied by the order corresponding to the license plate at the current moment", the system can mark the parking space as abnormal and further analyze whether it constitutes a time slice handover conflict in the subsequent steps.

[0053] In a specific embodiment, for example, the system records that the license plate corresponding to the time slice order O1 is "Yue A·12345" and the order time is 9:00–11:00; the license plate corresponding to the order O2 is "Yue A·67890" and the time is 11:00–13:00. When the camera continuously identifies that the license plate on P1 is "Yue A·12345" during the period from 10:50 to 11:10, it can be determined that P1 is occupied by the vehicle corresponding to O1 during this period, rather than O2 or other vehicles. Combining with the time information, it can be further determined whether O1 still occupies the parking space after 11:00.

[0054] Furthermore, after collecting the actual occupancy status of the parking space and the occupied vehicle identifier, step S20 further includes associating the actual occupancy status with the corresponding time slice order according to the matching of the vehicle identifier and the order information. Specifically, it includes: when the user places an order or the vehicle enters the venue, the system has recorded the license plate number, reserved parking space (or allocated parking space) and reserved time slice corresponding to each time slice order; at each sampling moment, the system searches for the order that matches the license plate number and the time slice in the order information according to the parking space number and the identified license plate number; if a matching relationship is found, the actual occupancy status of "parking space P1 is occupied by license plate X at time t" is associated with the corresponding time slice order (such as O1), forming a record of "order O1 actually occupies P1 at time t". Through this association, the system not only has the planned information of "who bought which time slice" on the time axis, but also has the running information of "who actually occupies which parking space at what time".

[0055] The above solution associates "actual occupancy" with "time slice orders", which is equivalent to maintaining both "planned usage time sequence" and "actual usage time sequence" in the system, facilitating the comparison of whether the two are consistent at any time. When determining whether the previous time slice order still occupies the parking space after the allowed end time, the system only needs to check whether the corresponding time point is still in the occupied state in the actual occupancy record associated with the order, avoiding complex queries across multiple tables and multiple parking spaces. In the subsequent determination of "time slice handover conflict", it is necessary to determine that "a certain parking space is still occupied by the previous time slice order after the allowed end time of the previous time slice order" and that "the user of the next time slice order has arrived and all parking spaces within the time window where the parking space is located have been allocated". The above associated information directly provides key factual support.

[0056] In a specific embodiment, still taking P1 and orders O1, O2 as examples: O1: license plate "Yue A·12345", time slice 9:00–11:00, allowed end time = 11:05; O2: license plate "Yue A·67890", time slice 11:00–13:00. The system samples at 11:06 and obtains: parking space P1: actual occupancy status = occupied by a vehicle, recognized license plate = "Yue A·12345". Since "Yue A·12345" matches the license plate recorded in order O1, the system associates the occupancy record of "P1 is occupied by Yue A·12345 at 11:06" with order O1, which is equivalent to "order O1 still actually occupies P1 at 11:06". Combining with the allowed end time of O1 at 11:05, it can be determined in the subsequent steps that O1 still occupies the parking space beyond the allowed end time, thus providing direct evidence for the trigger of "time slice handover conflict".

[0057] Specifically, the occupancy detection method in step S20 specifically includes the following steps: S21: Collect the occupancy status of each parking space through at least one detection method such as a geomagnetic sensor, a feedback of a parking space lock, or a video camera.

[0058] In an embodiment of the present application, each parking space in the parking lot is equipped with a hardware device for detecting the occupancy status, which may specifically include any one or any combination of the following: Geomagnetic sensor: Installed on the ground of the parking space, used to detect the geomagnetic change caused by the metal mass of the vehicle; Feedback of a parking space lock: A parking space lock with a lifting structure, determining whether there is a vehicle on the parking space through the lifting state or pressure / displacement feedback of the lock body; Video camera: Installed above or in front of the parking space, identifying whether there is a vehicle contour on the parking space through the video image. The system obtains the occupancy status of each parking space at the current moment, such as "idle" or "occupied", from the above devices through polling or active reporting.

[0059] Furthermore, if the system relies solely on users clicking "enter" or "exit" in the app to determine parking space occupancy, it cannot accurately grasp the true status of the parking space if the user forgets to do so, delays doing so, or deliberately does not do so. This makes it impossible to reliably determine whether the previous time slot has been exceeded. By deploying geomagnetic sensors, parking lock feedback, or video cameras at the physical parking spaces, this embodiment directly obtains information on whether a parking space is occupied by a vehicle at the hardware level, forming an objective verification of user behavior.

[0060] Furthermore, the determination of time slice handover conflicts relies on whether the parking space is still occupied after the allowed end time. By periodically collecting occupancy status data, an occupancy time sequence for each parking space can be constructed, such as an "idle / occupied" status frame every 10 seconds. This allows us to trace whether the parking space is actually occupied at any given time, providing a data foundation for subsequent determination of whether the space is still occupied after the allowed end time.

[0061] Furthermore, by using "at least one of the following detection methods: geomagnetic sensor, parking space lock feedback, or video camera", it is possible to select a detection method with higher adaptability in different parking lot environments. Multiple methods can be combined for cross-verification, such as using geomagnetic detection as the main method and video as a supplement to confirm abnormal situations, thereby improving the accuracy and reliability of occupancy detection.

[0062] In a specific implementation scenario: Parking space P1 is equipped with a geomagnetic sensor and a video camera. Every 10 seconds, the system reads a "0 / 1" occupancy flag from the geomagnetic sensor, while the video camera captures images for backup. At 10:59, 11:00, and 11:01: the geomagnetic sensor continuously returns "1" (indicating a vehicle is present); the video footage identifies the outline of a vehicle in the parking space area. Based on this, the system determines that parking space P1 is actually "occupied" between 10:59 and 11:01. This status information will be used for subsequent association with time-slot orders.

[0063] S22: Perform license plate recognition on the video image to obtain the occupied vehicle identifier, compare the occupied vehicle identifier with the entry registration information, determine the time slice order corresponding to the currently occupied vehicle, and associate the occupancy status with the time slice order for storage.

[0064] In one embodiment of this application, in order to distinguish "whose car is in this parking space", the system configures video cameras near each parking space or parking area to continuously or periodically capture images of the parking area. When the system detects that a parking space is "occupied", it extracts the vehicle license plate location from the video image obtained by the camera, executes a license plate recognition algorithm, and obtains the identifier of the occupied vehicle (e.g., license plate number).

[0065] The system then compares the vehicle's identification with the entry registration information recorded at the parking lot entrance or in the reservation system to find the time slot order information that matches the license plate number, thereby determining which time slot order corresponds to the currently occupied vehicle. Finally, the time slot order is associated with the current occupancy status and stored, for example, recorded as "Order O1 occupies parking space P1 at time t".

[0066] Furthermore, S21 alone provides a parking space occupancy status (available / unavailable), which cannot distinguish whether the occupied vehicle corresponds to a previous time slot order, a subsequent time slot order, or an unreserved vehicle. By performing license plate recognition in S22 and comparing it with the entry registration information, the system can determine which specific order the vehicle in the current parking space belongs to, thus providing the necessary information basis for determining whether it belongs to a previous time slot order that has expired.

[0067] Furthermore, in time-slice handover conflict scenarios, the system needs to clearly identify "who has timed out" and "who is waiting." S22 binds the vehicle's identifier to the time-slice order, allowing the system to directly determine: the currently occupied vehicle belongs to the previous time-slice order O1, and O1's allowed end time has expired; the waiting vehicle belongs to the next time-slice order O2. In this way, the system can not only determine that "a handover conflict exists," but also adopt different processing methods for different orders in subsequent scheduling strategies, such as recording a default for O1 and prioritizing service for O2.

[0068] Furthermore, by associating occupancy status with time-slice orders, the system essentially establishes an "order-dimensional" occupancy time series: not only can it see "parking space P1 is occupied at time t," but it can also directly see "order O1 occupies parking space P1 at time t." In subsequent time-slice handover conflict judgment and intelligent scheduling calculations, the system can easily retrieve "the actual occupancy time period of a certain order" by order dimension and compare it with its flexible time-slice parameters (core time period, adjustable time boundary, minimum continuous parking duration), thereby more accurately performing time adjustments and determining responsibility.

[0069] In a specific embodiment, order O1: license plate "Yue A·12345", time slice 9:00–11:00, parking space P1; order O2: license plate "Yue A·67890", time slice 11:00–13:00, parking space P1. At 11:03: In S21, it is detected that P1 is in the "occupied" state; in S22, the license plate "Yue A·12345" is obtained through license plate recognition of the camera image; the system searches in the entry registration and order form and finds that the order corresponding to "Yue A·12345" is O1; the system associates the record of "P1 was occupied by Yue A·12345 at 11:03" with "order O1 actually occupied P1 at 11:03". Combining with the allowed end time of O1 (such as 11:00 or 11:02), the system can directly determine that O1 has exceeded the occupancy time at this moment, and trigger the time slice handover conflict handling and intelligent scheduling according to the arrival status of O2 and the overall allocation situation in the subsequent steps.

[0070] The occupancy detection method further includes the following steps: S23: Periodically update the occupancy status of each parking space and the corresponding time slice order identifier, and generate a parking space occupancy time series.

[0071] It should be noted that based on the foregoing S21 and S22, the system can already obtain the information of "whether a parking space is occupied" and "which vehicle corresponding to a time slice order occupies it" at a certain moment. In step S23, the system performs a centralized update on all parking spaces in the parking lot once every preset time interval (such as every 10 seconds, every 30 seconds, or every 1 minute), including: obtaining the current occupancy status (idle / occupied) of each parking space; if it is in the occupied state, determining the time slice order identifier corresponding to the current occupancy according to the license plate recognition result and order information; writing the current time, parking space number, occupancy status, and the corresponding time slice order identifier into the storage together to form a record of this parking space at the current time point. As time progresses, for each parking space, the records obtained from multiple periodic updates are arranged in chronological order, which forms the occupancy time series of this parking space. Similarly, the system can also construct an "order occupancy time series" according to the time slice order dimension, that is, record whether a certain time slice order occupies a certain parking space at each time point.

[0072] Furthermore, if the system only retains the occupancy status at a certain moment and does not retain the records evolving over time, it is very difficult to judge time-related facts such as "whether a vehicle has exceeded the time limit" and "whether a vehicle has arrived early". Through step S23, the system continuously records the occupancy status of each parking space and the corresponding order on the time axis, so that it can be traced back for any time point to determine "who should use this parking space" and "who is actually using it", providing a fine-grained time basis for conflict determination.

[0073] Furthermore, the essence of time-slice handover conflicts is that at the same point in time, the "planned user" and the "actual user" are inconsistent, and this inconsistency occurs during critical handover periods. With the occupancy time series, the system only needs to check the actual occupancy record of the parking space (or order) at the corresponding time point to obtain the "actual user," and then compare it with the planned time-slice order to facilitate automatic detection.

[0074] Furthermore, occupancy time series data can be used not only for determining the status at a specific moment, but also for statistical analysis of parking space occupancy rates and actual usage duration of orders over a given time period. This provides valuable data support for subsequent functions such as dynamic pricing and flexible parameter optimization.

[0075] In one specific embodiment, for example, for parking space P1, the system is set to update every 10 seconds. The occupancy time sequence might be similar to: 10:50, Occupancy status = Occupied, corresponding order = O1; 10:55, Occupancy status = Occupied, corresponding order = O1; 11:00, Occupancy status = Occupied, corresponding order = O1; 11:05, Occupancy status = Occupied, corresponding order = O1; 11:10, Occupancy status = Idle, corresponding order = None; 11:15, Occupancy status = Occupied, corresponding order = O2; ...

[0076] By combining the allowed end time of order O1, the nominal start time of order O2, and the flexible time boundary, the system can accurately identify that the actual departure time of O1 falls between 11:05 and 11:10, and determine whether it exceeds the allowed end time, thus providing a basis for handover conflict judgment.

[0077] S24: During the update, detect the difference between the parking space occupancy status at a certain time point and the time slice order plan occupancy status, and mark the parking spaces with differences as abnormal parking spaces, which is used to provide input for time slice handover conflict judgment.

[0078] When completing the S23 periodic update, the system not only simply records the "current state," but also synchronously performs a comparison of "planned state vs. actual state" in each update, specifically including: For each parking space, at the current time point, based on the planned allocation results of time-slice orders, it is determined which time-slice order should occupy the parking space or whether it should be in an idle state. Simultaneously, based on the current record of the occupancy time sequence obtained in S23, it is determined whether the parking space is actually occupied and by which order. The planned occupancy status is compared with the actual occupancy status: if the planned occupancy is idle but the actual occupancy is; or the planned occupancy is by order Oa but the actual occupancy is by order Ob or another vehicle; or the planned occupancy is by the next time-slice order but is still by the previous time-slice order; then it is considered that there is a discrepancy between the planned and actual occupancy at the current time point. Parking spaces with detected discrepancies are marked as abnormal parking spaces, and information such as the time of the discrepancy, planned status, and actual status is recorded for subsequent time-slice handover conflict judgment and scheduling.

[0079] Furthermore, in a large parking lot with numerous parking spaces, performing a full comparison of all parking spaces and all orders every time a time slice handover conflict is determined is computationally intensive and inefficient. By comparing the planned and actual status in real-time during updates in S24, parking spaces with discrepancies are marked as abnormal parking spaces. This effectively filters out "potentially problematic" parking spaces in advance. Subsequent determinations only need to assess whether these abnormal parking spaces constitute a time slice handover conflict, significantly reducing the computational scope.

[0080] Furthermore, the difference between "planned vs. actual" not only includes situations where the preceding vehicle exceeds its permitted time limit, but also situations where unreserved vehicles occupy parking spaces, vehicles parked in the wrong space, or system allocation errors occur. By recording the specific form of the difference (e.g., "planned = O2, actual = O1", "planned = idle, actual = O3", etc.), the system can take different follow-up strategies for different situations: for the situation where "the previous time slot order is still occupied after the allowed end time," it is directly related to time slot handover conflict; for the situation where "unreserved vehicles are occupying parking spaces," it can trigger the illegal parking management process. This mechanism helps ensure that the judgment of time slot handover conflict is not interfered with by other anomalies, improving the accuracy of the judgment.

[0081] Furthermore, after processing by S24, the system can obtain a set of abnormal parking spaces and their abnormal times. For each abnormal parking space, the system can quickly determine whether the conditions of "the preceding vehicle has timed out + the following vehicle has arrived + all parking spaces have been allocated" are met by combining the corresponding previous time-slice orders, the following time-slice orders, and the flexible time window situation, thereby deciding whether to activate the intelligent scheduling logic.

[0082] In one specific embodiment, continuing with the example of P1 above: Schedule: To be used by order O1 from 9:00 to 11:00; to be used by order O2 from 11:00 to 13:00; the allowed end time of O1 is 11:05; the system performs a periodic update at 11:06.

[0083] At 11:06: Schedule status: According to the time slice order allocation, at 11:06, it is already within the time slice of O2, so the P1 schedule should be occupied by O2 (or occupied by O2 at the latest after allowing the handover buffer); Actual status: According to the occupancy time sequence, P1 is still occupied by the license plate "Yue A·12345", corresponding to order O1.

[0084] S24 comparison result: Scheduled occupied order = O2; actually occupied order = O1; the two are inconsistent, and the current time has exceeded the allowed end time of O1. Therefore, the system marks P1 as an abnormal parking space in S24 and records "abnormal type = previous time slice order occupied beyond the time limit". This abnormal parking space mark will be focused on in the subsequent time slice handover conflict judgment step, and is used to further combine the arrival status of the user of the subsequent time slice order and the overall parking space allocation situation in the whole field to judge whether to trigger intelligent scheduling.

[0085] S30: When the allowed end time of the previous time slice order arrives, judge whether the current time exceeds this allowed end time and the corresponding parking space is still occupied by the previous time slice order, judge whether the user of the subsequent time slice order has arrived at the parking lot, and based on the allocation relationship between the current parking space and the time slice order, judge whether all the parking spaces within the flexible time window of the subsequent time slice order have been allocated to the time slice orders. When all the above conditions are met simultaneously, it is determined that there is a time slice handover conflict.

[0086] In a preferred embodiment of the present application, step S30 is used to combine, at a unified judgment node, the three conditions of whether the previous time slice is occupied beyond the time limit, whether the user of the subsequent time slice has arrived, and whether all the parking spaces in the whole field within the flexible time window have been allocated. When all three conditions are established simultaneously, it is clearly determined that there is a "time slice handover conflict". This step can be understood as the "main switch" after a series of detections and markings in the previous S23 - S35.

[0087] Specifically, in the previous steps, the system has periodically updated the occupancy status of each parking space and the corresponding time slice order identifier through the occupancy detection method, generated the parking space occupancy time sequence, and identified the parking spaces with inconsistent "schedule status" and "actual status" through the abnormal parking space mark.

[0088] At the judgment time t in step S30 (e.g., when the allowed end time of the previous time-slice order arrives or within a slightly later detection cycle), the system first reads the following for the parking space related to the time-slice handover, such as parking space P1: the allowed end time Te of the previous time-slice order A (e.g., the nominal end time plus the allowed buffer time); the actual occupancy status of parking space P1 at the current time t; and the corresponding time-slice order identifier. If the current time t is greater than Te (t > Te), and P1 is still occupied by the vehicle corresponding to order A at time t, then in S30, it is determined that the condition "the previous time-slice order still occupies the parking space after exceeding the allowed end time" is met. This judgment ensures that the system only considers the previous order as an actual obstacle to the handover when "the system's allowed departure time has indeed exceeded" and "the parking space is still occupied by the previous time-slice order," rather than prematurely identifying a conflict while still within the allowed buffer period.

[0089] Furthermore, as mentioned above, the system has already calculated the distance between the user's current location and the parking lot location corresponding to order B in the next time slice using the user terminal's location data, and determined whether the user has arrived within the parking lot area based on the distance and time conditions.

[0090] At the determination time in step S30, the system reads the arrival marker for order B, for example: If the user terminal's location is less than a preset radius (e.g., 300 meters) from the center point of the parking lot, and the current time is within a preset advance time range (e.g., 15 minutes) before the nominal start time of order B, then the user corresponding to B has already been marked as "arrived within the parking lot area" in the aforementioned steps. In step S30, the system directly determines whether the condition "the user of the next time slot order has arrived within the parking lot area" is met based on this mark. By introducing this condition, the system ensures that the current situation is only considered a serious time slot handover problem when the user of the following vehicle has actually arrived near the parking lot and is indeed ready to use the reserved parking space; for situations where the user is still on the road or far away, complex scheduling will not be triggered prematurely.

[0091] Furthermore, as mentioned above, the system has already divided the flexible time window of order B into time units (determined by the earliest acceptable start time and the latest acceptable end time), and based on the current allocation relationship between parking spaces and time-slice orders, it has statistically analyzed the occupancy status of each parking space in each time unit within the flexible time window.

[0092] When the system detects that all parking spaces in each time unit within the flexible time window of order B have been allocated to a specific time slot order, meaning that every "time unit-parking space" combination is occupied and there are no unallocated empty parking spaces in any time unit, the flexible time window of order B is marked as a "time window in which all parking spaces have been allocated".

[0093] In step S30, the system reads this flag to determine whether the condition "all parking spaces have been allocated to time-slot orders within the flexible time window of the next time-slot order" is true. This condition ensures that the current scenario is indeed a peak period with no spare parking spaces, rather than a situation where there is still space that can be easily adjusted to other empty parking spaces.

[0094] In summary, in step S30, the system performs the following comprehensive judgment on the time-slice handover related parking spaces (e.g., P1): The system checks whether the current time has exceeded the allowed end time of the previous time-slot order A, and whether the parking space is still actually occupied by order A; whether the user corresponding to the next time-slot order B has been determined to have arrived within the parking lot area; and whether all parking spaces in the entire parking lot have been fully allocated to time-slot orders in each time unit within the flexible time window of order B (i.e., the flexible time window is the time window in which all parking spaces have been allocated). When the above three conditions are met simultaneously at time point t, the system determines parking space P1 as a parking space with a "time-slot handover conflict" in S30, that is, identifies it as a "time-slot handover conflict parking space".

[0095] In one specific embodiment, the parking space P1 allocation is as follows: Order A: 9:00–11:00, with an allowed end time Te = 11:05; Order B: 11:00–13:00, with a flexible time window of 10:50–11:20.

[0096] All other parking spaces (such as P2 and P3) were used through other orders between 10:50 and 11:20.

[0097] Operating status: By analyzing the occupancy detection time series and abnormal parking space markers, it can be seen that at 11:06, P1 is still actually occupied by the vehicle corresponding to order A; at this time, 11:06 > Te = 11:05, thus satisfying the condition that "the previous time slice order still occupies the parking space after the allowed end time".

[0098] The user of order B entered the parking lot within 300 meters at 10:55, and 10:55 falls within the 15-minute window before B's nominal start time of 11:00. Therefore, at 11:06, the user has been marked as "arrived within the parking lot area", which satisfies the condition that "the user of the order in the next time slice has arrived within the parking lot area".

[0099] The system detected that within the flexible time window of B (10:50–11:20), all three parking spaces P1, P2, and P3 were already occupied by a time-slice order plan in each 5-minute time unit. This flexible time window was marked as a "time window in which all parking spaces have been allocated." Reading this mark at 11:06 confirmed that the condition "all parking spaces have been allocated to time-slice orders within the flexible time window of the next time-slice order" was met.

[0100] Therefore, at 11:06, step S30 concludes that parking space P1 simultaneously meets three conditions: the preceding vehicle has exceeded its time limit, the following vehicle has arrived, and there are no available parking spaces within the flexible time window. P1 is thus identified as a parking space with a time-slice handover conflict. This determination will serve as the triggering condition and input basis for subsequent intelligent scheduling based on flexible time-slice parameters (i.e., recalculating the parking space and time allocation scheme in step four). This ensures that the system only initiates complex scheduling logic when there are no available parking spaces during typical peak periods and users are indeed affected, thereby more accurately and efficiently resolving the problem of following vehicles being unable to park due to the preceding vehicle not leaving in time.

[0101] Furthermore, the conflict determination method includes the following steps: S31: Obtain the current location data from the terminal of the user with the next time slice order, and calculate the distance between the current location and the parking lot location; S32: When the distance is less than the preset radius and the current time is within the preset advance time range before the nominal start time of the next time slice order, the user of the next time slice order is determined to have arrived within the parking lot range; S33: When it is determined that the previous time slot order still occupies the parking space after the allowed end time, the user of the next time slot order has arrived within the parking lot area, and the parking space marked as abnormal is bound to the previous time slot order, the parking space is determined as a time slot handover conflict parking space.

[0102] In a preferred embodiment of this application, the conflict determination method works in combination through steps S31 to S33 to mark a specific parking space as a time slot handover conflict parking space, under the premise of accurately identifying that "the previous time slot order has expired and the user of the next time slot order has actually arrived and the current parking space is indeed a handover point", thereby providing a clear target for subsequent intelligent scheduling.

[0103] Specifically, in step S31, the current location data is obtained from the terminal of the user who placed the order in the next time slot. For example, the user's real-time coordinates are obtained through GPS, base station positioning, or WiFi positioning on the mobile terminal, and the distance between the current location and the pre-stored location in the parking lot is calculated. In this way, the user's proximity to the parking lot is automatically determined based on the terminal location, without relying on the user manually clicking "Arrived".

[0104] In step S32, if the distance is less than a preset radius and the current time falls within a preset advance time range before the nominal start time of the order in the next time slice, the user is determined to have arrived within the parking lot area. For example, if the preset radius is set to 300 meters around the parking lot and the preset advance time is set to 15 minutes before the nominal start time, when the user terminal enters the 300-meter range between 10:50 and 11:00, it can be determined that the user has "arrived," thus distinguishing between cases where the user is merely passing by or remotely viewing the order, and avoiding prematurely triggering scheduling before the user has actually approached the parking lot.

[0105] In step S33, the system integrates the aforementioned occupancy detection results and arrival judgment results to confirm the conflict: on the one hand, based on the occupancy time sequence and its association with time-slot orders, it has been determined that the previous time-slot order still occupies the corresponding parking space after its allowed end time has expired; on the other hand, through S31 and S32, it has been determined that the user of the next time-slot order has arrived within the parking lot area; simultaneously, the abnormal parking space marker indicates that the currently abnormal parking space is indeed bound to the previous time-slot order. When these three conditions are met simultaneously, the parking space is determined as a time-slot handover conflict parking space, that is, this parking space is clearly identified as the specific conflict point of "the preceding vehicle exceeding its time limit and blocking the following vehicle".

[0106] In one specific embodiment: Assume parking space P1 is allocated to order A from 9:00–11:00 and to order B from 11:00–13:00, with A's allowed end time being 11:05. The system detects occupancy and determines that P1 is still occupied by vehicle A at 11:08. Simultaneously, user B's terminal enters within 300 meters of the parking lot at 10:55, and the nominal start time of the order is 11:00, satisfying the advance time and distance conditions, and is therefore marked as "arrived." P1 is marked as an abnormal parking space because "it was planned to be occupied by B but is actually still occupied by A," and the abnormal record is bound to order A. At this moment, S33 marks P1 as a time-slice handover conflict parking space. With this design, conflict judgment is only triggered under the conditions that "the preceding vehicle has indeed exceeded the time limit, the following vehicle has actually arrived, and the parking space is indeed the handover point". This avoids misjudgments caused by situations such as being slightly late or checking orders too early, and provides accurate and reliable input for subsequent scheduling adjustments based on flexible time slice parameters.

[0107] Furthermore, the conflict determination method also includes the following steps: S34: Within the flexible time window of the next time slice order, calculate the parking space occupancy status for each time unit based on the current parking space allocation relationship with the time slice order. S35: In each time unit, when all parking spaces are occupied by time-slice orders and there are no unallocated time units, the flexible time window of the next time-slice order is determined as the time window in which all parking spaces have been allocated, and the parking spaces with time-slice handover conflicts and this time window are used together as the scheduling input conditions for step four.

[0108] In a preferred embodiment of this application, steps S34 and S35 are used in combination to determine whether the order for the next time slice is in a true "no available slots" state based on the "overall resource status" in the time dimension, thereby deciding whether it is necessary to enter the subsequent intelligent scheduling.

[0109] Specifically, in step S34, for subsequent time-slot orders that have been determined to have handover risks, the flexible time window of the order is first obtained (e.g., a continuous time interval determined by the earliest acceptable start time and the latest acceptable end time), and this time interval is discretized according to preset time units, such as dividing it into several 5-minute or 10-minute time units. In each time unit, based on the current allocation relationship between parking spaces and time-slot orders, it is calculated whether each parking space in the parking lot has been occupied by a time-slot order in that time unit, forming an occupancy distribution of "time unit - parking space".

[0110] In step S35, based on the above statistical results, the system checks each time unit of the entire flexible time window for the next time-slot order: when all parking spaces are occupied by time-slot orders and there is no idle time-parking space combination in each time unit within the flexible time window, the flexible time window is determined to be a time window where all parking spaces have been allocated. At this time, combined with the time-slot handover conflict parking spaces marked in the previous steps, "the handover conflict parking space + the corresponding flexible time window is a time window where all parking spaces have been allocated" are used as the input conditions for time adjustment and scheduling calculation in step four. In this way, before entering complex scheduling, the system first strictly confirms from the overall perspective that within the acceptable time range of the next time-slot order, there are indeed no available parking spaces that can be directly relocated. Therefore, it is necessary to rely on the flexible time-slot parameters to rearrange the actual start and end times of multiple orders, thereby more effectively solving the problem of the previous vehicle exceeding its time limit and the subsequent vehicle being unable to park.

[0111] In one specific embodiment of this application, for a subsequent time-slot order that has been determined to have a time-slot handover conflict through the aforementioned steps, the conflict determination method further determines, through steps S34 and S35, whether the subsequent time-slot order is in a state where parking space resources have been fully allocated within its flexible time window.

[0112] Suppose a parking lot has three physical parking spaces P1, P2, and P3. The time-slot order allocation for a certain period is as follows: Order A: Parking space P1, nominal time slot 9:00–11:00; Order B: Parking space P1, nominal time slot 11:00–13:00, which is the next time slot order, with a flexible time window of 10:50–11:20; Order C: Parking space P2, nominal time slot 10:30–12:00; Order D: Parking space P3, nominal time slot 10:50–11:30.

[0113] In the aforementioned steps, order B has been identified as an order with a time slice handover risk with order A, meaning that parking space P1 is a parking space with a time slice handover conflict.

[0114] In step S34, the system first obtains the flexible time window of order B, 10:50–11:20, and then divides this time interval into several sub-intervals according to preset time units, for example, with 5 minutes as a time unit, resulting in the following time units: T1: 10:50–10:55; T2: 10:55–11:00; T3: 11:00–11:05; T4: 11:05–11:10; T5: 11:10–11:15; T6: 11:15–11:20.

[0115] Within each time unit, the system calculates the occupancy status of each parking space based on the current allocation relationship between parking spaces and time-slice orders. Taking this embodiment as an example, the following "time unit – parking space" occupancy status can be obtained (for ease of understanding, it is listed in text here; the system can actually store it in matrix form): On T1 (10:50–10:55): P1 is occupied by order A (A's time slice covers 11:00); P2 is occupied by order C (C's time slice covers 10:30–12:00); P3 is occupied by order D (D's time slice covers 10:50–11:30).

[0116] At T2 (10:55–11:00): P1 is occupied by order A; P2 is occupied by order C; P3 is occupied by order D.

[0117] At time T3 (11:00–11:05): P1 is scheduled to be occupied by order B; P2 is occupied by order C. P3 is occupied by order D.

[0118] On T4 (11:05–11:10): P1 is still occupied by order B as planned (e.g., B's allowed start range covers 11:05); P2 is occupied by order C; P3 is occupied by order D.

[0119] At time T5 (11:10–11:15): P1 is scheduled to be occupied by order B; P2 is occupied by order C; P3 is occupied by order D.

[0120] On T6 (11:15–11:20): P1 is occupied by order B as planned; P2 is occupied by order C; P3 is occupied by order D.

[0121] Based on the above statistics, the system obtained in S34 that: within the entire flexible time window of order B, 10:50–11:20, parking spaces P1, P2, and P3 were all occupied by a certain time slot order plan in each time unit, and there was no situation of "a certain parking space in a certain time unit not being assigned an order".

[0122] In step S35, based on the statistical results of S34, the system makes an overall judgment on the flexible time window of order B: when it is found that for each time unit within the flexible time window, all three parking spaces P1, P2, and P3 have been allocated to specific time-slot orders, the flexible time window of order B is determined to be a time window in which all parking spaces have been allocated. At this time, combined with the parking space P1 with time-slot handover conflict identified in the previous steps, the system uses the two conditions "parking space P1 is a parking space with time-slot handover conflict" and "the flexible time window of order B has been fully allocated throughout the entire site" together as input conditions for subsequent scheduling steps.

[0123] In this situation, the following conclusions can be drawn: Within the acceptable flexible time window of 10:50–11:20 for order B, from the perspective of planned allocation, all parking spaces in the parking lot are occupied by time-slice orders in every time unit. The system cannot simply solve the problem by giving order B an empty parking space or inserting an idle time period. Instead, it must rely on the flexible time-slice parameters to make overall adjustments to the actual start and end times of orders A, B, C, and D, and regenerate a new parking space and time allocation plan.

[0124] For comparison, consider a contrasting scenario: If, during the above statistical process, parking space P3 has no time-slice orders allocated in a certain time unit (e.g., T3: 11:00–11:05), then the system will not classify the flexible time window of order B as a "time window where all parking spaces have been allocated" in S35. In this case, the system can directly consider scheduling order B to P3 within that time unit and adjacent time units without needing to make complex time adjustments to other orders, thus avoiding unnecessary scheduling calculations.

[0125] Therefore, through the cooperation of S34 and S35, this invention not only confirms "the existence of conflicting parking spaces during time slice handover" in the conflict judgment stage, but also further judges at the time unit granularity whether the flexible time window of the next time slice order has been filled by existing orders. Only when there is indeed "no empty space that can be directly relocated" will the conflicting parking space and the corresponding flexible time window be used as input conditions for intelligent scheduling, thus more effectively solving the problem of the following vehicle being unable to park due to the previous vehicle exceeding the time limit under the condition of no spare parking space during peak hours.

[0126] The time adjustment method includes the following steps: S41: First, adjust the actual parking start time and / or end time of the next time slice order only within the adjustable time boundary of the next time slice order to generate the first parking space and time allocation scheme; S42: When the actual parking duration of the subsequent time slot order in the first parking space and time allocation scheme is less than the minimum continuous parking duration within the flexible time window, select multiple time slot orders that have an overlapping relationship with the time range of the subsequent time slot order to form an adjustment set. Within the adjustment set, jointly adjust the actual parking start and end times of each time slot order to generate the second parking space and time allocation scheme.

[0127] In a preferred embodiment of this application, the time adjustment method is executed in two stages through steps S41 and S42. Under the premise of satisfying the flexible time slice parameter constraints, it prioritizes "adjusting only the order of the next time slice itself". If it cannot meet its minimum continuous parking time, other time slice orders that overlap with its time range are introduced for joint adjustment, thereby freeing up a usable continuous parking time period for the order of the next time slice without increasing the number of parking spaces.

[0128] Specifically, in step S41, given that a time slot handover conflict has been determined, the system first adjusts the actual parking start time and / or end time of the subsequent time slot order only within its adjustable time boundary, while keeping the actual start and end times of other time slot orders unchanged. In this way, the system attempts to find a feasible actual parking time period for the subsequent time slot order at the conflicting parking space without disturbing other users, thereby generating the first parking space and time allocation scheme.

[0129] If, in the first parking space and time allocation scheme, the actual continuous parking time obtained by the subsequent time slot order within its flexible time window is greater than or equal to its minimum continuous parking time, then it is considered that the handover conflict can be resolved simply by adjusting the subsequent time slot order itself, and the scheduling process ends here.

[0130] In step S42, when the system detects that in the first parking space and time allocation scheme, the actual parking duration obtained by the subsequent time-slot order within the flexible time window is still less than its minimum continuous parking duration, it indicates that simply moving the subsequent time-slot order itself is insufficient to allocate a sufficiently long continuous time period without conflicting with other orders. At this point, the system selects multiple time-slot orders whose time ranges overlap with the subsequent time-slot order to form an adjustment set. Within this adjustment set, the actual parking start and end times of each time-slot order are jointly adjusted. Taking into account the flexible time-slot parameter constraints of each time-slot order, the system recalculates and generates the second parking space and time allocation scheme, aiming to globally squeeze out continuous usage time that satisfies the minimum continuous parking duration for the subsequent time-slot order.

[0131] Therefore, S41 corresponds to "local adjustment of a single order, prioritizing not affecting others", and S42 corresponds to "introducing overlapping orders for global joint adjustment when it is impossible to meet the requirements". The two form a progressive relationship.

[0132] In a specific embodiment, the execution process of S41 and S42 is illustrated below with an example along a timeline. Assume that in a parking lot, parking space P1 has the following time-slice orders (nominal arrangements) within the time period 9:00–12:30: Order A: Parking space P1, nominal time slice 9:00–10:30; Order B: Parking space P1, nominal time slice 10:30–11:30, the next time-slice order; Order C: Parking space P1, nominal time slice 11:30–12:30. The flexible time-slice parameters for order B are set as follows: Flexible time window: 10:30–12:00 (i.e., the earliest acceptable start time is 10:30, and the latest acceptable end time is 12:00); minimum continuous parking duration: 60 minutes. Order C also has certain flexible time-slice parameters, such as allowing its end time to be slightly delayed, but its core requirement is between 11:45–12:15. In actual operation, due to the delay in the departure of the vehicle corresponding to Order A, the actual usage of parking space P1 is as follows: Order A actually occupies P1 from 9:00–10:45 (exceeding its nominal end time of 10:30 and the allowed end time); Order B's user has arrived at the parking lot ahead of schedule; Order C still plans to occupy P1 according to the nominal time slice of 11:30–12:30. At this time, for Order B, which has been determined to have a time slice handover conflict, the system enters steps S31 and S32 of the time adjustment mode.

[0133] Furthermore, the time adjustment method also includes the following steps: S43: When generating the second parking space and time allocation scheme, calculate the time shift of the actual parking start time relative to the original planned start time and the time compression of the actual parking duration relative to the original planned duration for each time slot order, and count the number of time slot orders participating in the time adjustment, and construct an evaluation index with the sum of time shift, the sum of time compression, and the number of orders participating in the time adjustment as components. S44: Using the weighted sum of evaluation indicators as the optimization objective, select the scheme with the smallest weighted sum of evaluation indicators from multiple candidate parking space and time allocation schemes as the new parking space and time allocation scheme, and output the new parking space and time allocation scheme to the corresponding user.

[0134] In a preferred embodiment of this application, after the time adjustment method completes the joint adjustment (to obtain several candidate "second parking space and time allocation schemes"), it performs quantitative evaluation and optimization output on these candidate schemes through steps S43 and S44, so that the system can resolve handover conflicts while minimizing the disturbance to the original reservation plan.

[0135] Specifically, in step S43, for each candidate parking space and time allocation scheme, the system calculates the following for each time slot order involved in the adjustment: the time shift of the actual parking start time relative to the original planned start time (e.g., if it changes from 10:30 to 10:40, the shift is +10 minutes); the time compression of the actual parking duration relative to the original planned duration (e.g., if the original planned duration is 60 minutes and the actual duration is 50 minutes, the compression is 10 minutes); and counts the number of time slot orders adjusted in this scheme. Based on this, the system constructs an evaluation index vector using the three quantities of "total time shift," "total time compression," and "number of orders involved in the adjustment" as components to reflect the degree of disturbance of the candidate scheme to the overall user time arrangement. In step S44, the system assigns weights to the above evaluation indexes, for example, assigning different importance to time shift, time compression, and the number of affected users according to business strategy or service level, and uses the weighted sum of the evaluation indexes as the optimization target. The system compares multiple candidate parking space and time allocation schemes, selecting the scheme with the smallest weighted sum as the final "new parking space and time allocation scheme," and then sends the corresponding actual parking start and end times to the relevant user terminals. This approach ensures that subsequent time-slice orders receive service for at least the minimum continuous parking duration within their flexible time window. Furthermore, it automatically selects the scheme with the smallest overall offset, least compression, and fewest affected orders from among the many feasible schemes that meet the constraints, minimizing the impact of conflict resolution on the overall reservation plan. For example, in the same handover conflict scenario, the system might have two candidate schemes: Scheme 1 adjusts 3 orders, with a cumulative time shift of 40 minutes and a cumulative compression of 20 minutes; Scheme 2 adjusts 2 orders, with a cumulative time shift of 30 minutes and a cumulative compression of 10 minutes. Given the weight settings, Scheme 2 has a smaller weighted sum of evaluation metrics, so the system selects Scheme 2 as the new parking space and time allocation scheme, thus resolving a handover conflict with a smaller overall adjustment cost.

[0136] Example 2 Please see Figure 2 This second embodiment provides a shared parking space e-commerce operation system 100 based on time-slice trading and intelligent scheduling, including: The time slice management module 10 is used to divide the right to use physical parking spaces into multiple time slices and publish them as products. When generating a time slice order, it records flexible time slice parameters for each time slice. The flexible time slice parameters include at least the core usage period, adjustable time boundaries, and minimum continuous parking duration. The occupancy association module 20 is used to collect the actual occupancy status of each parking space and the identification of the occupied vehicle, and associate the actual occupancy status with the corresponding time slot order. The conflict judgment module 30 is used to determine, when the allowed end time of the previous time slot order arrives, whether the current time exceeds the allowed end time and the corresponding parking space is still occupied by the previous time slot order, whether the user of the next time slot order has arrived at the parking lot, and based on the allocation relationship between the current parking space and the time slot order, whether all parking spaces are allocated to the time slot order within the flexible time window of the next time slot order, thereby determining the time slot handover conflict. The scheduling execution module 40 is used to calculate a new parking space and time allocation scheme when there is a time slice handover conflict, with the flexible time slice parameters of the relevant time slice orders as constraints. Within the adjustable time boundary, it adjusts the actual parking start time and / or end time of at least the later time slice order, and can simultaneously adjust the actual parking start and end times of one or more other time slice orders, so that the actual parking time obtained by the later time slice order within the flexible time window is greater than or equal to the minimum continuous parking time, and each parking space corresponds to only one time slice order at any given time.

[0137] It should be noted that when the system shown in this embodiment 2 is running, it operates exactly as described in embodiment 1. Therefore, all the beneficial effects in this embodiment 2 are exactly the same as those in embodiment 1, and will not be elaborated further here.

[0138] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for e-commerce operation of shared parking spaces based on time-slice trading and intelligent scheduling, characterized in that, Includes the following steps: The right to use a physical parking space is divided into multiple time slices and listed as a product. When generating a time slice order, flexible time slice parameters are recorded for each time slice. The flexible time slice parameters include at least the core usage period, adjustable time boundaries, and minimum continuous parking duration. Collect the actual occupancy status of each parking space and the identification of the occupied vehicle, and associate the actual occupancy status with the corresponding time slot order; When the allowed end time of the previous time slot order arrives, determine whether the current time has exceeded the allowed end time and whether the corresponding parking space is still occupied by the previous time slot order. Determine whether the user of the next time slot order has arrived at the parking lot. Based on the allocation relationship between the current parking space and the time slot order, determine whether all parking spaces have been allocated to the time slot order within the flexible time window of the next time slot order. When the above conditions are met at the same time, it is determined that there is a time slot handover conflict. In the event of a time-slice handover conflict, a new parking space and time allocation scheme is calculated with the flexible time-slice parameters of the relevant time-slice orders as constraints. Within the adjustable time boundary, the actual parking start time and / or end time of at least the later time-slice order is adjusted, and the actual parking start and end times of one or more other time-slice orders can be adjusted simultaneously, so that the actual parking duration obtained by the later time-slice order within its flexible time window is greater than or equal to the minimum continuous parking duration, and each parking space corresponds to the actual occupancy of only one time-slice order at any given time.

2. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 1, characterized in that, The time slice generation method specifically includes the following steps: The nominal start and nominal end times of each time slice order are divided into a pre-flexible period, a core period, and a post-flexible period; Record the start and end times of the pre-flexible period, core period, and post-flexible period in the flexible time slice parameters, and record the earliest acceptable start time and the latest acceptable end time, so that the core period is located within the continuous time interval between the earliest acceptable start time and the latest acceptable end time.

3. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 2, characterized in that, The time slice generation method also includes the following steps: Record flexibility level parameters for each time slice order. The flexibility level parameters limit the maximum compression ratio of the preceding and following flexible time periods, the maximum length of the adjustable time boundary, and the range of values ​​for the minimum continuous parking time. When releasing time-slice products, the sales price is set according to the flexibility level parameter, so that time-slice orders with larger flexibility level parameter values ​​correspond to lower sales prices, and in subsequent time-slice handover conflicts, time-slice orders with larger flexibility level parameter values ​​are given priority to participate in the time adjustment.

4. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 1, characterized in that, The occupancy detection method specifically includes the following steps: The occupancy status of each parking space is collected through at least one of the following detection methods: geomagnetic sensor, parking space lock feedback, or video camera. License plate recognition is performed on the video image to obtain the occupied vehicle identifier. The occupied vehicle identifier is then compared with the entry registration information to determine the time slot order corresponding to the currently occupied vehicle. The occupancy status is then associated with and stored with that time slot order.

5. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 4, characterized in that, The occupancy detection method also includes the following steps: The occupancy status and corresponding time slice order identifier of each parking space are updated periodically to generate a parking space occupancy time series; During the update, the system detects the difference between the parking space occupancy status at a certain point in time and the planned occupancy status of the time slice order, and marks the parking spaces with differences as abnormal parking spaces, which provides input for judging time slice handover conflicts.

6. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 5, characterized in that, The conflict resolution method includes the following steps: Obtain the current location data from the terminal of the user who placed the order in the next time slice, and calculate the distance between the current location and the parking lot location; If the distance is less than the preset radius and the current time is within the preset advance time range before the nominal start time of the next time slice order, the user of the next time slice order will be determined as having arrived within the parking lot area; If it is determined that a parking space is still occupied after the previous time slot order has exceeded the allowed end time, and the user of the next time slot order has arrived within the parking lot area, and the parking space marked as abnormal is bound to the previous time slot order, then the parking space is identified as a time slot handover conflict parking space.

7. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 6, characterized in that, The conflict resolution method also includes the following steps: Within the flexible time window of the next time slice order, the parking space occupancy status of each time unit is calculated based on the current parking space allocation relationship with the time slice order. In each time unit, when all parking spaces are occupied by time-slice orders and there are no unallocated time units, the flexible time window of the next time-slice order is determined as the time window in which all parking spaces have been allocated, and the parking spaces with time-slice handover conflicts and this time window are used together as the scheduling input conditions for step four.

8. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 1, characterized in that, The time adjustment method includes the following steps: First, adjust the actual parking start time and / or end time of the next time slice order only within the adjustable time boundary of the next time slice order to generate the first parking space and time allocation scheme; When the actual parking duration of a subsequent time slot order in the first parking space and time allocation scheme is less than the minimum continuous parking duration within the flexible time window, multiple time slot orders that overlap with the time range of the subsequent time slot order are selected to form an adjustment set. Within the adjustment set, the actual parking start and end times of each time slot order are jointly adjusted to generate the second parking space and time allocation scheme.

9. The shared parking space e-commerce operation method based on time-slice trading and intelligent scheduling according to claim 8, characterized in that, The time adjustment method also includes the following steps: When generating the second parking space and time allocation scheme, calculate the time shift of the actual parking start time relative to the original planned start time and the time compression of the actual parking duration relative to the original planned duration for each time slot order, and count the number of time slot orders participating in the time adjustment, and construct an evaluation index with the sum of time shift, the sum of time compression, and the number of orders participating in the time adjustment as components. Using the weighted sum of evaluation indicators as the optimization objective, the scheme with the smallest weighted sum of evaluation indicators is selected from multiple candidate parking space and time allocation schemes as the new parking space and time allocation scheme, and the new parking space and time allocation scheme is output to the corresponding user.

10. A shared parking space e-commerce operation system based on time-slice trading and intelligent scheduling, characterized in that, include: The time slice management module is used to divide the right to use physical parking spaces into multiple time slices and publish them as products. When generating a time slice order, it records flexible time slice parameters for each time slice. The flexible time slice parameters include at least the core usage period, adjustable time boundaries, and minimum continuous parking duration. The occupancy association module is used to collect the actual occupancy status of each parking space and the identification of the occupied vehicle, and associate the actual occupancy status with the corresponding time slot order; The conflict detection module is used to determine whether the current time has exceeded the allowed end time and the corresponding parking space is still occupied by the previous time slot order when the allowed end time of the previous time slot order arrives, whether the user of the next time slot order has arrived at the parking lot, and to determine whether all parking spaces are allocated to the time slot order within the flexible time window of the next time slot order based on the allocation relationship between the current parking space and the time slot order, thereby determining the time slot handover conflict. The scheduling execution module is used to calculate a new parking space and time allocation scheme when time slice handover conflicts occur, with the flexible time slice parameters of the relevant time slice orders as constraints. Within the adjustable time boundary, it adjusts the actual parking start time and / or end time of at least the next time slice order, and can simultaneously adjust the actual parking start and end times of one or more other time slice orders, so that the actual parking duration obtained by the next time slice order within the flexible time window is greater than or equal to the minimum continuous parking duration, and each parking space corresponds to the actual occupancy of only one time slice order at any given time.

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